Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware.

PubMed

Rast, Alexander; Galluppi, Francesco; Davies, Sergio; Plana, Luis; Patterson, Cameron; Sharp, Thomas; Lester, David; Furber, Steve

2011-11-01

Dedicated hardware is becoming increasingly essential to simulate emerging very-large-scale neural models. Equally, however, it needs to be able to support multiple models of the neural dynamics, possibly operating simultaneously within the same system. This may be necessary either to simulate large models with heterogeneous neural types, or to simplify simulation and analysis of detailed, complex models in a large simulation by isolating the new model to a small subpopulation of a larger overall network. The SpiNNaker neuromimetic chip is a dedicated neural processor able to support such heterogeneous simulations. Implementing these models on-chip uses an integrated library-based tool chain incorporating the emerging PyNN interface that allows a modeller to input a high-level description and use an automated process to generate an on-chip simulation. Simulations using both LIF and Izhikevich models demonstrate the ability of the SpiNNaker system to generate and simulate heterogeneous networks on-chip, while illustrating, through the network-scale effects of wavefront synchronisation and burst gating, methods that can provide effective behavioural abstractions for large-scale hardware modelling. SpiNNaker's asynchronous virtual architecture permits greater scope for model exploration, with scalable levels of functional and temporal abstraction, than conventional (or neuromorphic) computing platforms. The complete system illustrates a potential path to understanding the neural model of computation, by building (and breaking) neural models at various scales, connecting the blocks, then comparing them against the biology: computational cognitive neuroscience. Copyright © 2011 Elsevier Ltd. All rights reserved.

Particle physics and polyedra proximity calculation for hazard simulations in large-scale industrial plants

NASA Astrophysics Data System (ADS)

Plebe, Alice; Grasso, Giorgio

2016-12-01

This paper describes a system developed for the simulation of flames inside an open-source 3D computer graphic software, Blender, with the aim of analyzing in virtual reality scenarios of hazards in large-scale industrial plants. The advantages of Blender are of rendering at high resolution the very complex structure of large industrial plants, and of embedding a physical engine based on smoothed particle hydrodynamics. This particle system is used to evolve a simulated fire. The interaction of this fire with the components of the plant is computed using polyhedron separation distance, adopting a Voronoi-based strategy that optimizes the number of feature distance computations. Results on a real oil and gas refining industry are presented.

Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware

PubMed Central

Knight, James C.; Tully, Philip J.; Kaplan, Bernhard A.; Lansner, Anders; Furber, Steve B.

2016-01-01

SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 2.0 × 104 neurons and 5.1 × 107 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately 45× more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models. PMID:27092061

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

Performance of distributed multiscale simulations

PubMed Central

Borgdorff, J.; Ben Belgacem, M.; Bona-Casas, C.; Fazendeiro, L.; Groen, D.; Hoenen, O.; Mizeranschi, A.; Suter, J. L.; Coster, D.; Coveney, P. V.; Dubitzky, W.; Hoekstra, A. G.; Strand, P.; Chopard, B.

2014-01-01

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption. PMID:24982258

A Study on Fast Gates for Large-Scale Quantum Simulation with Trapped Ions

PubMed Central

Taylor, Richard L.; Bentley, Christopher D. B.; Pedernales, Julen S.; Lamata, Lucas; Solano, Enrique; Carvalho, André R. R.; Hope, Joseph J.

2017-01-01

Large-scale digital quantum simulations require thousands of fundamental entangling gates to construct the simulated dynamics. Despite success in a variety of small-scale simulations, quantum information processing platforms have hitherto failed to demonstrate the combination of precise control and scalability required to systematically outmatch classical simulators. We analyse how fast gates could enable trapped-ion quantum processors to achieve the requisite scalability to outperform classical computers without error correction. We analyze the performance of a large-scale digital simulator, and find that fidelity of around 70% is realizable for π-pulse infidelities below 10−5 in traps subject to realistic rates of heating and dephasing. This scalability relies on fast gates: entangling gates faster than the trap period. PMID:28401945

A Study on Fast Gates for Large-Scale Quantum Simulation with Trapped Ions.

PubMed

Taylor, Richard L; Bentley, Christopher D B; Pedernales, Julen S; Lamata, Lucas; Solano, Enrique; Carvalho, André R R; Hope, Joseph J

2017-04-12

Large-scale digital quantum simulations require thousands of fundamental entangling gates to construct the simulated dynamics. Despite success in a variety of small-scale simulations, quantum information processing platforms have hitherto failed to demonstrate the combination of precise control and scalability required to systematically outmatch classical simulators. We analyse how fast gates could enable trapped-ion quantum processors to achieve the requisite scalability to outperform classical computers without error correction. We analyze the performance of a large-scale digital simulator, and find that fidelity of around 70% is realizable for π-pulse infidelities below 10 -5 in traps subject to realistic rates of heating and dephasing. This scalability relies on fast gates: entangling gates faster than the trap period.

High performance cellular level agent-based simulation with FLAME for the GPU.

PubMed

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

Large scale cardiac modeling on the Blue Gene supercomputer.

PubMed

Reumann, Matthias; Fitch, Blake G; Rayshubskiy, Aleksandr; Keller, David U; Weiss, Daniel L; Seemann, Gunnar; Dössel, Olaf; Pitman, Michael C; Rice, John J

2008-01-01

Multi-scale, multi-physical heart models have not yet been able to include a high degree of accuracy and resolution with respect to model detail and spatial resolution due to computational limitations of current systems. We propose a framework to compute large scale cardiac models. Decomposition of anatomical data in segments to be distributed on a parallel computer is carried out by optimal recursive bisection (ORB). The algorithm takes into account a computational load parameter which has to be adjusted according to the cell models used. The diffusion term is realized by the monodomain equations. The anatomical data-set was given by both ventricles of the Visible Female data-set in a 0.2 mm resolution. Heterogeneous anisotropy was included in the computation. Model weights as input for the decomposition and load balancing were set to (a) 1 for tissue and 0 for non-tissue elements; (b) 10 for tissue and 1 for non-tissue elements. Scaling results for 512, 1024, 2048, 4096 and 8192 computational nodes were obtained for 10 ms simulation time. The simulations were carried out on an IBM Blue Gene/L parallel computer. A 1 s simulation was then carried out on 2048 nodes for the optimal model load. Load balances did not differ significantly across computational nodes even if the number of data elements distributed to each node differed greatly. Since the ORB algorithm did not take into account computational load due to communication cycles, the speedup is close to optimal for the computation time but not optimal overall due to the communication overhead. However, the simulation times were reduced form 87 minutes on 512 to 11 minutes on 8192 nodes. This work demonstrates that it is possible to run simulations of the presented detailed cardiac model within hours for the simulation of a heart beat.

The large scale microelectronics Computer-Aided Design and Test (CADAT) system

NASA Technical Reports Server (NTRS)

Gould, J. M.

1978-01-01

The CADAT system consists of a number of computer programs written in FORTRAN that provide the capability to simulate, lay out, analyze, and create the artwork for large scale microelectronics. The function of each software component of the system is described with references to specific documentation for each software component.

Large-scale dynamo action precedes turbulence in shearing box simulations of the magnetorotational instability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhat, Pallavi; Ebrahimi, Fatima; Blackman, Eric G.

Here, we study the dynamo generation (exponential growth) of large-scale (planar averaged) fields in unstratified shearing box simulations of the magnetorotational instability (MRI). In contrast to previous studies restricted to horizontal (x–y) averaging, we also demonstrate the presence of large-scale fields when vertical (y–z) averaging is employed instead. By computing space–time planar averaged fields and power spectra, we find large-scale dynamo action in the early MRI growth phase – a previously unidentified feature. Non-axisymmetric linear MRI modes with low horizontal wavenumbers and vertical wavenumbers near that of expected maximal growth, amplify the large-scale fields exponentially before turbulence and high wavenumbermore » fluctuations arise. Thus the large-scale dynamo requires only linear fluctuations but not non-linear turbulence (as defined by mode–mode coupling). Vertical averaging also allows for monitoring the evolution of the large-scale vertical field and we find that a feedback from horizontal low wavenumber MRI modes provides a clue as to why the large-scale vertical field sustains against turbulent diffusion in the non-linear saturation regime. We compute the terms in the mean field equations to identify the individual contributions to large-scale field growth for both types of averaging. The large-scale fields obtained from vertical averaging are found to compare well with global simulations and quasi-linear analytical analysis from a previous study by Ebrahimi & Blackman. We discuss the potential implications of these new results for understanding the large-scale MRI dynamo saturation and turbulence.« less

Large-scale dynamo action precedes turbulence in shearing box simulations of the magnetorotational instability

DOE PAGES

Bhat, Pallavi; Ebrahimi, Fatima; Blackman, Eric G.

2016-07-06

Here, we study the dynamo generation (exponential growth) of large-scale (planar averaged) fields in unstratified shearing box simulations of the magnetorotational instability (MRI). In contrast to previous studies restricted to horizontal (x–y) averaging, we also demonstrate the presence of large-scale fields when vertical (y–z) averaging is employed instead. By computing space–time planar averaged fields and power spectra, we find large-scale dynamo action in the early MRI growth phase – a previously unidentified feature. Non-axisymmetric linear MRI modes with low horizontal wavenumbers and vertical wavenumbers near that of expected maximal growth, amplify the large-scale fields exponentially before turbulence and high wavenumbermore » fluctuations arise. Thus the large-scale dynamo requires only linear fluctuations but not non-linear turbulence (as defined by mode–mode coupling). Vertical averaging also allows for monitoring the evolution of the large-scale vertical field and we find that a feedback from horizontal low wavenumber MRI modes provides a clue as to why the large-scale vertical field sustains against turbulent diffusion in the non-linear saturation regime. We compute the terms in the mean field equations to identify the individual contributions to large-scale field growth for both types of averaging. The large-scale fields obtained from vertical averaging are found to compare well with global simulations and quasi-linear analytical analysis from a previous study by Ebrahimi & Blackman. We discuss the potential implications of these new results for understanding the large-scale MRI dynamo saturation and turbulence.« less

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Sand waves in environmental flows: Insights gained by coupling large-eddy simulation with morphodynamics

NASA Astrophysics Data System (ADS)

Sotiropoulos, Fotis; Khosronejad, Ali

2016-02-01

Sand waves arise in subaqueous and Aeolian environments as the result of the complex interaction between turbulent flows and mobile sand beds. They occur across a wide range of spatial scales, evolve at temporal scales much slower than the integral scale of the transporting turbulent flow, dominate river morphodynamics, undermine streambank stability and infrastructure during flooding, and sculpt terrestrial and extraterrestrial landscapes. In this paper, we present the vision for our work over the last ten years, which has sought to develop computational tools capable of simulating the coupled interactions of sand waves with turbulence across the broad range of relevant scales: from small-scale ripples in laboratory flumes to mega-dunes in large rivers. We review the computational advances that have enabled us to simulate the genesis and long-term evolution of arbitrarily large and complex sand dunes in turbulent flows using large-eddy simulation and summarize numerous novel physical insights derived from our simulations. Our findings explain the role of turbulent sweeps in the near-bed region as the primary mechanism for destabilizing the sand bed, show that the seeds of the emergent structure in dune fields lie in the heterogeneity of the turbulence and bed shear stress fluctuations over the initially flatbed, and elucidate how large dunes at equilibrium give rise to energetic coherent structures and modify the spectra of turbulence. We also discuss future challenges and our vision for advancing a data-driven simulation-based engineering science approach for site-specific simulations of river flooding.

Advanced computational simulations of water waves interacting with wave energy converters

NASA Astrophysics Data System (ADS)

Pathak, Ashish; Freniere, Cole; Raessi, Mehdi

2017-03-01

Wave energy converter (WEC) devices harness the renewable ocean wave energy and convert it into useful forms of energy, e.g. mechanical or electrical. This paper presents an advanced 3D computational framework to study the interaction between water waves and WEC devices. The computational tool solves the full Navier-Stokes equations and considers all important effects impacting the device performance. To enable large-scale simulations in fast turnaround times, the computational solver was developed in an MPI parallel framework. A fast multigrid preconditioned solver is introduced to solve the computationally expensive pressure Poisson equation. The computational solver was applied to two surface-piercing WEC geometries: bottom-hinged cylinder and flap. Their numerically simulated response was validated against experimental data. Additional simulations were conducted to investigate the applicability of Froude scaling in predicting full-scale WEC response from the model experiments.

Opportunities for Breakthroughs in Large-Scale Computational Simulation and Design

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Alter, Stephen J.; Atkins, Harold L.; Bey, Kim S.; Bibb, Karen L.; Biedron, Robert T.; Carpenter, Mark H.; Cheatwood, F. McNeil; Drummond, Philip J.; Gnoffo, Peter A.

2002-01-01

Opportunities for breakthroughs in the large-scale computational simulation and design of aerospace vehicles are presented. Computational fluid dynamics tools to be used within multidisciplinary analysis and design methods are emphasized. The opportunities stem from speedups and robustness improvements in the underlying unit operations associated with simulation (geometry modeling, grid generation, physical modeling, analysis, etc.). Further, an improved programming environment can synergistically integrate these unit operations to leverage the gains. The speedups result from reducing the problem setup time through geometry modeling and grid generation operations, and reducing the solution time through the operation counts associated with solving the discretized equations to a sufficient accuracy. The opportunities are addressed only at a general level here, but an extensive list of references containing further details is included. The opportunities discussed are being addressed through the Fast Adaptive Aerospace Tools (FAAST) element of the Advanced Systems Concept to Test (ASCoT) and the third Generation Reusable Launch Vehicles (RLV) projects at NASA Langley Research Center. The overall goal is to enable greater inroads into the design process with large-scale simulations.

BlazeDEM3D-GPU A Large Scale DEM simulation code for GPUs

NASA Astrophysics Data System (ADS)

Govender, Nicolin; Wilke, Daniel; Pizette, Patrick; Khinast, Johannes

2017-06-01

Accurately predicting the dynamics of particulate materials is of importance to numerous scientific and industrial areas with applications ranging across particle scales from powder flow to ore crushing. Computational discrete element simulations is a viable option to aid in the understanding of particulate dynamics and design of devices such as mixers, silos and ball mills, as laboratory scale tests comes at a significant cost. However, the computational time required to simulate an industrial scale simulation which consists of tens of millions of particles can take months to complete on large CPU clusters, making the Discrete Element Method (DEM) unfeasible for industrial applications. Simulations are therefore typically restricted to tens of thousands of particles with highly detailed particle shapes or a few million of particles with often oversimplified particle shapes. However, a number of applications require accurate representation of the particle shape to capture the macroscopic behaviour of the particulate system. In this paper we give an overview of the recent extensions to the open source GPU based DEM code, BlazeDEM3D-GPU, that can simulate millions of polyhedra and tens of millions of spheres on a desktop computer with a single or multiple GPUs.

Computation of large-scale statistics in decaying isotropic turbulence

NASA Technical Reports Server (NTRS)

Chasnov, Jeffrey R.

1993-01-01

We have performed large-eddy simulations of decaying isotropic turbulence to test the prediction of self-similar decay of the energy spectrum and to compute the decay exponents of the kinetic energy. In general, good agreement between the simulation results and the assumption of self-similarity were obtained. However, the statistics of the simulations were insufficient to compute the value of gamma which corrects the decay exponent when the spectrum follows a k(exp 4) wave number behavior near k = 0. To obtain good statistics, it was found necessary to average over a large ensemble of turbulent flows.

Simulation of turbulent shear flows at Stanford and NASA-Ames - What can we do and what have we learned?

NASA Technical Reports Server (NTRS)

Reynolds, W. C.

1983-01-01

The capabilities and limitations of large eddy simulation (LES) and full turbulence simulation (FTS) are outlined. It is pointed out that LES, although limited at the present time by the need for periodic boundary conditions, produces large-scale flow behavior in general agreement with experiments. What is more, FTS computations produce small-scale behavior that is consistent with available experiments. The importance of the development work being done on the National Aerodynamic Simulator is emphasized. Studies at present are limited to situations in which periodic boundary conditions can be applied on boundaries of the computational domain where the flow is turbulent.

A qualitative analysis of bus simulator training on transit incidents : a case study in Florida. [Summary].

DOT National Transportation Integrated Search

2013-01-01

The simulator was once a very expensive, large-scale mechanical device for training military pilots or astronauts. Modern computers, linking sophisticated software and large-screen displays, have yielded simulators for the desktop or configured as sm...

Predictive wind turbine simulation with an adaptive lattice Boltzmann method for moving boundaries

NASA Astrophysics Data System (ADS)

Deiterding, Ralf; Wood, Stephen L.

2016-09-01

Operating horizontal axis wind turbines create large-scale turbulent wake structures that affect the power output of downwind turbines considerably. The computational prediction of this phenomenon is challenging as efficient low dissipation schemes are necessary that represent the vorticity production by the moving structures accurately and that are able to transport wakes without significant artificial decay over distances of several rotor diameters. We have developed a parallel adaptive lattice Boltzmann method for large eddy simulation of turbulent weakly compressible flows with embedded moving structures that considers these requirements rather naturally and enables first principle simulations of wake-turbine interaction phenomena at reasonable computational costs. The paper describes the employed computational techniques and presents validation simulations for the Mexnext benchmark experiments as well as simulations of the wake propagation in the Scaled Wind Farm Technology (SWIFT) array consisting of three Vestas V27 turbines in triangular arrangement.

Northwest Trajectory Analysis Capability: A Platform for Enhancing Computational Biophysics Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Elena S.; Stephan, Eric G.; Corrigan, Abigail L.

2008-07-30

As computational resources continue to increase, the ability of computational simulations to effectively complement, and in some cases replace, experimentation in scientific exploration also increases. Today, large-scale simulations are recognized as an effective tool for scientific exploration in many disciplines including chemistry and biology. A natural side effect of this trend has been the need for an increasingly complex analytical environment. In this paper, we describe Northwest Trajectory Analysis Capability (NTRAC), an analytical software suite developed to enhance the efficiency of computational biophysics analyses. Our strategy is to layer higher-level services and introduce improved tools within the user’s familiar environmentmore » without preventing researchers from using traditional tools and methods. Our desire is to share these experiences to serve as an example for effectively analyzing data intensive large scale simulation data.« less

Large-eddy simulation of a boundary layer with concave streamwise curvature

NASA Technical Reports Server (NTRS)

Lund, Thomas S.

1994-01-01

Turbulence modeling continues to be one of the most difficult problems in fluid mechanics. Existing prediction methods are well developed for certain classes of simple equilibrium flows, but are still not entirely satisfactory for a large category of complex non-equilibrium flows found in engineering practice. Direct and large-eddy simulation (LES) approaches have long been believed to have great potential for the accurate prediction of difficult turbulent flows, but the associated computational cost has been prohibitive for practical problems. This remains true for direct simulation but is no longer clear for large-eddy simulation. Advances in computer hardware, numerical methods, and subgrid-scale modeling have made it possible to conduct LES for flows or practical interest at Reynolds numbers in the range of laboratory experiments. The objective of this work is to apply ES and the dynamic subgrid-scale model to the flow of a boundary layer over a concave surface.

Coniferous canopy BRF simulation based on 3-D realistic scene.

PubMed

Wang, Xin-Yun; Guo, Zhi-Feng; Qin, Wen-Han; Sun, Guo-Qing

2011-09-01

It is difficulties for the computer simulation method to study radiation regime at large-scale. Simplified coniferous model was investigated in the present study. It makes the computer simulation methods such as L-systems and radiosity-graphics combined method (RGM) more powerful in remote sensing of heterogeneous coniferous forests over a large-scale region. L-systems is applied to render 3-D coniferous forest scenarios, and RGM model was used to calculate BRF (bidirectional reflectance factor) in visible and near-infrared regions. Results in this study show that in most cases both agreed well. Meanwhile at a tree and forest level, the results are also good.

Coniferous Canopy BRF Simulation Based on 3-D Realistic Scene

NASA Technical Reports Server (NTRS)

Wang, Xin-yun; Guo, Zhi-feng; Qin, Wen-han; Sun, Guo-qing

2011-01-01

It is difficulties for the computer simulation method to study radiation regime at large-scale. Simplified coniferous model was investigate d in the present study. It makes the computer simulation methods such as L-systems and radiosity-graphics combined method (RGM) more powerf ul in remote sensing of heterogeneous coniferous forests over a large -scale region. L-systems is applied to render 3-D coniferous forest scenarios: and RGM model was used to calculate BRF (bidirectional refle ctance factor) in visible and near-infrared regions. Results in this study show that in most cases both agreed well. Meanwhiie at a tree and forest level. the results are also good.

Concepts and Plans towards fast large scale Monte Carlo production for the ATLAS Experiment

NASA Astrophysics Data System (ADS)

Ritsch, E.; Atlas Collaboration

2014-06-01

The huge success of the physics program of the ATLAS experiment at the Large Hadron Collider (LHC) during Run 1 relies upon a great number of simulated Monte Carlo events. This Monte Carlo production takes the biggest part of the computing resources being in use by ATLAS as of now. In this document we describe the plans to overcome the computing resource limitations for large scale Monte Carlo production in the ATLAS Experiment for Run 2, and beyond. A number of fast detector simulation, digitization and reconstruction techniques are being discussed, based upon a new flexible detector simulation framework. To optimally benefit from these developments, a redesigned ATLAS MC production chain is presented at the end of this document.

A Large number of fast cosmological simulations

NASA Astrophysics Data System (ADS)

Koda, Jun; Kazin, E.; Blake, C.

2014-01-01

Mock galaxy catalogs are essential tools to analyze large-scale structure data. Many independent realizations of mock catalogs are necessary to evaluate the uncertainties in the measurements. We perform 3600 cosmological simulations for the WiggleZ Dark Energy Survey to obtain the new improved Baron Acoustic Oscillation (BAO) cosmic distance measurements using the density field "reconstruction" technique. We use 1296^3 particles in a periodic box of 600/h Mpc on a side, which is the minimum requirement from the survey volume and observed galaxies. In order to perform such large number of simulations, we developed a parallel code using the COmoving Lagrangian Acceleration (COLA) method, which can simulate cosmological large-scale structure reasonably well with only 10 time steps. Our simulation is more than 100 times faster than conventional N-body simulations; one COLA simulation takes only 15 minutes with 216 computing cores. We have completed the 3600 simulations with a reasonable computation time of 200k core hours. We also present the results of the revised WiggleZ BAO distance measurement, which are significantly improved by the reconstruction technique.

Argonne Simulation Framework for Intelligent Transportation Systems

DOT National Transportation Integrated Search

1996-01-01

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distribu...

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

Large-Eddy Simulation of Internal Flow through Human Vocal Folds

NASA Astrophysics Data System (ADS)

Lasota, Martin; Šidlof, Petr

2018-06-01

The phonatory process occurs when air is expelled from the lungs through the glottis and the pressure drop causes flow-induced oscillations of the vocal folds. The flow fields created in phonation are highly unsteady and the coherent vortex structures are also generated. For accuracy it is essential to compute on humanlike computational domain and appropriate mathematical model. The work deals with numerical simulation of air flow within the space between plicae vocales and plicae vestibulares. In addition to the dynamic width of the rima glottidis, where the sound is generated, there are lateral ventriculus laryngis and sacculus laryngis included in the computational domain as well. The paper presents the results from OpenFOAM which are obtained with a large-eddy simulation using second-order finite volume discretization of incompressible Navier-Stokes equations. Large-eddy simulations with different subgrid scale models are executed on structured mesh. In these cases are used only the subgrid scale models which model turbulence via turbulent viscosity and Boussinesq approximation in subglottal and supraglottal area in larynx.

Large-scale expensive black-box function optimization

NASA Astrophysics Data System (ADS)

Rashid, Kashif; Bailey, William; Couët, Benoît

2012-09-01

This paper presents the application of an adaptive radial basis function method to a computationally expensive black-box reservoir simulation model of many variables. An iterative proxy-based scheme is used to tune the control variables, distributed for finer control over a varying number of intervals covering the total simulation period, to maximize asset NPV. The method shows that large-scale simulation-based function optimization of several hundred variables is practical and effective.

Wall Modeled Large Eddy Simulation of Airfoil Trailing Edge Noise

NASA Astrophysics Data System (ADS)

Kocheemoolayil, Joseph; Lele, Sanjiva

2014-11-01

Large eddy simulation (LES) of airfoil trailing edge noise has largely been restricted to low Reynolds numbers due to prohibitive computational cost. Wall modeled LES (WMLES) is a computationally cheaper alternative that makes full-scale Reynolds numbers relevant to large wind turbines accessible. A systematic investigation of trailing edge noise prediction using WMLES is conducted. Detailed comparisons are made with experimental data. The stress boundary condition from a wall model does not constrain the fluctuating velocity to vanish at the wall. This limitation has profound implications for trailing edge noise prediction. The simulation over-predicts the intensity of fluctuating wall pressure and far-field noise. An improved wall model formulation that minimizes the over-prediction of fluctuating wall pressure is proposed and carefully validated. The flow configurations chosen for the study are from the workshop on benchmark problems for airframe noise computations. The large eddy simulation database is used to examine the adequacy of scaling laws that quantify the dependence of trailing edge noise on Mach number, Reynolds number and angle of attack. Simplifying assumptions invoked in engineering approaches towards predicting trailing edge noise are critically evaluated. We gratefully acknowledge financial support from GE Global Research and thank Cascade Technologies Inc. for providing access to their massively-parallel large eddy simulation framework.

Large-scale three-dimensional phase-field simulations for phase coarsening at ultrahigh volume fraction on high-performance architectures

NASA Astrophysics Data System (ADS)

Yan, Hui; Wang, K. G.; Jones, Jim E.

2016-06-01

A parallel algorithm for large-scale three-dimensional phase-field simulations of phase coarsening is developed and implemented on high-performance architectures. From the large-scale simulations, a new kinetics in phase coarsening in the region of ultrahigh volume fraction is found. The parallel implementation is capable of harnessing the greater computer power available from high-performance architectures. The parallelized code enables increase in three-dimensional simulation system size up to a 5123 grid cube. Through the parallelized code, practical runtime can be achieved for three-dimensional large-scale simulations, and the statistical significance of the results from these high resolution parallel simulations are greatly improved over those obtainable from serial simulations. A detailed performance analysis on speed-up and scalability is presented, showing good scalability which improves with increasing problem size. In addition, a model for prediction of runtime is developed, which shows a good agreement with actual run time from numerical tests.

Efficient coarse simulation of a growing avascular tumor

PubMed Central

Kavousanakis, Michail E.; Liu, Ping; Boudouvis, Andreas G.; Lowengrub, John; Kevrekidis, Ioannis G.

2013-01-01

The subject of this work is the development and implementation of algorithms which accelerate the simulation of early stage tumor growth models. Among the different computational approaches used for the simulation of tumor progression, discrete stochastic models (e.g., cellular automata) have been widely used to describe processes occurring at the cell and subcell scales (e.g., cell-cell interactions and signaling processes). To describe macroscopic characteristics (e.g., morphology) of growing tumors, large numbers of interacting cells must be simulated. However, the high computational demands of stochastic models make the simulation of large-scale systems impractical. Alternatively, continuum models, which can describe behavior at the tumor scale, often rely on phenomenological assumptions in place of rigorous upscaling of microscopic models. This limits their predictive power. In this work, we circumvent the derivation of closed macroscopic equations for the growing cancer cell populations; instead, we construct, based on the so-called “equation-free” framework, a computational superstructure, which wraps around the individual-based cell-level simulator and accelerates the computations required for the study of the long-time behavior of systems involving many interacting cells. The microscopic model, e.g., a cellular automaton, which simulates the evolution of cancer cell populations, is executed for relatively short time intervals, at the end of which coarse-scale information is obtained. These coarse variables evolve on slower time scales than each individual cell in the population, enabling the application of forward projection schemes, which extrapolate their values at later times. This technique is referred to as coarse projective integration. Increasing the ratio of projection times to microscopic simulator execution times enhances the computational savings. Crucial accuracy issues arising for growing tumors with radial symmetry are addressed by applying the coarse projective integration scheme in a cotraveling (cogrowing) frame. As a proof of principle, we demonstrate that the application of this scheme yields highly accurate solutions, while preserving the computational savings of coarse projective integration. PMID:22587128

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

PubMed Central

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2017-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

Large-Scale Traffic Microsimulation From An MPO Perspective

DOT National Transportation Integrated Search

1997-01-01

One potential advancement of the four-step travel model process is the forecasting and simulation of individual activities and travel. A common concern with such an approach is that the data and computational requirements for a large-scale, regional ...

A novel representation of groundwater dynamics in large-scale land surface modelling

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael; Kollet, Stefan

2017-04-01

Land surface processes are connected to groundwater dynamics via shallow soil moisture. For example, groundwater affects evapotranspiration (by influencing the variability of soil moisture) and runoff generation mechanisms. However, contemporary Land Surface Models (LSM) generally consider isolated soil columns and free drainage lower boundary condition for simulating hydrology. This is mainly due to the fact that incorporating detailed groundwater dynamics in LSMs usually requires considerable computing resources, especially for large-scale applications (e.g., continental to global). Yet, these simplifications undermine the potential effect of groundwater dynamics on land surface mass and energy fluxes. In this study, we present a novel approach of representing high-resolution groundwater dynamics in LSMs that is computationally efficient for large-scale applications. This new parameterization is incorporated in the Joint UK Land Environment Simulator (JULES) and tested at the continental-scale.

Localization Algorithm Based on a Spring Model (LASM) for Large Scale Wireless Sensor Networks.

PubMed

Chen, Wanming; Mei, Tao; Meng, Max Q-H; Liang, Huawei; Liu, Yumei; Li, Yangming; Li, Shuai

2008-03-15

A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM) method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1) for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

Maestro: an orchestration framework for large-scale WSN simulations.

PubMed

Riliskis, Laurynas; Osipov, Evgeny

2014-03-18

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation.

Maestro: An Orchestration Framework for Large-Scale WSN Simulations

PubMed Central

Riliskis, Laurynas; Osipov, Evgeny

2014-01-01

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation. PMID:24647123

Advances and trends in computational structural mechanics

NASA Technical Reports Server (NTRS)

Noor, A. K.

1986-01-01

Recent developments in computational structural mechanics are reviewed with reference to computational needs for future structures technology, advances in computational models for material behavior, discrete element technology, assessment and control of numerical simulations of structural response, hybrid analysis, and techniques for large-scale optimization. Research areas in computational structural mechanics which have high potential for meeting future technological needs are identified. These include prediction and analysis of the failure of structural components made of new materials, development of computational strategies and solution methodologies for large-scale structural calculations, and assessment of reliability and adaptive improvement of response predictions.

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

Ultra-Scale Computing for Emergency Evacuation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhaduri, Budhendra L; Nutaro, James J; Liu, Cheng

2010-01-01

Emergency evacuations are carried out in anticipation of a disaster such as hurricane landfall or flooding, and in response to a disaster that strikes without a warning. Existing emergency evacuation modeling and simulation tools are primarily designed for evacuation planning and are of limited value in operational support for real time evacuation management. In order to align with desktop computing, these models reduce the data and computational complexities through simple approximations and representations of real network conditions and traffic behaviors, which rarely represent real-world scenarios. With the emergence of high resolution physiographic, demographic, and socioeconomic data and supercomputing platforms, itmore » is possible to develop micro-simulation based emergency evacuation models that can foster development of novel algorithms for human behavior and traffic assignments, and can simulate evacuation of millions of people over a large geographic area. However, such advances in evacuation modeling and simulations demand computational capacity beyond the desktop scales and can be supported by high performance computing platforms. This paper explores the motivation and feasibility of ultra-scale computing for increasing the speed of high resolution emergency evacuation simulations.« less

Reversible Parallel Discrete-Event Execution of Large-scale Epidemic Outbreak Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Seal, Sudip K

2010-01-01

The spatial scale, runtime speed and behavioral detail of epidemic outbreak simulations together require the use of large-scale parallel processing. In this paper, an optimistic parallel discrete event execution of a reaction-diffusion simulation model of epidemic outbreaks is presented, with an implementation over themore » $$\\mu$$sik simulator. Rollback support is achieved with the development of a novel reversible model that combines reverse computation with a small amount of incremental state saving. Parallel speedup and other runtime performance metrics of the simulation are tested on a small (8,192-core) Blue Gene / P system, while scalability is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes (up to several hundred million individuals in the largest case) are exercised.« less

A Science Cloud: OneSpaceNet

NASA Astrophysics Data System (ADS)

Morikawa, Y.; Murata, K. T.; Watari, S.; Kato, H.; Yamamoto, K.; Inoue, S.; Tsubouchi, K.; Fukazawa, K.; Kimura, E.; Tatebe, O.; Shimojo, S.

2010-12-01

Main methodologies of Solar-Terrestrial Physics (STP) so far are theoretical, experimental and observational, and computer simulation approaches. Recently "informatics" is expected as a new (fourth) approach to the STP studies. Informatics is a methodology to analyze large-scale data (observation data and computer simulation data) to obtain new findings using a variety of data processing techniques. At NICT (National Institute of Information and Communications Technology, Japan) we are now developing a new research environment named "OneSpaceNet". The OneSpaceNet is a cloud-computing environment specialized for science works, which connects many researchers with high-speed network (JGN: Japan Gigabit Network). The JGN is a wide-area back-born network operated by NICT; it provides 10G network and many access points (AP) over Japan. The OneSpaceNet also provides with rich computer resources for research studies, such as super-computers, large-scale data storage area, licensed applications, visualization devices (like tiled display wall: TDW), database/DBMS, cluster computers (4-8 nodes) for data processing and communication devices. What is amazing in use of the science cloud is that a user simply prepares a terminal (low-cost PC). Once connecting the PC to JGN2plus, the user can make full use of the rich resources of the science cloud. Using communication devices, such as video-conference system, streaming and reflector servers, and media-players, the users on the OneSpaceNet can make research communications as if they belong to a same (one) laboratory: they are members of a virtual laboratory. The specification of the computer resources on the OneSpaceNet is as follows: The size of data storage we have developed so far is almost 1PB. The number of the data files managed on the cloud storage is getting larger and now more than 40,000,000. What is notable is that the disks forming the large-scale storage are distributed to 5 data centers over Japan (but the storage system performs as one disk). There are three supercomputers allocated on the cloud, one from Tokyo, one from Osaka and the other from Nagoya. One's simulation job data on any supercomputers are saved on the cloud data storage (same directory); it is a kind of virtual computing environment. The tiled display wall has 36 panels acting as one display; the pixel (resolution) size of it is as large as 18000x4300. This size is enough to preview or analyze the large-scale computer simulation data. It also allows us to take a look of multiple (e.g., 100 pictures) on one screen together with many researchers. In our talk we also present a brief report of the initial results using the OneSpaceNet for Global MHD simulations as an example of successful use of our science cloud; (i) Ultra-high time resolution visualization of Global MHD simulations on the large-scale storage and parallel processing system on the cloud, (ii) Database of real-time Global MHD simulation and statistic analyses of the data, and (iii) 3D Web service of Global MHD simulations.

Implementing Parquet equations using HPX

NASA Astrophysics Data System (ADS)

Kellar, Samuel; Wagle, Bibek; Yang, Shuxiang; Tam, Ka-Ming; Kaiser, Hartmut; Moreno, Juana; Jarrell, Mark

A new C++ runtime system (HPX) enables simulations of complex systems to run more efficiently on parallel and heterogeneous systems. This increased efficiency allows for solutions to larger simulations of the parquet approximation for a system with impurities. The relevancy of the parquet equations depends upon the ability to solve systems which require long runs and large amounts of memory. These limitations, in addition to numerical complications arising from stability of the solutions, necessitate running on large distributed systems. As the computational resources trend towards the exascale and the limitations arising from computational resources vanish efficiency of large scale simulations becomes a focus. HPX facilitates efficient simulations through intelligent overlapping of computation and communication. Simulations such as the parquet equations which require the transfer of large amounts of data should benefit from HPX implementations. Supported by the the NSF EPSCoR Cooperative Agreement No. EPS-1003897 with additional support from the Louisiana Board of Regents.

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

DOE PAGES

Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; ...

2013-01-01

Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determinedmore » the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.« less

Multi-scale simulations of space problems with iPIC3D

NASA Astrophysics Data System (ADS)

Lapenta, Giovanni; Bettarini, Lapo; Markidis, Stefano

The implicit Particle-in-Cell method for the computer simulation of space plasma, and its im-plementation in a three-dimensional parallel code, called iPIC3D, are presented. The implicit integration in time of the Vlasov-Maxwell system removes the numerical stability constraints and enables kinetic plasma simulations at magnetohydrodynamics scales. Simulations of mag-netic reconnection in plasma are presented to show the effectiveness of the algorithm. In particular we will show a number of simulations done for large scale 3D systems using the physical mass ratio for Hydrogen. Most notably one simulation treats kinetically a box of tens of Earth radii in each direction and was conducted using about 16000 processors of the Pleiades NASA computer. The work is conducted in collaboration with the MMS-IDS theory team from University of Colorado (M. Goldman, D. Newman and L. Andersson). Reference: Stefano Markidis, Giovanni Lapenta, Rizwan-uddin Multi-scale simulations of plasma with iPIC3D Mathematics and Computers in Simulation, Available online 17 October 2009, http://dx.doi.org/10.1016/j.matcom.2009.08.038

Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model

NASA Astrophysics Data System (ADS)

Kumar, M.; Duffy, C.

2006-05-01

Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and complexity associated with these model increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with limited number of physical processes needs lesser computational load. But this negatively affects the accuracy of model results and restricts physical realization of the problem. So it is imperative to have an integrated modeling strategy (a) which can be universally applied at various scales in order to study the tradeoffs between computational complexity (determined by spatio- temporal resolution), accuracy and predictive uncertainty in relation to various approximations of physical processes (b) which can be applied at adaptively different spatial scales in the same domain by taking into account the local heterogeneity of topography and hydrogeologic variables c) which is flexible enough to incorporate different number and approximation of process equations depending on model purpose and computational constraint. An efficient implementation of this strategy becomes all the more important for Great Salt Lake river basin which is relatively large (~89000 sq. km) and complex in terms of hydrologic and geomorphic conditions. Also the types and the time scales of hydrologic processes which are dominant in different parts of basin are different. Part of snow melt runoff generated in the Uinta Mountains infiltrates and contributes as base flow to the Great Salt Lake over a time scale of decades to centuries. The adaptive strategy helps capture the steep topographic and climatic gradient along the Wasatch front. Here we present the aforesaid modeling strategy along with an associated hydrologic modeling framework which facilitates a seamless, computationally efficient and accurate integration of the process model with the data model. The flexibility of this framework leads to implementation of multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations with least computational burden. However, performing these simulations and related calibration of these models over a large basin at higher spatio- temporal resolutions is computationally intensive and requires use of increasing computing power. With the advent of parallel processing architectures, high computing performance can be achieved by parallelization of existing serial integrated-hydrologic-model code. This translates to running the same model simulation on a network of large number of processors thereby reducing the time needed to obtain solution. The paper also discusses the implementation of the integrated model on parallel processors. Also will be discussed the mapping of the problem on multi-processor environment, method to incorporate coupling between hydrologic processes using interprocessor communication models, model data structure and parallel numerical algorithms to obtain high performance.

Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.

PubMed

Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L

2002-09-01

We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.

Large-eddy simulations of compressible convection on massively parallel computers. [stellar physics

NASA Technical Reports Server (NTRS)

Xie, Xin; Toomre, Juri

1993-01-01

We report preliminary implementation of the large-eddy simulation (LES) technique in 2D simulations of compressible convection carried out on the CM-2 massively parallel computer. The convective flow fields in our simulations possess structures similar to those found in a number of direct simulations, with roll-like flows coherent across the entire depth of the layer that spans several density scale heights. Our detailed assessment of the effects of various subgrid scale (SGS) terms reveals that they may affect the gross character of convection. Yet, somewhat surprisingly, we find that our LES solutions, and another in which the SGS terms are turned off, only show modest differences. The resulting 2D flows realized here are rather laminar in character, and achieving substantial turbulence may require stronger forcing and less dissipation.

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

Collins, W. D.; Johansen, H.; Evans, K. J.; ...

2015-06-01

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Quake Final Video

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

Critical infrastructures of the world are at constant risks for earthquakes. Most of these critical structures are designed using archaic, seismic, simulation methods that were built from early digital computers from the 1970s. Idaho National Laboratory’s Seismic Research Group are working to modernize the simulation methods through computational research and large-scale laboratory experiments.

Advances in Parallelization for Large Scale Oct-Tree Mesh Generation

NASA Technical Reports Server (NTRS)

O'Connell, Matthew; Karman, Steve L.

2015-01-01

Despite great advancements in the parallelization of numerical simulation codes over the last 20 years, it is still common to perform grid generation in serial. Generating large scale grids in serial often requires using special "grid generation" compute machines that can have more than ten times the memory of average machines. While some parallel mesh generation techniques have been proposed, generating very large meshes for LES or aeroacoustic simulations is still a challenging problem. An automated method for the parallel generation of very large scale off-body hierarchical meshes is presented here. This work enables large scale parallel generation of off-body meshes by using a novel combination of parallel grid generation techniques and a hybrid "top down" and "bottom up" oct-tree method. Meshes are generated using hardware commonly found in parallel compute clusters. The capability to generate very large meshes is demonstrated by the generation of off-body meshes surrounding complex aerospace geometries. Results are shown including a one billion cell mesh generated around a Predator Unmanned Aerial Vehicle geometry, which was generated on 64 processors in under 45 minutes.

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Large Eddy Simulation of a Turbulent Jet

NASA Technical Reports Server (NTRS)

Webb, A. T.; Mansour, Nagi N.

2001-01-01

Here we present the results of a Large Eddy Simulation of a non-buoyant jet issuing from a circular orifice in a wall, and developing in neutral surroundings. The effects of the subgrid scales on the large eddies have been modeled with the dynamic large eddy simulation model applied to the fully 3D domain in spherical coordinates. The simulation captures the unsteady motions of the large-scales within the jet as well as the laminar motions in the entrainment region surrounding the jet. The computed time-averaged statistics (mean velocity, concentration, and turbulence parameters) compare well with laboratory data without invoking an empirical entrainment coefficient as employed by line integral models. The use of the large eddy simulation technique allows examination of unsteady and inhomogeneous features such as the evolution of eddies and the details of the entrainment process.

Software Engineering for Scientific Computer Simulations

NASA Astrophysics Data System (ADS)

Post, Douglass E.; Henderson, Dale B.; Kendall, Richard P.; Whitney, Earl M.

2004-11-01

Computer simulation is becoming a very powerful tool for analyzing and predicting the performance of fusion experiments. Simulation efforts are evolving from including only a few effects to many effects, from small teams with a few people to large teams, and from workstations and small processor count parallel computers to massively parallel platforms. Successfully making this transition requires attention to software engineering issues. We report on the conclusions drawn from a number of case studies of large scale scientific computing projects within DOE, academia and the DoD. The major lessons learned include attention to sound project management including setting reasonable and achievable requirements, building a good code team, enforcing customer focus, carrying out verification and validation and selecting the optimum computational mathematics approaches.

WarpIV: In situ visualization and analysis of ion accelerator simulations

DOE PAGES

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc; ...

2016-05-09

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

Accelerating large-scale simulation of seismic wave propagation by multi-GPUs and three-dimensional domain decomposition

NASA Astrophysics Data System (ADS)

Okamoto, Taro; Takenaka, Hiroshi; Nakamura, Takeshi; Aoki, Takayuki

2010-12-01

We adopted the GPU (graphics processing unit) to accelerate the large-scale finite-difference simulation of seismic wave propagation. The simulation can benefit from the high-memory bandwidth of GPU because it is a "memory intensive" problem. In a single-GPU case we achieved a performance of about 56 GFlops, which was about 45-fold faster than that achieved by a single core of the host central processing unit (CPU). We confirmed that the optimized use of fast shared memory and registers were essential for performance. In the multi-GPU case with three-dimensional domain decomposition, the non-contiguous memory alignment in the ghost zones was found to impose quite long time in data transfer between GPU and the host node. This problem was solved by using contiguous memory buffers for ghost zones. We achieved a performance of about 2.2 TFlops by using 120 GPUs and 330 GB of total memory: nearly (or more than) 2200 cores of host CPUs would be required to achieve the same performance. The weak scaling was nearly proportional to the number of GPUs. We therefore conclude that GPU computing for large-scale simulation of seismic wave propagation is a promising approach as a faster simulation is possible with reduced computational resources compared to CPUs.

Optical correlator using very-large-scale integrated circuit/ferroelectric-liquid-crystal electrically addressed spatial light modulators

NASA Technical Reports Server (NTRS)

Turner, Richard M.; Jared, David A.; Sharp, Gary D.; Johnson, Kristina M.

1993-01-01

The use of 2-kHz 64 x 64 very-large-scale integrated circuit/ferroelectric-liquid-crystal electrically addressed spatial light modulators as the input and filter planes of a VanderLugt-type optical correlator is discussed. Liquid-crystal layer thickness variations that are present in the devices are analyzed, and the effects on correlator performance are investigated through computer simulations. Experimental results from the very-large-scale-integrated / ferroelectric-liquid-crystal optical-correlator system are presented and are consistent with the level of performance predicted by the simulations.

Computational aerodynamics development and outlook /Dryden Lecture in Research for 1979/

NASA Technical Reports Server (NTRS)

Chapman, D. R.

1979-01-01

Some past developments and current examples of computational aerodynamics are briefly reviewed. An assessment is made of the requirements on future computer memory and speed imposed by advanced numerical simulations, giving emphasis to the Reynolds averaged Navier-Stokes equations and to turbulent eddy simulations. Experimental scales of turbulence structure are used to determine the mesh spacings required to adequately resolve turbulent energy and shear. Assessment also is made of the changing market environment for developing future large computers, and of the projections of micro-electronics memory and logic technology that affect future computer capability. From the two assessments, estimates are formed of the future time scale in which various advanced types of aerodynamic flow simulations could become feasible. Areas of research judged especially relevant to future developments are noted.

Hydrodynamic Simulations and Tomographic Reconstructions of the Intergalactic Medium

NASA Astrophysics Data System (ADS)

Stark, Casey William

The Intergalactic Medium (IGM) is the dominant reservoir of matter in the Universe from which the cosmic web and galaxies form. The structure and physical state of the IGM provides insight into the cosmological model of the Universe, the origin and timeline of the reionization of the Universe, as well as being an essential ingredient in our understanding of galaxy formation and evolution. Our primary handle on this information is a signal known as the Lyman-alpha forest (or Ly-alpha forest) -- the collection of absorption features in high-redshift sources due to intervening neutral hydrogen, which scatters HI Ly-alpha photons out of the line of sight. The Ly-alpha forest flux traces density fluctuations at high redshift and at moderate overdensities, making it an excellent tool for mapping large-scale structure and constraining cosmological parameters. Although the computational methodology for simulating the Ly-alpha forest has existed for over a decade, we are just now approaching the scale of computing power required to simultaneously capture large cosmological scales and the scales of the smallest absorption systems. My thesis focuses on using simulations at the edge of modern computing to produce precise predictions of the statistics of the Ly-alpha forest and to better understand the structure of the IGM. In the first part of my thesis, I review the state of hydrodynamic simulations of the IGM, including pitfalls of the existing under-resolved simulations. Our group developed a new cosmological hydrodynamics code to tackle the computational challenge, and I developed a distributed analysis framework to compute flux statistics from our simulations. I present flux statistics derived from a suite of our large hydrodynamic simulations and demonstrate convergence to the per cent level. I also compare flux statistics derived from simulations using different discretizations and hydrodynamic schemes (Eulerian finite volume vs. smoothed particle hydrodynamics) and discuss differences in their convergence behavior, their overall agreement, and the implications for cosmological constraints. In the second part of my thesis, I present a tomographic reconstruction method that allows us to make 3D maps of the IGM with Mpc resolution. In order to make reconstructions of large surveys computationally feasible, I developed a new Wiener Filter application with an algorithm specialized to our problem, which significantly reduces the space and time complexity compared to previous implementations. I explore two scientific applications of the maps: finding protoclusters by searching the maps for large, contiguous regions of low flux and finding cosmic voids by searching the maps for regions of high flux. Using a large N-body simulation, I identify and characterize both protoclusters and voids at z = 2.5, in the middle of the redshift range being mapped by ongoing surveys. I provide simple methods for identifying protocluster and void candidates in the tomographic flux maps, and then test them on mock surveys and reconstructions. I present forecasts for sample purity and completeness and other scientific applications of these large, high-redshift objects.

Tracking of large-scale structures in turbulent channel with direct numerical simulation of low Prandtl number passive scalar

NASA Astrophysics Data System (ADS)

Tiselj, Iztok

2014-12-01

Channel flow DNS (Direct Numerical Simulation) at friction Reynolds number 180 and with passive scalars of Prandtl numbers 1 and 0.01 was performed in various computational domains. The "normal" size domain was ˜2300 wall units long and ˜750 wall units wide; size taken from the similar DNS of Moser et al. The "large" computational domain, which is supposed to be sufficient to describe the largest structures of the turbulent flows was 3 times longer and 3 times wider than the "normal" domain. The "very large" domain was 6 times longer and 6 times wider than the "normal" domain. All simulations were performed with the same spatial and temporal resolution. Comparison of the standard and large computational domains shows the velocity field statistics (mean velocity, root-mean-square (RMS) fluctuations, and turbulent Reynolds stresses) that are within 1%-2%. Similar agreement is observed for Pr = 1 temperature fields and can be observed also for the mean temperature profiles at Pr = 0.01. These differences can be attributed to the statistical uncertainties of the DNS. However, second-order moments, i.e., RMS temperature fluctuations of standard and large computational domains at Pr = 0.01 show significant differences of up to 20%. Stronger temperature fluctuations in the "large" and "very large" domains confirm the existence of the large-scale structures. Their influence is more or less invisible in the main velocity field statistics or in the statistics of the temperature fields at Prandtl numbers around 1. However, these structures play visible role in the temperature fluctuations at low Prandtl number, where high temperature diffusivity effectively smears the small-scale structures in the thermal field and enhances the relative contribution of large-scales. These large thermal structures represent some kind of an echo of the large scale velocity structures: the highest temperature-velocity correlations are not observed between the instantaneous temperatures and instantaneous streamwise velocities, but between the instantaneous temperatures and velocities averaged over certain time interval.

epiDMS: Data Management and Analytics for Decision-Making From Epidemic Spread Simulation Ensembles.

PubMed

Liu, Sicong; Poccia, Silvestro; Candan, K Selçuk; Chowell, Gerardo; Sapino, Maria Luisa

2016-12-01

Carefully calibrated large-scale computational models of epidemic spread represent a powerful tool to support the decision-making process during epidemic emergencies. Epidemic models are being increasingly used for generating forecasts of the spatial-temporal progression of epidemics at different spatial scales and for assessing the likely impact of different intervention strategies. However, the management and analysis of simulation ensembles stemming from large-scale computational models pose challenges, particularly when dealing with multiple interdependent parameters, spanning multiple layers and geospatial frames, affected by complex dynamic processes operating at different resolutions. We describe and illustrate with examples a novel epidemic simulation data management system, epiDMS, that was developed to address the challenges that arise from the need to generate, search, visualize, and analyze, in a scalable manner, large volumes of epidemic simulation ensembles and observations during the progression of an epidemic. epiDMS is a publicly available system that facilitates management and analysis of large epidemic simulation ensembles. epiDMS aims to fill an important hole in decision-making during healthcare emergencies by enabling critical services with significant economic and health impact. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

OpenMP parallelization of a gridded SWAT (SWATG)

NASA Astrophysics Data System (ADS)

Zhang, Ying; Hou, Jinliang; Cao, Yongpan; Gu, Juan; Huang, Chunlin

2017-12-01

Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.

The Numerical Propulsion System Simulation: An Overview

NASA Technical Reports Server (NTRS)

Lytle, John K.

2000-01-01

Advances in computational technology and in physics-based modeling are making large-scale, detailed simulations of complex systems possible within the design environment. For example, the integration of computing, communications, and aerodynamics has reduced the time required to analyze major propulsion system components from days and weeks to minutes and hours. This breakthrough has enabled the detailed simulation of major propulsion system components to become a routine part of designing systems, providing the designer with critical information about the components early in the design process. This paper describes the development of the numerical propulsion system simulation (NPSS), a modular and extensible framework for the integration of multicomponent and multidisciplinary analysis tools using geographically distributed resources such as computing platforms, data bases, and people. The analysis is currently focused on large-scale modeling of complete aircraft engines. This will provide the product developer with a "virtual wind tunnel" that will reduce the number of hardware builds and tests required during the development of advanced aerospace propulsion systems.

Lightweight computational steering of very large scale molecular dynamics simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beazley, D.M.; Lomdahl, P.S.

1996-09-01

We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show howmore » this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages.« less

Simulation framework for intelligent transportation systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ewing, T.; Doss, E.; Hanebutte, U.

1996-10-01

A simulation framework has been developed for a large-scale, comprehensive, scaleable simulation of an Intelligent Transportation System (ITS). The simulator is designed for running on parallel computers and distributed (networked) computer systems, but can run on standalone workstations for smaller simulations. The simulator currently models instrumented smart vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide two-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphicalmore » user interfaces to support human-factors studies. Realistic modeling of variations of the posted driving speed are based on human factors studies that take into consideration weather, road conditions, driver personality and behavior, and vehicle type. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on parallel computers, such as ANL`s IBM SP-2, for large-scale problems. A novel feature of the approach is that vehicles are represented by autonomous computer processes which exchange messages with other processes. The vehicles have a behavior model which governs route selection and driving behavior, and can react to external traffic events much like real vehicles. With this approach, the simulation is scaleable to take advantage of emerging massively parallel processor (MPP) systems.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

PubMed Central

Montes, Jesus; Gomez, Elena; Merchán-Pérez, Angel; DeFelipe, Javier; Peña, Jose-Maria

2013-01-01

Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is therefore an excellent tool for multi-scale simulations. PMID:23894367

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU

PubMed Central

Xia, Yong; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations. PMID:26581957

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU.

PubMed

Xia, Yong; Wang, Kuanquan; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations.

HRLSim: a high performance spiking neural network simulator for GPGPU clusters.

PubMed

Minkovich, Kirill; Thibeault, Corey M; O'Brien, Michael John; Nogin, Aleksey; Cho, Youngkwan; Srinivasa, Narayan

2014-02-01

Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called HRL Spiking Simulator (HRLSim). This simulator is suitable for implementation on a cluster of general purpose graphical processing units (GPGPUs). Novel aspects of HRLSim are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive GPGPU cards and compute power, HRLSim offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.

Delivering better power: the role of simulation in reducing the environmental impact of aircraft engines.

PubMed

Menzies, Kevin

2014-08-13

The growth in simulation capability over the past 20 years has led to remarkable changes in the design process for gas turbines. The availability of relatively cheap computational power coupled to improvements in numerical methods and physical modelling in simulation codes have enabled the development of aircraft propulsion systems that are more powerful and yet more efficient than ever before. However, the design challenges are correspondingly greater, especially to reduce environmental impact. The simulation requirements to achieve a reduced environmental impact are described along with the implications of continued growth in available computational power. It is concluded that achieving the environmental goals will demand large-scale multi-disciplinary simulations requiring significantly increased computational power, to enable optimization of the airframe and propulsion system over the entire operational envelope. However even with massive parallelization, the limits imposed by communications latency will constrain the time required to achieve a solution, and therefore the position of such large-scale calculations in the industrial design process. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Generation of dense granular deposits for porosity analysis: assessment and application of large-scale non-smooth granular dynamics

NASA Astrophysics Data System (ADS)

Schruff, T.; Liang, R.; Rüde, U.; Schüttrumpf, H.; Frings, R. M.

2018-01-01

The knowledge of structural properties of granular materials such as porosity is highly important in many application-oriented and scientific fields. In this paper we present new results of computer-based packing simulations where we use the non-smooth granular dynamics (NSGD) method to simulate gravitational random dense packing of spherical particles with various particle size distributions and two types of depositional conditions. A bin packing scenario was used to compare simulation results to laboratory porosity measurements and to quantify the sensitivity of the NSGD regarding critical simulation parameters such as time step size. The results of the bin packing simulations agree well with laboratory measurements across all particle size distributions with all absolute errors below 1%. A large-scale packing scenario with periodic side walls was used to simulate the packing of up to 855,600 spherical particles with various particle size distributions (PSD). Simulation outcomes are used to quantify the effect of particle-domain-size ratio on the packing compaction. A simple correction model, based on the coordination number, is employed to compensate for this effect on the porosity and to determine the relationship between PSD and porosity. Promising accuracy and stability results paired with excellent computational performance recommend the application of NSGD for large-scale packing simulations, e.g. to further enhance the generation of representative granular deposits.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

Scaling up to address data science challenges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendelberger, Joanne R.

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Scaling up to address data science challenges

DOE PAGES

Wendelberger, Joanne R.

2017-04-27

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

A 100,000 Scale Factor Radar Range.

PubMed

Blanche, Pierre-Alexandre; Neifeld, Mark; Peyghambarian, Nasser

2017-12-19

The radar cross section of an object is an important electromagnetic property that is often measured in anechoic chambers. However, for very large and complex structures such as ships or sea and land clutters, this common approach is not practical. The use of computer simulations is also not viable since it would take many years of computational time to model and predict the radar characteristics of such large objects. We have now devised a new scaling technique to overcome these difficulties, and make accurate measurements of the radar cross section of large items. In this article we demonstrate that by reducing the scale of the model by a factor 100,000, and using near infrared wavelength, the radar cross section can be determined in a tabletop setup. The accuracy of the method is compared to simulations, and an example of measurement is provided on a 1 mm highly detailed model of a ship. The advantages of this scaling approach is its versatility, and the possibility to perform fast, convenient, and inexpensive measurements.

Streaming parallel GPU acceleration of large-scale filter-based spiking neural networks.

PubMed

Slażyński, Leszek; Bohte, Sander

2012-01-01

The arrival of graphics processing (GPU) cards suitable for massively parallel computing promises affordable large-scale neural network simulation previously only available at supercomputing facilities. While the raw numbers suggest that GPUs may outperform CPUs by at least an order of magnitude, the challenge is to develop fine-grained parallel algorithms to fully exploit the particulars of GPUs. Computation in a neural network is inherently parallel and thus a natural match for GPU architectures: given inputs, the internal state for each neuron can be updated in parallel. We show that for filter-based spiking neurons, like the Spike Response Model, the additive nature of membrane potential dynamics enables additional update parallelism. This also reduces the accumulation of numerical errors when using single precision computation, the native precision of GPUs. We further show that optimizing simulation algorithms and data structures to the GPU's architecture has a large pay-off: for example, matching iterative neural updating to the memory architecture of the GPU speeds up this simulation step by a factor of three to five. With such optimizations, we can simulate in better-than-realtime plausible spiking neural networks of up to 50 000 neurons, processing over 35 million spiking events per second.

Linear Scaling Density Functional Calculations with Gaussian Orbitals

NASA Technical Reports Server (NTRS)

Scuseria, Gustavo E.

1999-01-01

Recent advances in linear scaling algorithms that circumvent the computational bottlenecks of large-scale electronic structure simulations make it possible to carry out density functional calculations with Gaussian orbitals on molecules containing more than 1000 atoms and 15000 basis functions using current workstations and personal computers. This paper discusses the recent theoretical developments that have led to these advances and demonstrates in a series of benchmark calculations the present capabilities of state-of-the-art computational quantum chemistry programs for the prediction of molecular structure and properties.

A class of hybrid finite element methods for electromagnetics: A review

NASA Technical Reports Server (NTRS)

Volakis, J. L.; Chatterjee, A.; Gong, J.

1993-01-01

Integral equation methods have generally been the workhorse for antenna and scattering computations. In the case of antennas, they continue to be the prominent computational approach, but for scattering applications the requirement for large-scale computations has turned researchers' attention to near neighbor methods such as the finite element method, which has low O(N) storage requirements and is readily adaptable in modeling complex geometrical features and material inhomogeneities. In this paper, we review three hybrid finite element methods for simulating composite scatterers, conformal microstrip antennas, and finite periodic arrays. Specifically, we discuss the finite element method and its application to electromagnetic problems when combined with the boundary integral, absorbing boundary conditions, and artificial absorbers for terminating the mesh. Particular attention is given to large-scale simulations, methods, and solvers for achieving low memory requirements and code performance on parallel computing architectures.

Communication interval selection in distributed heterogeneous simulation of large-scale dynamical systems

NASA Astrophysics Data System (ADS)

Lucas, Charles E.; Walters, Eric A.; Jatskevich, Juri; Wasynczuk, Oleg; Lamm, Peter T.

2003-09-01

In this paper, a new technique useful for the numerical simulation of large-scale systems is presented. This approach enables the overall system simulation to be formed by the dynamic interconnection of the various interdependent simulations, each representing a specific component or subsystem such as control, electrical, mechanical, hydraulic, or thermal. Each simulation may be developed separately using possibly different commercial-off-the-shelf simulation programs thereby allowing the most suitable language or tool to be used based on the design/analysis needs. These subsystems communicate the required interface variables at specific time intervals. A discussion concerning the selection of appropriate communication intervals is presented herein. For the purpose of demonstration, this technique is applied to a detailed simulation of a representative aircraft power system, such as that found on the Joint Strike Fighter (JSF). This system is comprised of ten component models each developed using MATLAB/Simulink, EASY5, or ACSL. When the ten component simulations were distributed across just four personal computers (PCs), a greater than 15-fold improvement in simulation speed (compared to the single-computer implementation) was achieved.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Computational study of 3-D hot-spot initiation in shocked insensitive high-explosive

NASA Astrophysics Data System (ADS)

Najjar, F. M.; Howard, W. M.; Fried, L. E.; Manaa, M. R.; Nichols, A., III; Levesque, G.

2012-03-01

High-explosive (HE) material consists of large-sized grains with micron-sized embedded impurities and pores. Under various mechanical/thermal insults, these pores collapse generating hightemperature regions leading to ignition. A hydrodynamic study has been performed to investigate the mechanisms of pore collapse and hot spot initiation in TATB crystals, employing a multiphysics code, ALE3D, coupled to the chemistry module, Cheetah. This computational study includes reactive dynamics. Two-dimensional high-resolution large-scale meso-scale simulations have been performed. The parameter space is systematically studied by considering various shock strengths, pore diameters and multiple pore configurations. Preliminary 3-D simulations are undertaken to quantify the 3-D dynamics.

LASSIE: simulating large-scale models of biochemical systems on GPUs.

PubMed

Tangherloni, Andrea; Nobile, Marco S; Besozzi, Daniela; Mauri, Giancarlo; Cazzaniga, Paolo

2017-05-10

Mathematical modeling and in silico analysis are widely acknowledged as complementary tools to biological laboratory methods, to achieve a thorough understanding of emergent behaviors of cellular processes in both physiological and perturbed conditions. Though, the simulation of large-scale models-consisting in hundreds or thousands of reactions and molecular species-can rapidly overtake the capabilities of Central Processing Units (CPUs). The purpose of this work is to exploit alternative high-performance computing solutions, such as Graphics Processing Units (GPUs), to allow the investigation of these models at reduced computational costs. LASSIE is a "black-box" GPU-accelerated deterministic simulator, specifically designed for large-scale models and not requiring any expertise in mathematical modeling, simulation algorithms or GPU programming. Given a reaction-based model of a cellular process, LASSIE automatically generates the corresponding system of Ordinary Differential Equations (ODEs), assuming mass-action kinetics. The numerical solution of the ODEs is obtained by automatically switching between the Runge-Kutta-Fehlberg method in the absence of stiffness, and the Backward Differentiation Formulae of first order in presence of stiffness. The computational performance of LASSIE are assessed using a set of randomly generated synthetic reaction-based models of increasing size, ranging from 64 to 8192 reactions and species, and compared to a CPU-implementation of the LSODA numerical integration algorithm. LASSIE adopts a novel fine-grained parallelization strategy to distribute on the GPU cores all the calculations required to solve the system of ODEs. By virtue of this implementation, LASSIE achieves up to 92× speed-up with respect to LSODA, therefore reducing the running time from approximately 1 month down to 8 h to simulate models consisting in, for instance, four thousands of reactions and species. Notably, thanks to its smaller memory footprint, LASSIE is able to perform fast simulations of even larger models, whereby the tested CPU-implementation of LSODA failed to reach termination. LASSIE is therefore expected to make an important breakthrough in Systems Biology applications, for the execution of faster and in-depth computational analyses of large-scale models of complex biological systems.

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Li, Xiaoye; Heber, Gerd; Biswas, Rupak

2000-01-01

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Parallel computing in enterprise modeling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldsby, Michael E.; Armstrong, Robert C.; Shneider, Max S.

2008-08-01

This report presents the results of our efforts to apply high-performance computing to entity-based simulations with a multi-use plugin for parallel computing. We use the term 'Entity-based simulation' to describe a class of simulation which includes both discrete event simulation and agent based simulation. What simulations of this class share, and what differs from more traditional models, is that the result sought is emergent from a large number of contributing entities. Logistic, economic and social simulations are members of this class where things or people are organized or self-organize to produce a solution. Entity-based problems never have an a priorimore » ergodic principle that will greatly simplify calculations. Because the results of entity-based simulations can only be realized at scale, scalable computing is de rigueur for large problems. Having said that, the absence of a spatial organizing principal makes the decomposition of the problem onto processors problematic. In addition, practitioners in this domain commonly use the Java programming language which presents its own problems in a high-performance setting. The plugin we have developed, called the Parallel Particle Data Model, overcomes both of these obstacles and is now being used by two Sandia frameworks: the Decision Analysis Center, and the Seldon social simulation facility. While the ability to engage U.S.-sized problems is now available to the Decision Analysis Center, this plugin is central to the success of Seldon. Because Seldon relies on computationally intensive cognitive sub-models, this work is necessary to achieve the scale necessary for realistic results. With the recent upheavals in the financial markets, and the inscrutability of terrorist activity, this simulation domain will likely need a capability with ever greater fidelity. High-performance computing will play an important part in enabling that greater fidelity.« less

Performance of an MPI-only semiconductor device simulator on a quad socket/quad core InfiniBand platform.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shadid, John Nicolas; Lin, Paul Tinphone

2009-01-01

This preliminary study considers the scaling and performance of a finite element (FE) semiconductor device simulator on a capacity cluster with 272 compute nodes based on a homogeneous multicore node architecture utilizing 16 cores. The inter-node communication backbone for this Tri-Lab Linux Capacity Cluster (TLCC) machine is comprised of an InfiniBand interconnect. The nonuniform memory access (NUMA) nodes consist of 2.2 GHz quad socket/quad core AMD Opteron processors. The performance results for this study are obtained with a FE semiconductor device simulation code (Charon) that is based on a fully-coupled Newton-Krylov solver with domain decomposition and multilevel preconditioners. Scaling andmore » multicore performance results are presented for large-scale problems of 100+ million unknowns on up to 4096 cores. A parallel scaling comparison is also presented with the Cray XT3/4 Red Storm capability platform. The results indicate that an MPI-only programming model for utilizing the multicore nodes is reasonably efficient on all 16 cores per compute node. However, the results also indicated that the multilevel preconditioner, which is critical for large-scale capability type simulations, scales better on the Red Storm machine than the TLCC machine.« less

Simulating Microbial Community Patterning Using Biocellion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Seung-Hwa; Kahan, Simon H.; Momeni, Babak

2014-04-17

Mathematical modeling and computer simulation are important tools for understanding complex interactions between cells and their biotic and abiotic environment: similarities and differences between modeled and observed behavior provide the basis for hypothesis forma- tion. Momeni et al. [5] investigated pattern formation in communities of yeast strains engaging in different types of ecological interactions, comparing the predictions of mathematical modeling and simulation to actual patterns observed in wet-lab experiments. However, simu- lations of millions of cells in a three-dimensional community are ex- tremely time-consuming. One simulation run in MATLAB may take a week or longer, inhibiting exploration of the vastmore » space of parameter combinations and assumptions. Improving the speed, scale, and accu- racy of such simulations facilitates hypothesis formation and expedites discovery. Biocellion is a high performance software framework for ac- celerating discrete agent-based simulation of biological systems with millions to trillions of cells. Simulations of comparable scale and accu- racy to those taking a week of computer time using MATLAB require just hours using Biocellion on a multicore workstation. Biocellion fur- ther accelerates large scale, high resolution simulations using cluster computers by partitioning the work to run on multiple compute nodes. Biocellion targets computational biologists who have mathematical modeling backgrounds and basic C++ programming skills. This chap- ter describes the necessary steps to adapt the original Momeni et al.'s model to the Biocellion framework as a case study.« less

Simulations of turbulent rotating flows using a subfilter scale stress model derived from the partially integrated transport modeling method

NASA Astrophysics Data System (ADS)

Chaouat, Bruno

2012-04-01

The partially integrated transport modeling (PITM) method [B. Chaouat and R. Schiestel, "A new partially integrated transport model for subgrid-scale stresses and dissipation rate for turbulent developing flows," Phys. Fluids 17, 065106 (2005), 10.1063/1.1928607; R. Schiestel and A. Dejoan, "Towards a new partially integrated transport model for coarse grid and unsteady turbulent flow simulations," Theor. Comput. Fluid Dyn. 18, 443 (2005), 10.1007/s00162-004-0155-z; B. Chaouat and R. Schiestel, "From single-scale turbulence models to multiple-scale and subgridscale models by Fourier transform," Theor. Comput. Fluid Dyn. 21, 201 (2007), 10.1007/s00162-007-0044-3; B. Chaouat and R. Schiestel, "Progress in subgrid-scale transport modelling for continuous hybrid non-zonal RANS/LES simulations," Int. J. Heat Fluid Flow 30, 602 (2009), 10.1016/j.ijheatfluidflow.2009.02.021] viewed as a continuous approach for hybrid RANS/LES (Reynolds averaged Navier-Stoke equations/large eddy simulations) simulations with seamless coupling between RANS and LES regions is used to derive a subfilter scale stress model in the framework of second-moment closure applicable in a rotating frame of reference. This present subfilter scale model is based on the transport equations for the subfilter stresses and the dissipation rate and appears well appropriate for simulating unsteady flows on relatively coarse grids or flows with strong departure from spectral equilibrium because the cutoff wave number can be located almost anywhere inside the spectrum energy. According to the spectral theory developed in the wave number space [B. Chaouat and R. Schiestel, "From single-scale turbulence models to multiple-scale and subgrid-scale models by Fourier transform," Theor. Comput. Fluid Dyn. 21, 201 (2007), 10.1007/s00162-007-0044-3], the coefficients used in this model are no longer constants but they are some analytical functions of a dimensionless parameter controlling the spectral distribution of turbulence. The pressure-strain correlation term encompassed in this model is inspired from the nonlinear SSG model [C. G. Speziale, S. Sarkar, and T. B. Gatski, "Modelling the pressure-strain correlation of turbulence: an invariant dynamical systems approach," J. Fluid Mech. 227, 245 (1991), 10.1017/S0022112091000101] developed initially for homogeneous rotating flows in RANS methodology. It is modeled in system rotation using the principle of objectivity. Its modeling is especially extended in a low Reynolds number version for handling non-homogeneous wall flows. The present subfilter scale stress model is then used for simulating large scales of rotating turbulent flows on coarse and medium grids at moderate, medium, and high rotation rates. It is also applied to perform a simulation on a refined grid at the highest rotation rate. As a result, it is found that the PITM simulations reproduce fairly well the mean features of rotating channel flows allowing a drastic reduction of the computational cost in comparison with the one required for performing highly resolved LES. Overall, the mean velocities and turbulent stresses are found to be in good agreement with the data of highly resolved LES [E. Lamballais, O. Metais, and M. Lesieur, "Spectral-dynamic model for large-eddy simulations of turbulent rotating flow," Theor. Comput. Fluid Dyn. 12, 149 (1998)]. The anisotropy character of the flow resulting from the rotation effects is also well reproduced in accordance with the reference data. Moreover, the PITM2 simulations performed on the medium grid predict qualitatively well the three-dimensional flow structures as well as the longitudinal roll cells which appear in the anticyclonic wall-region of the rotating flows. As expected, the PITM3 simulation performed on the refined grid reverts to highly resolved LES. The present model based on a rational formulation appears to be an interesting candidate for tackling a large variety of engineering flows subjected to rotation.

Toward large eddy simulation of turbulent flow over an airfoil

NASA Technical Reports Server (NTRS)

Choi, Haecheon

1993-01-01

The flow field over an airfoil contains several distinct flow characteristics, e.g. laminar, transitional, turbulent boundary layer flow, flow separation, unstable free shear layers, and a wake. This diversity of flow regimes taxes the presently available Reynolds averaged turbulence models. Such models are generally tuned to predict a particular flow regime, and adjustments are necessary for the prediction of a different flow regime. Similar difficulties are likely to emerge when the large eddy simulation technique is applied with the widely used Smagorinsky model. This model has not been successful in correctly representing different turbulent flow fields with a single universal constant and has an incorrect near-wall behavior. Germano et al. (1991) and Ghosal, Lund & Moin have developed a new subgrid-scale model, the dynamic model, which is very promising in alleviating many of the persistent inadequacies of the Smagorinsky model: the model coefficient is computed dynamically as the calculation progresses rather than input a priori. The model has been remarkably successful in prediction of several turbulent and transitional flows. We plan to simulate turbulent flow over a '2D' airfoil using the large eddy simulation technique. Our primary objective is to assess the performance of the newly developed dynamic subgrid-scale model for computation of complex flows about aircraft components and to compare the results with those obtained using the Reynolds average approach and experiments. The present computation represents the first application of large eddy simulation to a flow of aeronautical interest and a key demonstration of the capabilities of the large eddy simulation technique.

The CP-PACS parallel computer

NASA Astrophysics Data System (ADS)

Ukawa, Akira

1998-05-01

The CP-PACS computer is a massively parallel computer consisting of 2048 processing units and having a peak speed of 614 GFLOPS and 128 GByte of main memory. It was developed over the four years from 1992 to 1996 at the Center for Computational Physics, University of Tsukuba, for large-scale numerical simulations in computational physics, especially those of lattice QCD. The CP-PACS computer has been in full operation for physics computations since October 1996. In this article we describe the chronology of the development, the hardware and software characteristics of the computer, and its performance for lattice QCD simulations.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Computer Science Techniques Applied to Parallel Atomistic Simulation

NASA Astrophysics Data System (ADS)

Nakano, Aiichiro

1998-03-01

Recent developments in parallel processing technology and multiresolution numerical algorithms have established large-scale molecular dynamics (MD) simulations as a new research mode for studying materials phenomena such as fracture. However, this requires large system sizes and long simulated times. We have developed: i) Space-time multiresolution schemes; ii) fuzzy-clustering approach to hierarchical dynamics; iii) wavelet-based adaptive curvilinear-coordinate load balancing; iv) multilevel preconditioned conjugate gradient method; and v) spacefilling-curve-based data compression for parallel I/O. Using these techniques, million-atom parallel MD simulations are performed for the oxidation dynamics of nanocrystalline Al. The simulations take into account the effect of dynamic charge transfer between Al and O using the electronegativity equalization scheme. The resulting long-range Coulomb interaction is calculated efficiently with the fast multipole method. Results for temperature and charge distributions, residual stresses, bond lengths and bond angles, and diffusivities of Al and O will be presented. The oxidation of nanocrystalline Al is elucidated through immersive visualization in virtual environments. A unique dual-degree education program at Louisiana State University will also be discussed in which students can obtain a Ph.D. in Physics & Astronomy and a M.S. from the Department of Computer Science in five years. This program fosters interdisciplinary research activities for interfacing High Performance Computing and Communications with large-scale atomistic simulations of advanced materials. This work was supported by NSF (CAREER Program), ARO, PRF, and Louisiana LEQSF.

Numerical Simulation of a High Mach Number Jet Flow

NASA Technical Reports Server (NTRS)

Hayder, M. Ehtesham; Turkel, Eli; Mankbadi, Reda R.

1993-01-01

The recent efforts to develop accurate numerical schemes for transition and turbulent flows are motivated, among other factors, by the need for accurate prediction of flow noise. The success of developing high speed civil transport plane (HSCT) is contingent upon our understanding and suppression of the jet exhaust noise. The radiated sound can be directly obtained by solving the full (time-dependent) compressible Navier-Stokes equations. However, this requires computational storage that is beyond currently available machines. This difficulty can be overcome by limiting the solution domain to the near field where the jet is nonlinear and then use acoustic analogy (e.g., Lighthill) to relate the far-field noise to the near-field sources. The later requires obtaining the time-dependent flow field. The other difficulty in aeroacoustics computations is that at high Reynolds numbers the turbulent flow has a large range of scales. Direct numerical simulations (DNS) cannot obtain all the scales of motion at high Reynolds number of technological interest. However, it is believed that the large scale structure is more efficient than the small-scale structure in radiating noise. Thus, one can model the small scales and calculate the acoustically active scales. The large scale structure in the noise-producing initial region of the jet can be viewed as a wavelike nature, the net radiated sound is the net cancellation after integration over space. As such, aeroacoustics computations are highly sensitive to errors in computing the sound sources. It is therefore essential to use a high-order numerical scheme to predict the flow field. The present paper presents the first step in a ongoing effort to predict jet noise. The emphasis here is in accurate prediction of the unsteady flow field. We solve the full time-dependent Navier-Stokes equations by a high order finite difference method. Time accurate spatial simulations of both plane and axisymmetric jet are presented. Jet Mach numbers of 1.5 and 2.1 are considered. Reynolds number in the simulations was about a million. Our numerical model is based on the 2-4 scheme by Gottlieb & Turkel. Bayliss et al. applied the 2-4 scheme in boundary layer computations. This scheme was also used by Ragab and Sheen to study the nonlinear development of supersonic instability waves in a mixing layer. In this study, we present two dimensional direct simulation results for both plane and axisymmetric jets. These results are compared with linear theory predictions. These computations were made for near nozzle exit region and velocity in spanwise/azimuthal direction was assumed to be zero.

Statistical Surrogate Modeling of Atmospheric Dispersion Events Using Bayesian Adaptive Splines

NASA Astrophysics Data System (ADS)

Francom, D.; Sansó, B.; Bulaevskaya, V.; Lucas, D. D.

2016-12-01

Uncertainty in the inputs of complex computer models, including atmospheric dispersion and transport codes, is often assessed via statistical surrogate models. Surrogate models are computationally efficient statistical approximations of expensive computer models that enable uncertainty analysis. We introduce Bayesian adaptive spline methods for producing surrogate models that capture the major spatiotemporal patterns of the parent model, while satisfying all the necessities of flexibility, accuracy and computational feasibility. We present novel methodological and computational approaches motivated by a controlled atmospheric tracer release experiment conducted at the Diablo Canyon nuclear power plant in California. Traditional methods for building statistical surrogate models often do not scale well to experiments with large amounts of data. Our approach is well suited to experiments involving large numbers of model inputs, large numbers of simulations, and functional output for each simulation. Our approach allows us to perform global sensitivity analysis with ease. We also present an approach to calibration of simulators using field data.

A fast image simulation algorithm for scanning transmission electron microscopy.

PubMed

Ophus, Colin

2017-01-01

Image simulation for scanning transmission electron microscopy at atomic resolution for samples with realistic dimensions can require very large computation times using existing simulation algorithms. We present a new algorithm named PRISM that combines features of the two most commonly used algorithms, namely the Bloch wave and multislice methods. PRISM uses a Fourier interpolation factor f that has typical values of 4-20 for atomic resolution simulations. We show that in many cases PRISM can provide a speedup that scales with f 4 compared to multislice simulations, with a negligible loss of accuracy. We demonstrate the usefulness of this method with large-scale scanning transmission electron microscopy image simulations of a crystalline nanoparticle on an amorphous carbon substrate.

A fast image simulation algorithm for scanning transmission electron microscopy

DOE PAGES

Ophus, Colin

2017-05-10

Image simulation for scanning transmission electron microscopy at atomic resolution for samples with realistic dimensions can require very large computation times using existing simulation algorithms. Here, we present a new algorithm named PRISM that combines features of the two most commonly used algorithms, namely the Bloch wave and multislice methods. PRISM uses a Fourier interpolation factor f that has typical values of 4-20 for atomic resolution simulations. We show that in many cases PRISM can provide a speedup that scales with f 4 compared to multislice simulations, with a negligible loss of accuracy. We demonstrate the usefulness of this methodmore » with large-scale scanning transmission electron microscopy image simulations of a crystalline nanoparticle on an amorphous carbon substrate.« less

Enhanced nonlinearity interval mapping scheme for high-performance simulation-optimization of watershed-scale BMP placement

NASA Astrophysics Data System (ADS)

Zou, Rui; Riverson, John; Liu, Yong; Murphy, Ryan; Sim, Youn

2015-03-01

Integrated continuous simulation-optimization models can be effective predictors of a process-based responses for cost-benefit optimization of best management practices (BMPs) selection and placement. However, practical application of simulation-optimization model is computationally prohibitive for large-scale systems. This study proposes an enhanced Nonlinearity Interval Mapping Scheme (NIMS) to solve large-scale watershed simulation-optimization problems several orders of magnitude faster than other commonly used algorithms. An efficient interval response coefficient (IRC) derivation method was incorporated into the NIMS framework to overcome a computational bottleneck. The proposed algorithm was evaluated using a case study watershed in the Los Angeles County Flood Control District. Using a continuous simulation watershed/stream-transport model, Loading Simulation Program in C++ (LSPC), three nested in-stream compliance points (CP)—each with multiple Total Maximum Daily Loads (TMDL) targets—were selected to derive optimal treatment levels for each of the 28 subwatersheds, so that the TMDL targets at all the CP were met with the lowest possible BMP implementation cost. Genetic Algorithm (GA) and NIMS were both applied and compared. The results showed that the NIMS took 11 iterations (about 11 min) to complete with the resulting optimal solution having a total cost of 67.2 million, while each of the multiple GA executions took 21-38 days to reach near optimal solutions. The best solution obtained among all the GA executions compared had a minimized cost of 67.7 million—marginally higher, but approximately equal to that of the NIMS solution. The results highlight the utility for decision making in large-scale watershed simulation-optimization formulations.

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Findings and Challenges in Fine-Resolution Large-Scale Hydrological Modeling

NASA Astrophysics Data System (ADS)

Her, Y. G.

2017-12-01

Fine-resolution large-scale (FL) modeling can provide the overall picture of the hydrological cycle and transport while taking into account unique local conditions in the simulation. It can also help develop water resources management plans consistent across spatial scales by describing the spatial consequences of decisions and hydrological events extensively. FL modeling is expected to be common in the near future as global-scale remotely sensed data are emerging, and computing resources have been advanced rapidly. There are several spatially distributed models available for hydrological analyses. Some of them rely on numerical methods such as finite difference/element methods (FDM/FEM), which require excessive computing resources (implicit scheme) to manipulate large matrices or small simulation time intervals (explicit scheme) to maintain the stability of the solution, to describe two-dimensional overland processes. Others make unrealistic assumptions such as constant overland flow velocity to reduce the computational loads of the simulation. Thus, simulation efficiency often comes at the expense of precision and reliability in FL modeling. Here, we introduce a new FL continuous hydrological model and its application to four watersheds in different landscapes and sizes from 3.5 km2 to 2,800 km2 at the spatial resolution of 30 m on an hourly basis. The model provided acceptable accuracy statistics in reproducing hydrological observations made in the watersheds. The modeling outputs including the maps of simulated travel time, runoff depth, soil water content, and groundwater recharge, were animated, visualizing the dynamics of hydrological processes occurring in the watersheds during and between storm events. Findings and challenges were discussed in the context of modeling efficiency, accuracy, and reproducibility, which we found can be improved by employing advanced computing techniques and hydrological understandings, by using remotely sensed hydrological observations such as soil moisture and radar rainfall depth and by sharing the model and its codes in public domain, respectively.

Fluid-structure interaction simulation of floating structures interacting with complex, large-scale ocean waves and atmospheric turbulence with application to floating offshore wind turbines

NASA Astrophysics Data System (ADS)

Calderer, Antoni; Guo, Xin; Shen, Lian; Sotiropoulos, Fotis

2018-02-01

We develop a numerical method for simulating coupled interactions of complex floating structures with large-scale ocean waves and atmospheric turbulence. We employ an efficient large-scale model to develop offshore wind and wave environmental conditions, which are then incorporated into a high resolution two-phase flow solver with fluid-structure interaction (FSI). The large-scale wind-wave interaction model is based on a two-fluid dynamically-coupled approach that employs a high-order spectral method for simulating the water motion and a viscous solver with undulatory boundaries for the air motion. The two-phase flow FSI solver is based on the level set method and is capable of simulating the coupled dynamic interaction of arbitrarily complex bodies with airflow and waves. The large-scale wave field solver is coupled with the near-field FSI solver with a one-way coupling approach by feeding into the latter waves via a pressure-forcing method combined with the level set method. We validate the model for both simple wave trains and three-dimensional directional waves and compare the results with experimental and theoretical solutions. Finally, we demonstrate the capabilities of the new computational framework by carrying out large-eddy simulation of a floating offshore wind turbine interacting with realistic ocean wind and waves.

An extended algebraic variational multiscale-multigrid-multifractal method (XAVM4) for large-eddy simulation of turbulent two-phase flow

NASA Astrophysics Data System (ADS)

Rasthofer, U.; Wall, W. A.; Gravemeier, V.

2018-04-01

A novel and comprehensive computational method, referred to as the eXtended Algebraic Variational Multiscale-Multigrid-Multifractal Method (XAVM4), is proposed for large-eddy simulation of the particularly challenging problem of turbulent two-phase flow. The XAVM4 involves multifractal subgrid-scale modeling as well as a Nitsche-type extended finite element method as an approach for two-phase flow. The application of an advanced structural subgrid-scale modeling approach in conjunction with a sharp representation of the discontinuities at the interface between two bulk fluids promise high-fidelity large-eddy simulation of turbulent two-phase flow. The high potential of the XAVM4 is demonstrated for large-eddy simulation of turbulent two-phase bubbly channel flow, that is, turbulent channel flow carrying a single large bubble of the size of the channel half-width in this particular application.

A computationally efficient Bayesian sequential simulation approach for the assimilation of vast and diverse hydrogeophysical datasets

NASA Astrophysics Data System (ADS)

Nussbaumer, Raphaël; Gloaguen, Erwan; Mariéthoz, Grégoire; Holliger, Klaus

2016-04-01

Bayesian sequential simulation (BSS) is a powerful geostatistical technique, which notably has shown significant potential for the assimilation of datasets that are diverse with regard to the spatial resolution and their relationship. However, these types of applications of BSS require a large number of realizations to adequately explore the solution space and to assess the corresponding uncertainties. Moreover, such simulations generally need to be performed on very fine grids in order to adequately exploit the technique's potential for characterizing heterogeneous environments. Correspondingly, the computational cost of BSS algorithms in their classical form is very high, which so far has limited an effective application of this method to large models and/or vast datasets. In this context, it is also important to note that the inherent assumption regarding the independence of the considered datasets is generally regarded as being too strong in the context of sequential simulation. To alleviate these problems, we have revisited the classical implementation of BSS and incorporated two key features to increase the computational efficiency. The first feature is a combined quadrant spiral - superblock search, which targets run-time savings on large grids and adds flexibility with regard to the selection of neighboring points using equal directional sampling and treating hard data and previously simulated points separately. The second feature is a constant path of simulation, which enhances the efficiency for multiple realizations. We have also modified the aggregation operator to be more flexible with regard to the assumption of independence of the considered datasets. This is achieved through log-linear pooling, which essentially allows for attributing weights to the various data components. Finally, a multi-grid simulating path was created to enforce large-scale variance and to allow for adapting parameters, such as, for example, the log-linear weights or the type of simulation path at various scales. The newly implemented search method for kriging reduces the computational cost from an exponential dependence with regard to the grid size in the original algorithm to a linear relationship, as each neighboring search becomes independent from the grid size. For the considered examples, our results show a sevenfold reduction in run time for each additional realization when a constant simulation path is used. The traditional criticism that constant path techniques introduce a bias to the simulations was explored and our findings do indeed reveal a minor reduction in the diversity of the simulations. This bias can, however, be largely eliminated by changing the path type at different scales through the use of the multi-grid approach. Finally, we show that adapting the aggregation weight at each scale considered in our multi-grid approach allows for reproducing both the variogram and histogram, and the spatial trend of the underlying data.

Numerical Propulsion System Simulation (NPSS) 1999 Industry Review

NASA Technical Reports Server (NTRS)

Lytle, John; Follen, Greg; Naiman, Cynthia; Evans, Austin

2000-01-01

The technologies necessary to enable detailed numerical simulations of complete propulsion systems are being developed at the NASA Glenn Research Center in cooperation with industry, academia, and other government agencies. Large scale, detailed simulations will be of great value to the nation because they eliminate some of the costly testing required to develop and certify advanced propulsion systems. In addition, time and cost savings will be achieved by enabling design details to be evaluated early in the development process before a commitment is made to a specific design. This concept is called the Numerical Propulsion System Simulation (NPSS). NPSS consists of three main elements: (1) engineering models that enable multidisciplinary analysis of large subsystems and systems at various levels of detail, (2) a simulation environment that maximizes designer productivity, and (3) a cost-effective, high-performance computing platform. A fundamental requirement of the concept is that the simulations must be capable of overnight execution on easily accessible computing platforms. This will greatly facilitate the use of large-scale simulations in a design environment. This paper describes the current status of the NPSS with specific emphasis on the progress made over the past year on air breathing propulsion applications. In addition, the paper contains a summary of the feedback received from industry partners in the development effort and the actions taken over the past year to respond to that feedback. The NPSS development was supported in FY99 by the High Performance Computing and Communications Program.

Effect of turbulence modelling to predict combustion and nanoparticle production in the flame assisted spray dryer based on computational fluid dynamics

NASA Astrophysics Data System (ADS)

Septiani, Eka Lutfi; Widiyastuti, W.; Winardi, Sugeng; Machmudah, Siti; Nurtono, Tantular; Kusdianto

2016-02-01

Flame assisted spray dryer are widely uses for large-scale production of nanoparticles because of it ability. Numerical approach is needed to predict combustion and particles production in scale up and optimization process due to difficulty in experimental observation and relatively high cost. Computational Fluid Dynamics (CFD) can provide the momentum, energy and mass transfer, so that CFD more efficient than experiment due to time and cost. Here, two turbulence models, k-ɛ and Large Eddy Simulation were compared and applied in flame assisted spray dryer system. The energy sources for particle drying was obtained from combustion between LPG as fuel and air as oxidizer and carrier gas that modelled by non-premixed combustion in simulation. Silica particles was used to particle modelling from sol silica solution precursor. From the several comparison result, i.e. flame contour, temperature distribution and particle size distribution, Large Eddy Simulation turbulence model can provide the closest data to the experimental result.

A Zonal Approach for Prediction of Jet Noise

NASA Technical Reports Server (NTRS)

Shih, S. H.; Hixon, D. R.; Mankbadi, Reda R.

1995-01-01

A zonal approach for direct computation of sound generation and propagation from a supersonic jet is investigated. The present work splits the computational domain into a nonlinear, acoustic-source regime and a linear acoustic wave propagation regime. In the nonlinear regime, the unsteady flow is governed by the large-scale equations, which are the filtered compressible Navier-Stokes equations. In the linear acoustic regime, the sound wave propagation is described by the linearized Euler equations. Computational results are presented for a supersonic jet at M = 2. 1. It is demonstrated that no spurious modes are generated in the matching region and the computational expense is reduced substantially as opposed to fully large-scale simulation.

Simulating chemistry using quantum computers.

PubMed

Kassal, Ivan; Whitfield, James D; Perdomo-Ortiz, Alejandro; Yung, Man-Hong; Aspuru-Guzik, Alán

2011-01-01

The difficulty of simulating quantum systems, well known to quantum chemists, prompted the idea of quantum computation. One can avoid the steep scaling associated with the exact simulation of increasingly large quantum systems on conventional computers, by mapping the quantum system to another, more controllable one. In this review, we discuss to what extent the ideas in quantum computation, now a well-established field, have been applied to chemical problems. We describe algorithms that achieve significant advantages for the electronic-structure problem, the simulation of chemical dynamics, protein folding, and other tasks. Although theory is still ahead of experiment, we outline recent advances that have led to the first chemical calculations on small quantum information processors.

Large scale Brownian dynamics of confined suspensions of rigid particles

NASA Astrophysics Data System (ADS)

Sprinkle, Brennan; Balboa Usabiaga, Florencio; Patankar, Neelesh A.; Donev, Aleksandar

2017-12-01

We introduce methods for large-scale Brownian Dynamics (BD) simulation of many rigid particles of arbitrary shape suspended in a fluctuating fluid. Our method adds Brownian motion to the rigid multiblob method [F. Balboa Usabiaga et al., Commun. Appl. Math. Comput. Sci. 11(2), 217-296 (2016)] at a cost comparable to the cost of deterministic simulations. We demonstrate that we can efficiently generate deterministic and random displacements for many particles using preconditioned Krylov iterative methods, if kernel methods to efficiently compute the action of the Rotne-Prager-Yamakawa (RPY) mobility matrix and its "square" root are available for the given boundary conditions. These kernel operations can be computed with near linear scaling for periodic domains using the positively split Ewald method. Here we study particles partially confined by gravity above a no-slip bottom wall using a graphical processing unit implementation of the mobility matrix-vector product, combined with a preconditioned Lanczos iteration for generating Brownian displacements. We address a major challenge in large-scale BD simulations, capturing the stochastic drift term that arises because of the configuration-dependent mobility. Unlike the widely used Fixman midpoint scheme, our methods utilize random finite differences and do not require the solution of resistance problems or the computation of the action of the inverse square root of the RPY mobility matrix. We construct two temporal schemes which are viable for large-scale simulations, an Euler-Maruyama traction scheme and a trapezoidal slip scheme, which minimize the number of mobility problems to be solved per time step while capturing the required stochastic drift terms. We validate and compare these schemes numerically by modeling suspensions of boomerang-shaped particles sedimented near a bottom wall. Using the trapezoidal scheme, we investigate the steady-state active motion in dense suspensions of confined microrollers, whose height above the wall is set by a combination of thermal noise and active flows. We find the existence of two populations of active particles, slower ones closer to the bottom and faster ones above them, and demonstrate that our method provides quantitative accuracy even with relatively coarse resolutions of the particle geometry.

Seafloor identification in sonar imagery via simulations of Helmholtz equations and discrete optimization

NASA Astrophysics Data System (ADS)

Engquist, Björn; Frederick, Christina; Huynh, Quyen; Zhou, Haomin

2017-06-01

We present a multiscale approach for identifying features in ocean beds by solving inverse problems in high frequency seafloor acoustics. The setting is based on Sound Navigation And Ranging (SONAR) imaging used in scientific, commercial, and military applications. The forward model incorporates multiscale simulations, by coupling Helmholtz equations and geometrical optics for a wide range of spatial scales in the seafloor geometry. This allows for detailed recovery of seafloor parameters including material type. Simulated backscattered data is generated using numerical microlocal analysis techniques. In order to lower the computational cost of the large-scale simulations in the inversion process, we take advantage of a pre-computed library of representative acoustic responses from various seafloor parameterizations.

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has tomore » gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a scaling study that compares instrumented ROSS simulations with their noninstrumented counterparts in order to determine the amount of perturbation when running at different simulation scales.« less

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE PAGES

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.; ...

2016-11-07

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Optimization and large scale computation of an entropy-based moment closure

NASA Astrophysics Data System (ADS)

Kristopher Garrett, C.; Hauck, Cory; Hill, Judith

2015-12-01

We present computational advances and results in the implementation of an entropy-based moment closure, MN, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as PN, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which are used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. These results show, in particular, load balancing issues in scaling the MN algorithm that do not appear for the PN algorithm. We also observe that in weak scaling tests, the ratio in time to solution of MN to PN decreases.

Optimization and large scale computation of an entropy-based moment closure

DOE PAGES

Hauck, Cory D.; Hill, Judith C.; Garrett, C. Kristopher

2015-09-10

We present computational advances and results in the implementation of an entropy-based moment closure, M N, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as P N, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which aremore » used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. Lastly, these results show, in particular, load balancing issues in scaling the M N algorithm that do not appear for the P N algorithm. We also observe that in weak scaling tests, the ratio in time to solution of M N to P N decreases.« less

Design and Evaluation of Simulations for the Development of Complex Decision-Making Skills.

ERIC Educational Resources Information Center

Hartley, Roger; Varley, Glen

2002-01-01

Command and Control Training Using Simulation (CACTUS) is a computer digital mapping system used by police to manage large-scale public events. Audio and video records of adaptive training scenarios using CACTUS show how the simulation develops decision-making skills for strategic and tactical event management. (SK)

Time-Accurate Simulations and Acoustic Analysis of Slat Free-Shear-Layer. Part 2

NASA Technical Reports Server (NTRS)

Khorrami, Mehdi R.; Singer, Bart A.; Lockard, David P.

2002-01-01

Unsteady computational simulations of a multi-element, high-lift configuration are performed. Emphasis is placed on accurate spatiotemporal resolution of the free shear layer in the slat-cove region. The excessive dissipative effects of the turbulence model, so prevalent in previous simulations, are circumvented by switching off the turbulence-production term in the slat cove region. The justifications and physical arguments for taking such a step are explained in detail. The removal of this excess damping allows the shear layer to amplify large-scale structures, to achieve a proper non-linear saturation state, and to permit vortex merging. The large-scale disturbances are self-excited, and unlike our prior fully turbulent simulations, no external forcing of the shear layer is required. To obtain the farfield acoustics, the Ffowcs Williams and Hawkings equation is evaluated numerically using the simulated time-accurate flow data. The present comparison between the computed and measured farfield acoustic spectra shows much better agreement for the amplitude and frequency content than past calculations. The effect of the angle-of-attack on the slat's flow features radiated acoustic field are also simulated presented.

Comparison of HSPF and PRMS model simulated flows using different temporal and spatial scales in the Black Hills, South Dakota

USGS Publications Warehouse

Chalise, D. R.; Haj, Adel E.; Fontaine, T.A.

2018-01-01

The hydrological simulation program Fortran (HSPF) [Hydrological Simulation Program Fortran version 12.2 (Computer software). USEPA, Washington, DC] and the precipitation runoff modeling system (PRMS) [Precipitation Runoff Modeling System version 4.0 (Computer software). USGS, Reston, VA] models are semidistributed, deterministic hydrological tools for simulating the impacts of precipitation, land use, and climate on basin hydrology and streamflow. Both models have been applied independently to many watersheds across the United States. This paper reports the statistical results assessing various temporal (daily, monthly, and annual) and spatial (small versus large watershed) scale biases in HSPF and PRMS simulations using two watersheds in the Black Hills, South Dakota. The Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient (r">rr), and coefficient of determination (R2">R2R2) statistics for the daily, monthly, and annual flows were used to evaluate the models’ performance. Results from the HSPF models showed that the HSPF consistently simulated the annual flows for both large and small basins better than the monthly and daily flows, and the simulated flows for the small watershed better than flows for the large watershed. In comparison, the PRMS model results show that the PRMS simulated the monthly flows for both the large and small watersheds better than the daily and annual flows, and the range of statistical error in the PRMS models was greater than that in the HSPF models. Moreover, it can be concluded that the statistical error in the HSPF and the PRMSdaily, monthly, and annual flow estimates for watersheds in the Black Hills was influenced by both temporal and spatial scale variability.

A Comparison of Linking Methods for Estimating National Trends in International Comparative Large-Scale Assessments in the Presence of Cross-national DIF

ERIC Educational Resources Information Center

Sachse, Karoline A.; Roppelt, Alexander; Haag, Nicole

2016-01-01

Trend estimation in international comparative large-scale assessments relies on measurement invariance between countries. However, cross-national differential item functioning (DIF) has been repeatedly documented. We ran a simulation study using national item parameters, which required trends to be computed separately for each country, to compare…

Three-dimensional time dependent computation of turbulent flow

NASA Technical Reports Server (NTRS)

Kwak, D.; Reynolds, W. C.; Ferziger, J. H.

1975-01-01

The three-dimensional, primitive equations of motion are solved numerically for the case of isotropic box turbulence and the distortion of homogeneous turbulence by irrotational plane strain at large Reynolds numbers. A Gaussian filter is applied to governing equations to define the large scale field. This gives rise to additional second order computed scale stresses (Leonard stresses). The residual stresses are simulated through an eddy viscosity. Uniform grids are used, with a fourth order differencing scheme in space and a second order Adams-Bashforth predictor for explicit time stepping. The results are compared to the experiments and statistical information extracted from the computer generated data.

Teaching Real Science with a Microcomputer.

ERIC Educational Resources Information Center

Naiman, Adeline

1983-01-01

Discusses various ways science can be taught using microcomputers, including simulations/games which allow large-scale or historic experiments to be replicated on a manageable scale in a brief time. Examples of several computer programs are also presented, including "Experiments in Human Physiology,""Health Awareness…

Physics-based animation of large-scale splashing liquids, elastoplastic solids, and model-reduced flow

NASA Astrophysics Data System (ADS)

Gerszewski, Daniel James

Physical simulation has become an essential tool in computer animation. As the use of visual effects increases, the need for simulating real-world materials increases. In this dissertation, we consider three problems in physics-based animation: large-scale splashing liquids, elastoplastic material simulation, and dimensionality reduction techniques for fluid simulation. Fluid simulation has been one of the greatest successes of physics-based animation, generating hundreds of research papers and a great many special effects over the last fifteen years. However, the animation of large-scale, splashing liquids remains challenging. We show that a novel combination of unilateral incompressibility, mass-full FLIP, and blurred boundaries is extremely well-suited to the animation of large-scale, violent, splashing liquids. Materials that incorporate both plastic and elastic deformations, also referred to as elastioplastic materials, are frequently encountered in everyday life. Methods for animating such common real-world materials are useful for effects practitioners and have been successfully employed in films. We describe a point-based method for animating elastoplastic materials. Our primary contribution is a simple method for computing the deformation gradient for each particle in the simulation. Given the deformation gradient, we can apply arbitrary constitutive models and compute the resulting elastic forces. Our method has two primary advantages: we do not store or compare to an initial rest configuration and we work directly with the deformation gradient. The first advantage avoids poor numerical conditioning and the second naturally leads to a multiplicative model of deformation appropriate for finite deformations. One of the most significant drawbacks of physics-based animation is that ever-higher fidelity leads to an explosion in the number of degrees of freedom. This problem leads us to the consideration of dimensionality reduction techniques. We present several enhancements to model-reduced fluid simulation that allow improved simulation bases and two-way solid-fluid coupling. Specifically, we present a basis enrichment scheme that allows us to combine data-driven or artistically derived bases with more general analytic bases derived from Laplacian Eigenfunctions. Additionally, we handle two-way solid-fluid coupling in a time-splitting fashion---we alternately timestep the fluid and rigid body simulators, while taking into account the effects of the fluid on the rigid bodies and vice versa. We employ the vortex panel method to handle solid-fluid coupling and use dynamic pressure to compute the effect of the fluid on rigid bodies. Taken together, these contributions have advanced the state-of-the art in physics-based animation and are practical enough to be used in production pipelines.

Large-scale high-throughput computer-aided discovery of advanced materials using cloud computing

NASA Astrophysics Data System (ADS)

Bazhirov, Timur; Mohammadi, Mohammad; Ding, Kevin; Barabash, Sergey

Recent advances in cloud computing made it possible to access large-scale computational resources completely on-demand in a rapid and efficient manner. When combined with high fidelity simulations, they serve as an alternative pathway to enable computational discovery and design of new materials through large-scale high-throughput screening. Here, we present a case study for a cloud platform implemented at Exabyte Inc. We perform calculations to screen lightweight ternary alloys for thermodynamic stability. Due to the lack of experimental data for most such systems, we rely on theoretical approaches based on first-principle pseudopotential density functional theory. We calculate the formation energies for a set of ternary compounds approximated by special quasirandom structures. During an example run we were able to scale to 10,656 CPUs within 7 minutes from the start, and obtain results for 296 compounds within 38 hours. The results indicate that the ultimate formation enthalpy of ternary systems can be negative for some of lightweight alloys, including Li and Mg compounds. We conclude that compared to traditional capital-intensive approach that requires in on-premises hardware resources, cloud computing is agile and cost-effective, yet scalable and delivers similar performance.

Load Balancing Scientific Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pearce, Olga Tkachyshyn

2014-12-01

The largest supercomputers have millions of independent processors, and concurrency levels are rapidly increasing. For ideal efficiency, developers of the simulations that run on these machines must ensure that computational work is evenly balanced among processors. Assigning work evenly is challenging because many large modern parallel codes simulate behavior of physical systems that evolve over time, and their workloads change over time. Furthermore, the cost of imbalanced load increases with scale because most large-scale scientific simulations today use a Single Program Multiple Data (SPMD) parallel programming model, and an increasing number of processors will wait for the slowest one atmore » the synchronization points. To address load imbalance, many large-scale parallel applications use dynamic load balance algorithms to redistribute work evenly. The research objective of this dissertation is to develop methods to decide when and how to load balance the application, and to balance it effectively and affordably. We measure and evaluate the computational load of the application, and develop strategies to decide when and how to correct the imbalance. Depending on the simulation, a fast, local load balance algorithm may be suitable, or a more sophisticated and expensive algorithm may be required. We developed a model for comparison of load balance algorithms for a specific state of the simulation that enables the selection of a balancing algorithm that will minimize overall runtime.« less

Accelerating three-dimensional FDTD calculations on GPU clusters for electromagnetic field simulation.

PubMed

Nagaoka, Tomoaki; Watanabe, Soichi

2012-01-01

Electromagnetic simulation with anatomically realistic computational human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the computational human model, we adapt three-dimensional FDTD code to a multi-GPU cluster environment with Compute Unified Device Architecture and Message Passing Interface. Our multi-GPU cluster system consists of three nodes. The seven GPU boards (NVIDIA Tesla C2070) are mounted on each node. We examined the performance of the FDTD calculation on multi-GPU cluster environment. We confirmed that the FDTD calculation on the multi-GPU clusters is faster than that on a multi-GPU (a single workstation), and we also found that the GPU cluster system calculate faster than a vector supercomputer. In addition, our GPU cluster system allowed us to perform the large-scale FDTD calculation because were able to use GPU memory of over 100 GB.

2000 Numerical Propulsion System Simulation Review

NASA Technical Reports Server (NTRS)

Lytle, John; Follen, Greg; Naiman, Cynthia; Veres, Joseph; Owen, Karl; Lopez, Isaac

2001-01-01

The technologies necessary to enable detailed numerical simulations of complete propulsion systems are being developed at the NASA Glenn Research Center in cooperation with industry, academia, and other government agencies. Large scale, detailed simulations will be of great value to the nation because they eliminate some of the costly testing required to develop and certify advanced propulsion systems. In addition, time and cost savings will be achieved by enabling design details to be evaluated early in the development process before a commitment is made to a specific design. This concept is called the Numerical Propulsion System Simulation (NPSS). NPSS consists of three main elements: (1) engineering models that enable multidisciplinary analysis of large subsystems and systems at various levels of detail, (2) a simulation environment that maximizes designer productivity, and (3) a cost-effective. high-performance computing platform. A fundamental requirement of the concept is that the simulations must be capable of overnight execution on easily accessible computing platforms. This will greatly facilitate the use of large-scale simulations in a design environment. This paper describes the current status of the NPSS with specific emphasis on the progress made over the past year on air breathing propulsion applications. Major accomplishments include the first formal release of the NPSS object-oriented architecture (NPSS Version 1) and the demonstration of a one order of magnitude reduction in computing cost-to-performance ratio using a cluster of personal computers. The paper also describes the future NPSS milestones, which include the simulation of space transportation propulsion systems in response to increased emphasis on safe, low cost access to space within NASA'S Aerospace Technology Enterprise. In addition, the paper contains a summary of the feedback received from industry partners on the fiscal year 1999 effort and the actions taken over the past year to respond to that feedback. NPSS was supported in fiscal year 2000 by the High Performance Computing and Communications Program.

2001 Numerical Propulsion System Simulation Review

NASA Technical Reports Server (NTRS)

Lytle, John; Follen, Gregory; Naiman, Cynthia; Veres, Joseph; Owen, Karl; Lopez, Isaac

2002-01-01

The technologies necessary to enable detailed numerical simulations of complete propulsion systems are being developed at the NASA Glenn Research Center in cooperation with industry, academia and other government agencies. Large scale, detailed simulations will be of great value to the nation because they eliminate some of the costly testing required to develop and certify advanced propulsion systems. In addition, time and cost savings will be achieved by enabling design details to be evaluated early in the development process before a commitment is made to a specific design. This concept is called the Numerical Propulsion System Simulation (NPSS). NPSS consists of three main elements: (1) engineering models that enable multidisciplinary analysis of large subsystems and systems at various levels of detail, (2) a simulation environment that maximizes designer productivity, and (3) a cost-effective, high-performance computing platform. A fundamental requirement of the concept is that the simulations must be capable of overnight execution on easily accessible computing platforms. This will greatly facilitate the use of large-scale simulations in a design environment. This paper describes the current status of the NPSS with specific emphasis on the progress made over the past year on air breathing propulsion applications. Major accomplishments include the first formal release of the NPSS object-oriented architecture (NPSS Version 1) and the demonstration of a one order of magnitude reduction in computing cost-to-performance ratio using a cluster of personal computers. The paper also describes the future NPSS milestones, which include the simulation of space transportation propulsion systems in response to increased emphasis on safe, low cost access to space within NASA's Aerospace Technology Enterprise. In addition, the paper contains a summary of the feedback received from industry partners on the fiscal year 2000 effort and the actions taken over the past year to respond to that feedback. NPSS was supported in fiscal year 2001 by the High Performance Computing and Communications Program.

Decomposition method for fast computation of gigapixel-sized Fresnel holograms on a graphics processing unit cluster.

PubMed

Jackin, Boaz Jessie; Watanabe, Shinpei; Ootsu, Kanemitsu; Ohkawa, Takeshi; Yokota, Takashi; Hayasaki, Yoshio; Yatagai, Toyohiko; Baba, Takanobu

2018-04-20

A parallel computation method for large-size Fresnel computer-generated hologram (CGH) is reported. The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from 2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The scale of the computation problem is also expanded to 2 gigapixels, making it closer to real application requirements. The significant feature of the reported method is its ability to avoid communication overhead and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of parallelism that favor small to large scale parallel computing machines. Simulation and optical experiments were conducted to demonstrate the workability and to evaluate the efficiency of the proposed technique. A two-times improvement in computation speed has been achieved compared to the conventional method, on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20-times improvement in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel machine with 16 nodes, where each node has 16 GPUs.

A scalable parallel black oil simulator on distributed memory parallel computers

NASA Astrophysics Data System (ADS)

Wang, Kun; Liu, Hui; Chen, Zhangxin

2015-11-01

This paper presents our work on developing a parallel black oil simulator for distributed memory computers based on our in-house parallel platform. The parallel simulator is designed to overcome the performance issues of common simulators that are implemented for personal computers and workstations. The finite difference method is applied to discretize the black oil model. In addition, some advanced techniques are employed to strengthen the robustness and parallel scalability of the simulator, including an inexact Newton method, matrix decoupling methods, and algebraic multigrid methods. A new multi-stage preconditioner is proposed to accelerate the solution of linear systems from the Newton methods. Numerical experiments show that our simulator is scalable and efficient, and is capable of simulating extremely large-scale black oil problems with tens of millions of grid blocks using thousands of MPI processes on parallel computers.

Computer-intensive simulation of solid-state NMR experiments using SIMPSON.

PubMed

Tošner, Zdeněk; Andersen, Rasmus; Stevensson, Baltzar; Edén, Mattias; Nielsen, Niels Chr; Vosegaard, Thomas

2014-09-01

Conducting large-scale solid-state NMR simulations requires fast computer software potentially in combination with efficient computational resources to complete within a reasonable time frame. Such simulations may involve large spin systems, multiple-parameter fitting of experimental spectra, or multiple-pulse experiment design using parameter scan, non-linear optimization, or optimal control procedures. To efficiently accommodate such simulations, we here present an improved version of the widely distributed open-source SIMPSON NMR simulation software package adapted to contemporary high performance hardware setups. The software is optimized for fast performance on standard stand-alone computers, multi-core processors, and large clusters of identical nodes. We describe the novel features for fast computation including internal matrix manipulations, propagator setups and acquisition strategies. For efficient calculation of powder averages, we implemented interpolation method of Alderman, Solum, and Grant, as well as recently introduced fast Wigner transform interpolation technique. The potential of the optimal control toolbox is greatly enhanced by higher precision gradients in combination with the efficient optimization algorithm known as limited memory Broyden-Fletcher-Goldfarb-Shanno. In addition, advanced parallelization can be used in all types of calculations, providing significant time reductions. SIMPSON is thus reflecting current knowledge in the field of numerical simulations of solid-state NMR experiments. The efficiency and novel features are demonstrated on the representative simulations. Copyright © 2014 Elsevier Inc. All rights reserved.

Development of mpi_EPIC model for global agroecosystem modeling

DOE PAGES

Kang, Shujiang; Wang, Dali; Jeff A. Nichols; ...

2014-12-31

Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmentalmore » effects.« less

Assessing the weighted multi-objective adaptive surrogate model optimization to derive large-scale reservoir operating rules with sensitivity analysis

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Wang, Xu; Liu, Pan; Lei, Xiaohui; Li, Zejun; Gong, Wei; Duan, Qingyun; Wang, Hao

2017-01-01

The optimization of large-scale reservoir system is time-consuming due to its intrinsic characteristics of non-commensurable objectives and high dimensionality. One way to solve the problem is to employ an efficient multi-objective optimization algorithm in the derivation of large-scale reservoir operating rules. In this study, the Weighted Multi-Objective Adaptive Surrogate Model Optimization (WMO-ASMO) algorithm is used. It consists of three steps: (1) simplifying the large-scale reservoir operating rules by the aggregation-decomposition model, (2) identifying the most sensitive parameters through multivariate adaptive regression splines (MARS) for dimensional reduction, and (3) reducing computational cost and speeding the searching process by WMO-ASMO, embedded with weighted non-dominated sorting genetic algorithm II (WNSGAII). The intercomparison of non-dominated sorting genetic algorithm (NSGAII), WNSGAII and WMO-ASMO are conducted in the large-scale reservoir system of Xijiang river basin in China. Results indicate that: (1) WNSGAII surpasses NSGAII in the median of annual power generation, increased by 1.03% (from 523.29 to 528.67 billion kW h), and the median of ecological index, optimized by 3.87% (from 1.879 to 1.809) with 500 simulations, because of the weighted crowding distance and (2) WMO-ASMO outperforms NSGAII and WNSGAII in terms of better solutions (annual power generation (530.032 billion kW h) and ecological index (1.675)) with 1000 simulations and computational time reduced by 25% (from 10 h to 8 h) with 500 simulations. Therefore, the proposed method is proved to be more efficient and could provide better Pareto frontier.

Large scale particle image velocimetry with helium filled soap bubbles

NASA Astrophysics Data System (ADS)

Bosbach, Johannes; Kühn, Matthias; Wagner, Claus

2009-03-01

The application of Particle Image Velocimetry (PIV) to measurement of flows on large scales is a challenging necessity especially for the investigation of convective air flows. Combining helium filled soap bubbles as tracer particles with high power quality switched solid state lasers as light sources allows conducting PIV on scales of the order of several square meters. The technique was applied to mixed convection in a full scale double aisle aircraft cabin mock-up for validation of Computational Fluid Dynamics simulations.

A second golden age of aeroacoustics?

PubMed

Lele, Sanjiva K; Nichols, Joseph W

2014-08-13

In 1992, Sir James Lighthill foresaw the dawn of a second golden age in aeroacoustics enabled by computer simulations (Hardin JC, Hussaini MY (eds) 1993 Computational aeroacoustics, New York, NY: Springer (doi:10.1007/978-1-4613-8342-0)). This review traces the progress in large-scale computations to resolve the noise-source processes and the methods devised to predict the far-field radiated sound using this information. Keeping focus on aviation-related noise sources a brief account of the progress in simulations of jet noise, fan noise and airframe noise is given highlighting the key technical issues and challenges. The complex geometry of nozzle elements and airframe components as well as the high Reynolds number of target applications require careful assessment of the discretization algorithms on unstructured grids and modelling compromises. High-fidelity simulations with 200-500 million points are not uncommon today and are used to improve scientific understanding of the noise generation process in specific situations. We attempt to discern where the future might take us, especially if exascale computing becomes a reality in 10 years. A pressing question in this context concerns the role of modelling in the coming era. While the sheer scale of the data generated by large-scale simulations will require new methods for data analysis and data visualization, it is our view that suitable theoretical formulations and reduced models will be even more important in future. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

On mechanics and material length scales of failure in heterogeneous interfaces using a finite strain high performance solver

NASA Astrophysics Data System (ADS)

Mosby, Matthew; Matouš, Karel

2015-12-01

Three-dimensional simulations capable of resolving the large range of spatial scales, from the failure-zone thickness up to the size of the representative unit cell, in damage mechanics problems of particle reinforced adhesives are presented. We show that resolving this wide range of scales in complex three-dimensional heterogeneous morphologies is essential in order to apprehend fracture characteristics, such as strength, fracture toughness and shape of the softening profile. Moreover, we show that computations that resolve essential physical length scales capture the particle size-effect in fracture toughness, for example. In the vein of image-based computational materials science, we construct statistically optimal unit cells containing hundreds to thousands of particles. We show that these statistically representative unit cells are capable of capturing the first- and second-order probability functions of a given data-source with better accuracy than traditional inclusion packing techniques. In order to accomplish these large computations, we use a parallel multiscale cohesive formulation and extend it to finite strains including damage mechanics. The high-performance parallel computational framework is executed on up to 1024 processing cores. A mesh convergence and a representative unit cell study are performed. Quantifying the complex damage patterns in simulations consisting of tens of millions of computational cells and millions of highly nonlinear equations requires data-mining the parallel simulations, and we propose two damage metrics to quantify the damage patterns. A detailed study of volume fraction and filler size on the macroscopic traction-separation response of heterogeneous adhesives is presented.

eScience for molecular-scale simulations and the eMinerals project.

PubMed

Salje, E K H; Artacho, E; Austen, K F; Bruin, R P; Calleja, M; Chappell, H F; Chiang, G-T; Dove, M T; Frame, I; Goodwin, A L; Kleese van Dam, K; Marmier, A; Parker, S C; Pruneda, J M; Todorov, I T; Trachenko, K; Tyer, R P; Walker, A M; White, T O H

2009-03-13

We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.

High performance computing applications in neurobiological research

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; Cheng, Rei; Doshay, David G.; Linton, Samuel W.; Montgomery, Kevin; Parnas, Bruce R.

1994-01-01

The human nervous system is a massively parallel processor of information. The vast numbers of neurons, synapses and circuits is daunting to those seeking to understand the neural basis of consciousness and intellect. Pervading obstacles are lack of knowledge of the detailed, three-dimensional (3-D) organization of even a simple neural system and the paucity of large scale, biologically relevant computer simulations. We use high performance graphics workstations and supercomputers to study the 3-D organization of gravity sensors as a prototype architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scale-up, three-dimensional versions run on the Cray Y-MP and CM5 supercomputers.

Structure and modeling of turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novikov, E.A.

The {open_quotes}vortex strings{close_quotes} scale l{sub s} {approximately} LRe{sup -3/10} (L-external scale, Re - Reynolds number) is suggested as a grid scale for the large-eddy simulation. Various aspects of the structure of turbulence and subgrid modeling are described in terms of conditional averaging, Markov processes with dependent increments and infinitely divisible distributions. The major request from the energy, naval, aerospace and environmental engineering communities to the theory of turbulence is to reduce the enormous number of degrees of freedom in turbulent flows to a level manageable by computer simulations. The vast majority of these degrees of freedom is in the small-scalemore » motion. The study of the structure of turbulence provides a basis for subgrid-scale (SGS) models, which are necessary for the large-eddy simulations (LES).« less

Development of Computational Aeroacoustics Code for Jet Noise and Flow Prediction

NASA Astrophysics Data System (ADS)

Keith, Theo G., Jr.; Hixon, Duane R.

2002-07-01

Accurate prediction of jet fan and exhaust plume flow and noise generation and propagation is very important in developing advanced aircraft engines that will pass current and future noise regulations. In jet fan flows as well as exhaust plumes, two major sources of noise are present: large-scale, coherent instabilities and small-scale turbulent eddies. In previous work for the NASA Glenn Research Center, three strategies have been explored in an effort to computationally predict the noise radiation from supersonic jet exhaust plumes. In order from the least expensive computationally to the most expensive computationally, these are: 1) Linearized Euler equations (LEE). 2) Very Large Eddy Simulations (VLES). 3) Large Eddy Simulations (LES). The first method solves the linearized Euler equations (LEE). These equations are obtained by linearizing about a given mean flow and the neglecting viscous effects. In this way, the noise from large-scale instabilities can be found for a given mean flow. The linearized Euler equations are computationally inexpensive, and have produced good noise results for supersonic jets where the large-scale instability noise dominates, as well as for the tone noise from a jet engine blade row. However, these linear equations do not predict the absolute magnitude of the noise; instead, only the relative magnitude is predicted. Also, the predicted disturbances do not modify the mean flow, removing a physical mechanism by which the amplitude of the disturbance may be controlled. Recent research for isolated airfoils' indicates that this may not affect the solution greatly at low frequencies. The second method addresses some of the concerns raised by the LEE method. In this approach, called Very Large Eddy Simulation (VLES), the unsteady Reynolds averaged Navier-Stokes equations are solved directly using a high-accuracy computational aeroacoustics numerical scheme. With the addition of a two-equation turbulence model and the use of a relatively coarse grid, the numerical solution is effectively filtered into a directly calculated mean flow with the small-scale turbulence being modeled, and an unsteady large-scale component that is also being directly calculated. In this way, the unsteady disturbances are calculated in a nonlinear way, with a direct effect on the mean flow. This method is not as fast as the LEE approach, but does have many advantages to recommend it; however, like the LEE approach, only the effect of the largest unsteady structures will be captured. An initial calculation was performed on a supersonic jet exhaust plume, with promising results, but the calculation was hampered by the explicit time marching scheme that was employed. This explicit scheme required a very small time step to resolve the nozzle boundary layer, which caused a long run time. Current work is focused on testing a lower-order implicit time marching method to combat this problem.

Simulating Biomass Fast Pyrolysis at the Single Particle Scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ciesielski, Peter; Wiggins, Gavin; Daw, C Stuart

2017-07-01

Simulating fast pyrolysis at the scale of single particles allows for the investigation of the impacts of feedstock-specific parameters such as particle size, shape, and species of origin. For this reason particle-scale modeling has emerged as an important tool for understanding how variations in feedstock properties affect the outcomes of pyrolysis processes. The origins of feedstock properties are largely dictated by the composition and hierarchical structure of biomass, from the microstructural porosity to the external morphology of milled particles. These properties may be accounted for in simulations of fast pyrolysis by several different computational approaches depending on the level ofmore » structural and chemical complexity included in the model. The predictive utility of particle-scale simulations of fast pyrolysis can still be enhanced substantially by advancements in several areas. Most notably, considerable progress would be facilitated by the development of pyrolysis kinetic schemes that are decoupled from transport phenomena, predict product evolution from whole-biomass with increased chemical speciation, and are still tractable with present-day computational resources.« less

A new paradigm for atomically detailed simulations of kinetics in biophysical systems.

PubMed

Elber, Ron

2017-01-01

The kinetics of biochemical and biophysical events determined the course of life processes and attracted considerable interest and research. For example, modeling of biological networks and cellular responses relies on the availability of information on rate coefficients. Atomically detailed simulations hold the promise of supplementing experimental data to obtain a more complete kinetic picture. However, simulations at biological time scales are challenging. Typical computer resources are insufficient to provide the ensemble of trajectories at the correct length that is required for straightforward calculations of time scales. In the last years, new technologies emerged that make atomically detailed simulations of rate coefficients possible. Instead of computing complete trajectories from reactants to products, these approaches launch a large number of short trajectories at different positions. Since the trajectories are short, they are computed trivially in parallel on modern computer architecture. The starting and termination positions of the short trajectories are chosen, following statistical mechanics theory, to enhance efficiency. These trajectories are analyzed. The analysis produces accurate estimates of time scales as long as hours. The theory of Milestoning that exploits the use of short trajectories is discussed, and several applications are described.

A k-space method for large-scale models of wave propagation in tissue.

PubMed

Mast, T D; Souriau, L P; Liu, D L; Tabei, M; Nachman, A I; Waag, R C

2001-03-01

Large-scale simulation of ultrasonic pulse propagation in inhomogeneous tissue is important for the study of ultrasound-tissue interaction as well as for development of new imaging methods. Typical scales of interest span hundreds of wavelengths; most current two-dimensional methods, such as finite-difference and finite-element methods, are unable to compute propagation on this scale with the efficiency needed for imaging studies. Furthermore, for most available methods of simulating ultrasonic propagation, large-scale, three-dimensional computations of ultrasonic scattering are infeasible. Some of these difficulties have been overcome by previous pseudospectral and k-space methods, which allow substantial portions of the necessary computations to be executed using fast Fourier transforms. This paper presents a simplified derivation of the k-space method for a medium of variable sound speed and density; the derivation clearly shows the relationship of this k-space method to both past k-space methods and pseudospectral methods. In the present method, the spatial differential equations are solved by a simple Fourier transform method, and temporal iteration is performed using a k-t space propagator. The temporal iteration procedure is shown to be exact for homogeneous media, unconditionally stable for "slow" (c(x) < or = c0) media, and highly accurate for general weakly scattering media. The applicability of the k-space method to large-scale soft tissue modeling is shown by simulating two-dimensional propagation of an incident plane wave through several tissue-mimicking cylinders as well as a model chest wall cross section. A three-dimensional implementation of the k-space method is also employed for the example problem of propagation through a tissue-mimicking sphere. Numerical results indicate that the k-space method is accurate for large-scale soft tissue computations with much greater efficiency than that of an analogous leapfrog pseudospectral method or a 2-4 finite difference time-domain method. However, numerical results also indicate that the k-space method is less accurate than the finite-difference method for a high contrast scatterer with bone-like properties, although qualitative results can still be obtained by the k-space method with high efficiency. Possible extensions to the method, including representation of absorption effects, absorbing boundary conditions, elastic-wave propagation, and acoustic nonlinearity, are discussed.

The use of imprecise processing to improve accuracy in weather & climate prediction

NASA Astrophysics Data System (ADS)

Düben, Peter D.; McNamara, Hugh; Palmer, T. N.

2014-08-01

The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing bit-reproducibility and precision in exchange for improvements in performance and potentially accuracy of forecasts, due to a reduction in power consumption that could allow higher resolution. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud-resolving atmospheric modelling. The impact of both hardware induced faults and low precision arithmetic is tested using the Lorenz '96 model and the dynamical core of a global atmosphere model. In the Lorenz '96 model there is a natural scale separation; the spectral discretisation used in the dynamical core also allows large and small scale dynamics to be treated separately within the code. Such scale separation allows the impact of lower-accuracy arithmetic to be restricted to components close to the truncation scales and hence close to the necessarily inexact parametrised representations of unresolved processes. By contrast, the larger scales are calculated using high precision deterministic arithmetic. Hardware faults from stochastic processors are emulated using a bit-flip model with different fault rates. Our simulations show that both approaches to inexact calculations do not substantially affect the large scale behaviour, provided they are restricted to act only on smaller scales. By contrast, results from the Lorenz '96 simulations are superior when small scales are calculated on an emulated stochastic processor than when those small scales are parametrised. This suggests that inexact calculations at the small scale could reduce computation and power costs without adversely affecting the quality of the simulations. This would allow higher resolution models to be run at the same computational cost.

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoginath, Srikanth B.; Perumalla, Kalyan S.

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a largemore » parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.« less

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

DOE PAGES

Yoginath, Srikanth B.; Perumalla, Kalyan S.

2018-01-31

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a largemore » parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.« less

Simulation of nitrate reduction in groundwater - An upscaling approach from small catchments to the Baltic Sea basin

NASA Astrophysics Data System (ADS)

Hansen, A. L.; Donnelly, C.; Refsgaard, J. C.; Karlsson, I. B.

2018-01-01

This paper describes a modeling approach proposed to simulate the impact of local-scale, spatially targeted N-mitigation measures for the Baltic Sea Basin. Spatially targeted N-regulations aim at exploiting the considerable spatial differences in the natural N-reduction taking place in groundwater and surface water. While such measures can be simulated using local-scale physically-based catchment models, use of such detailed models for the 1.8 million km2 Baltic Sea basin is not feasible due to constraints on input data and computing power. Large-scale models that are able to simulate the Baltic Sea basin, on the other hand, do not have adequate spatial resolution to simulate some of the field-scale measures. Our methodology combines knowledge and results from two local-scale physically-based MIKE SHE catchment models, the large-scale and more conceptual E-HYPE model, and auxiliary data in order to enable E-HYPE to simulate how spatially targeted regulation of agricultural practices may affect N-loads to the Baltic Sea. We conclude that the use of E-HYPE with this upscaling methodology enables the simulation of the impact on N-loads of applying a spatially targeted regulation at the Baltic Sea basin scale to the correct order-of-magnitude. The E-HYPE model together with the upscaling methodology therefore provides a sound basis for large-scale policy analysis; however, we do not expect it to be sufficiently accurate to be useful for the detailed design of local-scale measures.

Computing general-relativistic effects from Newtonian N-body simulations: Frame dragging in the post-Friedmann approach

NASA Astrophysics Data System (ADS)

Bruni, Marco; Thomas, Daniel B.; Wands, David

2014-02-01

We present the first calculation of an intrinsically relativistic quantity, the leading-order correction to Newtonian theory, in fully nonlinear cosmological large-scale structure studies. Traditionally, nonlinear structure formation in standard ΛCDM cosmology is studied using N-body simulations, based on Newtonian gravitational dynamics on an expanding background. When one derives the Newtonian regime in a way that is a consistent approximation to the Einstein equations, the first relativistic correction to the usual Newtonian scalar potential is a gravitomagnetic vector potential, giving rise to frame dragging. At leading order, this vector potential does not affect the matter dynamics, thus it can be computed from Newtonian N-body simulations. We explain how we compute the vector potential from simulations in ΛCDM and examine its magnitude relative to the scalar potential, finding that the power spectrum of the vector potential is of the order 10-5 times the scalar power spectrum over the range of nonlinear scales we consider. On these scales the vector potential is up to two orders of magnitudes larger than the value predicted by second-order perturbation theory extrapolated to the same scales. We also discuss some possible observable effects and future developments.

Mantle convection on modern supercomputers

NASA Astrophysics Data System (ADS)

Weismüller, Jens; Gmeiner, Björn; Mohr, Marcus; Waluga, Christian; Wohlmuth, Barbara; Rüde, Ulrich; Bunge, Hans-Peter

2015-04-01

Mantle convection is the cause for plate tectonics, the formation of mountains and oceans, and the main driving mechanism behind earthquakes. The convection process is modeled by a system of partial differential equations describing the conservation of mass, momentum and energy. Characteristic to mantle flow is the vast disparity of length scales from global to microscopic, turning mantle convection simulations into a challenging application for high-performance computing. As system size and technical complexity of the simulations continue to increase, design and implementation of simulation models for next generation large-scale architectures demand an interdisciplinary co-design. Here we report about recent advances of the TERRA-NEO project, which is part of the high visibility SPPEXA program, and a joint effort of four research groups in computer sciences, mathematics and geophysical application under the leadership of FAU Erlangen. TERRA-NEO develops algorithms for future HPC infrastructures, focusing on high computational efficiency and resilience in next generation mantle convection models. We present software that can resolve the Earth's mantle with up to 1012 grid points and scales efficiently to massively parallel hardware with more than 50,000 processors. We use our simulations to explore the dynamic regime of mantle convection assessing the impact of small scale processes on global mantle flow.

Large-Scale NASA Science Applications on the Columbia Supercluster

NASA Technical Reports Server (NTRS)

Brooks, Walter

2005-01-01

Columbia, NASA's newest 61 teraflops supercomputer that became operational late last year, is a highly integrated Altix cluster of 10,240 processors, and was named to honor the crew of the Space Shuttle lost in early 2003. Constructed in just four months, Columbia increased NASA's computing capability ten-fold, and revitalized the Agency's high-end computing efforts. Significant cutting-edge science and engineering simulations in the areas of space and Earth sciences, as well as aeronautics and space operations, are already occurring on this largest operational Linux supercomputer, demonstrating its capacity and capability to accelerate NASA's space exploration vision. The presentation will describe how an integrated environment consisting not only of next-generation systems, but also modeling and simulation, high-speed networking, parallel performance optimization, and advanced data analysis and visualization, is being used to reduce design cycle time, accelerate scientific discovery, conduct parametric analysis of multiple scenarios, and enhance safety during the life cycle of NASA missions. The talk will conclude by discussing how NAS partnered with various NASA centers, other government agencies, computer industry, and academia, to create a national resource in large-scale modeling and simulation.

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

NASA Astrophysics Data System (ADS)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.; Papka, M. E.; Benjamin, D. P.

2017-01-01

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application and the performance that was achieved.

Can a numerically stable subgrid-scale model for turbulent flow computation be ideally accurate?: a preliminary theoretical study for the Gaussian filtered Navier-Stokes equations.

PubMed

Ida, Masato; Taniguchi, Nobuyuki

2003-09-01

This paper introduces a candidate for the origin of the numerical instabilities in large eddy simulation repeatedly observed in academic and practical industrial flow computations. Without resorting to any subgrid-scale modeling, but based on a simple assumption regarding the streamwise component of flow velocity, it is shown theoretically that in a channel-flow computation, the application of the Gaussian filtering to the incompressible Navier-Stokes equations yields a numerically unstable term, a cross-derivative term, which is similar to one appearing in the Gaussian filtered Vlasov equation derived by Klimas [J. Comput. Phys. 68, 202 (1987)] and also to one derived recently by Kobayashi and Shimomura [Phys. Fluids 15, L29 (2003)] from the tensor-diffusivity subgrid-scale term in a dynamic mixed model. The present result predicts that not only the numerical methods and the subgrid-scale models employed but also only the applied filtering process can be a seed of this numerical instability. An investigation concerning the relationship between the turbulent energy scattering and the unstable term shows that the instability of the term does not necessarily represent the backscatter of kinetic energy which has been considered a possible origin of numerical instabilities in large eddy simulation. The present findings raise the question whether a numerically stable subgrid-scale model can be ideally accurate.

Advanced computations in plasma physics

NASA Astrophysics Data System (ADS)

Tang, W. M.

2002-05-01

Scientific simulation in tandem with theory and experiment is an essential tool for understanding complex plasma behavior. In this paper we review recent progress and future directions for advanced simulations in magnetically confined plasmas with illustrative examples chosen from magnetic confinement research areas such as microturbulence, magnetohydrodynamics, magnetic reconnection, and others. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales together with access to powerful new computational resources. In particular, the fusion energy science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of turbulence self-regulation by zonal flows. It should be emphasized that these calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to plasma science.

An engineering closure for heavily under-resolved coarse-grid CFD in large applications

NASA Astrophysics Data System (ADS)

Class, Andreas G.; Yu, Fujiang; Jordan, Thomas

2016-11-01

Even though high performance computation allows very detailed description of a wide range of scales in scientific computations, engineering simulations used for design studies commonly merely resolve the large scales thus speeding up simulation time. The coarse-grid CFD (CGCFD) methodology is developed for flows with repeated flow patterns as often observed in heat exchangers or porous structures. It is proposed to use inviscid Euler equations on a very coarse numerical mesh. This coarse mesh needs not to conform to the geometry in all details. To reinstall physics on all smaller scales cheap subgrid models are employed. Subgrid models are systematically constructed by analyzing well-resolved generic representative simulations. By varying the flow conditions in these simulations correlations are obtained. These comprehend for each individual coarse mesh cell a volume force vector and volume porosity. Moreover, for all vertices, surface porosities are derived. CGCFD is related to the immersed boundary method as both exploit volume forces and non-body conformal meshes. Yet, CGCFD differs with respect to the coarser mesh and the use of Euler equations. We will describe the methodology based on a simple test case and the application of the method to a 127 pin wire-wrap fuel bundle.

Challenges in scaling NLO generators to leadership computers

NASA Astrophysics Data System (ADS)

Benjamin, D.; Childers, JT; Hoeche, S.; LeCompte, T.; Uram, T.

2017-10-01

Exascale computing resources are roughly a decade away and will be capable of 100 times more computing than current supercomputers. In the last year, Energy Frontier experiments crossed a milestone of 100 million core-hours used at the Argonne Leadership Computing Facility, Oak Ridge Leadership Computing Facility, and NERSC. The Fortran-based leading-order parton generator called Alpgen was successfully scaled to millions of threads to achieve this level of usage on Mira. Sherpa and MadGraph are next-to-leading order generators used heavily by LHC experiments for simulation. Integration times for high-multiplicity or rare processes can take a week or more on standard Grid machines, even using all 16-cores. We will describe our ongoing work to scale the Sherpa generator to thousands of threads on leadership-class machines and reduce run-times to less than a day. This work allows the experiments to leverage large-scale parallel supercomputers for event generation today, freeing tens of millions of grid hours for other work, and paving the way for future applications (simulation, reconstruction) on these and future supercomputers.

Initial conditions and modeling for simulations of shock driven turbulent material mixing

DOE PAGES

Grinstein, Fernando F.

2016-11-17

Here, we focus on the simulation of shock-driven material mixing driven by flow instabilities and initial conditions (IC). Beyond complex multi-scale resolution issues of shocks and variable density turbulence, me must address the equally difficult problem of predicting flow transition promoted by energy deposited at the material interfacial layer during the shock interface interactions. Transition involves unsteady large-scale coherent-structure dynamics capturable by a large eddy simulation (LES) strategy, but not by an unsteady Reynolds-Averaged Navier–Stokes (URANS) approach based on developed equilibrium turbulence assumptions and single-point-closure modeling. On the engineering end of computations, such URANS with reduced 1D/2D dimensionality and coarsermore » grids, tend to be preferred for faster turnaround in full-scale configurations.« less

Scale-Resolving simulations (SRS): How much resolution do we really need?

NASA Astrophysics Data System (ADS)

Pereira, Filipe M. S.; Girimaji, Sharath

2017-11-01

Scale-resolving simulations (SRS) are emerging as the computational approach of choice for many engineering flows with coherent structures. The SRS methods seek to resolve only the most important features of the coherent structures and model the remainder of the flow field with canonical closures. With reference to a typical Large-Eddy Simulation (LES), practical SRS methods aim to resolve a considerably narrower range of scales (reduced physical resolution) to achieve an adequate degree of accuracy at reasonable computational effort. While the objective of SRS is well-founded, the criteria for establishing the optimal degree of resolution required to achieve an acceptable level of accuracy are not clear. This study considers the canonical case of the flow around a circular cylinder to address the issue of `optimal' resolution. Two important criteria are developed. The first condition addresses the issue of adequate resolution of the flow field. The second guideline provides an assessment of whether the modeled field is canonical (stochastic) turbulence amenable to closure-based computations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, William D; Johansen, Hans; Evans, Katherine J

We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy andmore » fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

To simulate or not to simulate: what are the questions?

PubMed

Dudai, Yadin; Evers, Kathinka

2014-10-22

Simulation is a powerful method in science and engineering. However, simulation is an umbrella term, and its meaning and goals differ among disciplines. Rapid advances in neuroscience and computing draw increasing attention to large-scale brain simulations. What is the meaning of simulation, and what should the method expect to achieve? We discuss the concept of simulation from an integrated scientific and philosophical vantage point and pinpoint selected issues that are specific to brain simulation.

Large Eddy Simulation Study for Fluid Disintegration and Mixing

NASA Technical Reports Server (NTRS)

Bellan, Josette; Taskinoglu, Ezgi

2011-01-01

A new modeling approach is based on the concept of large eddy simulation (LES) within which the large scales are computed and the small scales are modeled. The new approach is expected to retain the fidelity of the physics while also being computationally efficient. Typically, only models for the small-scale fluxes of momentum, species, and enthalpy are used to reintroduce in the simulation the physics lost because the computation only resolves the large scales. These models are called subgrid (SGS) models because they operate at a scale smaller than the LES grid. In a previous study of thermodynamically supercritical fluid disintegration and mixing, additional small-scale terms, one in the momentum and one in the energy conservation equations, were identified as requiring modeling. These additional terms were due to the tight coupling between dynamics and real-gas thermodynamics. It was inferred that if these terms would not be modeled, the high density-gradient magnitude regions, experimentally identified as a characteristic feature of these flows, would not be accurately predicted without the additional term in the momentum equation; these high density-gradient magnitude regions were experimentally shown to redistribute turbulence in the flow. And it was also inferred that without the additional term in the energy equation, the heat flux magnitude could not be accurately predicted; the heat flux to the wall of combustion devices is a crucial quantity that determined necessary wall material properties. The present work involves situations where only the term in the momentum equation is important. Without this additional term in the momentum equation, neither the SGS-flux constant-coefficient Smagorinsky model nor the SGS-flux constant-coefficient Gradient model could reproduce in LES the pressure field or the high density-gradient magnitude regions; the SGS-flux constant- coefficient Scale-Similarity model was the most successful in this endeavor although not totally satisfactory. With a model for the additional term in the momentum equation, the predictions of the constant-coefficient Smagorinsky and constant-coefficient Scale-Similarity models were improved to a certain extent; however, most of the improvement was obtained for the Gradient model. The previously derived model and a newly developed model for the additional term in the momentum equation were both tested, with the new model proving even more successful than the previous model at reproducing the high density-gradient magnitude regions. Several dynamic SGS-flux models, in which the SGS-flux model coefficient is computed as part of the simulation, were tested in conjunction with the new model for this additional term in the momentum equation. The most successful dynamic model was a "mixed" model combining the Smagorinsky and Gradient models. This work is directly applicable to simulations of gas turbine engines (aeronautics) and rocket engines (astronautics).

Data Intensive Analysis of Biomolecular Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straatsma, TP; Soares, Thereza A.

2007-12-01

The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less

Data Intensive Analysis of Biomolecular Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straatsma, TP

2008-03-01

The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less

Large Eddy Simulation ... Where Do We Stand? International Workshop Held in St. Petersburg Beach, Florida on 19-21 December 1990.

DTIC Science & Technology

1990-01-01

S. Orszag, Chairman 1. P. Moin Some Issues in Computation of Turbulent Flows. 2. M. Lesieur, P. Comte, X. Normand, 0. Metais and A. Silveira Spectral...Richtmeyer’s computational experience with one-dimensional shock waves (1950) indicated the value of a non-linear artificial viscosity. Charney and... computer architecture and the advantages of semi-Lagrangian advective schemes may lure large-scale atmospheric modelers back to finite-difference

Cosmological neutrino simulations at extreme scale

DOE PAGES

Emberson, J. D.; Yu, Hao-Ran; Inman, Derek; ...

2017-08-01

Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision from theoretical predictions of neutrino clustering. Numerical simulations of the non-linear evolution of cold dark matter and neutrinos play a pivotal role in this process. We incorporate neutrinos into the cosmological N-body code CUBEP3M and discuss the challenges associated with pushing to the extreme scales demanded by the neutrino problem. We highlight code optimizations made to exploit modern high performance computing architectures and present a novel method ofmore » data compression that reduces the phase-space particle footprint from 24 bytes in single precision to roughly 9 bytes. We scale the neutrino problem to the Tianhe-2 supercomputer and provide details of our production run, named TianNu, which uses 86% of the machine (13,824 compute nodes). With a total of 2.97 trillion particles, TianNu is currently the world’s largest cosmological N-body simulation and improves upon previous neutrino simulations by two orders of magnitude in scale. We finish with a discussion of the unanticipated computational challenges that were encountered during the TianNu runtime.« less

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

DOE PAGES

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake; ...

2017-03-24

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Efficient Constant-Time Complexity Algorithm for Stochastic Simulation of Large Reaction Networks.

PubMed

Thanh, Vo Hong; Zunino, Roberto; Priami, Corrado

2017-01-01

Exact stochastic simulation is an indispensable tool for a quantitative study of biochemical reaction networks. The simulation realizes the time evolution of the model by randomly choosing a reaction to fire and update the system state according to a probability that is proportional to the reaction propensity. Two computationally expensive tasks in simulating large biochemical networks are the selection of next reaction firings and the update of reaction propensities due to state changes. We present in this work a new exact algorithm to optimize both of these simulation bottlenecks. Our algorithm employs the composition-rejection on the propensity bounds of reactions to select the next reaction firing. The selection of next reaction firings is independent of the number reactions while the update of propensities is skipped and performed only when necessary. It therefore provides a favorable scaling for the computational complexity in simulating large reaction networks. We benchmark our new algorithm with the state of the art algorithms available in literature to demonstrate its applicability and efficiency.

New Challenges in Computational Thermal Hydraulics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yadigaroglu, George; Lakehal, Djamel

New needs and opportunities drive the development of novel computational methods for the design and safety analysis of light water reactors (LWRs). Some new methods are likely to be three dimensional. Coupling is expected between system codes, computational fluid dynamics (CFD) modules, and cascades of computations at scales ranging from the macro- or system scale to the micro- or turbulence scales, with the various levels continuously exchanging information back and forth. The ISP-42/PANDA and the international SETH project provide opportunities for testing applications of single-phase CFD methods to LWR safety problems. Although industrial single-phase CFD applications are commonplace, computational multifluidmore » dynamics is still under development. However, first applications are appearing; the state of the art and its potential uses are discussed. The case study of condensation of steam/air mixtures injected from a downward-facing vent into a pool of water is a perfect illustration of a simulation cascade: At the top of the hierarchy of scales, system behavior can be modeled with a system code; at the central level, the volume-of-fluid method can be applied to predict large-scale bubbling behavior; at the bottom of the cascade, direct-contact condensation can be treated with direct numerical simulation, in which turbulent flow (in both the gas and the liquid), interfacial dynamics, and heat/mass transfer are directly simulated without resorting to models.« less

An efficient and reliable predictive method for fluidized bed simulation

DOE PAGES

Lu, Liqiang; Benyahia, Sofiane; Li, Tingwen

2017-06-13

In past decades, the continuum approach was the only practical technique to simulate large-scale fluidized bed reactors because discrete approaches suffer from the cost of tracking huge numbers of particles and their collisions. This study significantly improved the computation speed of discrete particle methods in two steps: First, the time-driven hard-sphere (TDHS) algorithm with a larger time-step is proposed allowing a speedup of 20-60 times; second, the number of tracked particles is reduced by adopting the coarse-graining technique gaining an additional 2-3 orders of magnitude speedup of the simulations. A new velocity correction term was introduced and validated in TDHSmore » to solve the over-packing issue in dense granular flow. The TDHS was then coupled with the coarse-graining technique to simulate a pilot-scale riser. The simulation results compared well with experiment data and proved that this new approach can be used for efficient and reliable simulations of large-scale fluidized bed systems.« less

An efficient and reliable predictive method for fluidized bed simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Liqiang; Benyahia, Sofiane; Li, Tingwen

2017-06-29

In past decades, the continuum approach was the only practical technique to simulate large-scale fluidized bed reactors because discrete approaches suffer from the cost of tracking huge numbers of particles and their collisions. This study significantly improved the computation speed of discrete particle methods in two steps: First, the time-driven hard-sphere (TDHS) algorithm with a larger time-step is proposed allowing a speedup of 20-60 times; second, the number of tracked particles is reduced by adopting the coarse-graining technique gaining an additional 2-3 orders of magnitude speedup of the simulations. A new velocity correction term was introduced and validated in TDHSmore » to solve the over-packing issue in dense granular flow. The TDHS was then coupled with the coarse-graining technique to simulate a pilot-scale riser. The simulation results compared well with experiment data and proved that this new approach can be used for efficient and reliable simulations of large-scale fluidized bed systems.« less

Users matter : multi-agent systems model of high performance computing cluster users.

DOE Office of Scientific and Technical Information (OSTI.GOV)

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

Argonne simulation framework for intelligent transportation systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ewing, T.; Doss, E.; Hanebutte, U.

1996-04-01

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distributed (networked) computer systems; however, a version for a stand alone workstation is also available. The ITS simulator includes an Expert Driver Model (EDM) of instrumented ``smart`` vehicles with in-vehicle navigation units. The EDM is capable of performing optimal route planning and communicating with Traffic Management Centers (TMC). A dynamic road map data base is sued for optimum route planning, where the data is updated periodically tomore » reflect any changes in road or weather conditions. The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces that includes human-factors studies to support safety and operational research. Realistic modeling of variations of the posted driving speed are based on human factor studies that take into consideration weather, road conditions, driver`s personality and behavior and vehicle type. The simulator has been developed on a distributed system of networked UNIX computers, but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of the developed simulator is that vehicles will be represented by autonomous computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. Vehicle processes interact with each other and with ITS components by exchanging messages. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.« less

Large-scale large eddy simulation of nuclear reactor flows: Issues and perspectives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merzari, Elia; Obabko, Aleks; Fischer, Paul

Numerical simulation has been an intrinsic part of nuclear engineering research since its inception. In recent years a transition is occurring toward predictive, first-principle-based tools such as computational fluid dynamics. Even with the advent of petascale computing, however, such tools still have significant limitations. In the present work some of these issues, and in particular the presence of massive multiscale separation, are discussed, as well as some of the research conducted to mitigate them. Petascale simulations at high fidelity (large eddy simulation/direct numerical simulation) were conducted with the massively parallel spectral element code Nek5000 on a series of representative problems.more » These simulations shed light on the requirements of several types of simulation: (1) axial flow around fuel rods, with particular attention to wall effects; (2) natural convection in the primary vessel; and (3) flow in a rod bundle in the presence of spacing devices. Finally, the focus of the work presented here is on the lessons learned and the requirements to perform these simulations at exascale. Additional physical insight gained from these simulations is also emphasized.« less

Large-scale large eddy simulation of nuclear reactor flows: Issues and perspectives

DOE PAGES

Merzari, Elia; Obabko, Aleks; Fischer, Paul; ...

2016-11-03

Numerical simulation has been an intrinsic part of nuclear engineering research since its inception. In recent years a transition is occurring toward predictive, first-principle-based tools such as computational fluid dynamics. Even with the advent of petascale computing, however, such tools still have significant limitations. In the present work some of these issues, and in particular the presence of massive multiscale separation, are discussed, as well as some of the research conducted to mitigate them. Petascale simulations at high fidelity (large eddy simulation/direct numerical simulation) were conducted with the massively parallel spectral element code Nek5000 on a series of representative problems.more » These simulations shed light on the requirements of several types of simulation: (1) axial flow around fuel rods, with particular attention to wall effects; (2) natural convection in the primary vessel; and (3) flow in a rod bundle in the presence of spacing devices. Finally, the focus of the work presented here is on the lessons learned and the requirements to perform these simulations at exascale. Additional physical insight gained from these simulations is also emphasized.« less

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

NASA Technical Reports Server (NTRS)

Rutherford, Brian

2000-01-01

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

A large-scale computer facility for computational aerodynamics

NASA Technical Reports Server (NTRS)

Bailey, F. R.; Ballhaus, W. F., Jr.

1985-01-01

As a result of advances related to the combination of computer system technology and numerical modeling, computational aerodynamics has emerged as an essential element in aerospace vehicle design methodology. NASA has, therefore, initiated the Numerical Aerodynamic Simulation (NAS) Program with the objective to provide a basis for further advances in the modeling of aerodynamic flowfields. The Program is concerned with the development of a leading-edge, large-scale computer facility. This facility is to be made available to Government agencies, industry, and universities as a necessary element in ensuring continuing leadership in computational aerodynamics and related disciplines. Attention is given to the requirements for computational aerodynamics, the principal specific goals of the NAS Program, the high-speed processor subsystem, the workstation subsystem, the support processing subsystem, the graphics subsystem, the mass storage subsystem, the long-haul communication subsystem, the high-speed data-network subsystem, and software.

Full-color large-scaled computer-generated holograms using RGB color filters.

PubMed

Tsuchiyama, Yasuhiro; Matsushima, Kyoji

2017-02-06

A technique using RGB color filters is proposed for creating high-quality full-color computer-generated holograms (CGHs). The fringe of these CGHs is composed of more than a billion pixels. The CGHs reconstruct full-parallax three-dimensional color images with a deep sensation of depth caused by natural motion parallax. The simulation technique as well as the principle and challenges of high-quality full-color reconstruction are presented to address the design of filter properties suitable for large-scaled CGHs. Optical reconstructions of actual fabricated full-color CGHs are demonstrated in order to verify the proposed techniques.

Improvement of CFD Methods for Modeling Full Scale Circulating Fluidized Bed Combustion Systems

NASA Astrophysics Data System (ADS)

Shah, Srujal; Klajny, Marcin; Myöhänen, Kari; Hyppänen, Timo

With the currently available methods of computational fluid dynamics (CFD), the task of simulating full scale circulating fluidized bed combustors is very challenging. In order to simulate the complex fluidization process, the size of calculation cells should be small and the calculation should be transient with small time step size. For full scale systems, these requirements lead to very large meshes and very long calculation times, so that the simulation in practice is difficult. This study investigates the requirements of cell size and the time step size for accurate simulations, and the filtering effects caused by coarser mesh and longer time step. A modeling study of a full scale CFB furnace is presented and the model results are compared with experimental data.

Using a million cell simulation of the cerebellum: network scaling and task generality.

PubMed

Li, Wen-Ke; Hausknecht, Matthew J; Stone, Peter; Mauk, Michael D

2013-11-01

Several factors combine to make it feasible to build computer simulations of the cerebellum and to test them in biologically realistic ways. These simulations can be used to help understand the computational contributions of various cerebellar components, including the relevance of the enormous number of neurons in the granule cell layer. In previous work we have used a simulation containing 12000 granule cells to develop new predictions and to account for various aspects of eyelid conditioning, a form of motor learning mediated by the cerebellum. Here we demonstrate the feasibility of scaling up this simulation to over one million granule cells using parallel graphics processing unit (GPU) technology. We observe that this increase in number of granule cells requires only twice the execution time of the smaller simulation on the GPU. We demonstrate that this simulation, like its smaller predecessor, can emulate certain basic features of conditioned eyelid responses, with a slight improvement in performance in one measure. We also use this simulation to examine the generality of the computation properties that we have derived from studying eyelid conditioning. We demonstrate that this scaled up simulation can learn a high level of performance in a classic machine learning task, the cart-pole balancing task. These results suggest that this parallel GPU technology can be used to build very large-scale simulations whose connectivity ratios match those of the real cerebellum and that these simulations can be used guide future studies on cerebellar mediated tasks and on machine learning problems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Evidence for Bolgiano-Obukhov scaling in rotating stratified turbulence using high-resolution direct numerical simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosenberg, Duane L; Pouquet, Dr. Annick; Mininni, Dr. Pablo D.

2015-01-01

We report results on rotating stratified turbulence in the absence of forcing, with large-scale isotropic initial conditions, using direct numerical simulations computed on grids of up tomore » $4096^3$ points. The Reynolds and Froude numbers are respectively equal to $$Re=5.4\\times 10^4$$ and $Fr=0.0242$$. The ratio of the Brunt-V\\"ais\\"al\\"a to the inertial wave frequency, $$N/f$, is taken to be equal to 5, a choice appropriate to model the dynamics of the southern abyssal ocean at mid latitudes. This gives a global buoyancy Reynolds number $$R_B=ReFr^2=32$$, a value sufficient for some isotropy to be recovered in the small scales beyond the Ozmidov scale, but still moderate enough that the intermediate scales where waves are prevalent are well resolved. We concentrate on the large-scale dynamics and confirm that the Froude number based on a typical vertical length scale is of order unity, with strong gradients in the vertical. Two characteristic scales emerge from this computation, and are identified from sharp variations in the spectral distribution of either total energy or helicity. A spectral break is also observed at a scale at which the partition of energy between the kinetic and potential modes changes abruptly, and beyond which a Kolmogorov-like spectrum recovers. Large slanted layers are ubiquitous in the flow in the velocity and temperature fields, and a large-scale enhancement of energy is also observed, directly attributable to the effect of rotation.« less

A Priori Subgrid Analysis of Temporal Mixing Layers with Evaporating Droplets

NASA Technical Reports Server (NTRS)

Okongo, Nora; Bellan, Josette

1999-01-01

Subgrid analysis of a transitional temporal mixing layer with evaporating droplets has been performed using three sets of results from a Direct Numerical Simulation (DNS) database, with Reynolds numbers (based on initial vorticity thickness) as large as 600 and with droplet mass loadings as large as 0.5. In the DNS, the gas phase is computed using a Eulerian formulation, with Lagrangian droplet tracking. The Large Eddy Simulation (LES) equations corresponding to the DNS are first derived, and key assumptions in deriving them are first confirmed by computing the terms using the DNS database. Since LES of this flow requires the computation of unfiltered gas-phase variables at droplet locations from filtered gas-phase variables at the grid points, it is proposed to model these by assuming the gas-phase variables to be the sum of the filtered variables and a correction based on the filtered standard deviation; this correction is then computed from the Subgrid Scale (SGS) standard deviation. This model predicts the unfiltered variables at droplet locations considerably better than simply interpolating the filtered variables. Three methods are investigated for modeling the SGS standard deviation: the Smagorinsky approach, the Gradient model and the Scale-Similarity formulation. When the proportionality constant inherent in the SGS models is properly calculated, the Gradient and Scale-Similarity methods give results in excellent agreement with the DNS.

GPU-based Space Situational Awareness Simulation utilising Parallelism for Enhanced Multi-sensor Management

NASA Astrophysics Data System (ADS)

Hobson, T.; Clarkson, V.

2012-09-01

As a result of continual space activity since the 1950s, there are now a large number of man-made Resident Space Objects (RSOs) orbiting the Earth. Because of the large number of items and their relative speeds, the possibility of destructive collisions involving important space assets is now of significant concern to users and operators of space-borne technologies. As a result, a growing number of international agencies are researching methods for improving techniques to maintain Space Situational Awareness (SSA). Computer simulation is a method commonly used by many countries to validate competing methodologies prior to full scale adoption. The use of supercomputing and/or reduced scale testing is often necessary to effectively simulate such a complex problem on todays computers. Recently the authors presented a simulation aimed at reducing the computational burden by selecting the minimum level of fidelity necessary for contrasting methodologies and by utilising multi-core CPU parallelism for increased computational efficiency. The resulting simulation runs on a single PC while maintaining the ability to effectively evaluate competing methodologies. Nonetheless, the ability to control the scale and expand upon the computational demands of the sensor management system is limited. In this paper, we examine the advantages of increasing the parallelism of the simulation by means of General Purpose computing on Graphics Processing Units (GPGPU). As many sub-processes pertaining to SSA management are independent, we demonstrate how parallelisation via GPGPU has the potential to significantly enhance not only research into techniques for maintaining SSA, but also to enhance the level of sophistication of existing space surveillance sensors and sensor management systems. Nonetheless, the use of GPGPU imposes certain limitations and adds to the implementation complexity, both of which require consideration to achieve an effective system. We discuss these challenges and how they can be overcome. We further describe an application of the parallelised system where visibility prediction is used to enhance sensor management. This facilitates significant improvement in maximum catalogue error when RSOs become temporarily unobservable. The objective is to demonstrate the enhanced scalability and increased computational capability of the system.

Towards the simulation of molecular collisions with a superconducting quantum computer

NASA Astrophysics Data System (ADS)

Geller, Michael

2013-05-01

I will discuss the prospects for the use of large-scale, error-corrected quantum computers to simulate complex quantum dynamics such as molecular collisions. This will likely require millions qubits. I will also discuss an alternative approach [M. R. Geller et al., arXiv:1210.5260] that is ideally suited for today's superconducting circuits, which uses the single-excitation subspace (SES) of a system of n tunably coupled qubits. The SES method allows many operations in the unitary group SU(n) to be implemented in a single step, bypassing the need for elementary gates, thereby making large computations possible without error correction. The method enables universal quantum simulation, including simulation of the time-dependent Schrodinger equation, and we argue that a 1000-qubit SES processor should be capable of achieving quantum speedup relative to a petaflop supercomputer. We speculate on the utility and practicality of such a simulator for atomic and molecular collision physics. Work supported by the US National Science Foundation CDI program.

Towards the computation of time-periodic inertial range dynamics

NASA Astrophysics Data System (ADS)

van Veen, L.; Vela-Martín, A.; Kawahara, G.

2018-04-01

We explore the possibility of computing simple invariant solutions, like travelling waves or periodic orbits, in Large Eddy Simulation (LES) on a periodic domain with constant external forcing. The absence of material boundaries and the simple forcing mechanism make this system a comparatively simple target for the study of turbulent dynamics through invariant solutions. We show, that in spite of the application of eddy viscosity the computations are still rather challenging and must be performed on GPU cards rather than conventional coupled CPUs. We investigate the onset of turbulence in this system by means of bifurcation analysis, and present a long-period, large-amplitude unstable periodic orbit that is filtered from a turbulent time series. Although this orbit is computed on a coarse grid, with only a small separation between the integral scale and the LES filter length, the periodic dynamics seem to capture a regeneration process of the large-scale vortices.

Using Modeling and Simulation to Complement Testing for Increased Understanding of Weapon Subassembly Response.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Michael K.; Davidson, Megan

As part of Sandia’s nuclear deterrence mission, the B61-12 Life Extension Program (LEP) aims to modernize the aging weapon system. Modernization requires requalification and Sandia is using high performance computing to perform advanced computational simulations to better understand, evaluate, and verify weapon system performance in conjunction with limited physical testing. The Nose Bomb Subassembly (NBSA) of the B61-12 is responsible for producing a fuzing signal upon ground impact. The fuzing signal is dependent upon electromechanical impact sensors producing valid electrical fuzing signals at impact. Computer generated models were used to assess the timing between the impact sensor’s response to themore » deceleration of impact and damage to major components and system subassemblies. The modeling and simulation team worked alongside the physical test team to design a large-scale reverse ballistic test to not only assess system performance, but to also validate their computational models. The reverse ballistic test conducted at Sandia’s sled test facility sent a rocket sled with a representative target into a stationary B61-12 (NBSA) to characterize the nose crush and functional response of NBSA components. Data obtained from data recorders and high-speed photometrics were integrated with previously generated computer models in order to refine and validate the model’s ability to reliably simulate real-world effects. Large-scale tests are impractical to conduct for every single impact scenario. By creating reliable computer models, we can perform simulations that identify trends and produce estimates of outcomes over the entire range of required impact conditions. Sandia’s HPCs enable geometric resolution that was unachievable before, allowing for more fidelity and detail, and creating simulations that can provide insight to support evaluation of requirements and performance margins. As computing resources continue to improve, researchers at Sandia are hoping to improve these simulations so they provide increasingly credible analysis of the system response and performance over the full range of conditions.« less

Enhanced job control language procedures for the SIMSYS2D two-dimensional water-quality simulation system

USGS Publications Warehouse

Karavitis, G.A.

1984-01-01

The SIMSYS2D two-dimensional water-quality simulation system is a large-scale digital modeling software system used to simulate flow and transport of solutes in freshwater and estuarine environments. Due to the size, processing requirements, and complexity of the system, there is a need to easily move the system and its associated files between computer sites when required. A series of job control language (JCL) procedures was written to allow transferability between IBM and IBM-compatible computers. (USGS)

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

USGS Publications Warehouse

O'Donnell, Michael

2015-01-01

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Dynamic ruptures on faults of complex geometry: insights from numerical simulations, from large-scale curvature to small-scale fractal roughness

NASA Astrophysics Data System (ADS)

Ulrich, T.; Gabriel, A. A.

2016-12-01

The geometry of faults is subject to a large degree of uncertainty. As buried structures being not directly observable, their complex shapes may only be inferred from surface traces, if available, or through geophysical methods, such as reflection seismology. As a consequence, most studies aiming at assessing the potential hazard of faults rely on idealized fault models, based on observable large-scale features. Yet, real faults are known to be wavy at all scales, their geometric features presenting similar statistical properties from the micro to the regional scale. The influence of roughness on the earthquake rupture process is currently a driving topic in the computational seismology community. From the numerical point of view, rough faults problems are challenging problems that require optimized codes able to run efficiently on high-performance computing infrastructure and simultaneously handle complex geometries. Physically, simulated ruptures hosted by rough faults appear to be much closer to source models inverted from observation in terms of complexity. Incorporating fault geometry on all scales may thus be crucial to model realistic earthquake source processes and to estimate more accurately seismic hazard. In this study, we use the software package SeisSol, based on an ADER-Discontinuous Galerkin scheme, to run our numerical simulations. SeisSol allows solving the spontaneous dynamic earthquake rupture problem and the wave propagation problem with high-order accuracy in space and time efficiently on large-scale machines. In this study, the influence of fault roughness on dynamic rupture style (e.g. onset of supershear transition, rupture front coherence, propagation of self-healing pulses, etc) at different length scales is investigated by analyzing ruptures on faults of varying roughness spectral content. In particular, we investigate the existence of a minimum roughness length scale in terms of rupture inherent length scales below which the rupture ceases to be sensible. Finally, the effect of fault geometry on ground-motions, in the near-field, is considered. Our simulations feature a classical linear slip weakening on the fault and a viscoplastic constitutive model off the fault. The benefits of using a more elaborate fast velocity-weakening friction law will also be considered.

Quantum chemistry simulation on quantum computers: theories and experiments.

PubMed

Lu, Dawei; Xu, Boruo; Xu, Nanyang; Li, Zhaokai; Chen, Hongwei; Peng, Xinhua; Xu, Ruixue; Du, Jiangfeng

2012-07-14

It has been claimed that quantum computers can mimic quantum systems efficiently in the polynomial scale. Traditionally, those simulations are carried out numerically on classical computers, which are inevitably confronted with the exponential growth of required resources, with the increasing size of quantum systems. Quantum computers avoid this problem, and thus provide a possible solution for large quantum systems. In this paper, we first discuss the ideas of quantum simulation, the background of quantum simulators, their categories, and the development in both theories and experiments. We then present a brief introduction to quantum chemistry evaluated via classical computers followed by typical procedures of quantum simulation towards quantum chemistry. Reviewed are not only theoretical proposals but also proof-of-principle experimental implementations, via a small quantum computer, which include the evaluation of the static molecular eigenenergy and the simulation of chemical reaction dynamics. Although the experimental development is still behind the theory, we give prospects and suggestions for future experiments. We anticipate that in the near future quantum simulation will become a powerful tool for quantum chemistry over classical computations.

InfoSymbiotics/DDDAS - The power of Dynamic Data Driven Applications Systems for New Capabilities in Environmental -, Geo-, and Space- Sciences

NASA Astrophysics Data System (ADS)

Darema, F.

2016-12-01

InfoSymbiotics/DDDAS embodies the power of Dynamic Data Driven Applications Systems (DDDAS), a concept whereby an executing application model is dynamically integrated, in a feed-back loop, with the real-time data-acquisition and control components, as well as other data sources of the application system. Advanced capabilities can be created through such new computational approaches in modeling and simulations, and in instrumentation methods, and include: enhancing the accuracy of the application model; speeding-up the computation to allow faster and more comprehensive models of a system, and create decision support systems with the accuracy of full-scale simulations; in addition, the notion of controlling instrumentation processes by the executing application results in more efficient management of application-data and addresses challenges of how to architect and dynamically manage large sets of heterogeneous sensors and controllers, an advance over the static and ad-hoc ways of today - with DDDAS these sets of resources can be managed adaptively and in optimized ways. Large-Scale-Dynamic-Data encompasses the next wave of Big Data, and namely dynamic data arising from ubiquitous sensing and control in engineered, natural, and societal systems, through multitudes of heterogeneous sensors and controllers instrumenting these systems, and where opportunities and challenges at these "large-scales" relate not only to data size but the heterogeneity in data, data collection modalities, fidelities, and timescales, ranging from real-time data to archival data. In tandem with this important dimension of dynamic data, there is an extended view of Big Computing, which includes the collective computing by networked assemblies of multitudes of sensors and controllers, this range from the high-end to the real-time seamlessly integrated and unified, and comprising the Large-Scale-Big-Computing. InfoSymbiotics/DDDAS engenders transformative impact in many application domains, ranging from the nano-scale to the terra-scale and to the extra-terra-scale. The talk will address opportunities for new capabilities together with corresponding research challenges, with illustrative examples from several application areas including environmental sciences, geosciences, and space sciences.

Advanced Computation in Plasma Physics

NASA Astrophysics Data System (ADS)

Tang, William

2001-10-01

Scientific simulation in tandem with theory and experiment is an essential tool for understanding complex plasma behavior. This talk will review recent progress and future directions for advanced simulations in magnetically-confined plasmas with illustrative examples chosen from areas such as microturbulence, magnetohydrodynamics, magnetic reconnection, and others. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales together with access to powerful new computational resources. In particular, the fusion energy science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop MPP's to produce 3-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of turbulence self-regulation by zonal flows. It should be emphasized that these calculations, which typically utilized billions of particles for tens of thousands time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to plasma science.

NASA Advanced Supercomputing Facility Expansion

NASA Technical Reports Server (NTRS)

Thigpen, William W.

2017-01-01

The NASA Advanced Supercomputing (NAS) Division enables advances in high-end computing technologies and in modeling and simulation methods to tackle some of the toughest science and engineering challenges facing NASA today. The name "NAS" has long been associated with leadership and innovation throughout the high-end computing (HEC) community. We play a significant role in shaping HEC standards and paradigms, and provide leadership in the areas of large-scale InfiniBand fabrics, Lustre open-source filesystems, and hyperwall technologies. We provide an integrated high-end computing environment to accelerate NASA missions and make revolutionary advances in science. Pleiades, a petaflop-scale supercomputer, is used by scientists throughout the U.S. to support NASA missions, and is ranked among the most powerful systems in the world. One of our key focus areas is in modeling and simulation to support NASA's real-world engineering applications and make fundamental advances in modeling and simulation methods.

Parallel algorithm for multiscale atomistic/continuum simulations using LAMMPS

NASA Astrophysics Data System (ADS)

Pavia, F.; Curtin, W. A.

2015-07-01

Deformation and fracture processes in engineering materials often require simultaneous descriptions over a range of length and time scales, with each scale using a different computational technique. Here we present a high-performance parallel 3D computing framework for executing large multiscale studies that couple an atomic domain, modeled using molecular dynamics and a continuum domain, modeled using explicit finite elements. We use the robust Coupled Atomistic/Discrete-Dislocation (CADD) displacement-coupling method, but without the transfer of dislocations between atoms and continuum. The main purpose of the work is to provide a multiscale implementation within an existing large-scale parallel molecular dynamics code (LAMMPS) that enables use of all the tools associated with this popular open-source code, while extending CADD-type coupling to 3D. Validation of the implementation includes the demonstration of (i) stability in finite-temperature dynamics using Langevin dynamics, (ii) elimination of wave reflections due to large dynamic events occurring in the MD region and (iii) the absence of spurious forces acting on dislocations due to the MD/FE coupling, for dislocations further than 10 Å from the coupling boundary. A first non-trivial example application of dislocation glide and bowing around obstacles is shown, for dislocation lengths of ∼50 nm using fewer than 1 000 000 atoms but reproducing results of extremely large atomistic simulations at much lower computational cost.

Bridging the scales in atmospheric composition simulations using a nudging technique

NASA Astrophysics Data System (ADS)

D'Isidoro, Massimo; Maurizi, Alberto; Russo, Felicita; Tampieri, Francesco

2010-05-01

Studying the interaction between climate and anthropogenic activities, specifically those concentrated in megacities/hot spots, requires the description of processes in a very wide range of scales from local, where anthropogenic emissions are concentrated to global where we are interested to study the impact of these sources. The description of all the processes at all scales within the same numerical implementation is not feasible because of limited computer resources. Therefore, different phenomena are studied by means of different numerical models that can cover different range of scales. The exchange of information from small to large scale is highly non-trivial though of high interest. In fact uncertainties in large scale simulations are expected to receive large contribution from the most polluted areas where the highly inhomogeneous distribution of sources connected to the intrinsic non-linearity of the processes involved can generate non negligible departures between coarse and fine scale simulations. In this work a new method is proposed and investigated in a case study (August 2009) using the BOLCHEM model. Monthly simulations at coarse (0.5° European domain, run A) and fine (0.1° Central Mediterranean domain, run B) horizontal resolution are performed using the coarse resolution as boundary condition for the fine one. Then another coarse resolution run (run C) is performed, in which the high resolution fields remapped on to the coarse grid are used to nudge the concentrations on the Po Valley area. The nudging is applied to all gas and aerosol species of BOLCHEM. Averaged concentrations and variances over Po Valley and other selected areas for O3 and PM are computed. It is observed that although the variance of run B is markedly larger than that of run A, the variance of run C is smaller because the remapping procedure removes large portion of variance from run B fields. Mean concentrations show some differences depending on species: in general mean values of run C lie between run A and run B. A propagation of the signal outside the nudging region is observed, and is evaluated in terms of differences between coarse resolution (with and without nudging) and fine resolution simulations.

TOPICAL REVIEW: Advances and challenges in computational plasma science

NASA Astrophysics Data System (ADS)

Tang, W. M.; Chan, V. S.

2005-02-01

Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behaviour. Recent advances in simulations of magnetically confined plasmas are reviewed in this paper, with illustrative examples, chosen from associated research areas such as microturbulence, magnetohydrodynamics and other topics. Progress has been stimulated, in particular, by the exponential growth of computer speed along with significant improvements in computer technology. The advances in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics have produced increasingly good agreement between experimental observations and computational modelling. This was enabled by two key factors: (a) innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales and (b) access to powerful new computational resources. Excellent progress has been made in developing codes for which computer run-time and problem-size scale well with the number of processors on massively parallel processors (MPPs). Examples include the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPPs to produce three-dimensional, general geometry, nonlinear particle simulations that have accelerated advances in understanding the nature of turbulence self-regulation by zonal flows. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In looking towards the future, the current results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. This should produce the scientific excitement which will help to (a) stimulate enhanced cross-cutting collaborations with other fields and (b) attract the bright young talent needed for the future health of the field of plasma science.

Advances and challenges in computational plasma science

NASA Astrophysics Data System (ADS)

Tang, W. M.

2005-02-01

Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behaviour. Recent advances in simulations of magnetically confined plasmas are reviewed in this paper, with illustrative examples, chosen from associated research areas such as microturbulence, magnetohydrodynamics and other topics. Progress has been stimulated, in particular, by the exponential growth of computer speed along with significant improvements in computer technology. The advances in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics have produced increasingly good agreement between experimental observations and computational modelling. This was enabled by two key factors: (a) innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales and (b) access to powerful new computational resources. Excellent progress has been made in developing codes for which computer run-time and problem-size scale well with the number of processors on massively parallel processors (MPPs). Examples include the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPPs to produce three-dimensional, general geometry, nonlinear particle simulations that have accelerated advances in understanding the nature of turbulence self-regulation by zonal flows. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In looking towards the future, the current results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. This should produce the scientific excitement which will help to (a) stimulate enhanced cross-cutting collaborations with other fields and (b) attract the bright young talent needed for the future health of the field of plasma science.

Remote visualization and scale analysis of large turbulence datatsets

NASA Astrophysics Data System (ADS)

Livescu, D.; Pulido, J.; Burns, R.; Canada, C.; Ahrens, J.; Hamann, B.

2015-12-01

Accurate simulations of turbulent flows require solving all the dynamically relevant scales of motions. This technique, called Direct Numerical Simulation, has been successfully applied to a variety of simple flows; however, the large-scale flows encountered in Geophysical Fluid Dynamics (GFD) would require meshes outside the range of the most powerful supercomputers for the foreseeable future. Nevertheless, the current generation of petascale computers has enabled unprecedented simulations of many types of turbulent flows which focus on various GFD aspects, from the idealized configurations extensively studied in the past to more complex flows closer to the practical applications. The pace at which such simulations are performed only continues to increase; however, the simulations themselves are restricted to a small number of groups with access to large computational platforms. Yet the petabytes of turbulence data offer almost limitless information on many different aspects of the flow, from the hierarchy of turbulence moments, spectra and correlations, to structure-functions, geometrical properties, etc. The ability to share such datasets with other groups can significantly reduce the time to analyze the data, help the creative process and increase the pace of discovery. Using the largest DOE supercomputing platforms, we have performed some of the biggest turbulence simulations to date, in various configurations, addressing specific aspects of turbulence production and mixing mechanisms. Until recently, the visualization and analysis of such datasets was restricted by access to large supercomputers. The public Johns Hopkins Turbulence database simplifies the access to multi-Terabyte turbulence datasets and facilitates turbulence analysis through the use of commodity hardware. First, one of our datasets, which is part of the database, will be described and then a framework that adds high-speed visualization and wavelet support for multi-resolution analysis of turbulence will be highlighted. The addition of wavelet support reduces the latency and bandwidth requirements for visualization, allowing for many concurrent users, and enables new types of analyses, including scale decomposition and coherent feature extraction.

A Lagrangian subgrid-scale model with dynamic estimation of Lagrangian time scale for large eddy simulation of complex flows

NASA Astrophysics Data System (ADS)

Verma, Aman; Mahesh, Krishnan

2012-08-01

The dynamic Lagrangian averaging approach for the dynamic Smagorinsky model for large eddy simulation is extended to an unstructured grid framework and applied to complex flows. The Lagrangian time scale is dynamically computed from the solution and does not need any adjustable parameter. The time scale used in the standard Lagrangian model contains an adjustable parameter θ. The dynamic time scale is computed based on a "surrogate-correlation" of the Germano-identity error (GIE). Also, a simple material derivative relation is used to approximate GIE at different events along a pathline instead of Lagrangian tracking or multi-linear interpolation. Previously, the time scale for homogeneous flows was computed by averaging along directions of homogeneity. The present work proposes modifications for inhomogeneous flows. This development allows the Lagrangian averaged dynamic model to be applied to inhomogeneous flows without any adjustable parameter. The proposed model is applied to LES of turbulent channel flow on unstructured zonal grids at various Reynolds numbers. Improvement is observed when compared to other averaging procedures for the dynamic Smagorinsky model, especially at coarse resolutions. The model is also applied to flow over a cylinder at two Reynolds numbers and good agreement with previous computations and experiments is obtained. Noticeable improvement is obtained using the proposed model over the standard Lagrangian model. The improvement is attributed to a physically consistent Lagrangian time scale. The model also shows good performance when applied to flow past a marine propeller in an off-design condition; it regularizes the eddy viscosity and adjusts locally to the dominant flow features.

Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Messer, Bronson; Sewell, Christopher; Heitmann, Katrin

2015-01-01

Large-scale simulations can produce tens of terabytes of data per analysis cycle, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in situ and co-scheduling approaches for handling Petabyte-size outputs. An initial inmore » situ step is used to reduce the amount of data to be analyzed, and to separate out the data-intensive tasks handled off-line. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.« less

High Performance Computing for Modeling Wind Farms and Their Impact

NASA Astrophysics Data System (ADS)

Mavriplis, D.; Naughton, J. W.; Stoellinger, M. K.

2016-12-01

As energy generated by wind penetrates further into our electrical system, modeling of power production, power distribution, and the economic impact of wind-generated electricity is growing in importance. The models used for this work can range in fidelity from simple codes that run on a single computer to those that require high performance computing capabilities. Over the past several years, high fidelity models have been developed and deployed on the NCAR-Wyoming Supercomputing Center's Yellowstone machine. One of the primary modeling efforts focuses on developing the capability to compute the behavior of a wind farm in complex terrain under realistic atmospheric conditions. Fully modeling this system requires the simulation of continental flows to modeling the flow over a wind turbine blade, including down to the blade boundary level, fully 10 orders of magnitude in scale. To accomplish this, the simulations are broken up by scale, with information from the larger scales being passed to the lower scale models. In the code being developed, four scale levels are included: the continental weather scale, the local atmospheric flow in complex terrain, the wind plant scale, and the turbine scale. The current state of the models in the latter three scales will be discussed. These simulations are based on a high-order accurate dynamic overset and adaptive mesh approach, which runs at large scale on the NWSC Yellowstone machine. A second effort on modeling the economic impact of new wind development as well as improvement in wind plant performance and enhancements to the transmission infrastructure will also be discussed.

Capturing remote mixing due to internal tides using multi-scale modeling tool: SOMAR-LES

NASA Astrophysics Data System (ADS)

Santilli, Edward; Chalamalla, Vamsi; Scotti, Alberto; Sarkar, Sutanu

2016-11-01

Internal tides that are generated during the interaction of an oscillating barotropic tide with the bottom bathymetry dissipate only a fraction of their energy near the generation region. The rest is radiated away in the form of low- high-mode internal tides. These internal tides dissipate energy at remote locations when they interact with the upper ocean pycnocline, continental slope, and large scale eddies. Capturing the wide range of length and time scales involved during the life-cycle of internal tides is computationally very expensive. A recently developed multi-scale modeling tool called SOMAR-LES combines the adaptive grid refinement features of SOMAR with the turbulence modeling features of a Large Eddy Simulation (LES) to capture multi-scale processes at a reduced computational cost. Numerical simulations of internal tide generation at idealized bottom bathymetries are performed to demonstrate this multi-scale modeling technique. Although each of the remote mixing phenomena have been considered independently in previous studies, this work aims to capture remote mixing processes during the life cycle of an internal tide in more realistic settings, by allowing multi-level (coarse and fine) grids to co-exist and exchange information during the time stepping process.

A scalable PC-based parallel computer for lattice QCD

NASA Astrophysics Data System (ADS)

Fodor, Z.; Katz, S. D.; Pappa, G.

2003-05-01

A PC-based parallel computer for medium/large scale lattice QCD simulations is suggested. The Eo¨tvo¨s Univ., Inst. Theor. Phys. cluster consists of 137 Intel P4-1.7GHz nodes. Gigabit Ethernet cards are used for nearest neighbor communication in a two-dimensional mesh. The sustained performance for dynamical staggered (wilson) quarks on large lattices is around 70(110) GFlops. The exceptional price/performance ratio is below $1/Mflop.

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the World- wide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

DOE PAGES

Childers, J. T.; Uram, T. D.; LeCompte, T. J.; ...

2016-09-29

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. Finally, this paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. Finally, this paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

GeNN: a code generation framework for accelerated brain simulations

NASA Astrophysics Data System (ADS)

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-01

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/.

GeNN: a code generation framework for accelerated brain simulations.

PubMed

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-07

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/.

GeNN: a code generation framework for accelerated brain simulations

PubMed Central

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-01

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/. PMID:26740369

Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues.

PubMed

Farisco, Michele; Kotaleski, Jeanette H; Evers, Kathinka

2018-01-01

Modeling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate the plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness (DOCs), e.g., Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State. Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs.

Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues

PubMed Central

Farisco, Michele; Kotaleski, Jeanette H.; Evers, Kathinka

2018-01-01

Modeling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain’s operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate the plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness (DOCs), e.g., Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State. Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs. PMID:29740372

High Fidelity Simulations of Large-Scale Wireless Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Onunkwo, Uzoma; Benz, Zachary

The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulationsmore » (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.« less

Efficient preconditioning of the electronic structure problem in large scale ab initio molecular dynamics simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiffmann, Florian; VandeVondele, Joost, E-mail: Joost.VandeVondele@mat.ethz.ch

2015-06-28

We present an improved preconditioning scheme for electronic structure calculations based on the orbital transformation method. First, a preconditioner is developed which includes information from the full Kohn-Sham matrix but avoids computationally demanding diagonalisation steps in its construction. This reduces the computational cost of its construction, eliminating a bottleneck in large scale simulations, while maintaining rapid convergence. In addition, a modified form of Hotelling’s iterative inversion is introduced to replace the exact inversion of the preconditioner matrix. This method is highly effective during molecular dynamics (MD), as the solution obtained in earlier MD steps is a suitable initial guess. Filteringmore » small elements during sparse matrix multiplication leads to linear scaling inversion, while retaining robustness, already for relatively small systems. For system sizes ranging from a few hundred to a few thousand atoms, which are typical for many practical applications, the improvements to the algorithm lead to a 2-5 fold speedup per MD step.« less

The ATLAS Simulation Infrastructure

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2010-09-25

The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, andmore » the validation of the simulated output against known physics processes.« less

Large-scale ground motion simulation using GPGPU

NASA Astrophysics Data System (ADS)

Aoi, S.; Maeda, T.; Nishizawa, N.; Aoki, T.

2012-12-01

Huge computation resources are required to perform large-scale ground motion simulations using 3-D finite difference method (FDM) for realistic and complex models with high accuracy. Furthermore, thousands of various simulations are necessary to evaluate the variability of the assessment caused by uncertainty of the assumptions of the source models for future earthquakes. To conquer the problem of restricted computational resources, we introduced the use of GPGPU (General purpose computing on graphics processing units) which is the technique of using a GPU as an accelerator of the computation which has been traditionally conducted by the CPU. We employed the CPU version of GMS (Ground motion Simulator; Aoi et al., 2004) as the original code and implemented the function for GPU calculation using CUDA (Compute Unified Device Architecture). GMS is a total system for seismic wave propagation simulation based on 3-D FDM scheme using discontinuous grids (Aoi&Fujiwara, 1999), which includes the solver as well as the preprocessor tools (parameter generation tool) and postprocessor tools (filter tool, visualization tool, and so on). The computational model is decomposed in two horizontal directions and each decomposed model is allocated to a different GPU. We evaluated the performance of our newly developed GPU version of GMS on the TSUBAME2.0 which is one of the Japanese fastest supercomputer operated by the Tokyo Institute of Technology. First we have performed a strong scaling test using the model with about 22 million grids and achieved 3.2 and 7.3 times of the speed-up by using 4 and 16 GPUs. Next, we have examined a weak scaling test where the model sizes (number of grids) are increased in proportion to the degree of parallelism (number of GPUs). The result showed almost perfect linearity up to the simulation with 22 billion grids using 1024 GPUs where the calculation speed reached to 79.7 TFlops and about 34 times faster than the CPU calculation using the same number of cores. Finally, we applied GPU calculation to the simulation of the 2011 Tohoku-oki earthquake. The model was constructed using a slip model from inversion of strong motion data (Suzuki et al., 2012), and a geological- and geophysical-based velocity structure model comprising all the Tohoku and Kanto regions as well as the large source area, which consists of about 1.9 billion grids. The overall characteristics of observed velocity seismograms for a longer period than range of 8 s were successfully reproduced (Maeda et al., 2012 AGU meeting). The turn around time for 50 thousand-step calculation (which correspond to 416 s in seismograph) using 100 GPUs was 52 minutes which is fairly short, especially considering this is the performance for the realistic and complex model.

A Priori Subgrid Scale Modeling for a Droplet Laden Temporal Mixing Layer

NASA Technical Reports Server (NTRS)

Okongo, Nora; Bellan, Josette

2000-01-01

Subgrid analysis of a transitional temporal mixing layer with evaporating droplets has been performed using a direct numerical simulation (DNS) database. The DNS is for a Reynolds number (based on initial vorticity thickness) of 600, with droplet mass loading of 0.2. The gas phase is computed using a Eulerian formulation, with Lagrangian droplet tracking. Since Large Eddy Simulation (LES) of this flow requires the computation of unfiltered gas-phase variables at droplet locations from filtered gas-phase variables at the grid points, it is proposed to model these by assuming the gas-phase variables to be given by the filtered variables plus a correction based on the filtered standard deviation, which can be computed from the sub-grid scale (SGS) standard deviation. This model predicts unfiltered variables at droplet locations better than simply interpolating the filtered variables. Three methods are investigated for modeling the SGS standard deviation: Smagorinsky, gradient and scale-similarity. When properly calibrated, the gradient and scale-similarity methods give results in excellent agreement with the DNS.

Towards mechanism-based simulation of impact damage using exascale computing

NASA Astrophysics Data System (ADS)

Shterenlikht, Anton; Margetts, Lee; McDonald, Samuel; Bourne, Neil K.

2017-01-01

Over the past 60 years, the finite element method has been very successful in modelling deformation in engineering structures. However the method requires the definition of constitutive models that represent the response of the material to applied loads. There are two issues. Firstly, the models are often difficult to define. Secondly, there is often no physical connection between the models and the mechanisms that accommodate deformation. In this paper, we present a potentially disruptive two-level strategy which couples the finite element method at the macroscale with cellular automata at the mesoscale. The cellular automata are used to simulate mechanisms, such as crack propagation. The stress-strain relationship emerges as a continuum mechanics scale interpretation of changes at the micro- and meso-scales. Iterative two-way updating between the cellular automata and finite elements drives the simulation forward as the material undergoes progressive damage at high strain rates. The strategy is particularly attractive on large-scale computing platforms as both methods scale well on tens of thousands of CPUs.

Numerical simulation using vorticity-vector potential formulation

NASA Technical Reports Server (NTRS)

Tokunaga, Hiroshi

1993-01-01

An accurate and efficient computational method is needed for three-dimensional incompressible viscous flows in engineering applications. On solving the turbulent shear flows directly or using the subgrid scale model, it is indispensable to resolve the small scale fluid motions as well as the large scale motions. From this point of view, the pseudo-spectral method is used so far as the computational method. However, the finite difference or the finite element methods are widely applied for computing the flow with practical importance since these methods are easily applied to the flows with complex geometric configurations. However, there exist several problems in applying the finite difference method to direct and large eddy simulations. Accuracy is one of most important problems. This point was already addressed by the present author on the direct simulations on the instability of the plane Poiseuille flow and also on the transition to turbulence. In order to obtain high efficiency, the multi-grid Poisson solver is combined with the higher-order, accurate finite difference method. The formulation method is also one of the most important problems in applying the finite difference method to the incompressible turbulent flows. The three-dimensional Navier-Stokes equations have been solved so far in the primitive variables formulation. One of the major difficulties of this method is the rigorous satisfaction of the equation of continuity. In general, the staggered grid is used for the satisfaction of the solenoidal condition for the velocity field at the wall boundary. However, the velocity field satisfies the equation of continuity automatically in the vorticity-vector potential formulation. From this point of view, the vorticity-vector potential method was extended to the generalized coordinate system. In the present article, we adopt the vorticity-vector potential formulation, the generalized coordinate system, and the 4th-order accurate difference method as the computational method. We present the computational method and apply the present method to computations of flows in a square cavity at large Reynolds number in order to investigate its effectiveness.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Recursive renormalization group theory based subgrid modeling

NASA Technical Reports Server (NTRS)

Zhou, YE

1991-01-01

Advancing the knowledge and understanding of turbulence theory is addressed. Specific problems to be addressed will include studies of subgrid models to understand the effects of unresolved small scale dynamics on the large scale motion which, if successful, might substantially reduce the number of degrees of freedom that need to be computed in turbulence simulation.

Tortuosity of lightning return stroke channels

NASA Technical Reports Server (NTRS)

Levine, D. M.; Gilson, B.

1984-01-01

Data obtained from photographs of lightning are presented on the tortuosity of return stroke channels. The data were obtained by making piecewise linear fits to the channels, and recording the cartesian coordinates of the ends of each linear segment. The mean change between ends of the segments was nearly zero in the horizontal direction and was about eight meters in the vertical direction. Histograms of these changes are presented. These data were used to create model lightning channels and to predict the electric fields radiated during return strokes. This was done using a computer generated random walk in which linear segments were placed end-to-end to form a piecewise linear representation of the channel. The computer selected random numbers for the ends of the segments assuming a normal distribution with the measured statistics. Once the channels were simulated, the electric fields radiated during a return stroke were predicted using a transmission line model on each segment. It was found that realistic channels are obtained with this procedure, but only if the model includes two scales of tortuosity: fine scale irregularities corresponding to the local channel tortuosity which are superimposed on large scale horizontal drifts. The two scales of tortuosity are also necessary to obtain agreement between the electric fields computed mathematically from the simulated channels and the electric fields radiated from real return strokes. Without large scale drifts, the computed electric fields do not have the undulations characteristics of the data.

On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

NASA Astrophysics Data System (ADS)

Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl

2016-09-01

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another ;equivalent; sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The proposed method can be efficiently used in many porous media applications for problems such as stochastic homogenization/upscaling, propagation of uncertainty from microscopic fluid and rock properties to macro-scale parameters, robust estimation of Representative Elementary Volume size for arbitrary physics.

FY10 Report on Multi-scale Simulation of Solvent Extraction Processes: Molecular-scale and Continuum-scale Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wardle, Kent E.; Frey, Kurt; Pereira, Candido

2014-02-02

This task is aimed at predictive modeling of solvent extraction processes in typical extraction equipment through multiple simulation methods at various scales of resolution. We have conducted detailed continuum fluid dynamics simulation on the process unit level as well as simulations of the molecular-level physical interactions which govern extraction chemistry. Through combination of information gained through simulations at each of these two tiers along with advanced techniques such as the Lattice Boltzmann Method (LBM) which can bridge these two scales, we can develop the tools to work towards predictive simulation for solvent extraction on the equipment scale (Figure 1). Themore » goal of such a tool-along with enabling optimized design and operation of extraction units-would be to allow prediction of stage extraction effrciency under specified conditions. Simulation efforts on each of the two scales will be described below. As the initial application of FELBM in the work performed during FYl0 has been on annular mixing it will be discussed in context of the continuum-scale. In the future, however, it is anticipated that the real value of FELBM will be in its use as a tool for sub-grid model development through highly refined DNS-like multiphase simulations facilitating exploration and development of droplet models including breakup and coalescence which will be needed for the large-scale simulations where droplet level physics cannot be resolved. In this area, it can have a significant advantage over traditional CFD methods as its high computational efficiency allows exploration of significantly greater physical detail especially as computational resources increase in the future.« less

Coupling of Large Eddy Simulations with Meteorological Models to simulate Methane Leaks from Natural Gas Storage Facilities

NASA Astrophysics Data System (ADS)

Prasad, K.

2017-12-01

Atmospheric transport is usually performed with weather models, e.g., the Weather Research and Forecasting (WRF) model that employs a parameterized turbulence model and does not resolve the fine scale dynamics generated by the flow around buildings and features comprising a large city. The NIST Fire Dynamics Simulator (FDS) is a computational fluid dynamics model that utilizes large eddy simulation methods to model flow around buildings at length scales much smaller than is practical with models like WRF. FDS has the potential to evaluate the impact of complex topography on near-field dispersion and mixing that is difficult to simulate with a mesoscale atmospheric model. A methodology has been developed to couple the FDS model with WRF mesoscale transport models. The coupling is based on nudging the FDS flow field towards that computed by WRF, and is currently limited to one way coupling performed in an off-line mode. This approach allows the FDS model to operate as a sub-grid scale model with in a WRF simulation. To test and validate the coupled FDS - WRF model, the methane leak from the Aliso Canyon underground storage facility was simulated. Large eddy simulations were performed over the complex topography of various natural gas storage facilities including Aliso Canyon, Honor Rancho and MacDonald Island at 10 m horizontal and vertical resolution. The goal of these simulations included improving and validating transport models as well as testing leak hypotheses. Forward simulation results were compared with aircraft and tower based in-situ measurements as well as methane plumes observed using the NASA Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) and the next generation instrument AVIRIS-NG. Comparison of simulation results with measurement data demonstrate the capability of the coupled FDS-WRF models to accurately simulate the transport and dispersion of methane plumes over urban domains. Simulated integrated methane enhancements will be presented and compared with results obtained from spectrometer data to estimate the temporally evolving methane flux during the Aliso Canyon blowout.

Two-step simulation of velocity and passive scalar mixing at high Schmidt number in turbulent jets

NASA Astrophysics Data System (ADS)

Rah, K. Jeff; Blanquart, Guillaume

2016-11-01

Simulation of passive scalar in the high Schmidt number turbulent mixing process requires higher computational cost than that of velocity fields, because the scalar is associated with smaller length scales than velocity. Thus, full simulation of both velocity and passive scalar with high Sc for a practical configuration is difficult to perform. In this work, a new approach to simulate velocity and passive scalar mixing at high Sc is suggested to reduce the computational cost. First, the velocity fields are resolved by Large Eddy Simulation (LES). Then, by extracting the velocity information from LES, the scalar inside a moving fluid blob is simulated by Direct Numerical Simulation (DNS). This two-step simulation method is applied to a turbulent jet and provides a new way to examine a scalar mixing process in a practical application with smaller computational cost. NSF, Samsung Scholarship.

Influence of savanna fire on Australian monsoon season precipitation and circulation as simulated using a distributed computing environment

NASA Astrophysics Data System (ADS)

Lynch, Amanda H.; Abramson, David; Görgen, Klaus; Beringer, Jason; Uotila, Petteri

2007-10-01

Fires in the Australian savanna have been hypothesized to affect monsoon evolution, but the hypothesis is controversial and the effects have not been quantified. A distributed computing approach allows the development of a challenging experimental design that permits simultaneous variation of all fire attributes. The climate model simulations are distributed around multiple independent computer clusters in six countries, an approach that has potential for a range of other large simulation applications in the earth sciences. The experiment clarifies that savanna burning can shape the monsoon through two mechanisms. Boundary-layer circulation and large-scale convergence is intensified monotonically through increasing fire intensity and area burned. However, thresholds of fire timing and area are evident in the consequent influence on monsoon rainfall. In the optimal band of late, high intensity fires with a somewhat limited extent, it is possible for the wet season to be significantly enhanced.

Discrete Event Modeling and Massively Parallel Execution of Epidemic Outbreak Phenomena

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Seal, Sudip K

2011-01-01

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post-facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks make it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction-diffusion simulation model of epidemic propagation is presented to facilitate in dramatically increasing the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallelmore » execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene / P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes exceeding several hundreds of millions of individuals in the largest cases are successfully exercised to verify model scalability.« less

Implementation and performance of FDPS: a framework for developing parallel particle simulation codes

NASA Astrophysics Data System (ADS)

Iwasawa, Masaki; Tanikawa, Ataru; Hosono, Natsuki; Nitadori, Keigo; Muranushi, Takayuki; Makino, Junichiro

2016-08-01

We present the basic idea, implementation, measured performance, and performance model of FDPS (Framework for Developing Particle Simulators). FDPS is an application-development framework which helps researchers to develop simulation programs using particle methods for large-scale distributed-memory parallel supercomputers. A particle-based simulation program for distributed-memory parallel computers needs to perform domain decomposition, exchange of particles which are not in the domain of each computing node, and gathering of the particle information in other nodes which are necessary for interaction calculation. Also, even if distributed-memory parallel computers are not used, in order to reduce the amount of computation, algorithms such as the Barnes-Hut tree algorithm or the Fast Multipole Method should be used in the case of long-range interactions. For short-range interactions, some methods to limit the calculation to neighbor particles are required. FDPS provides all of these functions which are necessary for efficient parallel execution of particle-based simulations as "templates," which are independent of the actual data structure of particles and the functional form of the particle-particle interaction. By using FDPS, researchers can write their programs with the amount of work necessary to write a simple, sequential and unoptimized program of O(N2) calculation cost, and yet the program, once compiled with FDPS, will run efficiently on large-scale parallel supercomputers. A simple gravitational N-body program can be written in around 120 lines. We report the actual performance of these programs and the performance model. The weak scaling performance is very good, and almost linear speed-up was obtained for up to the full system of the K computer. The minimum calculation time per timestep is in the range of 30 ms (N = 107) to 300 ms (N = 109). These are currently limited by the time for the calculation of the domain decomposition and communication necessary for the interaction calculation. We discuss how we can overcome these bottlenecks.

Krylov subspace methods for computing hydrodynamic interactions in Brownian dynamics simulations

PubMed Central

Ando, Tadashi; Chow, Edmond; Saad, Yousef; Skolnick, Jeffrey

2012-01-01

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a Brownian dynamics simulation. However, the calculation of correlated Brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studies methods based on Krylov subspaces for computing Brownian noise vectors. These methods are related to Chebyshev polynomial approximations, but do not require eigenvalue estimates. We show that only low accuracy is required in the Brownian noise vectors to accurately compute values of dynamic and static properties of polymer and monodisperse suspension models. With this level of accuracy, the computational time of Krylov subspace methods scales very nearly as O(N2) for the number of particles N up to 10 000, which was the limit tested. The performance of the Krylov subspace methods, especially the “block” version, is slightly better than that of the Chebyshev method, even without taking into account the additional cost of eigenvalue estimates required by the latter. Furthermore, at N = 10 000, the Krylov subspace method is 13 times faster than the exact Cholesky method. Thus, Krylov subspace methods are recommended for performing large-scale Brownian dynamics simulations with hydrodynamic interactions. PMID:22897254

Swept-Wing Ice Accretion Characterization and Aerodynamics

NASA Technical Reports Server (NTRS)

Broeren, Andy P.; Potapczuk, Mark G.; Riley, James T.; Villedieu, Philippe; Moens, Frederic; Bragg, Michael B.

2013-01-01

NASA, FAA, ONERA, the University of Illinois and Boeing have embarked on a significant, collaborative research effort to address the technical challenges associated with icing on large-scale, three-dimensional swept wings. The overall goal is to improve the fidelity of experimental and computational simulation methods for swept-wing ice accretion formation and resulting aerodynamic effect. A seven-phase research effort has been designed that incorporates ice-accretion and aerodynamic experiments and computational simulations. As the baseline, full-scale, swept-wing-reference geometry, this research will utilize the 65% scale Common Research Model configuration. Ice-accretion testing will be conducted in the NASA Icing Research Tunnel for three hybrid swept-wing models representing the 20%, 64% and 83% semispan stations of the baseline-reference wing. Three-dimensional measurement techniques are being developed and validated to document the experimental ice-accretion geometries. Artificial ice shapes of varying geometric fidelity will be developed for aerodynamic testing over a large Reynolds number range in the ONERA F1 pressurized wind tunnel and in a smaller-scale atmospheric wind tunnel. Concurrent research will be conducted to explore and further develop the use of computational simulation tools for ice accretion and aerodynamics on swept wings. The combined results of this research effort will result in an improved understanding of the ice formation and aerodynamic effects on swept wings. The purpose of this paper is to describe this research effort in more detail and report on the current results and status to date. 1

Swept-Wing Ice Accretion Characterization and Aerodynamics

NASA Technical Reports Server (NTRS)

Broeren, Andy P.; Potapczuk, Mark G.; Riley, James T.; Villedieu, Philippe; Moens, Frederic; Bragg, Michael B.

2013-01-01

NASA, FAA, ONERA, the University of Illinois and Boeing have embarked on a significant, collaborative research effort to address the technical challenges associated with icing on large-scale, three-dimensional swept wings. The overall goal is to improve the fidelity of experimental and computational simulation methods for swept-wing ice accretion formation and resulting aerodynamic effect. A seven-phase research effort has been designed that incorporates ice-accretion and aerodynamic experiments and computational simulations. As the baseline, full-scale, swept-wing-reference geometry, this research will utilize the 65 percent scale Common Research Model configuration. Ice-accretion testing will be conducted in the NASA Icing Research Tunnel for three hybrid swept-wing models representing the 20, 64 and 83 percent semispan stations of the baseline-reference wing. Threedimensional measurement techniques are being developed and validated to document the experimental ice-accretion geometries. Artificial ice shapes of varying geometric fidelity will be developed for aerodynamic testing over a large Reynolds number range in the ONERA F1 pressurized wind tunnel and in a smaller-scale atmospheric wind tunnel. Concurrent research will be conducted to explore and further develop the use of computational simulation tools for ice accretion and aerodynamics on swept wings. The combined results of this research effort will result in an improved understanding of the ice formation and aerodynamic effects on swept wings. The purpose of this paper is to describe this research effort in more detail and report on the current results and status to date.

Consequence modeling using the fire dynamics simulator.

PubMed

Ryder, Noah L; Sutula, Jason A; Schemel, Christopher F; Hamer, Andrew J; Van Brunt, Vincent

2004-11-11

The use of Computational Fluid Dynamics (CFD) and in particular Large Eddy Simulation (LES) codes to model fires provides an efficient tool for the prediction of large-scale effects that include plume characteristics, combustion product dispersion, and heat effects to adjacent objects. This paper illustrates the strengths of the Fire Dynamics Simulator (FDS), an LES code developed by the National Institute of Standards and Technology (NIST), through several small and large-scale validation runs and process safety applications. The paper presents two fire experiments--a small room fire and a large (15 m diameter) pool fire. The model results are compared to experimental data and demonstrate good agreement between the models and data. The validation work is then extended to demonstrate applicability to process safety concerns by detailing a model of a tank farm fire and a model of the ignition of a gaseous fuel in a confined space. In this simulation, a room was filled with propane, given time to disperse, and was then ignited. The model yields accurate results of the dispersion of the gas throughout the space. This information can be used to determine flammability and explosive limits in a space and can be used in subsequent models to determine the pressure and temperature waves that would result from an explosion. The model dispersion results were compared to an experiment performed by Factory Mutual. Using the above examples, this paper will demonstrate that FDS is ideally suited to build realistic models of process geometries in which large scale explosion and fire failure risks can be evaluated with several distinct advantages over more traditional CFD codes. Namely transient solutions to fire and explosion growth can be produced with less sophisticated hardware (lower cost) than needed for traditional CFD codes (PC type computer verses UNIX workstation) and can be solved for longer time histories (on the order of hundreds of seconds of computed time) with minimal computer resources and length of model run. Additionally results that are produced can be analyzed, viewed, and tabulated during and following a model run within a PC environment. There are some tradeoffs, however, as rapid computations in PC's may require a sacrifice in the grid resolution or in the sub-grid modeling, depending on the size of the geometry modeled.

Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guerrier, C.; Holcman, D., E-mail: david.holcman@ens.fr; Mathematical Institute, Oxford OX2 6GG, Newton Institute

The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationallymore » greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.« less

The Cell Collective: Toward an open and collaborative approach to systems biology

PubMed Central

2012-01-01

Background Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. Results The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. Conclusions The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction. PMID:22871178

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

2014-01-01

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

Predicting debris-flow initiation and run-out with a depth-averaged two-phase model and adaptive numerical methods

NASA Astrophysics Data System (ADS)

George, D. L.; Iverson, R. M.

2012-12-01

Numerically simulating debris-flow motion presents many challenges due to the complicated physics of flowing granular-fluid mixtures, the diversity of spatial scales (ranging from a characteristic particle size to the extent of the debris flow deposit), and the unpredictability of the flow domain prior to a simulation. Accurately predicting debris-flows requires models that are complex enough to represent the dominant effects of granular-fluid interaction, while remaining mathematically and computationally tractable. We have developed a two-phase depth-averaged mathematical model for debris-flow initiation and subsequent motion. Additionally, we have developed software that numerically solves the model equations efficiently on large domains. A unique feature of the mathematical model is that it includes the feedback between pore-fluid pressure and the evolution of the solid grain volume fraction, a process that regulates flow resistance. This feature endows the model with the ability to represent the transition from a stationary mass to a dynamic flow. With traditional approaches, slope stability analysis and flow simulation are treated separately, and the latter models are often initialized with force balances that are unrealistically far from equilibrium. Additionally, our new model relies on relatively few dimensionless parameters that are functions of well-known material properties constrained by physical data (eg. hydraulic permeability, pore-fluid viscosity, debris compressibility, Coulomb friction coefficient, etc.). We have developed numerical methods and software for accurately solving the model equations. By employing adaptive mesh refinement (AMR), the software can efficiently resolve an evolving debris flow as it advances through irregular topography, without needing terrain-fit computational meshes. The AMR algorithms utilize multiple levels of grid resolutions, so that computationally inexpensive coarse grids can be used where the flow is absent, and much higher resolution grids evolve with the flow. The reduction in computational cost, due to AMR, makes very large-scale problems tractable on personal computers. Model accuracy can be tested by comparison of numerical predictions and empirical data. These comparisons utilize controlled experiments conducted at the USGS debris-flow flume, which provide detailed data about flow mobilization and dynamics. Additionally, we have simulated historical large-scale debris flows, such as the (≈50 million m^3) debris flow that originated on Mt. Meager, British Columbia in 2010. This flow took a very complex route through highly variable topography and provides a valuable benchmark for testing. Maps of the debris flow deposit and data from seismic stations provide evidence regarding flow initiation, transit times and deposition. Our simulations reproduce many of the complex patterns of the event, such as run-out geometry and extent, and the large-scale nature of the flow and the complex topographical features demonstrate the utility of AMR in flow simulations.

Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Lee, Jonghyun; Yoon, Hongkyu; Kitanidis, Peter K.; Werth, Charles J.; Valocchi, Albert J.

2016-07-01

Characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydrogeophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with "big data" processing and numerous large-scale numerical simulations. To tackle such difficulties, the principal component geostatistical approach (PCGA) has been proposed as a "Jacobian-free" inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multiphysics simulation software with independent parallel executions. In this paper, we extend PCGA to handle a large number of measurements (e.g., 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data were compressed by the zeroth temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Only about 2000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method.

Turbulent structures in wall-bounded shear flows observed via three-dimensional numerical simulators. [using the Illiac 4 computer

NASA Technical Reports Server (NTRS)

Leonard, A.

1980-01-01

Three recent simulations of tubulent shear flow bounded by a wall using the Illiac computer are reported. These are: (1) vibrating-ribbon experiments; (2) study of the evolution of a spot-like disturbance in a laminar boundary layer; and (3) investigation of turbulent channel flow. A number of persistent flow structures were observed, including streamwise and vertical vorticity distributions near the wall, low-speed and high-speed streaks, and local regions of intense vertical velocity. The role of these structures in, for example, the growth or maintenance of turbulence is discussed. The problem of representing the large range of turbulent scales in a computer simulation is also discussed.

Large-Eddy Simulation of Aeroacoustic Applications

NASA Technical Reports Server (NTRS)

Pruett, C. David; Sochacki, James S.

1999-01-01

This report summarizes work accomplished under a one-year NASA grant from NASA Langley Research Center (LaRC). The effort culminates three years of NASA-supported research under three consecutive one-year grants. The period of support was April 6, 1998, through April 5, 1999. By request, the grant period was extended at no-cost until October 6, 1999. Its predecessors have been directed toward adapting the numerical tool of large-eddy simulation (LES) to aeroacoustic applications, with particular focus on noise suppression in subsonic round jets. In LES, the filtered Navier-Stokes equations are solved numerically on a relatively coarse computational grid. Residual stresses, generated by scales of motion too small to be resolved on the coarse grid, are modeled. Although most LES incorporate spatial filtering, time-domain filtering affords certain conceptual and computational advantages, particularly for aeroacoustic applications. Consequently, this work has focused on the development of subgrid-scale (SGS) models that incorporate time-domain filters.

The Space-Time Conservative Schemes for Large-Scale, Time-Accurate Flow Simulations with Tetrahedral Meshes

NASA Technical Reports Server (NTRS)

Venkatachari, Balaji Shankar; Streett, Craig L.; Chang, Chau-Lyan; Friedlander, David J.; Wang, Xiao-Yen; Chang, Sin-Chung

2016-01-01

Despite decades of development of unstructured mesh methods, high-fidelity time-accurate simulations are still predominantly carried out on structured, or unstructured hexahedral meshes by using high-order finite-difference, weighted essentially non-oscillatory (WENO), or hybrid schemes formed by their combinations. In this work, the space-time conservation element solution element (CESE) method is used to simulate several flow problems including supersonic jet/shock interaction and its impact on launch vehicle acoustics, and direct numerical simulations of turbulent flows using tetrahedral meshes. This paper provides a status report for the continuing development of the space-time conservation element solution element (CESE) numerical and software framework under the Revolutionary Computational Aerosciences (RCA) project. Solution accuracy and large-scale parallel performance of the numerical framework is assessed with the goal of providing a viable paradigm for future high-fidelity flow physics simulations.

Toward a first-principles integrated simulation of tokamak edge plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, C S; Klasky, Scott A; Cummings, Julian

2008-01-01

Performance of the ITER is anticipated to be highly sensitive to the edge plasma condition. The edge pedestal in ITER needs to be predicted from an integrated simulation of the necessary firstprinciples, multi-scale physics codes. The mission of the SciDAC Fusion Simulation Project (FSP) Prototype Center for Plasma Edge Simulation (CPES) is to deliver such a code integration framework by (1) building new kinetic codes XGC0 and XGC1, which can simulate the edge pedestal buildup; (2) using and improving the existing MHD codes ELITE, M3D-OMP, M3D-MPP and NIMROD, for study of large-scale edge instabilities called Edge Localized Modes (ELMs); andmore » (3) integrating the codes into a framework using cutting-edge computer science technology. Collaborative effort among physics, computer science, and applied mathematics within CPES has created the first working version of the End-to-end Framework for Fusion Integrated Simulation (EFFIS), which can be used to study the pedestal-ELM cycles.« less

Interactive, graphical processing unitbased evaluation of evacuation scenarios at the state scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Aaby, Brandon G; Yoginath, Srikanth B

2011-01-01

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulation time. For example, few real- time simulators scale to evacuation traffic scenarios at the level of an entire state, such as Louisiana (approximately 1 million links) or Florida (2.5 million links). New simulation approaches are needed to overcome severe computational demands of conventional (microscopic or mesoscopic) modeling techniques. Here, a new modeling and execution methodology is explored that holds the potential to provide a tradeoff among the level of behavioral detail, the scale of transportation network, and real-time execution capabilities. A novel, field-based modeling technique and its implementationmore » on graphical processing units are presented. Although additional research with input from domain experts is needed for refining and validating the models, the techniques reported here afford interactive experience at very large scales of multi-million road segments. Illustrative experiments on a few state-scale net- works are described based on an implementation of this approach in a software system called GARFIELD. Current modeling cap- abilities and implementation limitations are described, along with possible use cases and future research.« less

General relativistic corrections to the weak lensing convergence power spectrum

NASA Astrophysics Data System (ADS)

Giblin, John T.; Mertens, James B.; Starkman, Glenn D.; Zentner, Andrew R.

2017-11-01

We compute the weak lensing convergence power spectrum, Cℓκκ, in a dust-filled universe using fully nonlinear general relativistic simulations. The spectrum is then compared to more standard, approximate calculations by computing the Bardeen (Newtonian) potentials in linearized gravity and partially utilizing the Born approximation. We find corrections to the angular power spectrum amplitude of order ten percent at very large angular scales, ℓ˜2 - 3 , and percent-level corrections at intermediate angular scales of ℓ˜20 - 30 .

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

PubMed Central

Gallicchio, Emilio; Deng, Nanjie; He, Peng; Wickstrom, Lauren; Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Olson, Arthur J.; Levy, Ronald M.

2014-01-01

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization. PMID:24504704

Challenges of forest landscape modeling - simulating large landscapes and validating results

Treesearch

Hong S. He; Jian Yang; Stephen R. Shifley; Frank R. Thompson

2011-01-01

Over the last 20 years, we have seen a rapid development in the field of forest landscape modeling, fueled by both technological and theoretical advances. Two fundamental challenges have persisted since the inception of FLMs: (1) balancing realistic simulation of ecological processes at broad spatial and temporal scales with computing capacity, and (2) validating...

Development and application of a particle-particle particle-mesh Ewald method for dispersion interactions.

PubMed

Isele-Holder, Rolf E; Mitchell, Wayne; Ismail, Ahmed E

2012-11-07

For inhomogeneous systems with interfaces, the inclusion of long-range dispersion interactions is necessary to achieve consistency between molecular simulation calculations and experimental results. For accurate and efficient incorporation of these contributions, we have implemented a particle-particle particle-mesh Ewald solver for dispersion (r(-6)) interactions into the LAMMPS molecular dynamics package. We demonstrate that the solver's O(N log N) scaling behavior allows its application to large-scale simulations. We carefully determine a set of parameters for the solver that provides accurate results and efficient computation. We perform a series of simulations with Lennard-Jones particles, SPC/E water, and hexane to show that with our choice of parameters the dependence of physical results on the chosen cutoff radius is removed. Physical results and computation time of these simulations are compared to results obtained using either a plain cutoff or a traditional Ewald sum for dispersion.

Computational Challenges in the Analysis of Petrophysics Using Microtomography and Upscaling

NASA Astrophysics Data System (ADS)

Liu, J.; Pereira, G.; Freij-Ayoub, R.; Regenauer-Lieb, K.

2014-12-01

Microtomography provides detailed 3D internal structures of rocks in micro- to tens of nano-meter resolution and is quickly turning into a new technology for studying petrophysical properties of materials. An important step is the upscaling of these properties as micron or sub-micron resolution can only be done on the sample-scale of millimeters or even less than a millimeter. We present here a recently developed computational workflow for the analysis of microstructures including the upscaling of material properties. Computations of properties are first performed using conventional material science simulations at micro to nano-scale. The subsequent upscaling of these properties is done by a novel renormalization procedure based on percolation theory. We have tested the workflow using different rock samples, biological and food science materials. We have also applied the technique on high-resolution time-lapse synchrotron CT scans. In this contribution we focus on the computational challenges that arise from the big data problem of analyzing petrophysical properties and its subsequent upscaling. We discuss the following challenges: 1) Characterization of microtomography for extremely large data sets - our current capability. 2) Computational fluid dynamics simulations at pore-scale for permeability estimation - methods, computing cost and accuracy. 3) Solid mechanical computations at pore-scale for estimating elasto-plastic properties - computational stability, cost, and efficiency. 4) Extracting critical exponents from derivative models for scaling laws - models, finite element meshing, and accuracy. Significant progress in each of these challenges is necessary to transform microtomography from the current research problem into a robust computational big data tool for multi-scale scientific and engineering problems.

Plasmonic resonances of nanoparticles from large-scale quantum mechanical simulations

NASA Astrophysics Data System (ADS)

Zhang, Xu; Xiang, Hongping; Zhang, Mingliang; Lu, Gang

2017-09-01

Plasmonic resonance of metallic nanoparticles results from coherent motion of its conduction electrons, driven by incident light. For the nanoparticles less than 10 nm in diameter, localized surface plasmonic resonances become sensitive to the quantum nature of the conduction electrons. Unfortunately, quantum mechanical simulations based on time-dependent Kohn-Sham density functional theory are computationally too expensive to tackle metal particles larger than 2 nm. Herein, we introduce the recently developed time-dependent orbital-free density functional theory (TD-OFDFT) approach which enables large-scale quantum mechanical simulations of plasmonic responses of metallic nanostructures. Using TD-OFDFT, we have performed quantum mechanical simulations to understand size-dependent plasmonic response of Na nanoparticles and plasmonic responses in Na nanoparticle dimers and trimers. An outlook of future development of the TD-OFDFT method is also presented.

Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

NASA Astrophysics Data System (ADS)

Warrier, M.; Bhardwaj, U.; Bukkuru, S.

2016-10-01

Modification of materials in nuclear reactors due to neutron irradiation is a multiscale problem. These neutrons pass through materials creating several energetic primary knock-on atoms (PKA) which cause localized collision cascades creating damage tracks, defects (interstitials and vacancies) and defect clusters depending on the energy of the PKA. These defects diffuse and recombine throughout the whole duration of operation of the reactor, thereby changing the micro-structure of the material and its properties. It is therefore desirable to develop predictive computational tools to simulate the micro-structural changes of irradiated materials. In this paper we describe how statistical averages of the collision cascades from thousands of MD simulations are used to provide inputs to Kinetic Monte Carlo (KMC) simulations which can handle larger sizes, more defects and longer time durations. Use of unsupervised learning and graph optimization in handling and analyzing large scale MD data will be highlighted.

Compiling Planning into Quantum Optimization Problems: A Comparative Study

DTIC Science & Technology

2015-06-07

and Sipser, M. 2000. Quantum computation by adiabatic evolution. arXiv:quant- ph/0001106. Fikes, R. E., and Nilsson, N. J. 1972. STRIPS: A new...become available: quantum annealing. Quantum annealing is one of the most accessible quantum algorithms for a computer sci- ence audience not versed...in quantum computing because of its close ties to classical optimization algorithms such as simulated annealing. While large-scale universal quantum

Evaluation of subgrid-scale models in large-eddy simulations of turbulent flow in a centrifugal pump impeller

NASA Astrophysics Data System (ADS)

Yang, Zhengjun; Wang, Fujun; Zhou, Peijian

2012-09-01

The current research of large eddy simulation (LES) of turbulent flow in pumps mainly concentrates in applying conventional subgrid-scale (SGS) model to simulate turbulent flow, which aims at obtaining the flow field in pump. The selection of SGS model is usually not considered seriously, so the accuracy and efficiency of the simulation cannot be ensured. Three SGS models including Smagorinsky-Lilly model, dynamic Smagorinsky model and dynamic mixed model are comparably studied by using the commercial CFD code Fluent combined with its user define function. The simulations are performed for the turbulent flow in a centrifugal pump impeller. The simulation results indicate that the mean flows predicted by the three SGS models agree well with the experimental data obtained from the test that detailed measurements of the flow inside the rotating passages of a six-bladed shrouded centrifugal pump impeller performed using particle image velocimetry (PIV) and laser Doppler velocimetry (LDV). The comparable results show that dynamic mixed model gives the most accurate results for mean flow in the centrifugal pump impeller. The SGS stress of dynamic mixed model is decompose into the scale similar part and the eddy viscous part. The scale similar part of SGS stress plays a significant role in high curvature regions, such as the leading edge and training edge of pump blade. It is also found that the dynamic mixed model is more adaptive to compute turbulence in the pump impeller. The research results presented is useful to improve the computational accuracy and efficiency of LES for centrifugal pumps, and provide important reference for carrying out simulation in similar fluid machineries.

Interface COMSOL-PHREEQC (iCP), an efficient numerical framework for the solution of coupled multiphysics and geochemistry

NASA Astrophysics Data System (ADS)

Nardi, Albert; Idiart, Andrés; Trinchero, Paolo; de Vries, Luis Manuel; Molinero, Jorge

2014-08-01

This paper presents the development, verification and application of an efficient interface, denoted as iCP, which couples two standalone simulation programs: the general purpose Finite Element framework COMSOL Multiphysics® and the geochemical simulator PHREEQC. The main goal of the interface is to maximize the synergies between the aforementioned codes, providing a numerical platform that can efficiently simulate a wide number of multiphysics problems coupled with geochemistry. iCP is written in Java and uses the IPhreeqc C++ dynamic library and the COMSOL Java-API. Given the large computational requirements of the aforementioned coupled models, special emphasis has been placed on numerical robustness and efficiency. To this end, the geochemical reactions are solved in parallel by balancing the computational load over multiple threads. First, a benchmark exercise is used to test the reliability of iCP regarding flow and reactive transport. Then, a large scale thermo-hydro-chemical (THC) problem is solved to show the code capabilities. The results of the verification exercise are successfully compared with those obtained using PHREEQC and the application case demonstrates the scalability of a large scale model, at least up to 32 threads.

Numerical study of axial turbulent flow over long cylinders

NASA Technical Reports Server (NTRS)

Neves, J. C.; Moin, P.; Moser, R. D.

1991-01-01

The effects of transverse curvature are investigated by means of direct numerical simulations of turbulent axial flow over cylinders. Two cases of Reynolds number of about 3400 and layer-thickness-to-cylinder-radius ratios of 5 and 11 were simulated. All essential turbulence scales were resolved in both calculations, and a large number of turbulence statistics were computed. The results are compared with the plane channel results of Kim et al. (1987) and with experiments. With transverse curvature the skin friction coefficient increases and the turbulence statistics, when scaled with wall units, are lower than in the plane channel. The momentum equation provides a scaling that collapses the cylinder statistics, and allows the results to be interpreted in light of the plane channel flow. The azimuthal and radial length scales of the structures in the flow are of the order of the cylinder diameter. Boomerang-shaped structures with large spanwise length scales were observed in the flow.

LAMMPS strong scaling performance optimization on Blue Gene/Q

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coffman, Paul; Jiang, Wei; Romero, Nichols A.

2014-11-12

LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using anmore » 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.« less

The Next Frontier in Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarrao, John

2016-11-16

Exascale computing refers to computing systems capable of at least one exaflop or a billion calculations per second (1018). That is 50 times faster than the most powerful supercomputers being used today and represents a thousand-fold increase over the first petascale computer that came into operation in 2008. How we use these large-scale simulation resources is the key to solving some of today’s most pressing problems, including clean energy production, nuclear reactor lifetime extension and nuclear stockpile aging.

Scientific Discovery through Advanced Computing in Plasma Science

NASA Astrophysics Data System (ADS)

Tang, William

2005-03-01

Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of plasma turbulence in magnetically-confined high temperature plasmas. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to the computational science area.

Combined Monte Carlo and path-integral method for simulated library of time-resolved reflectance curves from layered tissue models

NASA Astrophysics Data System (ADS)

Wilson, Robert H.; Vishwanath, Karthik; Mycek, Mary-Ann

2009-02-01

Monte Carlo (MC) simulations are considered the "gold standard" for mathematical description of photon transport in tissue, but they can require large computation times. Therefore, it is important to develop simple and efficient methods for accelerating MC simulations, especially when a large "library" of related simulations is needed. A semi-analytical method involving MC simulations and a path-integral (PI) based scaling technique generated time-resolved reflectance curves from layered tissue models. First, a zero-absorption MC simulation was run for a tissue model with fixed scattering properties in each layer. Then, a closed-form expression for the average classical path of a photon in tissue was used to determine the percentage of time that the photon spent in each layer, to create a weighted Beer-Lambert factor to scale the time-resolved reflectance of the simulated zero-absorption tissue model. This method is a unique alternative to other scaling techniques in that it does not require the path length or number of collisions of each photon to be stored during the initial simulation. Effects of various layer thicknesses and absorption and scattering coefficients on the accuracy of the method will be discussed.

Development of an Output-based Adaptive Method for Multi-Dimensional Euler and Navier-Stokes Simulations

NASA Technical Reports Server (NTRS)

Darmofal, David L.

2003-01-01

The use of computational simulations in the prediction of complex aerodynamic flows is becoming increasingly prevalent in the design process within the aerospace industry. Continuing advancements in both computing technology and algorithmic development are ultimately leading to attempts at simulating ever-larger, more complex problems. However, by increasing the reliance on computational simulations in the design cycle, we must also increase the accuracy of these simulations in order to maintain or improve the reliability arid safety of the resulting aircraft. At the same time, large-scale computational simulations must be made more affordable so that their potential benefits can be fully realized within the design cycle. Thus, a continuing need exists for increasing the accuracy and efficiency of computational algorithms such that computational fluid dynamics can become a viable tool in the design of more reliable, safer aircraft. The objective of this research was the development of an error estimation and grid adaptive strategy for reducing simulation errors in integral outputs (functionals) such as lift or drag from from multi-dimensional Euler and Navier-Stokes simulations. In this final report, we summarize our work during this grant.

Parallel Adjective High-Order CFD Simulations Characterizing SOFIA Cavity Acoustics

NASA Technical Reports Server (NTRS)

Barad, Michael F.; Brehm, Christoph; Kiris, Cetin C.; Biswas, Rupak

2016-01-01

This paper presents large-scale MPI-parallel computational uid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft fuselage of a Boeing 747SP. These simulations focus on how the unsteady ow eld inside and over the cavity interferes with the optical path and mounting structure of the telescope. A temporally fourth-order accurate Runge-Kutta, and spatially fth-order accurate WENO- 5Z scheme was used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh re nement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32k CPU cores and 4 billion compu- tational cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregular numerical cost associated with blocks con- taining boundaries. Limits to scaling beyond 32k cores are identi ed, and targeted code optimizations are discussed.

Parallel Adaptive High-Order CFD Simulations Characterizing SOFIA Cavitiy Acoustics

NASA Technical Reports Server (NTRS)

Barad, Michael F.; Brehm, Christoph; Kiris, Cetin C.; Biswas, Rupak

2015-01-01

This paper presents large-scale MPI-parallel computational uid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft fuselage of a Boeing 747SP. These simulations focus on how the unsteady ow eld inside and over the cavity interferes with the optical path and mounting structure of the telescope. A tempo- rally fourth-order accurate Runge-Kutta, and a spatially fth-order accurate WENO-5Z scheme were used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh re nement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32k CPU cores and 4 billion compu- tational cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregular numerical cost associated with blocks con- taining boundaries. Limits to scaling beyond 32k cores are identi ed, and targeted code optimizations are discussed.

Mesoscale Effective Property Simulations Incorporating Conductive Binder

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trembacki, Bradley L.; Noble, David R.; Brunini, Victor E.

Lithium-ion battery electrodes are composed of active material particles, binder, and conductive additives that form an electrolyte-filled porous particle composite. The mesoscale (particle-scale) interplay of electrochemistry, mechanical deformation, and transport through this tortuous multi-component network dictates the performance of a battery at the cell-level. Effective electrode properties connect mesoscale phenomena with computationally feasible battery-scale simulations. We utilize published tomography data to reconstruct a large subsection (1000+ particles) of an NMC333 cathode into a computational mesh and extract electrode-scale effective properties from finite element continuum-scale simulations. We present a novel method to preferentially place a composite binder phase throughout the mesostructure,more » a necessary approach due difficulty distinguishing between non-active phases in tomographic data. We compare stress generation and effective thermal, electrical, and ionic conductivities across several binder placement approaches. Isotropic lithiation-dependent mechanical swelling of the NMC particles and the consideration of strain-dependent composite binder conductivity significantly impact the resulting effective property trends and stresses generated. Lastly, our results suggest that composite binder location significantly affects mesoscale behavior, indicating that a binder coating on active particles is not sufficient and that more accurate approaches should be used when calculating effective properties that will inform battery-scale models in this inherently multi-scale battery simulation challenge.« less

Mesoscale Effective Property Simulations Incorporating Conductive Binder

DOE PAGES

Trembacki, Bradley L.; Noble, David R.; Brunini, Victor E.; ...

2017-07-26

Lithium-ion battery electrodes are composed of active material particles, binder, and conductive additives that form an electrolyte-filled porous particle composite. The mesoscale (particle-scale) interplay of electrochemistry, mechanical deformation, and transport through this tortuous multi-component network dictates the performance of a battery at the cell-level. Effective electrode properties connect mesoscale phenomena with computationally feasible battery-scale simulations. We utilize published tomography data to reconstruct a large subsection (1000+ particles) of an NMC333 cathode into a computational mesh and extract electrode-scale effective properties from finite element continuum-scale simulations. We present a novel method to preferentially place a composite binder phase throughout the mesostructure,more » a necessary approach due difficulty distinguishing between non-active phases in tomographic data. We compare stress generation and effective thermal, electrical, and ionic conductivities across several binder placement approaches. Isotropic lithiation-dependent mechanical swelling of the NMC particles and the consideration of strain-dependent composite binder conductivity significantly impact the resulting effective property trends and stresses generated. Lastly, our results suggest that composite binder location significantly affects mesoscale behavior, indicating that a binder coating on active particles is not sufficient and that more accurate approaches should be used when calculating effective properties that will inform battery-scale models in this inherently multi-scale battery simulation challenge.« less

GENASIS Mathematics : Object-oriented manifolds, operations, and solvers for large-scale physics simulations

NASA Astrophysics Data System (ADS)

Cardall, Christian Y.; Budiardja, Reuben D.

2018-01-01

The large-scale computer simulation of a system of physical fields governed by partial differential equations requires some means of approximating the mathematical limit of continuity. For example, conservation laws are often treated with a 'finite-volume' approach in which space is partitioned into a large number of small 'cells,' with fluxes through cell faces providing an intuitive discretization modeled on the mathematical definition of the divergence operator. Here we describe and make available Fortran 2003 classes furnishing extensible object-oriented implementations of simple meshes and the evolution of generic conserved currents thereon, along with individual 'unit test' programs and larger example problems demonstrating their use. These classes inaugurate the Mathematics division of our developing astrophysics simulation code GENASIS (Gen eral A strophysical Si mulation S ystem), which will be expanded over time to include additional meshing options, mathematical operations, solver types, and solver variations appropriate for many multiphysics applications.

New Distributed Multipole Methods for Accurate Electrostatics for Large-Scale Biomolecular Simultations

NASA Astrophysics Data System (ADS)

Sagui, Celeste

2006-03-01

An accurate and numerically efficient treatment of electrostatics is essential for biomolecular simulations, as this stabilizes much of the delicate 3-d structure associated with biomolecules. Currently, force fields such as AMBER and CHARMM assign ``partial charges'' to every atom in a simulation in order to model the interatomic electrostatic forces, so that the calculation of the electrostatics rapidly becomes the computational bottleneck in large-scale simulations. There are two main issues associated with the current treatment of classical electrostatics: (i) how does one eliminate the artifacts associated with the point-charges (e.g., the underdetermined nature of the current RESP fitting procedure for large, flexible molecules) used in the force fields in a physically meaningful way? (ii) how does one efficiently simulate the very costly long-range electrostatic interactions? Recently, we have dealt with both of these challenges as follows. In order to improve the description of the molecular electrostatic potentials (MEPs), a new distributed multipole analysis based on localized functions -- Wannier, Boys, and Edminston-Ruedenberg -- was introduced, which allows for a first principles calculation of the partial charges and multipoles. Through a suitable generalization of the particle mesh Ewald (PME) and multigrid method, one can treat electrostatic multipoles all the way to hexadecapoles all without prohibitive extra costs. The importance of these methods for large-scale simulations will be discussed, and examplified by simulations from polarizable DNA models.

Need for speed: An optimized gridding approach for spatially explicit disease simulations.

PubMed

Sellman, Stefan; Tsao, Kimberly; Tildesley, Michael J; Brommesson, Peter; Webb, Colleen T; Wennergren, Uno; Keeling, Matt J; Lindström, Tom

2018-04-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power.

Need for speed: An optimized gridding approach for spatially explicit disease simulations

PubMed Central

Tildesley, Michael J.; Brommesson, Peter; Webb, Colleen T.; Wennergren, Uno; Lindström, Tom

2018-01-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power. PMID:29624574

Cortical circuitry implementing graphical models.

PubMed

Litvak, Shai; Ullman, Shimon

2009-11-01

In this letter, we develop and simulate a large-scale network of spiking neurons that approximates the inference computations performed by graphical models. Unlike previous related schemes, which used sum and product operations in either the log or linear domains, the current model uses an inference scheme based on the sum and maximization operations in the log domain. Simulations show that using these operations, a large-scale circuit, which combines populations of spiking neurons as basic building blocks, is capable of finding close approximations to the full mathematical computations performed by graphical models within a few hundred milliseconds. The circuit is general in the sense that it can be wired for any graph structure, it supports multistate variables, and it uses standard leaky integrate-and-fire neuronal units. Following previous work, which proposed relations between graphical models and the large-scale cortical anatomy, we focus on the cortical microcircuitry and propose how anatomical and physiological aspects of the local circuitry may map onto elements of the graphical model implementation. We discuss in particular the roles of three major types of inhibitory neurons (small fast-spiking basket cells, large layer 2/3 basket cells, and double-bouquet neurons), subpopulations of strongly interconnected neurons with their unique connectivity patterns in different cortical layers, and the possible role of minicolumns in the realization of the population-based maximum operation.

DEM Based Modeling: Grid or TIN? The Answer Depends

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Moreno, H. A.

2015-12-01

The availability of petascale supercomputing power has enabled process-based hydrological simulations on large watersheds and two-way coupling with mesoscale atmospheric models. Of course with increasing watershed scale come corresponding increases in watershed complexity, including wide ranging water management infrastructure and objectives, and ever increasing demands for forcing data. Simulations of large watersheds using grid-based models apply a fixed resolution over the entire watershed. In large watersheds, this means an enormous number of grids, or coarsening of the grid resolution to reduce memory requirements. One alternative to grid-based methods is the triangular irregular network (TIN) approach. TINs provide the flexibility of variable resolution, which allows optimization of computational resources by providing high resolution where necessary and low resolution elsewhere. TINs also increase required effort in model setup, parameter estimation, and coupling with forcing data which are often gridded. This presentation discusses the costs and benefits of the use of TINs compared to grid-based methods, in the context of large watershed simulations within the traditional gridded WRF-HYDRO framework and the new TIN-based ADHydro high performance computing watershed simulator.

Optimized Materials From First Principles Simulations: Are We There Yet?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Galli, G; Gygi, F

2005-07-26

In the past thirty years, the use of scientific computing has become pervasive in all disciplines: collection and interpretation of most experimental data is carried out using computers, and physical models in computable form, with various degrees of complexity and sophistication, are utilized in all fields of science. However, full prediction of physical and chemical phenomena based on the basic laws of Nature, using computer simulations, is a revolution still in the making, and it involves some formidable theoretical and computational challenges. We illustrate the progress and successes obtained in recent years in predicting fundamental properties of materials in condensedmore » phases and at the nanoscale, using ab-initio, quantum simulations. We also discuss open issues related to the validation of the approximate, first principles theories used in large scale simulations, and the resulting complex interplay between computation and experiment. Finally, we describe some applications, with focus on nanostructures and liquids, both at ambient and under extreme conditions.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaurov, Alexander A., E-mail: kaurov@uchicago.edu

The methods for studying the epoch of cosmic reionization vary from full radiative transfer simulations to purely analytical models. While numerical approaches are computationally expensive and are not suitable for generating many mock catalogs, analytical methods are based on assumptions and approximations. We explore the interconnection between both methods. First, we ask how the analytical framework of excursion set formalism can be used for statistical analysis of numerical simulations and visual representation of the morphology of ionization fronts. Second, we explore the methods of training the analytical model on a given numerical simulation. We present a new code which emergedmore » from this study. Its main application is to match the analytical model with a numerical simulation. Then, it allows one to generate mock reionization catalogs with volumes exceeding the original simulation quickly and computationally inexpensively, meanwhile reproducing large-scale statistical properties. These mock catalogs are particularly useful for cosmic microwave background polarization and 21 cm experiments, where large volumes are required to simulate the observed signal.« less

Numerical investigation of turbulent channel flow

NASA Technical Reports Server (NTRS)

Moin, P.; Kim, J.

1981-01-01

Fully developed turbulent channel flow was simulated numerically at Reynolds number 13800, based on centerline velocity and channel halt width. The large-scale flow field was obtained by directly integrating the filtered, three dimensional, time dependent, Navier-Stokes equations. The small-scale field motions were simulated through an eddy viscosity model. The calculations were carried out on the ILLIAC IV computer with up to 516,096 grid points. The computed flow field was used to study the statistical properties of the flow as well as its time dependent features. The agreement of the computed mean velocity profile, turbulence statistics, and detailed flow structures with experimental data is good. The resolvable portion of the statistical correlations appearing in the Reynolds stress equations are calculated. Particular attention is given to the examination of the flow structure in the vicinity of the wall.

Large-eddy simulation of flow in a plane, asymmetric diffuser

NASA Technical Reports Server (NTRS)

Kaltenbach, Hans-Jakob

1993-01-01

Recent improvements in subgrid-scale modeling as well as increases in computer power make it feasible to investigate flows using large-eddy simulation (LES) which have been traditionally studied with techniques based on Reynolds averaging. However, LES has not yet been applied to many flows of immediate technical interest. Preliminary results from LES of a plane diffuser flow are described. The long term goal of this work is to investigate flow separation as well as separation control in ducts and ramp-like geometries.

A method for data handling numerical results in parallel OpenFOAM simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anton, Alin; Muntean, Sebastian

Parallel computational fluid dynamics simulations produce vast amount of numerical result data. This paper introduces a method for reducing the size of the data by replaying the interprocessor traffic. The results are recovered only in certain regions of interest configured by the user. A known test case is used for several mesh partitioning scenarios using the OpenFOAM toolkit{sup ®}[1]. The space savings obtained with classic algorithms remain constant for more than 60 Gb of floating point data. Our method is most efficient on large simulation meshes and is much better suited for compressing large scale simulation results than the regular algorithms.

Numerical simulation of a mini PEMFC stack

NASA Astrophysics Data System (ADS)

Liu, Zhixiang; Mao, Zongqiang; Wang, Cheng; Zhuge, Weilin; Zhang, Yangjun

Fuel cell modeling and simulation has aroused much attention recently because it can probe transport and reaction mechanism. In this paper, a computational fuel cell dynamics (CFCD) method was applied to simulate a proton exchange membrane fuel cell (PEMFC) stack for the first time. The air cooling mini fuel cell stack consisted of six cells, in which the active area was 8 cm 2 (2 cm × 4 cm). With reasonable simplification, the computational elements were effectively reduced and allowed a simulation which could be conducted on a personal computer without large-scale parallel computation. The results indicated that the temperature gradient inside the fuel cell stack was determined by the flow rate of the cooling air. If the air flow rate is too low, the stack could not be effectively cooled and the temperature will rise to a range that might cause unstable stack operation.

Assessment of Computer and Information Literacy in ICILS 2013: Do Different Item Types Measure the Same Construct?

ERIC Educational Resources Information Center

Ihme, Jan Marten; Senkbeil, Martin; Goldhammer, Frank; Gerick, Julia

2017-01-01

The combination of different item formats is found quite often in large scale assessments, and analyses on the dimensionality often indicate multi-dimensionality of tests regarding the task format. In ICILS 2013, three different item types (information-based response tasks, simulation tasks, and authoring tasks) were used to measure computer and…

Multiscale atomistic simulation of metal-oxygen surface interactions: Methodological development, theoretical investigation, and correlation with experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Judith C.

The purpose of this grant is to develop the multi-scale theoretical methods to describe the nanoscale oxidation of metal thin films, as the PI (Yang) extensive previous experience in the experimental elucidation of the initial stages of Cu oxidation by primarily in situ transmission electron microscopy methods. Through the use and development of computational tools at varying length (and time) scales, from atomistic quantum mechanical calculation, force field mesoscale simulations, to large scale Kinetic Monte Carlo (KMC) modeling, the fundamental underpinings of the initial stages of Cu oxidation have been elucidated. The development of computational modeling tools allows for acceleratedmore » materials discovery. The theoretical tools developed from this program impact a wide range of technologies that depend on surface reactions, including corrosion, catalysis, and nanomaterials fabrication.« less

Computational Cosmology at the Bleeding Edge

NASA Astrophysics Data System (ADS)

Habib, Salman

2013-04-01

Large-area sky surveys are providing a wealth of cosmological information to address the mysteries of dark energy and dark matter. Observational probes based on tracking the formation of cosmic structure are essential to this effort, and rely crucially on N-body simulations that solve the Vlasov-Poisson equation in an expanding Universe. As statistical errors from survey observations continue to shrink, and cosmological probes increase in number and complexity, simulations are entering a new regime in their use as tools for scientific inference. Changes in supercomputer architectures provide another rationale for developing new parallel simulation and analysis capabilities that can scale to computational concurrency levels measured in the millions to billions. In this talk I will outline the motivations behind the development of the HACC (Hardware/Hybrid Accelerated Cosmology Code) extreme-scale cosmological simulation framework and describe its essential features. By exploiting a novel algorithmic structure that allows flexible tuning across diverse computer architectures, including accelerated and many-core systems, HACC has attained a performance of 14 PFlops on the IBM BG/Q Sequoia system at 69% of peak, using more than 1.5 million cores.

Modeling Atmospheric Transport for Greenhouse Gas Observations within the Urban Dome

NASA Astrophysics Data System (ADS)

Nehrkorn, T.; Sargent, M. R.; Wofsy, S. C.

2016-12-01

Observations of CO2, CH4, and other greenhouse gases (GHGs) within the urban dome of major cities generally show large enhancements over background values, and large sensitivity to surface fluxes (as measured by the footprints computed by Lagrangian Particle Dispersion Models, LPDMs) within the urban dome. However, their use in top-down inversion studies to constrain urban emission estimates is complicated by difficulties in proper modeling of the atmospheric transport. We are conducting experiments with the Weather Research and Forecast model (WRF) coupled to the STILT LPDM to improve model simulation of atmospheric transport on spatial scales of a few km in urban domains, because errors in transport on short time/space scales are amplified by the patchiness of GHG emissions and may engender systematic errors of simulated concentrations.We are evaluating the quality of the meteorological simulations from model configurations with different resolutions and PBL packages, using both standard and non-standard (Lidar PBL height and ACARS aircraft profile) observations. To take into account the effect of building scale eddies for observations located on top of buildings, we are modifying the basic STILT algorithm for the computation of footprints by replacing the nominal receptor height by an effective sampling height. In addition, the footprint computations for near-field emissions make use of the vertical particle spread within the LPDM to arrive at a more appropriate estimate of mixing heights in the immediate vicinity of receptors. We present the effect of these and similar modifications on simulated concentrations and their level of agreement with observed values.

A High-Resolution WRF Tropical Channel Simulation Driven by a Global Reanalysis

NASA Astrophysics Data System (ADS)

Holland, G.; Leung, L.; Kuo, Y.; Hurrell, J.

2006-12-01

Since 2003, NCAR has invested in the development and application of Nested Regional Climate Model (NRCM) based on the Weather Research and Forecasting (WRF) model and the Community Climate System Model, as a key component of the Prediction Across Scales Initiative. A prototype tropical channel model has been developed to investigate scale interactions and the influence of tropical convection on large scale circulation and tropical modes. The model was developed based on the NCAR Weather Research and Forecasting Model (WRF), configured as a tropical channel between 30 ° S and 45 ° N, wide enough to allow teleconnection effects over the mid-latitudes. Compared to the limited area domain that WRF is typically applied over, the channel mode alleviates issues with reflection of tropical modes that could result from imposing east/west boundaries. Using a large amount of available computing resources on a supercomputer (Blue Vista) during its bedding in period, a simulation has been completed with the tropical channel applied at 36 km horizontal resolution for 5 years from 1996 to 2000, with large scale circulation provided by the NCEP/NCAR global reanalysis at the north/south boundaries. Shorter simulations of 2 years and 6 months have also been performed to include two-way nests at 12 km and 4 km resolution, respectively, over the western Pacific warm pool, to explicitly resolve tropical convection in the Maritime Continent. The simulations realistically captured the large-scale circulation including the trade winds over the tropical Pacific and Atlantic, the Australian and Asian monsoon circulation, and hurricane statistics. Preliminary analysis and evaluation of the simulations will be presented.

Enabling Predictive Simulation and UQ of Complex Multiphysics PDE Systems by the Development of Goal-Oriented Variational Sensitivity Analysis and a-Posteriori Error Estimation Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Estep, Donald

2015-11-30

This project addressed the challenge of predictive computational analysis of strongly coupled, highly nonlinear multiphysics systems characterized by multiple physical phenomena that span a large range of length- and time-scales. Specifically, the project was focused on computational estimation of numerical error and sensitivity analysis of computational solutions with respect to variations in parameters and data. In addition, the project investigated the use of accurate computational estimates to guide efficient adaptive discretization. The project developed, analyzed and evaluated new variational adjoint-based techniques for integration, model, and data error estimation/control and sensitivity analysis, in evolutionary multiphysics multiscale simulations.

Mantle Convection on Modern Supercomputers

NASA Astrophysics Data System (ADS)

Weismüller, J.; Gmeiner, B.; Huber, M.; John, L.; Mohr, M.; Rüde, U.; Wohlmuth, B.; Bunge, H. P.

2015-12-01

Mantle convection is the cause for plate tectonics, the formation of mountains and oceans, and the main driving mechanism behind earthquakes. The convection process is modeled by a system of partial differential equations describing the conservation of mass, momentum and energy. Characteristic to mantle flow is the vast disparity of length scales from global to microscopic, turning mantle convection simulations into a challenging application for high-performance computing. As system size and technical complexity of the simulations continue to increase, design and implementation of simulation models for next generation large-scale architectures is handled successfully only in an interdisciplinary context. A new priority program - named SPPEXA - by the German Research Foundation (DFG) addresses this issue, and brings together computer scientists, mathematicians and application scientists around grand challenges in HPC. Here we report from the TERRA-NEO project, which is part of the high visibility SPPEXA program, and a joint effort of four research groups. TERRA-NEO develops algorithms for future HPC infrastructures, focusing on high computational efficiency and resilience in next generation mantle convection models. We present software that can resolve the Earth's mantle with up to 1012 grid points and scales efficiently to massively parallel hardware with more than 50,000 processors. We use our simulations to explore the dynamic regime of mantle convection and assess the impact of small scale processes on global mantle flow.

Unsteady Aero Computation of a 1 1/2 Stage Large Scale Rotating Turbine

NASA Technical Reports Server (NTRS)

To, Wai-Ming

2012-01-01

This report is the documentation of the work performed for the Subsonic Rotary Wing Project under the NASA s Fundamental Aeronautics Program. It was funded through Task Number NNC10E420T under GESS-2 Contract NNC06BA07B in the period of 10/1/2010 to 8/31/2011. The objective of the task is to provide support for the development of variable speed power turbine technology through application of computational fluid dynamics analyses. This includes work elements in mesh generation, multistage URANS simulations, and post-processing of the simulation results for comparison with the experimental data. The unsteady CFD calculations were performed with the TURBO code running in multistage single passage (phase lag) mode. Meshes for the blade rows were generated with the NASA developed TCGRID code. The CFD performance is assessed and improvements are recommended for future research in this area. For that, the United Technologies Research Center's 1 1/2 stage Large Scale Rotating Turbine was selected to be the candidate engine configuration for this computational effort because of the completeness and availability of the data.

SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

PubMed

Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi

2018-01-01

Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

What Fermenter?

ERIC Educational Resources Information Center

Terry, John

1987-01-01

Discusses the feasibility of using fermenters in secondary school laboratories. Includes discussions of equipment, safety, and computer interfacing. Describes how a simple fermenter could be used to simulate large-scale processes. Concludes that, although teachers and technicians will require additional training, the prospects for biotechnology in…

Large scale rigidity-based flexibility analysis of biomolecules

PubMed Central

Streinu, Ileana

2016-01-01

KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the functionality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics simulations, and (c) is intended to work as seemlessly as possible on the large, idiosyncratic, publicly available repository of biomolecules, the Protein Data Bank. We describe the system design, along with the main data processing, computational, mathematical, and validation challenges underlying this phase of the KINARI project. PMID:26958583

Applying Parallel Adaptive Methods with GeoFEST/PYRAMID to Simulate Earth Surface Crustal Dynamics

NASA Technical Reports Server (NTRS)

Norton, Charles D.; Lyzenga, Greg; Parker, Jay; Glasscoe, Margaret; Donnellan, Andrea; Li, Peggy

2006-01-01

This viewgraph presentation reviews the use Adaptive Mesh Refinement (AMR) in simulating the Crustal Dynamics of Earth's Surface. AMR simultaneously improves solution quality, time to solution, and computer memory requirements when compared to generating/running on a globally fine mesh. The use of AMR in simulating the dynamics of the Earth's Surface is spurred by future proposed NASA missions, such as InSAR for Earth surface deformation and other measurements. These missions will require support for large-scale adaptive numerical methods using AMR to model observations. AMR was chosen because it has been successful in computation fluid dynamics for predictive simulation of complex flows around complex structures.

A divide-conquer-recombine algorithmic paradigm for large spatiotemporal quantum molecular dynamics simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shimojo, Fuyuki; Hattori, Shinnosuke; Department of Physics, Kumamoto University, Kumamoto 860-8555

We introduce an extension of the divide-and-conquer (DC) algorithmic paradigm called divide-conquer-recombine (DCR) to perform large quantum molecular dynamics (QMD) simulations on massively parallel supercomputers, in which interatomic forces are computed quantum mechanically in the framework of density functional theory (DFT). In DCR, the DC phase constructs globally informed, overlapping local-domain solutions, which in the recombine phase are synthesized into a global solution encompassing large spatiotemporal scales. For the DC phase, we design a lean divide-and-conquer (LDC) DFT algorithm, which significantly reduces the prefactor of the O(N) computational cost for N electrons by applying a density-adaptive boundary condition at themore » peripheries of the DC domains. Our globally scalable and locally efficient solver is based on a hybrid real-reciprocal space approach that combines: (1) a highly scalable real-space multigrid to represent the global charge density; and (2) a numerically efficient plane-wave basis for local electronic wave functions and charge density within each domain. Hybrid space-band decomposition is used to implement the LDC-DFT algorithm on parallel computers. A benchmark test on an IBM Blue Gene/Q computer exhibits an isogranular parallel efficiency of 0.984 on 786 432 cores for a 50.3 × 10{sup 6}-atom SiC system. As a test of production runs, LDC-DFT-based QMD simulation involving 16 661 atoms is performed on the Blue Gene/Q to study on-demand production of hydrogen gas from water using LiAl alloy particles. As an example of the recombine phase, LDC-DFT electronic structures are used as a basis set to describe global photoexcitation dynamics with nonadiabatic QMD (NAQMD) and kinetic Monte Carlo (KMC) methods. The NAQMD simulations are based on the linear response time-dependent density functional theory to describe electronic excited states and a surface-hopping approach to describe transitions between the excited states. A series of techniques are employed for efficiently calculating the long-range exact exchange correction and excited-state forces. The NAQMD trajectories are analyzed to extract the rates of various excitonic processes, which are then used in KMC simulation to study the dynamics of the global exciton flow network. This has allowed the study of large-scale photoexcitation dynamics in 6400-atom amorphous molecular solid, reaching the experimental time scales.« less

Computational Issues in Damping Identification for Large Scale Problems

NASA Technical Reports Server (NTRS)

Pilkey, Deborah L.; Roe, Kevin P.; Inman, Daniel J.

1997-01-01

Two damping identification methods are tested for efficiency in large-scale applications. One is an iterative routine, and the other a least squares method. Numerical simulations have been performed on multiple degree-of-freedom models to test the effectiveness of the algorithm and the usefulness of parallel computation for the problems. High Performance Fortran is used to parallelize the algorithm. Tests were performed using the IBM-SP2 at NASA Ames Research Center. The least squares method tested incurs high communication costs, which reduces the benefit of high performance computing. This method's memory requirement grows at a very rapid rate meaning that larger problems can quickly exceed available computer memory. The iterative method's memory requirement grows at a much slower pace and is able to handle problems with 500+ degrees of freedom on a single processor. This method benefits from parallelization, and significant speedup can he seen for problems of 100+ degrees-of-freedom.

Scalable parallel distance field construction for large-scale applications

DOE PAGES

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; ...

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate itsmore » efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.« less

Scalable Parallel Distance Field Construction for Large-Scale Applications.

PubMed

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

Unsteady flow simulations around complex geometries using stationary or rotating unstructured grids

NASA Astrophysics Data System (ADS)

Sezer-Uzol, Nilay

In this research, the computational analysis of three-dimensional, unsteady, separated, vortical flows around complex geometries is studied by using stationary or moving unstructured grids. Two main engineering problems are investigated. The first problem is the unsteady simulation of a ship airwake, where helicopter operations become even more challenging, by using stationary unstructured grids. The second problem is the unsteady simulation of wind turbine rotor flow fields by using moving unstructured grids which are rotating with the whole three-dimensional rigid rotor geometry. The three dimensional, unsteady, parallel, unstructured, finite volume flow solver, PUMA2, is used for the computational fluid dynamics (CFD) simulations considered in this research. The code is modified to have a moving grid capability to perform three-dimensional, time-dependent rotor simulations. An instantaneous log-law wall model for Large Eddy Simulations is also implemented in PUMA2 to investigate the very large Reynolds number flow fields of rotating blades. To verify the code modifications, several sample test cases are also considered. In addition, interdisciplinary studies, which are aiming to provide new tools and insights to the aerospace and wind energy scientific communities, are done during this research by focusing on the coupling of ship airwake CFD simulations with the helicopter flight dynamics and control analysis, the coupling of wind turbine rotor CFD simulations with the aeroacoustic analysis, and the analysis of these time-dependent and large-scale CFD simulations with the help of a computational monitoring, steering and visualization tool, POSSE.

Large-Scale Optimization for Bayesian Inference in Complex Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Willcox, Karen; Marzouk, Youssef

2013-11-12

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of themore » SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghattas, Omar

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUAROmore » Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Computational examination of utility scale wind turbine wake interactions

DOE PAGES

Okosun, Tyamo; Zhou, Chenn Q.

2015-07-14

We performed numerical simulations of small, utility scale wind turbine groupings to determine how wakes generated by upstream turbines affect the performance of the small turbine group as a whole. Specifically, various wind turbine arrangements were simulated to better understand how turbine location influences small group wake interactions. The minimization of power losses due to wake interactions certainly plays a significant role in the optimization of wind farms. Since wind turbines extract kinetic energy from the wind, the air passing through a wind turbine decreases in velocity, and turbines downstream of the initial turbine experience flows of lower energy, resultingmore » in reduced power output. Our study proposes two arrangements of turbines that could generate more power by exploiting the momentum of the wind to increase velocity at downstream turbines, while maintaining low wake interactions at the same time. Furthermore, simulations using Computational Fluid Dynamics are used to obtain results much more quickly than methods requiring wind tunnel models or a large scale experimental test.« less

DEM GPU studies of industrial scale particle simulations for granular flow civil engineering applications

NASA Astrophysics Data System (ADS)

Pizette, Patrick; Govender, Nicolin; Wilke, Daniel N.; Abriak, Nor-Edine

2017-06-01

The use of the Discrete Element Method (DEM) for industrial civil engineering industrial applications is currently limited due to the computational demands when large numbers of particles are considered. The graphics processing unit (GPU) with its highly parallelized hardware architecture shows potential to enable solution of civil engineering problems using discrete granular approaches. We demonstrate in this study the pratical utility of a validated GPU-enabled DEM modeling environment to simulate industrial scale granular problems. As illustration, the flow discharge of storage silos using 8 and 17 million particles is considered. DEM simulations have been performed to investigate the influence of particle size (equivalent size for the 20/40-mesh gravel) and induced shear stress for two hopper shapes. The preliminary results indicate that the shape of the hopper significantly influences the discharge rates for the same material. Specifically, this work shows that GPU-enabled DEM modeling environments can model industrial scale problems on a single portable computer within a day for 30 seconds of process time.

Computational Fluid Dynamics simulation of hydrothermal liquefaction of microalgae in a continuous plug-flow reactor.

PubMed

Ranganathan, Panneerselvam; Savithri, Sivaraman

2018-06-01

Computational Fluid Dynamics (CFD) technique is used in this work to simulate the hydrothermal liquefaction of Nannochloropsis sp. microalgae in a lab-scale continuous plug-flow reactor to understand the fluid dynamics, heat transfer, and reaction kinetics in a HTL reactor under hydrothermal condition. The temperature profile in the reactor and the yield of HTL products from the present simulation are obtained and they are validated with the experimental data available in the literature. Furthermore, the parametric study is carried out to study the effect of slurry flow rate, reactor temperature, and external heat transfer coefficient on the yield of products. Though the model predictions are satisfactory in comparison with the experimental results, it still needs to be improved for better prediction of the product yields. This improved model will be considered as a baseline for design and scale-up of large-scale HTL reactor. Copyright © 2018 Elsevier Ltd. All rights reserved.

Simulation of FRET dyes allows quantitative comparison against experimental data

NASA Astrophysics Data System (ADS)

Reinartz, Ines; Sinner, Claude; Nettels, Daniel; Stucki-Buchli, Brigitte; Stockmar, Florian; Panek, Pawel T.; Jacob, Christoph R.; Nienhaus, Gerd Ulrich; Schuler, Benjamin; Schug, Alexander

2018-03-01

Fully understanding biomolecular function requires detailed insight into the systems' structural dynamics. Powerful experimental techniques such as single molecule Förster Resonance Energy Transfer (FRET) provide access to such dynamic information yet have to be carefully interpreted. Molecular simulations can complement these experiments but typically face limits in accessing slow time scales and large or unstructured systems. Here, we introduce a coarse-grained simulation technique that tackles these challenges. While requiring only few parameters, we maintain full protein flexibility and include all heavy atoms of proteins, linkers, and dyes. We are able to sufficiently reduce computational demands to simulate large or heterogeneous structural dynamics and ensembles on slow time scales found in, e.g., protein folding. The simulations allow for calculating FRET efficiencies which quantitatively agree with experimentally determined values. By providing atomically resolved trajectories, this work supports the planning and microscopic interpretation of experiments. Overall, these results highlight how simulations and experiments can complement each other leading to new insights into biomolecular dynamics and function.

The Next Frontier in Computing

ScienceCinema

Sarrao, John

2018-06-13

Exascale computing refers to computing systems capable of at least one exaflop or a billion calculations per second (1018). That is 50 times faster than the most powerful supercomputers being used today and represents a thousand-fold increase over the first petascale computer that came into operation in 2008. How we use these large-scale simulation resources is the key to solving some of today’s most pressing problems, including clean energy production, nuclear reactor lifetime extension and nuclear stockpile aging.

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

PubMed

Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles

2004-07-15

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

Synchronization Of Parallel Discrete Event Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S.

1992-01-01

Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging

DOE PAGES

Lee, Jonghyun; Yoon, Hongkyu; Kitanidis, Peter K.; ...

2016-06-09

When characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydro-geophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the Principal Component Geostatistical Approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed inmore » the traditional inversion methods. PCGA can be conveniently linked to any multi-physics simulation software with independent parallel executions. In our paper, we extend PCGA to handle a large number of measurements (e.g. 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data was compressed by the zero-th temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Moreover, only about 2,000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method. This article is protected by copyright. All rights reserved.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Jonghyun; Yoon, Hongkyu; Kitanidis, Peter K.

When characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydro-geophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the Principal Component Geostatistical Approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed inmore » the traditional inversion methods. PCGA can be conveniently linked to any multi-physics simulation software with independent parallel executions. In our paper, we extend PCGA to handle a large number of measurements (e.g. 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data was compressed by the zero-th temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Moreover, only about 2,000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method. This article is protected by copyright. All rights reserved.« less

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

PubMed

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory

DOE PAGES

Tait, E. W.; Ratcliff, L. E.; Payne, M. C.; ...

2016-04-20

Experimental techniques for electron energy loss spectroscopy (EELS) combine high energy resolution with high spatial resolution. They are therefore powerful tools for investigating the local electronic structure of complex systems such as nanostructures, interfaces and even individual defects. Interpretation of experimental electron energy loss spectra is often challenging and can require theoretical modelling of candidate structures, which themselves may be large and complex, beyond the capabilities of traditional cubic-scaling density functional theory. In this work, we present functionality to compute electron energy loss spectra within the onetep linear-scaling density functional theory code. We first demonstrate that simulated spectra agree withmore » those computed using conventional plane wave pseudopotential methods to a high degree of precision. The ability of onetep to tackle large problems is then exploited to investigate convergence of spectra with respect to supercell size. As a result, we apply the novel functionality to a study of the electron energy loss spectra of defects on the (1 0 1) surface of an anatase slab and determine concentrations of defects which might be experimentally detectable.« less

Effects of cosmic rays on single event upsets

NASA Technical Reports Server (NTRS)

Venable, D. D.; Zajic, V.; Lowe, C. W.; Olidapupo, A.; Fogarty, T. N.

1989-01-01

Assistance was provided to the Brookhaven Single Event Upset (SEU) Test Facility. Computer codes were developed for fragmentation and secondary radiation affecting Very Large Scale Integration (VLSI) in space. A computer controlled CV (HP4192) test was developed for Terman analysis. Also developed were high speed parametric tests which are independent of operator judgment and a charge pumping technique for measurement of D(sub it) (E). The X-ray secondary effects, and parametric degradation as a function of dose rate were simulated. The SPICE simulation of static RAMs with various resistor filters was tested.

The NAS parallel benchmarks

NASA Technical Reports Server (NTRS)

Bailey, D. H.; Barszcz, E.; Barton, J. T.; Carter, R. L.; Lasinski, T. A.; Browning, D. S.; Dagum, L.; Fatoohi, R. A.; Frederickson, P. O.; Schreiber, R. S.

1991-01-01

A new set of benchmarks has been developed for the performance evaluation of highly parallel supercomputers in the framework of the NASA Ames Numerical Aerodynamic Simulation (NAS) Program. These consist of five 'parallel kernel' benchmarks and three 'simulated application' benchmarks. Together they mimic the computation and data movement characteristics of large-scale computational fluid dynamics applications. The principal distinguishing feature of these benchmarks is their 'pencil and paper' specification-all details of these benchmarks are specified only algorithmically. In this way many of the difficulties associated with conventional benchmarking approaches on highly parallel systems are avoided.

Structure identification methods for atomistic simulations of crystalline materials

DOE PAGES

Stukowski, Alexander

2012-05-28

Here, we discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as common neighbor analysis (CNA), centrosymmetry analysis, bond angle analysis, bond order analysis and Voronoi analysis. In addition we propose a simple extension to the CNA method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the neighbor distance analysis, which is designed to identify atomic structure units in grain boundaries.

Conceiving processes in atmospheric models-General equations, subscale parameterizations, and 'superparameterizations'

NASA Astrophysics Data System (ADS)

Gramelsberger, Gabriele

The scientific understanding of atmospheric processes has been rooted in the mechanical and physical view of nature ever since dynamic meteorology gained ground in the late 19th century. Conceiving the atmosphere as a giant 'air mass circulation engine' entails applying hydro- and thermodynamical theory to the subject in order to describe the atmosphere's behaviour on small scales. But when it comes to forecasting, it turns out that this view is far too complex to be computed. The limitation of analytical methods precludes an exact solution, forcing scientists to make use of numerical simulation. However, simulation introduces two prerequisites to meteorology: First, the partitioning of the theoretical view into two parts-the large-scale behaviour of the atmosphere, and the effects of smaller-scale processes on this large-scale behaviour, so-called parametrizations; and second, the dependency on computational power in order to achieve a higher resolution. The history of today's atmospheric circulation modelling can be reconstructed as the attempt to improve the handling of these basic constraints. It can be further seen as the old schism between theory and application under new circumstances, which triggers a new discussion about the question of how processes may be conceived in atmospheric modelling.

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Younge, Andrew J.; Pedretti, Kevin; Grant, Ryan

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In thismore » paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.« less

WeaVR: a self-contained and wearable immersive virtual environment simulation system.

PubMed

Hodgson, Eric; Bachmann, Eric R; Vincent, David; Zmuda, Michael; Waller, David; Calusdian, James

2015-03-01

We describe WeaVR, a computer simulation system that takes virtual reality technology beyond specialized laboratories and research sites and makes it available in any open space, such as a gymnasium or a public park. Novel hardware and software systems enable HMD-based immersive virtual reality simulations to be conducted in any arbitrary location, with no external infrastructure and little-to-no setup or site preparation. The ability of the WeaVR system to provide realistic motion-tracked navigation for users, to improve the study of large-scale navigation, and to generate usable behavioral data is shown in three demonstrations. First, participants navigated through a full-scale virtual grocery store while physically situated in an open grass field. Trajectory data are presented for both normal tracking and for tracking during the use of redirected walking that constrained users to a predefined area. Second, users followed a straight path within a virtual world for distances of up to 2 km while walking naturally and being redirected to stay within the field, demonstrating the ability of the system to study large-scale navigation by simulating virtual worlds that are potentially unlimited in extent. Finally, the portability and pedagogical implications of this system were demonstrated by taking it to a regional high school for live use by a computer science class on their own school campus.

Gibbs sampling on large lattice with GMRF

NASA Astrophysics Data System (ADS)

Marcotte, Denis; Allard, Denis

2018-02-01

Gibbs sampling is routinely used to sample truncated Gaussian distributions. These distributions naturally occur when associating latent Gaussian fields to category fields obtained by discrete simulation methods like multipoint, sequential indicator simulation and object-based simulation. The latent Gaussians are often used in data assimilation and history matching algorithms. When the Gibbs sampling is applied on a large lattice, the computing cost can become prohibitive. The usual practice of using local neighborhoods is unsatisfying as it can diverge and it does not reproduce exactly the desired covariance. A better approach is to use Gaussian Markov Random Fields (GMRF) which enables to compute the conditional distributions at any point without having to compute and invert the full covariance matrix. As the GMRF is locally defined, it allows simultaneous updating of all points that do not share neighbors (coding sets). We propose a new simultaneous Gibbs updating strategy on coding sets that can be efficiently computed by convolution and applied with an acceptance/rejection method in the truncated case. We study empirically the speed of convergence, the effect of choice of boundary conditions, of the correlation range and of GMRF smoothness. We show that the convergence is slower in the Gaussian case on the torus than for the finite case studied in the literature. However, in the truncated Gaussian case, we show that short scale correlation is quickly restored and the conditioning categories at each lattice point imprint the long scale correlation. Hence our approach enables to realistically apply Gibbs sampling on large 2D or 3D lattice with the desired GMRF covariance.

Ocean modelling on the CYBER 205 at GFDL

NASA Technical Reports Server (NTRS)

Cox, M.

1984-01-01

At the Geophysical Fluid Dynamics Laboratory, research is carried out for the purpose of understanding various aspects of climate, such as its variability, predictability, stability and sensitivity. The atmosphere and oceans are modelled mathematically and their phenomenology studied by computer simulation methods. The present state-of-the-art in the computer simulation of large scale oceans on the CYBER 205 is discussed. While atmospheric modelling differs in some aspects, the basic approach used is similar. The equations of the ocean model are presented along with a short description of the numerical techniques used to find their solution. Computational considerations and a typical solution are presented in section 4.

A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications.

PubMed

Sauer, Franz; Xie, Jinrong; Ma, Kwan-Liu

2017-10-01

The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a "unit cell" based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.

Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats

NASA Astrophysics Data System (ADS)

Stalter, S.; Yelash, L.; Emamy, N.; Statt, A.; Hanke, M.; Lukáčová-Medvid'ová, M.; Virnau, P.

2018-03-01

Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation boxes. We also argue that if colloidal systems are considered as opposed to atomistic systems, the gap between microscopic and macroscopic simulations regarding time and length scales is significantly smaller. We propose a novel reduced-order technique for the coupling to the macroscopic solver, which allows us to approximate a non-linear stress-strain relation efficiently and thus further reduce computational effort of microscopic simulations.

Fast Multipole Methods for Three-Dimensional N-body Problems

NASA Technical Reports Server (NTRS)

Koumoutsakos, P.

1995-01-01

We are developing computational tools for the simulations of three-dimensional flows past bodies undergoing arbitrary motions. High resolution viscous vortex methods have been developed that allow for extended simulations of two-dimensional configurations such as vortex generators. Our objective is to extend this methodology to three dimensions and develop a robust computational scheme for the simulation of such flows. A fundamental issue in the use of vortex methods is the ability of employing efficiently large numbers of computational elements to resolve the large range of scales that exist in complex flows. The traditional cost of the method scales as Omicron (N(sup 2)) as the N computational elements/particles induce velocities at each other, making the method unacceptable for simulations involving more than a few tens of thousands of particles. In the last decade fast methods have been developed that have operation counts of Omicron (N log N) or Omicron (N) (referred to as BH and GR respectively) depending on the details of the algorithm. These methods are based on the observation that the effect of a cluster of particles at a certain distance may be approximated by a finite series expansion. In order to exploit this observation we need to decompose the element population spatially into clusters of particles and build a hierarchy of clusters (a tree data structure) - smaller neighboring clusters combine to form a cluster of the next size up in the hierarchy and so on. This hierarchy of clusters allows one to determine efficiently when the approximation is valid. This algorithm is an N-body solver that appears in many fields of engineering and science. Some examples of its diverse use are in astrophysics, molecular dynamics, micro-magnetics, boundary element simulations of electromagnetic problems, and computer animation. More recently these N-body solvers have been implemented and applied in simulations involving vortex methods. Koumoutsakos and Leonard (1995) implemented the GR scheme in two dimensions for vector computer architectures allowing for simulations of bluff body flows using millions of particles. Winckelmans presented three-dimensional, viscous simulations of interacting vortex rings, using vortons and an implementation of a BH scheme for parallel computer architectures. Bhatt presented a vortex filament method to perform inviscid vortex ring interactions, with an alternative implementation of a BH scheme for a Connection Machine parallel computer architecture.

Aeroelastic-Acoustics Simulation of Flight Systems

NASA Technical Reports Server (NTRS)

Gupta, kajal K.; Choi, S.; Ibrahim, A.

2009-01-01

This paper describes the details of a numerical finite element (FE) based analysis procedure and a resulting code for the simulation of the acoustics phenomenon arising from aeroelastic interactions. Both CFD and structural simulations are based on FE discretization employing unstructured grids. The sound pressure level (SPL) on structural surfaces is calculated from the root mean square (RMS) of the unsteady pressure and the acoustic wave frequencies are computed from a fast Fourier transform (FFT) of the unsteady pressure distribution as a function of time. The resulting tool proves to be unique as it is designed to analyze complex practical problems, involving large scale computations, in a routine fashion.

Moving contact lines on vibrating surfaces

NASA Astrophysics Data System (ADS)

Solomenko, Zlatko; Spelt, Peter; Scott, Julian

2017-11-01

Large-scale simulations of flows with moving contact lines for realistic conditions generally requires a subgrid scale model (analyses based on matched asymptotics) to account for the unresolved part of the flow, given the large range of length scales involved near contact lines. Existing models for the interface shape in the contact-line region are primarily for steady flows on homogeneous substrates, with encouraging results in 3D simulations. Introduction of complexities would require further investigation of the contact-line region, however. Here we study flows with moving contact lines on planar substrates subject to vibrations, with applications in controlling wetting/dewetting. The challenge here is to determine the change in interface shape near contact lines due to vibrations. To develop further insight, 2D direct numerical simulations (wherein the flow is resolved down to an imposed slip length) have been performed to enable comparison with asymptotic theory, which is also developed further. Perspectives will also be presented on the final objective of the work, which is to develop a subgrid scale model that can be utilized in large-scale simulations. The authors gratefully acknowledge the ANR for financial support (ANR-15-CE08-0031) and the meso-centre FLMSN for use of computational resources. This work was Granted access to the HPC resources of CINES under the allocation A0012B06893 made by GENCI.

Final Report, DE-FG01-06ER25718 Domain Decomposition and Parallel Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Widlund, Olof B.

2015-06-09

The goal of this project is to develop and improve domain decomposition algorithms for a variety of partial differential equations such as those of linear elasticity and electro-magnetics.These iterative methods are designed for massively parallel computing systems and allow the fast solution of the very large systems of algebraic equations that arise in large scale and complicated simulations. A special emphasis is placed on problems arising from Maxwell's equation. The approximate solvers, the preconditioners, are combined with the conjugate gradient method and must always include a solver of a coarse model in order to have a performance which is independentmore » of the number of processors used in the computer simulation. A recent development allows for an adaptive construction of this coarse component of the preconditioner.« less

Least Squares Shadowing Sensitivity Analysis of Chaotic Flow Around a Two-Dimensional Airfoil

NASA Technical Reports Server (NTRS)

Blonigan, Patrick J.; Wang, Qiqi; Nielsen, Eric J.; Diskin, Boris

2016-01-01

Gradient-based sensitivity analysis has proven to be an enabling technology for many applications, including design of aerospace vehicles. However, conventional sensitivity analysis methods break down when applied to long-time averages of chaotic systems. This breakdown is a serious limitation because many aerospace applications involve physical phenomena that exhibit chaotic dynamics, most notably high-resolution large-eddy and direct numerical simulations of turbulent aerodynamic flows. A recently proposed methodology, Least Squares Shadowing (LSS), avoids this breakdown and advances the state of the art in sensitivity analysis for chaotic flows. The first application of LSS to a chaotic flow simulated with a large-scale computational fluid dynamics solver is presented. The LSS sensitivity computed for this chaotic flow is verified and shown to be accurate, but the computational cost of the current LSS implementation is high.

Consistent Large-Eddy Simulation of a Temporal Mixing Layer Laden with Evaporating Drops. Part 2; A Posteriori Modelling

NASA Technical Reports Server (NTRS)

Leboissertier, Anthony; Okong'O, Nora; Bellan, Josette

2005-01-01

Large-eddy simulation (LES) is conducted of a three-dimensional temporal mixing layer whose lower stream is initially laden with liquid drops which may evaporate during the simulation. The gas-phase equations are written in an Eulerian frame for two perfect gas species (carrier gas and vapour emanating from the drops), while the liquid-phase equations are written in a Lagrangian frame. The effect of drop evaporation on the gas phase is considered through mass, species, momentum and energy source terms. The drop evolution is modelled using physical drops, or using computational drops to represent the physical drops. Simulations are performed using various LES models previously assessed on a database obtained from direct numerical simulations (DNS). These LES models are for: (i) the subgrid-scale (SGS) fluxes and (ii) the filtered source terms (FSTs) based on computational drops. The LES, which are compared to filtered-and-coarsened (FC) DNS results at the coarser LES grid, are conducted with 64 times fewer grid points than the DNS, and up to 64 times fewer computational than physical drops. It is found that both constant-coefficient and dynamic Smagorinsky SGS-flux models, though numerically stable, are overly dissipative and damp generated small-resolved-scale (SRS) turbulent structures. Although the global growth and mixing predictions of LES using Smagorinsky models are in good agreement with the FC-DNS, the spatial distributions of the drops differ significantly. In contrast, the constant-coefficient scale-similarity model and the dynamic gradient model perform well in predicting most flow features, with the latter model having the advantage of not requiring a priori calibration of the model coefficient. The ability of the dynamic models to determine the model coefficient during LES is found to be essential since the constant-coefficient gradient model, although more accurate than the Smagorinsky model, is not consistently numerically stable despite using DNS-calibrated coefficients. With accurate SGS-flux models, namely scale-similarity and dynamic gradient, the FST model allows up to a 32-fold reduction in computational drops compared to the number of physical drops, without degradation of accuracy; a 64-fold reduction leads to a slight decrease in accuracy.

Consider a non-spherical elephant: computational fluid dynamics simulations of heat transfer coefficients and drag verified using wind tunnel experiments.

PubMed

Dudley, Peter N; Bonazza, Riccardo; Porter, Warren P

2013-07-01

Animal momentum and heat transfer analysis has historically used direct animal measurements or approximations to calculate drag and heat transfer coefficients. Research can now use modern 3D rendering and computational fluid dynamics software to simulate animal-fluid interactions. Key questions are the level of agreement between simulations and experiments and how superior they are to classical approximations. In this paper we compared experimental and simulated heat transfer and drag calculations on a scale model solid aluminum African elephant casting. We found good agreement between experimental and simulated data and large differences from classical approximations. We used the simulation results to calculate coefficients for heat transfer and drag of the elephant geometry. Copyright © 2013 Wiley Periodicals, Inc.

Resolving Dynamic Properties of Polymers through Coarse-Grained Computational Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora

2016-02-05

Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly modeled. In this paper, we probe the degree of coarse graining required to simultaneously retain significant atomistic details and access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using linear polyethylene as a model system, we probe how the coarse-graining scale affects the measured dynamics. Iterative Boltzmann inversion ismore » used to derive coarse-grained potentials with 2–6 methylene groups per coarse-grained bead from a fully atomistic melt simulation. We show that atomistic detail is critical to capturing large-scale dynamics. Finally, using these models we simulate polyethylene melts for times over 500 μs to study the viscoelastic properties of well-entangled polymer melts.« less

Optical Disk Technology.

ERIC Educational Resources Information Center

Abbott, George L.; And Others

1987-01-01

This special feature focuses on recent developments in optical disk technology. Nine articles discuss current trends, large scale image processing, data structures for optical disks, the use of computer simulators to create optical disks, videodisk use in training, interactive audio video systems, impacts on federal information policy, and…

Subgrid-scale models for large-eddy simulation of rotating turbulent flows

NASA Astrophysics Data System (ADS)

Silvis, Maurits; Trias, Xavier; Abkar, Mahdi; Bae, Hyunji Jane; Lozano-Duran, Adrian; Verstappen, Roel

2016-11-01

This paper discusses subgrid models for large-eddy simulation of anisotropic flows using anisotropic grids. In particular, we are looking into ways to model not only the subgrid dissipation, but also transport processes, since these are expected to play an important role in rotating turbulent flows. We therefore consider subgrid-scale models of the form τ = - 2νt S +μt (SΩ - ΩS) , where the eddy-viscosity νt is given by the minimum-dissipation model, μt represents a transport coefficient; S is the symmetric part of the velocity gradient and Ω the skew-symmetric part. To incorporate the effect of mesh anisotropy the filter length is taken in such a way that it minimizes the difference between the turbulent stress in physical and computational space, where the physical space is covered by an anisotropic mesh and the computational space is isotropic. The resulting model is successfully tested for rotating homogeneous isotropic turbulence and rotating plane-channel flows. The research was largely carried out during the CTR SP 2016. M.S, and R.V. acknowledge the financial support to attend this Summer Program.

Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks.

PubMed

Rangan, Aaditya V; Cai, David

2007-02-01

We discuss numerical methods for simulating large-scale, integrate-and-fire (I&F) neuronal networks. Important elements in our numerical methods are (i) a neurophysiologically inspired integrating factor which casts the solution as a numerically tractable integral equation, and allows us to obtain stable and accurate individual neuronal trajectories (i.e., voltage and conductance time-courses) even when the I&F neuronal equations are stiff, such as in strongly fluctuating, high-conductance states; (ii) an iterated process of spike-spike corrections within groups of strongly coupled neurons to account for spike-spike interactions within a single large numerical time-step; and (iii) a clustering procedure of firing events in the network to take advantage of localized architectures, such as spatial scales of strong local interactions, which are often present in large-scale computational models-for example, those of the primary visual cortex. (We note that the spike-spike corrections in our methods are more involved than the correction of single neuron spike-time via a polynomial interpolation as in the modified Runge-Kutta methods commonly used in simulations of I&F neuronal networks.) Our methods can evolve networks with relatively strong local interactions in an asymptotically optimal way such that each neuron fires approximately once in [Formula: see text] operations, where N is the number of neurons in the system. We note that quantifications used in computational modeling are often statistical, since measurements in a real experiment to characterize physiological systems are typically statistical, such as firing rate, interspike interval distributions, and spike-triggered voltage distributions. We emphasize that it takes much less computational effort to resolve statistical properties of certain I&F neuronal networks than to fully resolve trajectories of each and every neuron within the system. For networks operating in realistic dynamical regimes, such as strongly fluctuating, high-conductance states, our methods are designed to achieve statistical accuracy when very large time-steps are used. Moreover, our methods can also achieve trajectory-wise accuracy when small time-steps are used.

The accurate particle tracer code

NASA Astrophysics Data System (ADS)

Wang, Yulei; Liu, Jian; Qin, Hong; Yu, Zhi; Yao, Yicun

2017-11-01

The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runaway electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world's fastest computer, the Sunway TaihuLight supercomputer, by supporting master-slave architecture of Sunway many-core processors. Based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.

An iterative method for hydrodynamic interactions in Brownian dynamics simulations of polymer dynamics

NASA Astrophysics Data System (ADS)

Miao, Linling; Young, Charles D.; Sing, Charles E.

2017-07-01

Brownian Dynamics (BD) simulations are a standard tool for understanding the dynamics of polymers in and out of equilibrium. Quantitative comparison can be made to rheological measurements of dilute polymer solutions, as well as direct visual observations of fluorescently labeled DNA. The primary computational challenge with BD is the expensive calculation of hydrodynamic interactions (HI), which are necessary to capture physically realistic dynamics. The full HI calculation, performed via a Cholesky decomposition every time step, scales with the length of the polymer as O(N3). This limits the calculation to a few hundred simulated particles. A number of approximations in the literature can lower this scaling to O(N2 - N2.25), and explicit solvent methods scale as O(N); however both incur a significant constant per-time step computational cost. Despite this progress, there remains a need for new or alternative methods of calculating hydrodynamic interactions; large polymer chains or semidilute polymer solutions remain computationally expensive. In this paper, we introduce an alternative method for calculating approximate hydrodynamic interactions. Our method relies on an iterative scheme to establish self-consistency between a hydrodynamic matrix that is averaged over simulation and the hydrodynamic matrix used to run the simulation. Comparison to standard BD simulation and polymer theory results demonstrates that this method quantitatively captures both equilibrium and steady-state dynamics after only a few iterations. The use of an averaged hydrodynamic matrix allows the computationally expensive Brownian noise calculation to be performed infrequently, so that it is no longer the bottleneck of the simulation calculations. We also investigate limitations of this conformational averaging approach in ring polymers.

Solutions of the Taylor-Green Vortex Problem Using High-Resolution Explicit Finite Difference Methods

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2013-01-01

A computational fluid dynamics code that solves the compressible Navier-Stokes equations was applied to the Taylor-Green vortex problem to examine the code s ability to accurately simulate the vortex decay and subsequent turbulence. The code, WRLES (Wave Resolving Large-Eddy Simulation), uses explicit central-differencing to compute the spatial derivatives and explicit Low Dispersion Runge-Kutta methods for the temporal discretization. The flow was first studied and characterized using Bogey & Bailley s 13-point dispersion relation preserving (DRP) scheme. The kinetic energy dissipation rate, computed both directly and from the enstrophy field, vorticity contours, and the energy spectra are examined. Results are in excellent agreement with a reference solution obtained using a spectral method and provide insight into computations of turbulent flows. In addition the following studies were performed: a comparison of 4th-, 8th-, 12th- and DRP spatial differencing schemes, the effect of the solution filtering on the results, the effect of large-eddy simulation sub-grid scale models, and the effect of high-order discretization of the viscous terms.

Quantitative computational infrared imaging of buoyant diffusion flames

NASA Astrophysics Data System (ADS)

Newale, Ashish S.

Studies of infrared radiation from turbulent buoyant diffusion flames impinging on structural elements have applications to the development of fire models. A numerical and experimental study of radiation from buoyant diffusion flames with and without impingement on a flat plate is reported. Quantitative images of the radiation intensity from the flames are acquired using a high speed infrared camera. Large eddy simulations are performed using fire dynamics simulator (FDS version 6). The species concentrations and temperature from the simulations are used in conjunction with a narrow-band radiation model (RADCAL) to solve the radiative transfer equation. The computed infrared radiation intensities rendered in the form of images and compared with the measurements. The measured and computed radiation intensities reveal necking and bulging with a characteristic frequency of 7.1 Hz which is in agreement with previous empirical correlations. The results demonstrate the effects of stagnation point boundary layer on the upstream buoyant shear layer. The coupling between these two shear layers presents a model problem for sub-grid scale modeling necessary for future large eddy simulations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kojima, S.; Yokosawa, M.; Matsuyama, M.

To study the practical application of a tritium separation process using Self-Developing Gas Chromatography (SDGC) using a Pd-Pt alloy, intermediate scale-up experiments (22 mm ID x 2 m length column) and the development of a computational simulation method have been conducted. In addition, intermediate scale production of Pd-Pt powder has been developed for the scale-up experiments.The following results were obtained: (1) a 50-fold scale-up from 3 mm to 22 mm causes no significant impact on the SDGC process; (2) the Pd-Pt alloy powder is applicable to a large size SDGC process; and (3) the simulation enables preparation of a conceptualmore » design of a SDGC process for tritium separation.« less

Ground-motion signature of dynamic ruptures on rough faults

NASA Astrophysics Data System (ADS)

Mai, P. Martin; Galis, Martin; Thingbaijam, Kiran K. S.; Vyas, Jagdish C.

2016-04-01

Natural earthquakes occur on faults characterized by large-scale segmentation and small-scale roughness. This multi-scale geometrical complexity controls the dynamic rupture process, and hence strongly affects the radiated seismic waves and near-field shaking. For a fault system with given segmentation, the question arises what are the conditions for producing large-magnitude multi-segment ruptures, as opposed to smaller single-segment events. Similarly, for variable degrees of roughness, ruptures may be arrested prematurely or may break the entire fault. In addition, fault roughness induces rupture incoherence that determines the level of high-frequency radiation. Using HPC-enabled dynamic-rupture simulations, we generate physically self-consistent rough-fault earthquake scenarios (M~6.8) and their associated near-source seismic radiation. Because these computations are too expensive to be conducted routinely for simulation-based seismic hazard assessment, we thrive to develop an effective pseudo-dynamic source characterization that produces (almost) the same ground-motion characteristics. Therefore, we examine how variable degrees of fault roughness affect rupture properties and the seismic wavefield, and develop a planar-fault kinematic source representation that emulates the observed dynamic behaviour. We propose an effective workflow for improved pseudo-dynamic source modelling that incorporates rough-fault effects and its associated high-frequency radiation in broadband ground-motion computation for simulation-based seismic hazard assessment.

Efficiency analysis of numerical integrations for finite element substructure in real-time hybrid simulation

NASA Astrophysics Data System (ADS)

Wang, Jinting; Lu, Liqiao; Zhu, Fei

2018-01-01

Finite element (FE) is a powerful tool and has been applied by investigators to real-time hybrid simulations (RTHSs). This study focuses on the computational efficiency, including the computational time and accuracy, of numerical integrations in solving FE numerical substructure in RTHSs. First, sparse matrix storage schemes are adopted to decrease the computational time of FE numerical substructure. In this way, the task execution time (TET) decreases such that the scale of the numerical substructure model increases. Subsequently, several commonly used explicit numerical integration algorithms, including the central difference method (CDM), the Newmark explicit method, the Chang method and the Gui-λ method, are comprehensively compared to evaluate their computational time in solving FE numerical substructure. CDM is better than the other explicit integration algorithms when the damping matrix is diagonal, while the Gui-λ (λ = 4) method is advantageous when the damping matrix is non-diagonal. Finally, the effect of time delay on the computational accuracy of RTHSs is investigated by simulating structure-foundation systems. Simulation results show that the influences of time delay on the displacement response become obvious with the mass ratio increasing, and delay compensation methods may reduce the relative error of the displacement peak value to less than 5% even under the large time-step and large time delay.

Climate Modeling with a Million CPUs

NASA Astrophysics Data System (ADS)

Tobis, M.; Jackson, C. S.

2010-12-01

Michael Tobis, Ph.D. Research Scientist Associate University of Texas Institute for Geophysics Charles S. Jackson Research Scientist University of Texas Institute for Geophysics Meteorological, oceanographic, and climatological applications have been at the forefront of scientific computing since its inception. The trend toward ever larger and more capable computing installations is unabated. However, much of the increase in capacity is accompanied by an increase in parallelism and a concomitant increase in complexity. An increase of at least four additional orders of magnitude in the computational power of scientific platforms is anticipated. It is unclear how individual climate simulations can continue to make effective use of the largest platforms. Conversion of existing community codes to higher resolution, or to more complex phenomenology, or both, presents daunting design and validation challenges. Our alternative approach is to use the expected resources to run very large ensembles of simulations of modest size, rather than to await the emergence of very large simulations. We are already doing this in exploring the parameter space of existing models using the Multiple Very Fast Simulated Annealing algorithm, which was developed for seismic imaging. Our experiments have the dual intentions of tuning the model and identifying ranges of parameter uncertainty. Our approach is less strongly constrained by the dimensionality of the parameter space than are competing methods. Nevertheless, scaling up remains costly. Much could be achieved by increasing the dimensionality of the search and adding complexity to the search algorithms. Such ensemble approaches scale naturally to very large platforms. Extensions of the approach are anticipated. For example, structurally different models can be tuned to comparable effectiveness. This can provide an objective test for which there is no realistic precedent with smaller computations. We find ourselves inventing new code to manage our ensembles. Component computations involve tens to hundreds of CPUs and tens to hundreds of hours. The results of these moderately large parallel jobs influence the scheduling of subsequent jobs, and complex algorithms may be easily contemplated for this. The operating system concept of a "thread" re-emerges at a very coarse level, where each thread manages atomic computations of thousands of CPU-hours. That is, rather than multiple threads operating on a processor, at this level, multiple processors operate within a single thread. In collaboration with the Texas Advanced Computing Center, we are developing a software library at the system level, which should facilitate the development of computations involving complex strategies which invoke large numbers of moderately large multi-processor jobs. While this may have applications in other sciences, our key intent is to better characterize the coupled behavior of a very large set of climate model configurations.

Modelling magnetic reconnection events relevant for solar physics with the new Energy Conserving Moment Implicit Method

NASA Astrophysics Data System (ADS)

Boella, Elisabetta; Herrero-Gonzalez, Diego; Innocenti, Maria Elena; Bemporad, Alessandro; Lapenta, Giovanni

2017-04-01

Fully kinetic simulations of magnetic reconnection events in the solar environment are especially challenging due to the extreme range of spatial and temporal scales that characterises them. As one moves from the photosphere to the chromosphere and the corona, the temperature increases from sub eV to 10-100 eV, while the mass density decreases from 10-4 to 10-12 kg/m3 and further. The intrinsic scales of kinetic reconnection (inertial length and gyroradius) are tremendously smaller than the maximum resolution available in observations. Furthermore, no direct information is available on the size of reconnection regions, plasmoids and reconnection fronts, while observations suggest that the process can cascade down to very small scale te{Bemporad}. Resolving the electron and ion scales while simulating a sufficiently large domain is a great challenge facing solar modelling. An especially challenging aspect is the need to consider the Debye length. The very low temperature of the electrons and the large spatial and temporal scales make these simulations hard to implement within existing Particle in Cell (PIC) methods. The limit is the ratio of the grid spacing to the Debye length. PIC methods show good stability and energy conservation when the grid does not exceed the Debye length too much. Semi-implicit methods te{Brackbill, Langdon} improve on this point. Only the recently developed fully energy conserving implicit methods have solved the problem te{Markidis, Chen}, but at a high computational cost. Very recently, we have developed an efficient new semi-implicit algorithm, which has been proven to conserve energy exactly to machine precision te{Lapenta}. In this work, we illustrate the main steps that enabled this great breakthrough and report the implementation on a new massively parallel three dimensional PIC code, called ECsim te{Lapenta2}. The new approach is applied to the problem of reconnection in the solar environment. We compare results of a simple 2D configuration similar to the so-called GEM challenge for different ranges of electron temperature, density and magnetic field, relative to different distances from the photosphere, demonstrating the capability of the new code. Finally, we report on the first results (to the authors' knowledge) of realistic magnetic 3D reconnection simulations in the solar environment, considering a large domain sufficient to describe the interaction of large scale dynamics with the reconnection process. A. Bemporad, ApJ 689, 572 (2008). J.U. Brackbill and D.W. Forslund, J. Comput. Phys. 46, 271 (1982). A. Langdon et al., J. Comput. Phys. 51, 107 (1983). S. Markidis and G. Lapenta, J. Comput. Phys. 230, 7037 (2011). G. Chen et al., J. Comput. Phys. 230, 7018 (2011). G. Lapenta, arXiv preprint arXiv:1602.06326 (2016). G. Lapenta et al., arXiv preprint arXiv:1612.08289 (2016).

Large-scale computations in fluid mechanics; Proceedings of the Fifteenth Summer Seminar on Applied Mathematics, University of California, La Jolla, CA, June 27-July 8, 1983. Parts 1 & 2

NASA Technical Reports Server (NTRS)

Engquist, B. E. (Editor); Osher, S. (Editor); Somerville, R. C. J. (Editor)

1985-01-01

Papers are presented on such topics as the use of semi-Lagrangian advective schemes in meteorological modeling; computation with high-resolution upwind schemes for hyperbolic equations; dynamics of flame propagation in a turbulent field; a modified finite element method for solving the incompressible Navier-Stokes equations; computational fusion magnetohydrodynamics; and a nonoscillatory shock capturing scheme using flux-limited dissipation. Consideration is also given to the use of spectral techniques in numerical weather prediction; numerical methods for the incorporation of mountains in atmospheric models; techniques for the numerical simulation of large-scale eddies in geophysical fluid dynamics; high-resolution TVD schemes using flux limiters; upwind-difference methods for aerodynamic problems governed by the Euler equations; and an MHD model of the earth's magnetosphere.

Enabling Functional Neural Circuit Simulations with Distributed Computing of Neuromodulated Plasticity

PubMed Central

Potjans, Wiebke; Morrison, Abigail; Diesmann, Markus

2010-01-01

A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge the gap between the macroscopic and the microscopic level of learning. Crucial insights into this topic are expected to be gained from simulations of neural systems, as these allow the simultaneous study of the multiple spatial and temporal scales that are involved in the problem. In particular, synaptic plasticity can be studied during the whole learning process, i.e., on a time scale of minutes to hours and across multiple brain areas. Implementing neuromodulated plasticity in large-scale network simulations where the neuromodulatory signal is dynamically generated by the network itself is challenging, because the network structure is commonly defined purely by the connectivity graph without explicit reference to the embedding of the nodes in physical space. Furthermore, the simulation of networks with realistic connectivity entails the use of distributed computing. A neuromodulated synapse must therefore be informed in an efficient way about the neuromodulatory signal, which is typically generated by a population of neurons located on different machines than either the pre- or post-synaptic neuron. Here, we develop a general framework to solve the problem of implementing neuromodulated plasticity in a time-driven distributed simulation, without reference to a particular implementation language, neuromodulator, or neuromodulated plasticity mechanism. We implement our framework in the simulator NEST and demonstrate excellent scaling up to 1024 processors for simulations of a recurrent network incorporating neuromodulated spike-timing dependent plasticity. PMID:21151370

A fully coupled method for massively parallel simulation of hydraulically driven fractures in 3-dimensions: FULLY COUPLED PARALLEL SIMULATION OF HYDRAULIC FRACTURES IN 3-D

DOE PAGES

Settgast, Randolph R.; Fu, Pengcheng; Walsh, Stuart D. C.; ...

2016-09-18

This study describes a fully coupled finite element/finite volume approach for simulating field-scale hydraulically driven fractures in three dimensions, using massively parallel computing platforms. The proposed method is capable of capturing realistic representations of local heterogeneities, layering and natural fracture networks in a reservoir. A detailed description of the numerical implementation is provided, along with numerical studies comparing the model with both analytical solutions and experimental results. The results demonstrate the effectiveness of the proposed method for modeling large-scale problems involving hydraulically driven fractures in three dimensions.

A fully coupled method for massively parallel simulation of hydraulically driven fractures in 3-dimensions: FULLY COUPLED PARALLEL SIMULATION OF HYDRAULIC FRACTURES IN 3-D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Settgast, Randolph R.; Fu, Pengcheng; Walsh, Stuart D. C.

This study describes a fully coupled finite element/finite volume approach for simulating field-scale hydraulically driven fractures in three dimensions, using massively parallel computing platforms. The proposed method is capable of capturing realistic representations of local heterogeneities, layering and natural fracture networks in a reservoir. A detailed description of the numerical implementation is provided, along with numerical studies comparing the model with both analytical solutions and experimental results. The results demonstrate the effectiveness of the proposed method for modeling large-scale problems involving hydraulically driven fractures in three dimensions.

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

PubMed

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

A Neural Information Field Approach to Computational Cognition

DTIC Science & Technology

2016-11-18

We have extended our perceptual decision making model to account for the effects of context in this flexible DISTRIBUTION A. Approved for public...developed a new perceptual decision making model; demonstrated adaptive motor control in a large-scale cognitive simulation with spiking neurons (Spaun...TERMS EOARD, Computational Cognition, Mixed-initiative decision making 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF

Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

NASA Astrophysics Data System (ADS)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing.

PubMed

Li, Zhixin; Su, Dandan; Zhu, Haijiang; Li, Wei; Zhang, Fan; Li, Ruirui

2017-01-08

Synthetic Aperture Radar (SAR) raw data simulation is a fundamental problem in radar system design and imaging algorithm research. The growth of surveying swath and resolution results in a significant increase in data volume and simulation period, which can be considered to be a comprehensive data intensive and computing intensive issue. Although several high performance computing (HPC) methods have demonstrated their potential for accelerating simulation, the input/output (I/O) bottleneck of huge raw data has not been eased. In this paper, we propose a cloud computing based SAR raw data simulation algorithm, which employs the MapReduce model to accelerate the raw data computing and the Hadoop distributed file system (HDFS) for fast I/O access. The MapReduce model is designed for the irregular parallel accumulation of raw data simulation, which greatly reduces the parallel efficiency of graphics processing unit (GPU) based simulation methods. In addition, three kinds of optimization strategies are put forward from the aspects of programming model, HDFS configuration and scheduling. The experimental results show that the cloud computing based algorithm achieves 4_ speedup over the baseline serial approach in an 8-node cloud environment, and each optimization strategy can improve about 20%. This work proves that the proposed cloud algorithm is capable of solving the computing intensive and data intensive issues in SAR raw data simulation, and is easily extended to large scale computing to achieve higher acceleration.

Large-scale 3D modeling of projectile impact damage in brittle plates

NASA Astrophysics Data System (ADS)

Seagraves, A.; Radovitzky, R.

2015-10-01

The damage and failure of brittle plates subjected to projectile impact is investigated through large-scale three-dimensional simulation using the DG/CZM approach introduced by Radovitzky et al. [Comput. Methods Appl. Mech. Eng. 2011; 200(1-4), 326-344]. Two standard experimental setups are considered: first, we simulate edge-on impact experiments on Al2O3 tiles by Strassburger and Senf [Technical Report ARL-CR-214, Army Research Laboratory, 1995]. Qualitative and quantitative validation of the simulation results is pursued by direct comparison of simulations with experiments at different loading rates and good agreement is obtained. In the second example considered, we investigate the fracture patterns in normal impact of spheres on thin, unconfined ceramic plates over a wide range of loading rates. For both the edge-on and normal impact configurations, the full field description provided by the simulations is used to interpret the mechanisms underlying the crack propagation patterns and their strong dependence on loading rate.

Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra.

PubMed

Hine, N D M; Haynes, P D; Mostofi, A A; Payne, M C

2010-09-21

We present calculations of formation energies of defects in an ionic solid (Al(2)O(3)) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

Wake characteristics of wind turbines in utility-scale wind farms

NASA Astrophysics Data System (ADS)

Yang, Xiaolei; Foti, Daniel; Sotiropoulos, Fotis

2017-11-01

The dynamics of turbine wakes is affected by turbine operating conditions, ambient atmospheric turbulent flows, and wakes from upwind turbines. Investigations of the wake from a single turbine have been extensively carried out in the literature. Studies on the wake dynamics in utility-scale wind farms are relatively limited. In this work, we employ large-eddy simulation with an actuator surface or actuator line model for turbine blades to investigate the wake dynamics in utility-scale wind farms. Simulations of three wind farms, i.e., the Horns Rev wind farm in Denmark, Pleasant Valley wind farm in Minnesota, and the Vantage wind farm in Washington are carried out. The computed power shows a good agreement with measurements. Analysis of the wake dynamics in the three wind farms is underway and will be presented in the conference. This work was support by Xcel Energy (RD4-13). The computational resources were provided by National Renewable Energy Laboratory.

Using Wavelet Analysis To Assist in Identification of Significant Events in Molecular Dynamics Simulations.

PubMed

Heidari, Zahra; Roe, Daniel R; Galindo-Murillo, Rodrigo; Ghasemi, Jahan B; Cheatham, Thomas E

2016-07-25

Long time scale molecular dynamics (MD) simulations of biological systems are becoming increasingly commonplace due to the availability of both large-scale computational resources and significant advances in the underlying simulation methodologies. Therefore, it is useful to investigate and develop data mining and analysis techniques to quickly and efficiently extract the biologically relevant information from the incredible amount of generated data. Wavelet analysis (WA) is a technique that can quickly reveal significant motions during an MD simulation. Here, the application of WA on well-converged long time scale (tens of μs) simulations of a DNA helix is described. We show how WA combined with a simple clustering method can be used to identify both the physical and temporal locations of events with significant motion in MD trajectories. We also show that WA can not only distinguish and quantify the locations and time scales of significant motions, but by changing the maximum time scale of WA a more complete characterization of these motions can be obtained. This allows motions of different time scales to be identified or ignored as desired.

Numerical propulsion system simulation

NASA Technical Reports Server (NTRS)

Lytle, John K.; Remaklus, David A.; Nichols, Lester D.

1990-01-01

The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive. One of the major contributors to the high cost is the need to perform many large scale system tests. Extensive testing is used to capture the complex interactions among the multiple disciplines and the multiple components inherent in complex systems. The objective of the Numerical Propulsion System Simulation (NPSS) is to provide insight into these complex interactions through computational simulations. This will allow for comprehensive evaluation of new concepts early in the design phase before a commitment to hardware is made. It will also allow for rapid assessment of field-related problems, particularly in cases where operational problems were encountered during conditions that would be difficult to simulate experimentally. The tremendous progress taking place in computational engineering and the rapid increase in computing power expected through parallel processing make this concept feasible within the near future. However it is critical that the framework for such simulations be put in place now to serve as a focal point for the continued developments in computational engineering and computing hardware and software. The NPSS concept which is described will provide that framework.

Robust large-scale parallel nonlinear solvers for simulations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bader, Brett William; Pawlowski, Roger Patrick; Kolda, Tamara Gibson

2005-11-01

This report documents research to develop robust and efficient solution techniques for solving large-scale systems of nonlinear equations. The most widely used method for solving systems of nonlinear equations is Newton's method. While much research has been devoted to augmenting Newton-based solvers (usually with globalization techniques), little has been devoted to exploring the application of different models. Our research has been directed at evaluating techniques using different models than Newton's method: a lower order model, Broyden's method, and a higher order model, the tensor method. We have developed large-scale versions of each of these models and have demonstrated their usemore » in important applications at Sandia. Broyden's method replaces the Jacobian with an approximation, allowing codes that cannot evaluate a Jacobian or have an inaccurate Jacobian to converge to a solution. Limited-memory methods, which have been successful in optimization, allow us to extend this approach to large-scale problems. We compare the robustness and efficiency of Newton's method, modified Newton's method, Jacobian-free Newton-Krylov method, and our limited-memory Broyden method. Comparisons are carried out for large-scale applications of fluid flow simulations and electronic circuit simulations. Results show that, in cases where the Jacobian was inaccurate or could not be computed, Broyden's method converged in some cases where Newton's method failed to converge. We identify conditions where Broyden's method can be more efficient than Newton's method. We also present modifications to a large-scale tensor method, originally proposed by Bouaricha, for greater efficiency, better robustness, and wider applicability. Tensor methods are an alternative to Newton-based methods and are based on computing a step based on a local quadratic model rather than a linear model. The advantage of Bouaricha's method is that it can use any existing linear solver, which makes it simple to write and easily portable. However, the method usually takes twice as long to solve as Newton-GMRES on general problems because it solves two linear systems at each iteration. In this paper, we discuss modifications to Bouaricha's method for a practical implementation, including a special globalization technique and other modifications for greater efficiency. We present numerical results showing computational advantages over Newton-GMRES on some realistic problems. We further discuss a new approach for dealing with singular (or ill-conditioned) matrices. In particular, we modify an algorithm for identifying a turning point so that an increasingly ill-conditioned Jacobian does not prevent convergence.« less

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

PubMed

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Using Mesoscale Weather Model Output as Boundary Conditions for Atmospheric Large-Eddy Simulations and Wind-Plant Aerodynamic Simulations (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Churchfield, M. J.; Michalakes, J.; Vanderwende, B.

Wind plant aerodynamics are directly affected by the microscale weather, which is directly influenced by the mesoscale weather. Microscale weather refers to processes that occur within the atmospheric boundary layer with the largest scales being a few hundred meters to a few kilometers depending on the atmospheric stability of the boundary layer. Mesoscale weather refers to large weather patterns, such as weather fronts, with the largest scales being hundreds of kilometers wide. Sometimes microscale simulations that capture mesoscale-driven variations (changes in wind speed and direction over time or across the spatial extent of a wind plant) are important in windmore » plant analysis. In this paper, we present our preliminary work in coupling a mesoscale weather model with a microscale atmospheric large-eddy simulation model. The coupling is one-way beginning with the weather model and ending with a computational fluid dynamics solver using the weather model in coarse large-eddy simulation mode as an intermediary. We simulate one hour of daytime moderately convective microscale development driven by the mesoscale data, which are applied as initial and boundary conditions to the microscale domain, at a site in Iowa. We analyze the time and distance necessary for the smallest resolvable microscales to develop.« less

A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

EPA Science Inventory

Fine-scale Computational Fluid Dynamics (CFD) simulation of pollutant concentrations within roadway and building microenvironments is feasible using high performance computing. Unlike currently used regulatory air quality models, fine-scale CFD simulations are able to account rig...

Methods for High-Order Multi-Scale and Stochastic Problems Analysis, Algorithms, and Applications

DTIC Science & Technology

2016-10-17

finite volume schemes, discontinuous Galerkin finite element method, and related methods, for solving computational fluid dynamics (CFD) problems and...approximation for finite element methods. (3) The development of methods of simulation and analysis for the study of large scale stochastic systems of...laws, finite element method, Bernstein-Bezier finite elements , weakly interacting particle systems, accelerated Monte Carlo, stochastic networks 16

Communication: Polymer entanglement dynamics: Role of attractive interactions

DOE PAGES

Grest, Gary S.

2016-10-10

The coupled dynamics of entangled polymers, which span broad time and length scales, govern their unique viscoelastic properties. To follow chain mobility by numerical simulations from the intermediate Rouse and reptation regimes to the late time diffusive regime, highly coarse grained models with purely repulsive interactions between monomers are widely used since they are computationally the most efficient. In this paper, using large scale molecular dynamics simulations, the effect of including the attractive interaction between monomers on the dynamics of entangled polymer melts is explored for the first time over a wide temperature range. Attractive interactions have little effect onmore » the local packing for all temperatures T and on the chain mobility for T higher than about twice the glass transition T g. Finally, these results, across a broad range of molecular weight, show that to study the dynamics of entangled polymer melts, the interactions can be treated as pure repulsive, confirming a posteriori the validity of previous studies and opening the way to new large scale numerical simulations.« less

A reduced basis method for molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Vincent-Finley, Rachel Elisabeth

In this dissertation, we develop a method for molecular simulation based on principal component analysis (PCA) of a molecular dynamics trajectory and least squares approximation of a potential energy function. Molecular dynamics (MD) simulation is a computational tool used to study molecular systems as they evolve through time. With respect to protein dynamics, local motions, such as bond stretching, occur within femtoseconds, while rigid body and large-scale motions, occur within a range of nanoseconds to seconds. To capture motion at all levels, time steps on the order of a femtosecond are employed when solving the equations of motion and simulations must continue long enough to capture the desired large-scale motion. To date, simulations of solvated proteins on the order of nanoseconds have been reported. It is typically the case that simulations of a few nanoseconds do not provide adequate information for the study of large-scale motions. Thus, the development of techniques that allow longer simulation times can advance the study of protein function and dynamics. In this dissertation we use principal component analysis (PCA) to identify the dominant characteristics of an MD trajectory and to represent the coordinates with respect to these characteristics. We augment PCA with an updating scheme based on a reduced representation of a molecule and consider equations of motion with respect to the reduced representation. We apply our method to butane and BPTI and compare the results to standard MD simulations of these molecules. Our results indicate that the molecular activity with respect to our simulation method is analogous to that observed in the standard MD simulation with simulations on the order of picoseconds.

A Fourier-based total-field/scattered-field technique for three-dimensional broadband simulations of elastic targets near a water-sand interface.

PubMed

Shao, Yu; Wang, Shumin

2016-12-01

The numerical simulation of acoustic scattering from elastic objects near a water-sand interface is critical to underwater target identification. Frequency-domain methods are computationally expensive, especially for large-scale broadband problems. A numerical technique is proposed to enable the efficient use of finite-difference time-domain method for broadband simulations. By incorporating a total-field/scattered-field boundary, the simulation domain is restricted inside a tightly bounded region. The incident field is further synthesized by the Fourier transform for both subcritical and supercritical incidences. Finally, the scattered far field is computed using a half-space Green's function. Numerical examples are further provided to demonstrate the accuracy and efficiency of the proposed technique.

A Scalable Cyberinfrastructure for Interactive Visualization of Terascale Microscopy Data

PubMed Central

Venkat, A.; Christensen, C.; Gyulassy, A.; Summa, B.; Federer, F.; Angelucci, A.; Pascucci, V.

2017-01-01

The goal of the recently emerged field of connectomics is to generate a wiring diagram of the brain at different scales. To identify brain circuitry, neuroscientists use specialized microscopes to perform multichannel imaging of labeled neurons at a very high resolution. CLARITY tissue clearing allows imaging labeled circuits through entire tissue blocks, without the need for tissue sectioning and section-to-section alignment. Imaging the large and complex non-human primate brain with sufficient resolution to identify and disambiguate between axons, in particular, produces massive data, creating great computational challenges to the study of neural circuits. Researchers require novel software capabilities for compiling, stitching, and visualizing large imagery. In this work, we detail the image acquisition process and a hierarchical streaming platform, ViSUS, that enables interactive visualization of these massive multi-volume datasets using a standard desktop computer. The ViSUS visualization framework has previously been shown to be suitable for 3D combustion simulation, climate simulation and visualization of large scale panoramic images. The platform is organized around a hierarchical cache oblivious data layout, called the IDX file format, which enables interactive visualization and exploration in ViSUS, scaling to the largest 3D images. In this paper we showcase the VISUS framework used in an interactive setting with the microscopy data. PMID:28638896

A Scalable Cyberinfrastructure for Interactive Visualization of Terascale Microscopy Data.

PubMed

Venkat, A; Christensen, C; Gyulassy, A; Summa, B; Federer, F; Angelucci, A; Pascucci, V

2016-08-01

The goal of the recently emerged field of connectomics is to generate a wiring diagram of the brain at different scales. To identify brain circuitry, neuroscientists use specialized microscopes to perform multichannel imaging of labeled neurons at a very high resolution. CLARITY tissue clearing allows imaging labeled circuits through entire tissue blocks, without the need for tissue sectioning and section-to-section alignment. Imaging the large and complex non-human primate brain with sufficient resolution to identify and disambiguate between axons, in particular, produces massive data, creating great computational challenges to the study of neural circuits. Researchers require novel software capabilities for compiling, stitching, and visualizing large imagery. In this work, we detail the image acquisition process and a hierarchical streaming platform, ViSUS, that enables interactive visualization of these massive multi-volume datasets using a standard desktop computer. The ViSUS visualization framework has previously been shown to be suitable for 3D combustion simulation, climate simulation and visualization of large scale panoramic images. The platform is organized around a hierarchical cache oblivious data layout, called the IDX file format, which enables interactive visualization and exploration in ViSUS, scaling to the largest 3D images. In this paper we showcase the VISUS framework used in an interactive setting with the microscopy data.

Decentralized state estimation for a large-scale spatially interconnected system.

PubMed

Liu, Huabo; Yu, Haisheng

2018-03-01

A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem on the basis of linear matrix inequality (LMI) is constructed for the computations of improved subsystem parameter matrices. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, this decentralized state estimator is proved to converge to a stable system and obtain a bounded covariance matrix of estimation errors under certain conditions. Numerical simulations show that the obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A statics-dynamics equivalence through the fluctuation–dissipation ratio provides a window into the spin-glass phase from nonequilibrium measurements

PubMed Central

Baity-Jesi, Marco; Calore, Enrico; Cruz, Andres; Fernandez, Luis Antonio; Gil-Narvión, José Miguel; Gordillo-Guerrero, Antonio; Iñiguez, David; Maiorano, Andrea; Marinari, Enzo; Martin-Mayor, Victor; Monforte-Garcia, Jorge; Muñoz Sudupe, Antonio; Navarro, Denis; Parisi, Giorgio; Perez-Gaviro, Sergio; Ricci-Tersenghi, Federico; Ruiz-Lorenzo, Juan Jesus; Schifano, Sebastiano Fabio; Tarancón, Alfonso; Tripiccione, Raffaele; Yllanes, David

2017-01-01

We have performed a very accurate computation of the nonequilibrium fluctuation–dissipation ratio for the 3D Edwards–Anderson Ising spin glass, by means of large-scale simulations on the special-purpose computers Janus and Janus II. This ratio (computed for finite times on very large, effectively infinite, systems) is compared with the equilibrium probability distribution of the spin overlap for finite sizes. Our main result is a quantitative statics-dynamics dictionary, which could allow the experimental exploration of important features of the spin-glass phase without requiring uncontrollable extrapolations to infinite times or system sizes. PMID:28174274

Evaluation of permeability and non-Darcy flow in vuggy macroporous limestone aquifer samples with lattice Boltzmann methods

USGS Publications Warehouse

Sukop, Michael C.; Huang, Haibo; Alvarez, Pedro F.; Variano, Evan A.; Cunningham, Kevin J.

2013-01-01

Lattice Boltzmann flow simulations provide a physics-based means of estimating intrinsic permeability from pore structure and accounting for inertial flow that leads to departures from Darcy's law. Simulations were used to compute intrinsic permeability where standard measurement methods may fail and to provide better understanding of departures from Darcy's law under field conditions. Simulations also investigated resolution issues. Computed tomography (CT) images were acquired at 0.8 mm interscan spacing for seven samples characterized by centimeter-scale biogenic vuggy macroporosity from the extremely transmissive sole-source carbonate karst Biscayne aquifer in southeastern Florida. Samples were as large as 0.3 m in length; 7–9 cm-scale-length subsamples were used for lattice Boltzmann computations. Macroporosity of the subsamples was as high as 81%. Matrix porosity was ignored in the simulations. Non-Darcy behavior led to a twofold reduction in apparent hydraulic conductivity as an applied hydraulic gradient increased to levels observed at regional scale within the Biscayne aquifer; larger reductions are expected under higher gradients near wells and canals. Thus, inertial flows and departures from Darcy's law may occur under field conditions. Changes in apparent hydraulic conductivity with changes in head gradient computed with the lattice Boltzmann model closely fit the Darcy-Forchheimer equation allowing estimation of the Forchheimer parameter. CT-scan resolution appeared adequate to capture intrinsic permeability; however, departures from Darcy behavior were less detectable as resolution coarsened.

Predicting the breakdown strength and lifetime of nanocomposites using a multi-scale modeling approach

NASA Astrophysics Data System (ADS)

Huang, Yanhui; Zhao, He; Wang, Yixing; Ratcliff, Tyree; Breneman, Curt; Brinson, L. Catherine; Chen, Wei; Schadler, Linda S.

2017-08-01

It has been found that doping dielectric polymers with a small amount of nanofiller or molecular additive can stabilize the material under a high field and lead to increased breakdown strength and lifetime. Choosing appropriate fillers is critical to optimizing the material performance, but current research largely relies on experimental trial and error. The employment of computer simulations for nanodielectric design is rarely reported. In this work, we propose a multi-scale modeling approach that employs ab initio, Monte Carlo, and continuum scales to predict the breakdown strength and lifetime of polymer nanocomposites based on the charge trapping effect of the nanofillers. The charge transfer, charge energy relaxation, and space charge effects are modeled in respective hierarchical scales by distinctive simulation techniques, and these models are connected together for high fidelity and robustness. The preliminary results show good agreement with the experimental data, suggesting its promise for use in the computer aided material design of high performance dielectrics.

Finite-difference method Stokes solver (FDMSS) for 3D pore geometries: Software development, validation and case studies

NASA Astrophysics Data System (ADS)

Gerke, Kirill M.; Vasilyev, Roman V.; Khirevich, Siarhei; Collins, Daniel; Karsanina, Marina V.; Sizonenko, Timofey O.; Korost, Dmitry V.; Lamontagne, Sébastien; Mallants, Dirk

2018-05-01

Permeability is one of the fundamental properties of porous media and is required for large-scale Darcian fluid flow and mass transport models. Whilst permeability can be measured directly at a range of scales, there are increasing opportunities to evaluate permeability from pore-scale fluid flow simulations. We introduce the free software Finite-Difference Method Stokes Solver (FDMSS) that solves Stokes equation using a finite-difference method (FDM) directly on voxelized 3D pore geometries (i.e. without meshing). Based on explicit convergence studies, validation on sphere packings with analytically known permeabilities, and comparison against lattice-Boltzmann and other published FDM studies, we conclude that FDMSS provides a computationally efficient and accurate basis for single-phase pore-scale flow simulations. By implementing an efficient parallelization and code optimization scheme, permeability inferences can now be made from 3D images of up to 109 voxels using modern desktop computers. Case studies demonstrate the broad applicability of the FDMSS software for both natural and artificial porous media.

Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures

DOE PAGES

Ayachit, Utkarsh; Bauer, Andrew; Duque, Earl P. N.; ...

2016-11-01

A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. Our paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: Scalability, overhead,more » performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.« less

Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.

PubMed

Rinderspacher, Berend Christopher; Bardhan, Jaydeep P; Ismail, Ahmed E

2017-07-01

We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions. This approach does not require explicit preparation of atomistic-to-coarse-grained mappings, but instead uses the theory of diffusion wavelets for graph Laplacians to develop system-specific mappings. Our methodology leads to a hierarchy of system-specific coarse-grained degrees of freedom that provides a conceptually clear and mathematically rigorous framework for modeling chemical systems at relevant model scales. The approach is capable of automatically generating as many coarse-grained model scales as necessary, that is, to go beyond the two scales in conventional coarse-grained strategies; furthermore, the wavelet-based coarse-grained models explicitly link time and length scales. Furthermore, a straightforward method for the reintroduction of omitted degrees of freedom is presented, which plays a major role in maintaining model fidelity in long-time simulations and in capturing emergent behaviors.

The Effect of Large Scale Salinity Gradient on Langmuir Turbulence

NASA Astrophysics Data System (ADS)

Fan, Y.; Jarosz, E.; Yu, Z.; Jensen, T.; Sullivan, P. P.; Liang, J.

2017-12-01

Langmuir circulation (LC) is believed to be one of the leading order causes of turbulent mixing in the upper ocean. It is important for momentum and heat exchange across the mixed layer (ML) and directly impact the dynamics and thermodynamics in the upper ocean and lower atmosphere including the vertical distributions of chemical, biological, optical, and acoustic properties. Based on Craik and Leibovich (1976) theory, large eddy simulation (LES) models have been developed to simulate LC in the upper ocean, yielding new insights that could not be obtained from field observations and turbulent closure models. Due its high computational cost, LES models are usually limited to small domain sizes and cannot resolve large-scale flows. Furthermore, most LES models used in the LC simulations use periodic boundary conditions in the horizontal direction, which assumes the physical properties (i.e. temperature and salinity) and expected flow patterns in the area of interest are of a periodically repeating nature so that the limited small LES domain is representative for the larger area. Using periodic boundary condition can significantly reduce computational effort in problems, and it is a good assumption for isotropic shear turbulence. However, LC is anisotropic (McWilliams et al 1997) and was observed to be modulated by crosswind tidal currents (Kukulka et al 2011). Using symmetrical domains, idealized LES studies also indicate LC could interact with oceanic fronts (Hamlington et al 2014) and standing internal waves (Chini and Leibovich, 2005). The present study expands our previous LES modeling investigations of Langmuir turbulence to the real ocean conditions with large scale environmental motion that features fresh water inflow into the study region. Large scale gradient forcing is introduced to the NCAR LES model through scale separation analysis. The model is applied to a field observation in the Gulf of Mexico in July, 2016 when the measurement site was impacted by large fresh water inflow due to flooding from the Mississippi river. Model results indicate that the strong salinity gradient can reduce the mean flow in the ML and inhibit the turbulence in the planetary boundary layer. The Langmuir cells are also rotated clockwise by the pressure gradient.

Calculations of High-Temperature Jet Flow Using Hybrid Reynolds-Average Navier-Stokes Formulations

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Elmiligui, Alaa; Giriamaji, Sharath S.

2008-01-01

Two multiscale-type turbulence models are implemented in the PAB3D solver. The models are based on modifying the Reynolds-averaged Navier Stokes equations. The first scheme is a hybrid Reynolds-averaged- Navier Stokes/large-eddy-simulation model using the two-equation k(epsilon) model with a Reynolds-averaged-Navier Stokes/large-eddy-simulation transition function dependent on grid spacing and the computed turbulence length scale. The second scheme is a modified version of the partially averaged Navier Stokes model in which the unresolved kinetic energy parameter f(sub k) is allowed to vary as a function of grid spacing and the turbulence length scale. This parameter is estimated based on a novel two-stage procedure to efficiently estimate the level of scale resolution possible for a given flow on a given grid for partially averaged Navier Stokes. It has been found that the prescribed scale resolution can play a major role in obtaining accurate flow solutions. The parameter f(sub k) varies between zero and one and is equal to one in the viscous sublayer and when the Reynolds-averaged Navier Stokes turbulent viscosity becomes smaller than the large-eddy-simulation viscosity. The formulation, usage methodology, and validation examples are presented to demonstrate the enhancement of PAB3D's time-accurate turbulence modeling capabilities. The accurate simulations of flow and turbulent quantities will provide a valuable tool for accurate jet noise predictions. Solutions from these models are compared with Reynolds-averaged Navier Stokes results and experimental data for high-temperature jet flows. The current results show promise for the capability of hybrid Reynolds-averaged Navier Stokes and large eddy simulation and partially averaged Navier Stokes in simulating such flow phenomena.

Large eddy simulation of turbine wakes using higher-order methods

NASA Astrophysics Data System (ADS)

Deskos, Georgios; Laizet, Sylvain; Piggott, Matthew D.; Sherwin, Spencer

2017-11-01

Large eddy simulations (LES) of a horizontal-axis turbine wake are presented using the well-known actuator line (AL) model. The fluid flow is resolved by employing higher-order numerical schemes on a 3D Cartesian mesh combined with a 2D Domain Decomposition strategy for an efficient use of supercomputers. In order to simulate flows at relatively high Reynolds numbers for a reasonable computational cost, a novel strategy is used to introduce controlled numerical dissipation to a selected range of small scales. The idea is to mimic the contribution of the unresolved small-scales by imposing a targeted numerical dissipation at small scales when evaluating the viscous term of the Navier-Stokes equations. The numerical technique is shown to behave similarly to the traditional eddy viscosity sub-filter scale models such as the classic or the dynamic Smagorinsky models. The results from the simulations are compared to experimental data for a Reynolds number scaled by the diameter equal to ReD =1,000,000 and both the time-averaged stream wise velocity and turbulent kinetic energy (TKE) are showing a good overall agreement. At the end, suggestions for the amount of numerical dissipation required by our approach are made for the particular case of horizontal-axis turbine wakes.

Effects of forcing time scale on the simulated turbulent flows and turbulent collision statistics of inertial particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosa, B., E-mail: bogdan.rosa@imgw.pl; Parishani, H.; Department of Earth System Science, University of California, Irvine, California 92697-3100

2015-01-15

In this paper, we study systematically the effects of forcing time scale in the large-scale stochastic forcing scheme of Eswaran and Pope [“An examination of forcing in direct numerical simulations of turbulence,” Comput. Fluids 16, 257 (1988)] on the simulated flow structures and statistics of forced turbulence. Using direct numerical simulations, we find that the forcing time scale affects the flow dissipation rate and flow Reynolds number. Other flow statistics can be predicted using the altered flow dissipation rate and flow Reynolds number, except when the forcing time scale is made unrealistically large to yield a Taylor microscale flow Reynoldsmore » number of 30 and less. We then study the effects of forcing time scale on the kinematic collision statistics of inertial particles. We show that the radial distribution function and the radial relative velocity may depend on the forcing time scale when it becomes comparable to the eddy turnover time. This dependence, however, can be largely explained in terms of altered flow Reynolds number and the changing range of flow length scales present in the turbulent flow. We argue that removing this dependence is important when studying the Reynolds number dependence of the turbulent collision statistics. The results are also compared to those based on a deterministic forcing scheme to better understand the role of large-scale forcing, relative to that of the small-scale turbulence, on turbulent collision of inertial particles. To further elucidate the correlation between the altered flow structures and dynamics of inertial particles, a conditional analysis has been performed, showing that the regions of higher collision rate of inertial particles are well correlated with the regions of lower vorticity. Regions of higher concentration of pairs at contact are found to be highly correlated with the region of high energy dissipation rate.« less

Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

PubMed

Gething, Peter W; Patil, Anand P; Hay, Simon I

2010-04-01

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, A.; Di Girolamo, A.; Klimentov, A.; Oleynik, D.; Petrosyan, A.; Atlas Collaboration

2014-06-01

ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produced petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we describe the ATLAS Grid Information System (AGIS), designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

Design of a high-speed digital processing element for parallel simulation

NASA Technical Reports Server (NTRS)

Milner, E. J.; Cwynar, D. S.

1983-01-01

A prototype of a custom designed computer to be used as a processing element in a multiprocessor based jet engine simulator is described. The purpose of the custom design was to give the computer the speed and versatility required to simulate a jet engine in real time. Real time simulations are needed for closed loop testing of digital electronic engine controls. The prototype computer has a microcycle time of 133 nanoseconds. This speed was achieved by: prefetching the next instruction while the current one is executing, transporting data using high speed data busses, and using state of the art components such as a very large scale integration (VLSI) multiplier. Included are discussions of processing element requirements, design philosophy, the architecture of the custom designed processing element, the comprehensive instruction set, the diagnostic support software, and the development status of the custom design.

Development of a Aerothermoelastic-Acoustics Simulation Capability of Flight Vehicles

NASA Technical Reports Server (NTRS)

Gupta, K. K.; Choi, S. B.; Ibrahim, A.

2010-01-01

A novel numerical, finite element based analysis methodology is presented in this paper suitable for accurate and efficient simulation of practical, complex flight vehicles. An associated computer code, developed in this connection, is also described in some detail. Thermal effects of high speed flow obtained from a heat conduction analysis are incorporated in the modal analysis which in turn affects the unsteady flow arising out of interaction of elastic structures with the air. Numerical examples pertaining to representative problems are given in much detail testifying to the efficacy of the advocated techniques. This is a unique implementation of temperature effects in a finite element CFD based multidisciplinary simulation analysis capability involving large scale computations.

Study of Near-Surface Models in Large-Eddy Simulations of a Neutrally Stratified Atmospheric Boundary Layer

NASA Technical Reports Server (NTRS)

Senocak, I.; Ackerman, A. S.; Kirkpatrick, M. P.; Stevens, D. E.; Mansour, N. N.

2004-01-01

Large-eddy simulation (LES) is a widely used technique in armospheric modeling research. In LES, large, unsteady, three dimensional structures are resolved and small structures that are not resolved on the computational grid are modeled. A filtering operation is applied to distinguish between resolved and unresolved scales. We present two near-surface models that have found use in atmospheric modeling. We also suggest a simpler eddy viscosity model that adopts Prandtl's mixing length model (Prandtl 1925) in the vicinity of the surface and blends with the dynamic Smagotinsky model (Germano et al, 1991) away from the surface. We evaluate the performance of these surface models by simulating a neutraly stratified atmospheric boundary layer.

Parallel Tensor Compression for Large-Scale Scientific Data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolda, Tamara G.; Ballard, Grey; Austin, Woody Nathan

As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memorymore » parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.« less

Java Performance for Scientific Applications on LLNL Computer Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kapfer, C; Wissink, A

2002-05-10

Languages in use for high performance computing at the laboratory--Fortran (f77 and f90), C, and C++--have many years of development behind them and are generally considered the fastest available. However, Fortran and C do not readily extend to object-oriented programming models, limiting their capability for very complex simulation software. C++ facilitates object-oriented programming but is a very complex and error-prone language. Java offers a number of capabilities that these other languages do not. For instance it implements cleaner (i.e., easier to use and less prone to errors) object-oriented models than C++. It also offers networking and security as part ofmore » the language standard, and cross-platform executables that make it architecture neutral, to name a few. These features have made Java very popular for industrial computing applications. The aim of this paper is to explain the trade-offs in using Java for large-scale scientific applications at LLNL. Despite its advantages, the computational science community has been reluctant to write large-scale computationally intensive applications in Java due to concerns over its poor performance. However, considerable progress has been made over the last several years. The Java Grande Forum [1] has been promoting the use of Java for large-scale computing. Members have introduced efficient array libraries, developed fast just-in-time (JIT) compilers, and built links to existing packages used in high performance parallel computing.« less

A Hybrid Method for Accelerated Simulation of Coulomb Collisions in a Plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caflisch, R; Wang, C; Dimarco, G

2007-10-09

If the collisional time scale for Coulomb collisions is comparable to the characteristic time scales for a plasma, then simulation of Coulomb collisions may be important for computation of kinetic plasma dynamics. This can be a computational bottleneck because of the large number of simulated particles and collisions (or phase-space resolution requirements in continuum algorithms), as well as the wide range of collision rates over the velocity distribution function. This paper considers Monte Carlo simulation of Coulomb collisions using the binary collision models of Takizuka & Abe and Nanbu. It presents a hybrid method for accelerating the computation of Coulombmore » collisions. The hybrid method represents the velocity distribution function as a combination of a thermal component (a Maxwellian distribution) and a kinetic component (a set of discrete particles). Collisions between particles from the thermal component preserve the Maxwellian; collisions between particles from the kinetic component are performed using the method of or Nanbu. Collisions between the kinetic and thermal components are performed by sampling a particle from the thermal component and selecting a particle from the kinetic component. Particles are also transferred between the two components according to thermalization and dethermalization probabilities, which are functions of phase space.« less

Development of an Efficient Binaural Simulation for the Analysis of Structural Acoustic Data

NASA Technical Reports Server (NTRS)

Johnson, Marty E.; Lalime, Aimee L.; Grosveld, Ferdinand W.; Rizzi, Stephen A.; Sullivan, Brenda M.

2003-01-01

Applying binaural simulation techniques to structural acoustic data can be very computationally intensive as the number of discrete noise sources can be very large. Typically, Head Related Transfer Functions (HRTFs) are used to individually filter the signals from each of the sources in the acoustic field. Therefore, creating a binaural simulation implies the use of potentially hundreds of real time filters. This paper details two methods of reducing the number of real-time computations required by: (i) using the singular value decomposition (SVD) to reduce the complexity of the HRTFs by breaking them into dominant singular values and vectors and (ii) by using equivalent source reduction (ESR) to reduce the number of sources to be analyzed in real-time by replacing sources on the scale of a structural wavelength with sources on the scale of an acoustic wavelength. The ESR and SVD reduction methods can be combined to provide an estimated computation time reduction of 99.4% for the structural acoustic data tested. In addition, preliminary tests have shown that there is a 97% correlation between the results of the combined reduction methods and the results found with the current binaural simulation techniques

MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations

NASA Astrophysics Data System (ADS)

Dibak, Manuel; del Razo, Mauricio J.; De Sancho, David; Schütte, Christof; Noé, Frank

2018-06-01

Molecular dynamics (MD) simulations can model the interactions between macromolecules with high spatiotemporal resolution but at a high computational cost. By combining high-throughput MD with Markov state models (MSMs), it is now possible to obtain long time-scale behavior of small to intermediate biomolecules and complexes. To model the interactions of many molecules at large length scales, particle-based reaction-diffusion (RD) simulations are more suitable but lack molecular detail. Thus, coupling MSMs and RD simulations (MSM/RD) would be highly desirable, as they could efficiently produce simulations at large time and length scales, while still conserving the characteristic features of the interactions observed at atomic detail. While such a coupling seems straightforward, fundamental questions are still open: Which definition of MSM states is suitable? Which protocol to merge and split RD particles in an association/dissociation reaction will conserve the correct bimolecular kinetics and thermodynamics? In this paper, we make the first step toward MSM/RD by laying out a general theory of coupling and proposing a first implementation for association/dissociation of a protein with a small ligand (A + B ⇌ C). Applications on a toy model and CO diffusion into the heme cavity of myoglobin are reported.

Petascale self-consistent electromagnetic computations using scalable and accurate algorithms for complex structures

NASA Astrophysics Data System (ADS)

Cary, John R.; Abell, D.; Amundson, J.; Bruhwiler, D. L.; Busby, R.; Carlsson, J. A.; Dimitrov, D. A.; Kashdan, E.; Messmer, P.; Nieter, C.; Smithe, D. N.; Spentzouris, P.; Stoltz, P.; Trines, R. M.; Wang, H.; Werner, G. R.

2006-09-01

As the size and cost of particle accelerators escalate, high-performance computing plays an increasingly important role; optimization through accurate, detailed computermodeling increases performance and reduces costs. But consequently, computer simulations face enormous challenges. Early approximation methods, such as expansions in distance from the design orbit, were unable to supply detailed accurate results, such as in the computation of wake fields in complex cavities. Since the advent of message-passing supercomputers with thousands of processors, earlier approximations are no longer necessary, and it is now possible to compute wake fields, the effects of dampers, and self-consistent dynamics in cavities accurately. In this environment, the focus has shifted towards the development and implementation of algorithms that scale to large numbers of processors. So-called charge-conserving algorithms evolve the electromagnetic fields without the need for any global solves (which are difficult to scale up to many processors). Using cut-cell (or embedded) boundaries, these algorithms can simulate the fields in complex accelerator cavities with curved walls. New implicit algorithms, which are stable for any time-step, conserve charge as well, allowing faster simulation of structures with details small compared to the characteristic wavelength. These algorithmic and computational advances have been implemented in the VORPAL7 Framework, a flexible, object-oriented, massively parallel computational application that allows run-time assembly of algorithms and objects, thus composing an application on the fly.

Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers

PubMed Central

Chen, Weiliang; De Schutter, Erik

2017-01-01

Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation. PMID:28239346

Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.

PubMed

Chen, Weiliang; De Schutter, Erik

2017-01-01

Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation.

Enhanced Representation of Turbulent Flow Phenomena in Large-Eddy Simulations of the Atmospheric Boundary Layer using Grid Refinement with Pseudo-Spectral Numerics

NASA Astrophysics Data System (ADS)

Torkelson, G. Q.; Stoll, R., II

2017-12-01

Large Eddy Simulation (LES) is a tool commonly used to study the turbulent transport of momentum, heat, and moisture in the Atmospheric Boundary Layer (ABL). For a wide range of ABL LES applications, representing the full range of turbulent length scales in the flow field is a challenge. This is an acute problem in regions of the ABL with strong velocity or scalar gradients, which are typically poorly resolved by standard computational grids (e.g., near the ground surface, in the entrainment zone). Most efforts to address this problem have focused on advanced sub-grid scale (SGS) turbulence model development, or on the use of massive computational resources. While some work exists using embedded meshes, very little has been done on the use of grid refinement. Here, we explore the benefits of grid refinement in a pseudo-spectral LES numerical code. The code utilizes both uniform refinement of the grid in horizontal directions, and stretching of the grid in the vertical direction. Combining the two techniques allows us to refine areas of the flow while maintaining an acceptable grid aspect ratio. In tests that used only refinement of the vertical grid spacing, large grid aspect ratios were found to cause a significant unphysical spike in the stream-wise velocity variance near the ground surface. This was especially problematic in simulations of stably-stratified ABL flows. The use of advanced SGS models was not sufficient to alleviate this issue. The new refinement technique is evaluated using a series of idealized simulation test cases of neutrally and stably stratified ABLs. These test cases illustrate the ability of grid refinement to increase computational efficiency without loss in the representation of statistical features of the flow field.

Supermassive Black Hole Binaries in High Performance Massively Parallel Direct N-body Simulations on Large GPU Clusters

NASA Astrophysics Data System (ADS)

Spurzem, R.; Berczik, P.; Zhong, S.; Nitadori, K.; Hamada, T.; Berentzen, I.; Veles, A.

2012-07-01

Astrophysical Computer Simulations of Dense Star Clusters in Galactic Nuclei with Supermassive Black Holes are presented using new cost-efficient supercomputers in China accelerated by graphical processing cards (GPU). We use large high-accuracy direct N-body simulations with Hermite scheme and block-time steps, parallelised across a large number of nodes on the large scale and across many GPU thread processors on each node on the small scale. A sustained performance of more than 350 Tflop/s for a science run on using simultaneously 1600 Fermi C2050 GPUs is reached; a detailed performance model is presented and studies for the largest GPU clusters in China with up to Petaflop/s performance and 7000 Fermi GPU cards. In our case study we look at two supermassive black holes with equal and unequal masses embedded in a dense stellar cluster in a galactic nucleus. The hardening processes due to interactions between black holes and stars, effects of rotation in the stellar system and relativistic forces between the black holes are simultaneously taken into account. The simulation stops at the complete relativistic merger of the black holes.

Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model

PubMed Central

van Albada, Sacha J.; Rowley, Andrew G.; Senk, Johanna; Hopkins, Michael; Schmidt, Maximilian; Stokes, Alan B.; Lester, David R.; Diesmann, Markus; Furber, Steve B.

2018-01-01

The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale neural network simulations in real time and with low power consumption. Real-time performance is achieved with 1 ms integration time steps, and thus applies to neural networks for which faster time scales of the dynamics can be neglected. By slowing down the simulation, shorter integration time steps and hence faster time scales, which are often biologically relevant, can be incorporated. We here describe the first full-scale simulations of a cortical microcircuit with biological time scales on SpiNNaker. Since about half the synapses onto the neurons arise within the microcircuit, larger cortical circuits have only moderately more synapses per neuron. Therefore, the full-scale microcircuit paves the way for simulating cortical circuits of arbitrary size. With approximately 80, 000 neurons and 0.3 billion synapses, this model is the largest simulated on SpiNNaker to date. The scale-up is enabled by recent developments in the SpiNNaker software stack that allow simulations to be spread across multiple boards. Comparison with simulations using the NEST software on a high-performance cluster shows that both simulators can reach a similar accuracy, despite the fixed-point arithmetic of SpiNNaker, demonstrating the usability of SpiNNaker for computational neuroscience applications with biological time scales and large network size. The runtime and power consumption are also assessed for both simulators on the example of the cortical microcircuit model. To obtain an accuracy similar to that of NEST with 0.1 ms time steps, SpiNNaker requires a slowdown factor of around 20 compared to real time. The runtime for NEST saturates around 3 times real time using hybrid parallelization with MPI and multi-threading. However, achieving this runtime comes at the cost of increased power and energy consumption. The lowest total energy consumption for NEST is reached at around 144 parallel threads and 4.6 times slowdown. At this setting, NEST and SpiNNaker have a comparable energy consumption per synaptic event. Our results widen the application domain of SpiNNaker and help guide its development, showing that further optimizations such as synapse-centric network representation are necessary to enable real-time simulation of large biological neural networks. PMID:29875620

Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation

DOE PAGES

Lu, Liqiang; Konan, Arthur; Benyahia, Sofiane

2017-06-02

Here in this paper, a bubbling fluidized bed is simulated with different numerical parameters, such as grid resolution and parcel size. We examined also the effect of using two homogeneous drag correlations and a heterogeneous drag based on the energy minimization method. A fast and reliable bubble detection algorithm was developed based on the connected component labeling. The radial and axial solids volume fraction profiles are compared with experiment data and previous simulation results. These results show a significant influence of drag models on bubble size and voidage distributions and a much less dependence on numerical parameters. With a heterogeneousmore » drag model that accounts for sub-scale structures, the void fraction in the bubbling fluidized bed can be well captured with coarse grid and large computation parcels. Refining the CFD grid and reducing the parcel size can improve the simulation results but with a large increase in computation cost.« less

Systematic methods for defining coarse-grained maps in large biomolecules.

PubMed

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy inmore » reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.« less

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations.

PubMed

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-07-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310-323. doi: 10.1002/wcms.1220.

Regularization method for large eddy simulations of shock-turbulence interactions

NASA Astrophysics Data System (ADS)

Braun, N. O.; Pullin, D. I.; Meiron, D. I.

2018-05-01

The rapid change in scales over a shock has the potential to introduce unique difficulties in Large Eddy Simulations (LES) of compressible shock-turbulence flows if the governing model does not sufficiently capture the spectral distribution of energy in the upstream turbulence. A method for the regularization of LES of shock-turbulence interactions is presented which is constructed to enforce that the energy content in the highest resolved wavenumbers decays as k - 5 / 3, and is computed locally in physical-space at low computational cost. The application of the regularization to an existing subgrid scale model is shown to remove high wavenumber errors while maintaining agreement with Direct Numerical Simulations (DNS) of forced and decaying isotropic turbulence. Linear interaction analysis is implemented to model the interaction of a shock with isotropic turbulence from LES. Comparisons to analytical models suggest that the regularization significantly improves the ability of the LES to predict amplifications in subgrid terms over the modeled shockwave. LES and DNS of decaying, modeled post shock turbulence are also considered, and inclusion of the regularization in shock-turbulence LES is shown to improve agreement with lower Reynolds number DNS.

A novel combined SLAM based on RBPF-SLAM and EIF-SLAM for mobile system sensing in a large scale environment.

PubMed

He, Bo; Zhang, Shujing; Yan, Tianhong; Zhang, Tao; Liang, Yan; Zhang, Hongjin

2011-01-01

Mobile autonomous systems are very important for marine scientific investigation and military applications. Many algorithms have been studied to deal with the computational efficiency problem required for large scale simultaneous localization and mapping (SLAM) and its related accuracy and consistency. Among these methods, submap-based SLAM is a more effective one. By combining the strength of two popular mapping algorithms, the Rao-Blackwellised particle filter (RBPF) and extended information filter (EIF), this paper presents a combined SLAM-an efficient submap-based solution to the SLAM problem in a large scale environment. RBPF-SLAM is used to produce local maps, which are periodically fused into an EIF-SLAM algorithm. RBPF-SLAM can avoid linearization of the robot model during operating and provide a robust data association, while EIF-SLAM can improve the whole computational speed, and avoid the tendency of RBPF-SLAM to be over-confident. In order to further improve the computational speed in a real time environment, a binary-tree-based decision-making strategy is introduced. Simulation experiments show that the proposed combined SLAM algorithm significantly outperforms currently existing algorithms in terms of accuracy and consistency, as well as the computing efficiency. Finally, the combined SLAM algorithm is experimentally validated in a real environment by using the Victoria Park dataset.

Development of the US3D Code for Advanced Compressible and Reacting Flow Simulations

NASA Technical Reports Server (NTRS)

Candler, Graham V.; Johnson, Heath B.; Nompelis, Ioannis; Subbareddy, Pramod K.; Drayna, Travis W.; Gidzak, Vladimyr; Barnhardt, Michael D.

2015-01-01

Aerothermodynamics and hypersonic flows involve complex multi-disciplinary physics, including finite-rate gas-phase kinetics, finite-rate internal energy relaxation, gas-surface interactions with finite-rate oxidation and sublimation, transition to turbulence, large-scale unsteadiness, shock-boundary layer interactions, fluid-structure interactions, and thermal protection system ablation and thermal response. Many of the flows have a large range of length and time scales, requiring large computational grids, implicit time integration, and large solution run times. The University of Minnesota NASA US3D code was designed for the simulation of these complex, highly-coupled flows. It has many of the features of the well-established DPLR code, but uses unstructured grids and has many advanced numerical capabilities and physical models for multi-physics problems. The main capabilities of the code are described, the physical modeling approaches are discussed, the different types of numerical flux functions and time integration approaches are outlined, and the parallelization strategy is overviewed. Comparisons between US3D and the NASA DPLR code are presented, and several advanced simulations are presented to illustrate some of novel features of the code.

Neurite, a Finite Difference Large Scale Parallel Program for the Simulation of Electrical Signal Propagation in Neurites under Mechanical Loading

PubMed Central

García-Grajales, Julián A.; Rucabado, Gabriel; García-Dopico, Antonio; Peña, José-María; Jérusalem, Antoine

2015-01-01

With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite—explicit and implicit—were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted. PMID:25680098

A simple dynamic subgrid-scale model for LES of particle-laden turbulence

NASA Astrophysics Data System (ADS)

Park, George Ilhwan; Bassenne, Maxime; Urzay, Javier; Moin, Parviz

2017-04-01

In this study, a dynamic model for large-eddy simulations is proposed in order to describe the motion of small inertial particles in turbulent flows. The model is simple, involves no significant computational overhead, contains no adjustable parameters, and is flexible enough to be deployed in any type of flow solvers and grids, including unstructured setups. The approach is based on the use of elliptic differential filters to model the subgrid-scale velocity. The only model parameter, which is related to the nominal filter width, is determined dynamically by imposing consistency constraints on the estimated subgrid energetics. The performance of the model is tested in large-eddy simulations of homogeneous-isotropic turbulence laden with particles, where improved agreement with direct numerical simulation results is observed in the dispersed-phase statistics, including particle acceleration, local carrier-phase velocity, and preferential-concentration metrics.

Adjoint-based Simultaneous Estimation Method of Fault Slip and Asthenosphere Viscosity Using Large-Scale Finite Element Simulation of Viscoelastic Deformation

NASA Astrophysics Data System (ADS)

Agata, R.; Ichimura, T.; Hori, T.; Hirahara, K.; Hashimoto, C.; Hori, M.

2016-12-01

Estimation of the coseismic/postseismic slip using postseismic deformation observation data is an important topic in the field of geodetic inversion. Estimation methods for this purpose are expected to be improved by introducing numerical simulation tools (e.g. finite element (FE) method) of viscoelastic deformation, in which the computation model is of high fidelity to the available high-resolution crustal data. The authors have proposed a large-scale simulation method using such FE high-fidelity models (HFM), assuming use of a large-scale computation environment such as the K computer in Japan (Ichimura et al. 2016). On the other hand, the values of viscosity in the heterogeneous viscoelastic structure in the high-fidelity model are not trivial. In this study, we developed an adjoint-based optimization method incorporating HFM, in which fault slip and asthenosphere viscosity are simultaneously estimated. We carried out numerical experiments using synthetic crustal deformation data. We constructed an HFM in the domain of 2048x1536x850 km, which includes the Tohoku region in northeast Japan based on Ichimura et al. (2013). We used the model geometry data set of JTOPO30 (2003), Koketsu et al. (2008) and CAMP standard model (Hashimoto et al. 2004). The geometry of crustal structures in HFM is in 1km resolution, resulting in 36 billion degrees-of-freedom. Synthetic crustal deformation data due to prescribed coseismic slip and after slips in the location of GEONET, GPS/A observation points, and S-net are used. The target inverse analysis is formulated as minimization of L2 norm of the difference between the FE simulation results and the observation data with respect to viscosity and fault slip, combining the quasi-Newton algorithm with the adjoint method. Use of this combination decreases the necessary number of forward analyses in the optimization calculation. As a result, we are now able to finish the estimation using 2560 computer nodes of the K computer for less than 17 hours. Thus, the target inverse analysis is completed in a realistic time because of the combination of the fast solver and the adjoint method. In the future, we would like to apply the method to the actual data.

Visualization of the Eastern Renewable Generation Integration Study: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gruchalla, Kenny; Novacheck, Joshua; Bloom, Aaron

The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in the U.S. Eastern Interconnection and Quebec Interconnection (collectively, EI). In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and PV generation, we developed state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NREL's high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated withmore » evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions. state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NRELs high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions.« less

A scalable moment-closure approximation for large-scale biochemical reaction networks

PubMed Central

Kazeroonian, Atefeh; Theis, Fabian J.; Hasenauer, Jan

2017-01-01

Abstract Motivation: Stochastic molecular processes are a leading cause of cell-to-cell variability. Their dynamics are often described by continuous-time discrete-state Markov chains and simulated using stochastic simulation algorithms. As these stochastic simulations are computationally demanding, ordinary differential equation models for the dynamics of the statistical moments have been developed. The number of state variables of these approximating models, however, grows at least quadratically with the number of biochemical species. This limits their application to small- and medium-sized processes. Results: In this article, we present a scalable moment-closure approximation (sMA) for the simulation of statistical moments of large-scale stochastic processes. The sMA exploits the structure of the biochemical reaction network to reduce the covariance matrix. We prove that sMA yields approximating models whose number of state variables depends predominantly on local properties, i.e. the average node degree of the reaction network, instead of the overall network size. The resulting complexity reduction is assessed by studying a range of medium- and large-scale biochemical reaction networks. To evaluate the approximation accuracy and the improvement in computational efficiency, we study models for JAK2/STAT5 signalling and NFκB signalling. Our method is applicable to generic biochemical reaction networks and we provide an implementation, including an SBML interface, which renders the sMA easily accessible. Availability and implementation: The sMA is implemented in the open-source MATLAB toolbox CERENA and is available from https://github.com/CERENADevelopers/CERENA. Contact: jan.hasenauer@helmholtz-muenchen.de or atefeh.kazeroonian@tum.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881983

Advances and issues from the simulation of planetary magnetospheres with recent supercomputer systems

NASA Astrophysics Data System (ADS)

Fukazawa, K.; Walker, R. J.; Kimura, T.; Tsuchiya, F.; Murakami, G.; Kita, H.; Tao, C.; Murata, K. T.

2016-12-01

Planetary magnetospheres are very large, while phenomena within them occur on meso- and micro-scales. These scales range from 10s of planetary radii to kilometers. To understand dynamics in these multi-scale systems, numerical simulations have been performed by using the supercomputer systems. We have studied the magnetospheres of Earth, Jupiter and Saturn by using 3-dimensional magnetohydrodynamic (MHD) simulations for a long time, however, we have not obtained the phenomena near the limits of the MHD approximation. In particular, we have not studied meso-scale phenomena that can be addressed by using MHD.Recently we performed our MHD simulation of Earth's magnetosphere by using the K-computer which is the first 10PFlops supercomputer and obtained multi-scale flow vorticity for the both northward and southward IMF. Furthermore, we have access to supercomputer systems which have Xeon, SPARC64, and vector-type CPUs and can compare simulation results between the different systems. Finally, we have compared the results of our parameter survey of the magnetosphere with observations from the HISAKI spacecraft.We have encountered a number of difficulties effectively using the latest supercomputer systems. First the size of simulation output increases greatly. Now a simulation group produces over 1PB of output. Storage and analysis of this much data is difficult. The traditional way to analyze simulation results is to move the results to the investigator's home computer. This takes over three months using an end-to-end 10Gbps network. In reality, there are problems at some nodes such as firewalls that can increase the transfer time to over one year. Another issue is post-processing. It is hard to treat a few TB of simulation output due to the memory limitations of a post-processing computer. To overcome these issues, we have developed and introduced the parallel network storage, the highly efficient network protocol and the CUI based visualization tools.In this study, we will show the latest simulation results using the petascale supercomputer and problems from the use of these supercomputer systems.

Multi-fidelity methods for uncertainty quantification in transport problems

NASA Astrophysics Data System (ADS)

Tartakovsky, G.; Yang, X.; Tartakovsky, A. M.; Barajas-Solano, D. A.; Scheibe, T. D.; Dai, H.; Chen, X.

2016-12-01

We compare several multi-fidelity approaches for uncertainty quantification in flow and transport simulations that have a lower computational cost than the standard Monte Carlo method. The cost reduction is achieved by combining a small number of high-resolution (high-fidelity) simulations with a large number of low-resolution (low-fidelity) simulations. We propose a new method, a re-scaled Multi Level Monte Carlo (rMLMC) method. The rMLMC is based on the idea that the statistics of quantities of interest depends on scale/resolution. We compare rMLMC with existing multi-fidelity methods such as Multi Level Monte Carlo (MLMC) and reduced basis methods and discuss advantages of each approach.

Computer code for the prediction of nozzle admittance

NASA Technical Reports Server (NTRS)

Nguyen, Thong V.

1988-01-01

A procedure which can accurately characterize injector designs for large thrust (0.5 to 1.5 million pounds), high pressure (500 to 3000 psia) LOX/hydrocarbon engines is currently under development. In this procedure, a rectangular cross-sectional combustion chamber is to be used to simulate the lower traverse frequency modes of the large scale chamber. The chamber will be sized so that the first width mode of the rectangular chamber corresponds to the first tangential mode of the full-scale chamber. Test data to be obtained from the rectangular chamber will be used to assess the full scale engine stability. This requires the development of combustion stability models for rectangular chambers. As part of the combustion stability model development, a computer code, NOAD based on existing theory was developed to calculate the nozzle admittances for both rectangular and axisymmetric nozzles. This code is detailed.

Canopy BRF simulation of forest with different crown shape and height in larger scale based on Radiosity method

NASA Astrophysics Data System (ADS)

Song, Jinling; Qu, Yonghua; Wang, Jindi; Wan, Huawei; Liu, Xiaoqing

2007-06-01

Radiosity method is based on the computer simulation of 3D real structures of vegetations, such as leaves, branches and stems, which are composed by many facets. Using this method we can simulate the canopy reflectance and its bidirectional distribution of the vegetation canopy in visible and NIR regions. But with vegetations are more complex, more facets to compose them, so large memory and lots of time to calculate view factors are required, which are the choke points of using Radiosity method to calculate canopy BRF of lager scale vegetation scenes. We derived a new method to solve the problem, and the main idea is to abstract vegetation crown shapes and to simplify their structures, which can lessen the number of facets. The facets are given optical properties according to the reflectance, transmission and absorption of the real structure canopy. Based on the above work, we can simulate the canopy BRF of the mix scenes with different species vegetation in the large scale. In this study, taking broadleaf trees as an example, based on their structure characteristics, we abstracted their crowns as ellipsoid shells, and simulated the canopy BRF in visible and NIR regions of the large scale scene with different crown shape and different height ellipsoids. Form this study, we can conclude: LAI, LAD the probability gap, the sunlit and shaded surfaces are more important parameter to simulate the simplified vegetation canopy BRF. And the Radiosity method can apply us canopy BRF data in any conditions for our research.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations

PubMed Central

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the–server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models. PMID:27806061

Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatterjee, Abhijit; Vlachos, Dionisios G.

The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less

Computational biology in the cloud: methods and new insights from computing at scale.

PubMed

Kasson, Peter M

2013-01-01

The past few years have seen both explosions in the size of biological data sets and the proliferation of new, highly flexible on-demand computing capabilities. The sheer amount of information available from genomic and metagenomic sequencing, high-throughput proteomics, experimental and simulation datasets on molecular structure and dynamics affords an opportunity for greatly expanded insight, but it creates new challenges of scale for computation, storage, and interpretation of petascale data. Cloud computing resources have the potential to help solve these problems by offering a utility model of computing and storage: near-unlimited capacity, the ability to burst usage, and cheap and flexible payment models. Effective use of cloud computing on large biological datasets requires dealing with non-trivial problems of scale and robustness, since performance-limiting factors can change substantially when a dataset grows by a factor of 10,000 or more. New computing paradigms are thus often needed. The use of cloud platforms also creates new opportunities to share data, reduce duplication, and to provide easy reproducibility by making the datasets and computational methods easily available.

Large Eddy Simulation of jets laden with evaporating drops

NASA Technical Reports Server (NTRS)

Leboissetier, A.; Okong'o, N.; Bellan, J.

2004-01-01

LES of a circular jet laden with evaporating liquid drops are conducted to assess computational-drop modeling and three different SGS-flux models: the Scale Similarity model (SSC), using a constant coefficient calibrated on a temporal mixing layer DNS database, and dynamic-coefficient Gradient and Smagorinsky models.

Trapped-Ion Quantum Logic with Global Radiation Fields.

PubMed

Weidt, S; Randall, J; Webster, S C; Lake, K; Webb, A E; Cohen, I; Navickas, T; Lekitsch, B; Retzker, A; Hensinger, W K

2016-11-25

Trapped ions are a promising tool for building a large-scale quantum computer. However, the number of required radiation fields for the realization of quantum gates in any proposed ion-based architecture scales with the number of ions within the quantum computer, posing a major obstacle when imagining a device with millions of ions. Here, we present a fundamentally different approach for trapped-ion quantum computing where this detrimental scaling vanishes. The method is based on individually controlled voltages applied to each logic gate location to facilitate the actual gate operation analogous to a traditional transistor architecture within a classical computer processor. To demonstrate the key principle of this approach we implement a versatile quantum gate method based on long-wavelength radiation and use this method to generate a maximally entangled state of two quantum engineered clock qubits with fidelity 0.985(12). This quantum gate also constitutes a simple-to-implement tool for quantum metrology, sensing, and simulation.

Turbulence modeling for Francis turbine water passages simulation

NASA Astrophysics Data System (ADS)

Maruzewski, P.; Hayashi, H.; Munch, C.; Yamaishi, K.; Hashii, T.; Mombelli, H. P.; Sugow, Y.; Avellan, F.

2010-08-01

The applications of Computational Fluid Dynamics, CFD, to hydraulic machines life require the ability to handle turbulent flows and to take into account the effects of turbulence on the mean flow. Nowadays, Direct Numerical Simulation, DNS, is still not a good candidate for hydraulic machines simulations due to an expensive computational time consuming. Large Eddy Simulation, LES, even, is of the same category of DNS, could be an alternative whereby only the small scale turbulent fluctuations are modeled and the larger scale fluctuations are computed directly. Nevertheless, the Reynolds-Averaged Navier-Stokes, RANS, model have become the widespread standard base for numerous hydraulic machine design procedures. However, for many applications involving wall-bounded flows and attached boundary layers, various hybrid combinations of LES and RANS are being considered, such as Detached Eddy Simulation, DES, whereby the RANS approximation is kept in the regions where the boundary layers are attached to the solid walls. Furthermore, the accuracy of CFD simulations is highly dependent on the grid quality, in terms of grid uniformity in complex configurations. Moreover any successful structured and unstructured CFD codes have to offer a wide range to the variety of classic RANS model to hybrid complex model. The aim of this study is to compare the behavior of turbulent simulations for both structured and unstructured grids topology with two different CFD codes which used the same Francis turbine. Hence, the study is intended to outline the encountered discrepancy for predicting the wake of turbine blades by using either the standard k-epsilon model, or the standard k-epsilon model or the SST shear stress model in a steady CFD simulation. Finally, comparisons are made with experimental data from the EPFL Laboratory for Hydraulic Machines reduced scale model measurements.

3-D imaging of large scale buried structure by 1-D inversion of very early time electromagnetic (VETEM) data

USGS Publications Warehouse

Aydmer, A.A.; Chew, W.C.; Cui, T.J.; Wright, D.L.; Smith, D.V.; Abraham, J.D.

2001-01-01

A simple and efficient method for large scale three-dimensional (3-D) subsurface imaging of inhomogeneous background is presented. One-dimensional (1-D) multifrequency distorted Born iterative method (DBIM) is employed in the inversion. Simulation results utilizing synthetic scattering data are given. Calibration of the very early time electromagnetic (VETEM) experimental waveforms is detailed along with major problems encountered in practice and their solutions. This discussion is followed by the results of a large scale application of the method to the experimental data provided by the VETEM system of the U.S. Geological Survey. The method is shown to have a computational complexity that is promising for on-site inversion.

A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing

PubMed Central

Li, Zhixin; Su, Dandan; Zhu, Haijiang; Li, Wei; Zhang, Fan; Li, Ruirui

2017-01-01

Synthetic Aperture Radar (SAR) raw data simulation is a fundamental problem in radar system design and imaging algorithm research. The growth of surveying swath and resolution results in a significant increase in data volume and simulation period, which can be considered to be a comprehensive data intensive and computing intensive issue. Although several high performance computing (HPC) methods have demonstrated their potential for accelerating simulation, the input/output (I/O) bottleneck of huge raw data has not been eased. In this paper, we propose a cloud computing based SAR raw data simulation algorithm, which employs the MapReduce model to accelerate the raw data computing and the Hadoop distributed file system (HDFS) for fast I/O access. The MapReduce model is designed for the irregular parallel accumulation of raw data simulation, which greatly reduces the parallel efficiency of graphics processing unit (GPU) based simulation methods. In addition, three kinds of optimization strategies are put forward from the aspects of programming model, HDFS configuration and scheduling. The experimental results show that the cloud computing based algorithm achieves 4× speedup over the baseline serial approach in an 8-node cloud environment, and each optimization strategy can improve about 20%. This work proves that the proposed cloud algorithm is capable of solving the computing intensive and data intensive issues in SAR raw data simulation, and is easily extended to large scale computing to achieve higher acceleration. PMID:28075343

Cross-flow turbines: progress report on physical and numerical model studies at large laboratory scale

NASA Astrophysics Data System (ADS)

Wosnik, Martin; Bachant, Peter

2016-11-01

Cross-flow turbines show potential in marine hydrokinetic (MHK) applications. A research focus is on accurately predicting device performance and wake evolution to improve turbine array layouts for maximizing overall power output, i.e., minimizing wake interference, or taking advantage of constructive wake interaction. Experiments were carried with large laboratory-scale cross-flow turbines D O (1 m) using a turbine test bed in a large cross-section tow tank, designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. Several turbines of varying solidity were employed, including the UNH Reference Vertical Axis Turbine (RVAT) and a 1:6 scale model of the DOE-Sandia Reference Model 2 (RM2) turbine. To improve parameterization in array simulations, an actuator line model (ALM) was developed to provide a computationally feasible method for simulating full turbine arrays inside Navier-Stokes models. Results are presented for the simulation of performance and wake dynamics of cross-flow turbines and compared with experiments and body-fitted mesh, blade-resolving CFD. Supported by NSF-CBET Grant 1150797, Sandia National Laboratories.

Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials.

PubMed

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun; Wang, Bei; Bremer, Peer-Timo; Papka, Michael E; Curtiss, Larry A; Pascucci, Valerio

2016-01-01

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermally annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.

Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun

2016-01-01

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermallymore » annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.« less

Interstitial and interlayer ion diffusion geometry extraction in graphitic nanosphere battery materials

DOE PAGES

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun; ...

2016-01-31

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermallymore » annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Lastly, our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.« less

An immersed boundary method for direct and large eddy simulation of stratified flows in complex geometry

NASA Astrophysics Data System (ADS)

Rapaka, Narsimha R.; Sarkar, Sutanu

2016-10-01

A sharp-interface Immersed Boundary Method (IBM) is developed to simulate density-stratified turbulent flows in complex geometry using a Cartesian grid. The basic numerical scheme corresponds to a central second-order finite difference method, third-order Runge-Kutta integration in time for the advective terms and an alternating direction implicit (ADI) scheme for the viscous and diffusive terms. The solver developed here allows for both direct numerical simulation (DNS) and large eddy simulation (LES) approaches. Methods to enhance the mass conservation and numerical stability of the solver to simulate high Reynolds number flows are discussed. Convergence with second-order accuracy is demonstrated in flow past a cylinder. The solver is validated against past laboratory and numerical results in flow past a sphere, and in channel flow with and without stratification. Since topographically generated internal waves are believed to result in a substantial fraction of turbulent mixing in the ocean, we are motivated to examine oscillating tidal flow over a triangular obstacle to assess the ability of this computational model to represent nonlinear internal waves and turbulence. Results in laboratory-scale (order of few meters) simulations show that the wave energy flux, mean flow properties and turbulent kinetic energy agree well with our previous results obtained using a body-fitted grid (BFG). The deviation of IBM results from BFG results is found to increase with increasing nonlinearity in the wave field that is associated with either increasing steepness of the topography relative to the internal wave propagation angle or with the amplitude of the oscillatory forcing. LES is performed on a large scale ridge, of the order of few kilometers in length, that has the same geometrical shape and same non-dimensional values for the governing flow and environmental parameters as the laboratory-scale topography, but significantly larger Reynolds number. A non-linear drag law is utilized in the large-scale application to parameterize turbulent losses due to bottom friction at high Reynolds number. The large scale problem exhibits qualitatively similar behavior to the laboratory scale problem with some differences: slightly larger intensification of the boundary flow and somewhat higher non-dimensional values for the energy fluxed away by the internal wave field. The phasing of wave breaking and turbulence exhibits little difference between small-scale and large-scale obstacles as long as the important non-dimensional parameters are kept the same. We conclude that IBM is a viable approach to the simulation of internal waves and turbulence in high Reynolds number stratified flows over topography.

Nested high-resolution large-eddy simulations in WRF to support wind power

NASA Astrophysics Data System (ADS)

Mirocha, J.; Kirkil, G.; Kosovic, B.; Lundquist, J. K.

2009-12-01

The WRF model’s grid nesting capability provides a potentially powerful framework for simulating flow over a wide range of scales. One such application is computation of realistic inflow boundary conditions for large eddy simulations (LES) by nesting LES domains within mesoscale domains. While nesting has been widely and successfully applied at GCM to mesoscale resolutions, the WRF model’s nesting behavior at the high-resolution (Δx < 1000m) end of the spectrum is less well understood. Nesting LES within msoscale domains can significantly improve turbulent flow prediction at the scale of a wind park, providing a basis for superior site characterization, or for improved simulation of turbulent inflows encountered by turbines. We investigate WRF’s grid nesting capability at high mesh resolutions using nested mesoscale and large-eddy simulations. We examine the spatial scales required for flow structures to equilibrate to the finer mesh as flow enters a nest, and how the process depends on several parameters, including grid resolution, turbulence subfilter stress models, relaxation zones at nest interfaces, flow velocities, surface roughnesses, terrain complexity and atmospheric stability. Guidance on appropriate domain sizes and turbulence models for LES in light of these results is provided This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 LLNL-ABS-416482

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1991-01-01

This paper concerns the suppression of the vibration of a large flexible robot by inertial forces of a small robot which is located at the tip of the large robot. A controller for generating damping forces to a large robot is designed based on the two time scale model. The controller does not need to calculate the quasi-steady variables and is efficient in computation. Simulation results show the effectiveness of the inertial forces and the controller designed.

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1989-01-01

The suppression is examined of the vibration of a large flexible robot by inertial forces of a small robot which is located at the tip of the large robot. A controller for generating damping forces to a large robot is designed based on the two time scale mode. The controller does not need to calculate the quasi-steady state variables and is efficient in computation. Simulation results show the effectiveness of the inertial forces and the controller designed.

A Coherent vorticity preserving eddy-viscosity correction for Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Chapelier, J.-B.; Wasistho, B.; Scalo, C.

2018-04-01

This paper introduces a new approach to Large-Eddy Simulation (LES) where subgrid-scale (SGS) dissipation is applied proportionally to the degree of local spectral broadening, hence mitigated or deactivated in regions dominated by large-scale and/or laminar vortical motion. The proposed coherent-vorticity preserving (CvP) LES methodology is based on the evaluation of the ratio of the test-filtered to resolved (or grid-filtered) enstrophy, σ. Values of σ close to 1 indicate low sub-test-filter turbulent activity, justifying local deactivation of the SGS dissipation. The intensity of the SGS dissipation is progressively increased for σ < 1 which corresponds to a small-scale spectral broadening. The SGS dissipation is then fully activated in developed turbulence characterized by σ ≤σeq, where the value σeq is derived assuming a Kolmogorov spectrum. The proposed approach can be applied to any eddy-viscosity model, is algorithmically simple and computationally inexpensive. LES of Taylor-Green vortex breakdown demonstrates that the CvP methodology improves the performance of traditional, non-dynamic dissipative SGS models, capturing the peak of total turbulent kinetic energy dissipation during transition. Similar accuracy is obtained by adopting Germano's dynamic procedure albeit at more than twice the computational overhead. A CvP-LES of a pair of unstable periodic helical vortices is shown to predict accurately the experimentally observed growth rate using coarse resolutions. The ability of the CvP methodology to dynamically sort the coherent, large-scale motion from the smaller, broadband scales during transition is demonstrated via flow visualizations. LES of compressible channel are carried out and show a good match with a reference DNS.

Implementation of highly parallel and large scale GW calculations within the OpenAtom software

NASA Astrophysics Data System (ADS)

Ismail-Beigi, Sohrab

The need to describe electronic excitations with better accuracy than provided by band structures produced by Density Functional Theory (DFT) has been a long-term enterprise for the computational condensed matter and materials theory communities. In some cases, appropriate theoretical frameworks have existed for some time but have been difficult to apply widely due to computational cost. For example, the GW approximation incorporates a great deal of important non-local and dynamical electronic interaction effects but has been too computationally expensive for routine use in large materials simulations. OpenAtom is an open source massively parallel ab initiodensity functional software package based on plane waves and pseudopotentials (http://charm.cs.uiuc.edu/OpenAtom/) that takes advantage of the Charm + + parallel framework. At present, it is developed via a three-way collaboration, funded by an NSF SI2-SSI grant (ACI-1339804), between Yale (Ismail-Beigi), IBM T. J. Watson (Glenn Martyna) and the University of Illinois at Urbana Champaign (Laxmikant Kale). We will describe the project and our current approach towards implementing large scale GW calculations with OpenAtom. Potential applications of large scale parallel GW software for problems involving electronic excitations in semiconductor and/or metal oxide systems will be also be pointed out.

Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease.

PubMed

Randles, Amanda; Frakes, David H; Leopold, Jane A

2017-11-01

Noninvasive engineering models are now being used for diagnosing and planning the treatment of cardiovascular disease. Techniques in computational modeling and additive manufacturing have matured concurrently, and results from simulations can inform and enable the design and optimization of therapeutic devices and treatment strategies. The emerging synergy between large-scale simulations and 3D printing is having a two-fold benefit: first, 3D printing can be used to validate the complex simulations, and second, the flow models can be used to improve treatment planning for cardiovascular disease. In this review, we summarize and discuss recent methods and findings for leveraging advances in both additive manufacturing and patient-specific computational modeling, with an emphasis on new directions in these fields and remaining open questions. Copyright © 2017 Elsevier Ltd. All rights reserved.

MOOSE: A parallel computational framework for coupled systems of nonlinear equations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Derek Gaston; Chris Newman; Glen Hansen

Systems of coupled, nonlinear partial differential equations (PDEs) often arise in simulation of nuclear processes. MOOSE: Multiphysics Object Oriented Simulation Environment, a parallel computational framework targeted at the solution of such systems, is presented. As opposed to traditional data-flow oriented computational frameworks, MOOSE is instead founded on the mathematical principle of Jacobian-free Newton-Krylov (JFNK) solution methods. Utilizing the mathematical structure present in JFNK, physics expressions are modularized into `Kernels,'' allowing for rapid production of new simulation tools. In addition, systems are solved implicitly and fully coupled, employing physics based preconditioning, which provides great flexibility even with large variance in timemore » scales. A summary of the mathematics, an overview of the structure of MOOSE, and several representative solutions from applications built on the framework are presented.« less

The Neurona at Home project: Simulating a large-scale cellular automata brain in a distributed computing environment

NASA Astrophysics Data System (ADS)

Acedo, L.; Villanueva-Oller, J.; Moraño, J. A.; Villanueva, R.-J.

2013-01-01

The Berkeley Open Infrastructure for Network Computing (BOINC) has become the standard open source solution for grid computing in the Internet. Volunteers use their computers to complete an small part of the task assigned by a dedicated server. We have developed a BOINC project called Neurona@Home whose objective is to simulate a cellular automata random network with, at least, one million neurons. We consider a cellular automata version of the integrate-and-fire model in which excitatory and inhibitory nodes can activate or deactivate neighbor nodes according to a set of probabilistic rules. Our aim is to determine the phase diagram of the model and its behaviour and to compare it with the electroencephalographic signals measured in real brains.

Tackling some of the most intricate geophysical challenges via high-performance computing

NASA Astrophysics Data System (ADS)

Khosronejad, A.

2016-12-01

Recently, world has been witnessing significant enhancements in computing power of supercomputers. Computer clusters in conjunction with the advanced mathematical algorithms has set the stage for developing and applying powerful numerical tools to tackle some of the most intricate geophysical challenges that today`s engineers face. One such challenge is to understand how turbulent flows, in real-world settings, interact with (a) rigid and/or mobile complex bed bathymetry of waterways and sea-beds in the coastal areas; (b) objects with complex geometry that are fully or partially immersed; and (c) free-surface of waterways and water surface waves in the coastal area. This understanding is especially important because the turbulent flows in real-world environments are often bounded by geometrically complex boundaries, which dynamically deform and give rise to multi-scale and multi-physics transport phenomena, and characterized by multi-lateral interactions among various phases (e.g. air/water/sediment phases). Herein, I present some of the multi-scale and multi-physics geophysical fluid mechanics processes that I have attempted to study using an in-house high-performance computational model, the so-called VFS-Geophysics. More specifically, I will present the simulation results of turbulence/sediment/solute/turbine interactions in real-world settings. Parts of the simulations I present are performed to gain scientific insights into the processes such as sand wave formation (A. Khosronejad, and F. Sotiropoulos, (2014), Numerical simulation of sand waves in a turbulent open channel flow, Journal of Fluid Mechanics, 753:150-216), while others are carried out to predict the effects of climate change and large flood events on societal infrastructures ( A. Khosronejad, et al., (2016), Large eddy simulation of turbulence and solute transport in a forested headwater stream, Journal of Geophysical Research:, doi: 10.1002/2014JF003423).

NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations

NASA Astrophysics Data System (ADS)

Valiev, M.; Bylaska, E. J.; Govind, N.; Kowalski, K.; Straatsma, T. P.; Van Dam, H. J. J.; Wang, D.; Nieplocha, J.; Apra, E.; Windus, T. L.; de Jong, W. A.

2010-09-01

The latest release of NWChem delivers an open-source computational chemistry package with extensive capabilities for large scale simulations of chemical and biological systems. Utilizing a common computational framework, diverse theoretical descriptions can be used to provide the best solution for a given scientific problem. Scalable parallel implementations and modular software design enable efficient utilization of current computational architectures. This paper provides an overview of NWChem focusing primarily on the core theoretical modules provided by the code and their parallel performance. Program summaryProgram title: NWChem Catalogue identifier: AEGI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGI_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Open Source Educational Community License No. of lines in distributed program, including test data, etc.: 11 709 543 No. of bytes in distributed program, including test data, etc.: 680 696 106 Distribution format: tar.gz Programming language: Fortran 77, C Computer: all Linux based workstations and parallel supercomputers, Windows and Apple machines Operating system: Linux, OS X, Windows Has the code been vectorised or parallelized?: Code is parallelized Classification: 2.1, 2.2, 3, 7.3, 7.7, 16.1, 16.2, 16.3, 16.10, 16.13 Nature of problem: Large-scale atomistic simulations of chemical and biological systems require efficient and reliable methods for ground and excited solutions of many-electron Hamiltonian, analysis of the potential energy surface, and dynamics. Solution method: Ground and excited solutions of many-electron Hamiltonian are obtained utilizing density-functional theory, many-body perturbation approach, and coupled cluster expansion. These solutions or a combination thereof with classical descriptions are then used to analyze potential energy surface and perform dynamical simulations. Additional comments: Full documentation is provided in the distribution file. This includes an INSTALL file giving details of how to build the package. A set of test runs is provided in the examples directory. The distribution file for this program is over 90 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. Running time: Running time depends on the size of the chemical system, complexity of the method, number of cpu's and the computational task. It ranges from several seconds for serial DFT energy calculations on a few atoms to several hours for parallel coupled cluster energy calculations on tens of atoms or ab-initio molecular dynamics simulation on hundreds of atoms.

Characterization of Sound Radiation by Unresolved Scales of Motion in Computational Aeroacoustics

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Zhou, Ye

1999-01-01

Evaluation of the sound sources in a high Reynolds number turbulent flow requires time-accurate resolution of an extremely large number of scales of motion. Direct numerical simulations will therefore remain infeasible for the forseeable future: although current large eddy simulation methods can resolve the largest scales of motion accurately the, they must leave some scales of motion unresolved. A priori studies show that acoustic power can be underestimated significantly if the contribution of these unresolved scales is simply neglected. In this paper, the problem of evaluating the sound radiation properties of the unresolved, subgrid-scale motions is approached in the spirit of the simplest subgrid stress models: the unresolved velocity field is treated as isotropic turbulence with statistical descriptors, evaluated from the resolved field. The theory of isotropic turbulence is applied to derive formulas for the total power and the power spectral density of the sound radiated by a filtered velocity field. These quantities are compared with the corresponding quantities for the unfiltered field for a range of filter widths and Reynolds numbers.

The accurate particle tracer code

DOE PAGES

Wang, Yulei; Liu, Jian; Qin, Hong; ...

2017-07-20

The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runawaymore » electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world’s fastest computer, the Sunway TaihuLight supercomputer, by supporting master–slave architecture of Sunway many-core processors. Here, based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.« less

The accurate particle tracer code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Yulei; Liu, Jian; Qin, Hong

The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runawaymore » electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world’s fastest computer, the Sunway TaihuLight supercomputer, by supporting master–slave architecture of Sunway many-core processors. Here, based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.« less

Concurrent processing simulation of the space station

NASA Technical Reports Server (NTRS)

Gluck, R.; Hale, A. L.; Sunkel, John W.

1989-01-01

The development of a new capability for the time-domain simulation of multibody dynamic systems and its application to the study of a large angle rotational maneuvers of the Space Station is described. The effort was divided into three sequential tasks, which required significant advancements of the state-of-the art to accomplish. These were: (1) the development of an explicit mathematical model via symbol manipulation of a flexible, multibody dynamic system; (2) the development of a methodology for balancing the computational load of an explicit mathematical model for concurrent processing; and (3) the implementation and successful simulation of the above on a prototype Custom Architectured Parallel Processing System (CAPPS) containing eight processors. The throughput rate achieved by the CAPPS operating at only 70 percent efficiency, was 3.9 times greater than that obtained sequentially by the IBM 3090 supercomputer simulating the same problem. More significantly, analysis of the results leads to the conclusion that the relative cost effectiveness of concurrent vs. sequential digital computation will grow substantially as the computational load is increased. This is a welcomed development in an era when very complex and cumbersome mathematical models of large space vehicles must be used as substitutes for full scale testing which has become impractical.

High resolution global flood hazard map from physically-based hydrologic and hydraulic models.

NASA Astrophysics Data System (ADS)

Begnudelli, L.; Kaheil, Y.; McCollum, J.

2017-12-01

The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak corresponds to the return period corresponding to the hazard map being produced (e.g. 100 years, 500 years). Each numerical simulation models one river reach, except for the longest reaches which are split in smaller parts. Here we show results for selected river basins worldwide.

An Implicit Solver on A Parallel Block-Structured Adaptive Mesh Grid for FLASH

NASA Astrophysics Data System (ADS)

Lee, D.; Gopal, S.; Mohapatra, P.

2012-07-01

We introduce a fully implicit solver for FLASH based on a Jacobian-Free Newton-Krylov (JFNK) approach with an appropriate preconditioner. The main goal of developing this JFNK-type implicit solver is to provide efficient high-order numerical algorithms and methodology for simulating stiff systems of differential equations on large-scale parallel computer architectures. A large number of natural problems in nonlinear physics involve a wide range of spatial and time scales of interest. A system that encompasses such a wide magnitude of scales is described as "stiff." A stiff system can arise in many different fields of physics, including fluid dynamics/aerodynamics, laboratory/space plasma physics, low Mach number flows, reactive flows, radiation hydrodynamics, and geophysical flows. One of the big challenges in solving such a stiff system using current-day computational resources lies in resolving time and length scales varying by several orders of magnitude. We introduce FLASH's preliminary implementation of a time-accurate JFNK-based implicit solver in the framework of FLASH's unsplit hydro solver.

Large-scale structure non-Gaussianities with modal methods

NASA Astrophysics Data System (ADS)

Schmittfull, Marcel

2016-10-01

Relying on a separable modal expansion of the bispectrum, the implementation of a fast estimator for the full bispectrum of a 3d particle distribution is presented. The computational cost of accurate bispectrum estimation is negligible relative to simulation evolution, so the bispectrum can be used as a standard diagnostic whenever the power spectrum is evaluated. As an application, the time evolution of gravitational and primordial dark matter bispectra was measured in a large suite of N-body simulations. The bispectrum shape changes characteristically when the cosmic web becomes dominated by filaments and halos, therefore providing a quantitative probe of 3d structure formation. Our measured bispectra are determined by ~ 50 coefficients, which can be used as fitting formulae in the nonlinear regime and for non-Gaussian initial conditions. We also compare the measured bispectra with predictions from the Effective Field Theory of Large Scale Structures (EFTofLSS).

Numerically modelling the large scale coronal magnetic field

NASA Astrophysics Data System (ADS)

Panja, Mayukh; Nandi, Dibyendu

2016-07-01

The solar corona spews out vast amounts of magnetized plasma into the heliosphere which has a direct impact on the Earth's magnetosphere. Thus it is important that we develop an understanding of the dynamics of the solar corona. With our present technology it has not been possible to generate 3D magnetic maps of the solar corona; this warrants the use of numerical simulations to study the coronal magnetic field. A very popular method of doing this, is to extrapolate the photospheric magnetic field using NLFF or PFSS codes. However the extrapolations at different time intervals are completely independent of each other and do not capture the temporal evolution of magnetic fields. On the other hand full MHD simulations of the global coronal field, apart from being computationally very expensive would be physically less transparent, owing to the large number of free parameters that are typically used in such codes. This brings us to the Magneto-frictional model which is relatively simpler and computationally more economic. We have developed a Magnetofrictional Model, in 3D spherical polar co-ordinates to study the large scale global coronal field. Here we present studies of changing connectivities between active regions, in response to photospheric motions.

Modeling Large Scale Circuits Using Massively Parallel Descrete-Event Simulation

DTIC Science & Technology

2013-06-01

exascale levels of performance, the smallest elements of a single processor can greatly affect the entire computer system (e.g. its power consumption...grow to exascale levels of performance, the smallest elements of a single processor can greatly affect the entire computer system (e.g. its power...Warp Speed 10.0. 2.0 INTRODUCTION As supercomputer systems approach exascale , the core count will exceed 1024 and number of transistors used in

YF-12 cooperative airframe/propulsion control system program, volume 1

NASA Technical Reports Server (NTRS)

Anderson, D. L.; Connolly, G. F.; Mauro, F. M.; Reukauf, P. J.; Marks, R. (Editor)

1980-01-01

Several YF-12C airplane analog control systems were converted to a digital system. Included were the air data computer, autopilot, inlet control system, and autothrottle systems. This conversion was performed to allow assessment of digital technology applications to supersonic cruise aircraft. The digital system was composed of a digital computer and specialized interface unit. A large scale mathematical simulation of the airplane was used for integration testing and software checkout.

Requirements for Large Eddy Simulation Computations of Variable-Speed Power Turbine Flows

NASA Technical Reports Server (NTRS)

Ameri, Ali A.

2016-01-01

Variable-speed power turbines (VSPTs) operate at low Reynolds numbers and with a wide range of incidence angles. Transition, separation, and the relevant physics leading to them are important to VSPT flow. Higher fidelity tools such as large eddy simulation (LES) may be needed to resolve the flow features necessary for accurate predictive capability and design of such turbines. A survey conducted for this report explores the requirements for such computations. The survey is limited to the simulation of two-dimensional flow cases and endwalls are not included. It suggests that a grid resolution necessary for this type of simulation to accurately represent the physics may be of the order of Delta(x)+=45, Delta(x)+ =2 and Delta(z)+=17. Various subgrid-scale (SGS) models have been used and except for the Smagorinsky model, all seem to perform well and in some instances the simulations worked well without SGS modeling. A method of specifying the inlet conditions such as synthetic eddy modeling (SEM) is necessary to correctly represent the inlet conditions.

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

DOE PAGES

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk; ...

2017-11-07

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

Large eddy simulation of transitional flow in an idealized stenotic blood vessel: evaluation of subgrid scale models.

PubMed

Pal, Abhro; Anupindi, Kameswararao; Delorme, Yann; Ghaisas, Niranjan; Shetty, Dinesh A; Frankel, Steven H

2014-07-01

In the present study, we performed large eddy simulation (LES) of axisymmetric, and 75% stenosed, eccentric arterial models with steady inflow conditions at a Reynolds number of 1000. The results obtained are compared with the direct numerical simulation (DNS) data (Varghese et al., 2007, "Direct Numerical Simulation of Stenotic Flows. Part 1. Steady Flow," J. Fluid Mech., 582, pp. 253-280). An inhouse code (WenoHemo) employing high-order numerical methods for spatial and temporal terms, along with a 2nd order accurate ghost point immersed boundary method (IBM) (Mark, and Vanwachem, 2008, "Derivation and Validation of a Novel Implicit Second-Order Accurate Immersed Boundary Method," J. Comput. Phys., 227(13), pp. 6660-6680) for enforcing boundary conditions on curved geometries is used for simulations. Three subgrid scale (SGS) models, namely, the classical Smagorinsky model (Smagorinsky, 1963, "General Circulation Experiments With the Primitive Equations," Mon. Weather Rev., 91(10), pp. 99-164), recently developed Vreman model (Vreman, 2004, "An Eddy-Viscosity Subgrid-Scale Model for Turbulent Shear Flow: Algebraic Theory and Applications," Phys. Fluids, 16(10), pp. 3670-3681), and the Sigma model (Nicoud et al., 2011, "Using Singular Values to Build a Subgrid-Scale Model for Large Eddy Simulations," Phys. Fluids, 23(8), 085106) are evaluated in the present study. Evaluation of SGS models suggests that the classical constant coefficient Smagorinsky model gives best agreement with the DNS data, whereas the Vreman and Sigma models predict an early transition to turbulence in the poststenotic region. Supplementary simulations are performed using Open source field operation and manipulation (OpenFOAM) ("OpenFOAM," http://www.openfoam.org/) solver and the results are inline with those obtained with WenoHemo.

A parallel algorithm for the initial screening of space debris collisions prediction using the SGP4/SDP4 models and GPU acceleration

NASA Astrophysics Data System (ADS)

Lin, Mingpei; Xu, Ming; Fu, Xiaoyu

2017-05-01

Currently, a tremendous amount of space debris in Earth's orbit imperils operational spacecraft. It is essential to undertake risk assessments of collisions and predict dangerous encounters in space. However, collision predictions for an enormous amount of space debris give rise to large-scale computations. In this paper, a parallel algorithm is established on the Compute Unified Device Architecture (CUDA) platform of NVIDIA Corporation for collision prediction. According to the parallel structure of NVIDIA graphics processors, a block decomposition strategy is adopted in the algorithm. Space debris is divided into batches, and the computation and data transfer operations of adjacent batches overlap. As a consequence, the latency to access shared memory during the entire computing process is significantly reduced, and a higher computing speed is reached. Theoretically, a simulation of collision prediction for space debris of any amount and for any time span can be executed. To verify this algorithm, a simulation example including 1382 pieces of debris, whose operational time scales vary from 1 min to 3 days, is conducted on Tesla C2075 of NVIDIA. The simulation results demonstrate that with the same computational accuracy as that of a CPU, the computing speed of the parallel algorithm on a GPU is 30 times that on a CPU. Based on this algorithm, collision prediction of over 150 Chinese spacecraft for a time span of 3 days can be completed in less than 3 h on a single computer, which meets the timeliness requirement of the initial screening task. Furthermore, the algorithm can be adapted for multiple tasks, including particle filtration, constellation design, and Monte-Carlo simulation of an orbital computation.

On the Computation of Sound by Large-Eddy Simulations

NASA Technical Reports Server (NTRS)

Piomelli, Ugo; Streett, Craig L.; Sarkar, Sutanu

1997-01-01

The effect of the small scales on the source term in Lighthill's acoustic analogy is investigated, with the objective of determining the accuracy of large-eddy simulations when applied to studies of flow-generated sound. The distribution of the turbulent quadrupole is predicted accurately, if models that take into account the trace of the SGS stresses are used. Its spatial distribution is also correct, indicating that the low-wave-number (or frequency) part of the sound spectrum can be predicted well by LES. Filtering, however, removes the small-scale fluctuations that contribute significantly to the higher derivatives in space and time of Lighthill's stress tensor T(sub ij). The rms fluctuations of the filtered derivatives are substantially lower than those of the unfiltered quantities. The small scales, however, are not strongly correlated, and are not expected to contribute significantly to the far-field sound; separate modeling of the subgrid-scale density fluctuations might, however, be required in some configurations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lingerfelt, Eric J; Endeve, Eirik; Hui, Yawei

Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now--with the rise of multimodal acquisition systems and the associated processing capability--the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalablemore » data analysis and simulation and manage uploaded data files via an intuitive, cross-platform client user interface. This framework delivers authenticated, "push-button" execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing compute-and-data cloud infrastructures and HPC environments like Titan at the Oak Ridge Leadershp Computing Facility (OLCF).« less

Parameter Sweep and Optimization of Loosely Coupled Simulations Using the DAKOTA Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elwasif, Wael R; Bernholdt, David E; Pannala, Sreekanth

2012-01-01

The increasing availability of large scale computing capabilities has accelerated the development of high-fidelity coupled simulations. Such simulations typically involve the integration of models that implement various aspects of the complex phenomena under investigation. Coupled simulations are playing an integral role in fields such as climate modeling, earth systems modeling, rocket simulations, computational chemistry, fusion research, and many other computational fields. Model coupling provides scientists with systematic ways to virtually explore the physical, mathematical, and computational aspects of the problem. Such exploration is rarely done using a single execution of a simulation, but rather by aggregating the results from manymore » simulation runs that, together, serve to bring to light novel knowledge about the system under investigation. Furthermore, it is often the case (particularly in engineering disciplines) that the study of the underlying system takes the form of an optimization regime, where the control parameter space is explored to optimize an objective functions that captures system realizability, cost, performance, or a combination thereof. Novel and flexible frameworks that facilitate the integration of the disparate models into a holistic simulation are used to perform this research, while making efficient use of the available computational resources. In this paper, we describe the integration of the DAKOTA optimization and parameter sweep toolkit with the Integrated Plasma Simulator (IPS), a component-based framework for loosely coupled simulations. The integration allows DAKOTA to exploit the internal task and resource management of the IPS to dynamically instantiate simulation instances within a single IPS instance, allowing for greater control over the trade-off between efficiency of resource utilization and time to completion. We present a case study showing the use of the combined DAKOTA-IPS system to aid in the design of a lithium ion battery (LIB) cell, by studying a coupled system involving the electrochemistry and ion transport at the lower length scales and thermal energy transport at the device scales. The DAKOTA-IPS system provides a flexible tool for use in optimization and parameter sweep studies involving loosely coupled simulations that is suitable for use in situations where changes to the constituent components in the coupled simulation are impractical due to intellectual property or code heritage issues.« less

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2010-02-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled substantial interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1 °C over land installations. In contrast, surface cooling exceeding 1 °C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2009-09-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled legitimate interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1°C over land installations. In contrast, surface cooling exceeding 1°C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

XS: a FASTQ read simulator.

PubMed

Pratas, Diogo; Pinho, Armando J; Rodrigues, João M O S

2014-01-16

The emerging next-generation sequencing (NGS) is bringing, besides the natural huge amounts of data, an avalanche of new specialized tools (for analysis, compression, alignment, among others) and large public and private network infrastructures. Therefore, a direct necessity of specific simulation tools for testing and benchmarking is rising, such as a flexible and portable FASTQ read simulator, without the need of a reference sequence, yet correctly prepared for producing approximately the same characteristics as real data. We present XS, a skilled FASTQ read simulation tool, flexible, portable (does not need a reference sequence) and tunable in terms of sequence complexity. It has several running modes, depending on the time and memory available, and is aimed at testing computing infrastructures, namely cloud computing of large-scale projects, and testing FASTQ compression algorithms. Moreover, XS offers the possibility of simulating the three main FASTQ components individually (headers, DNA sequences and quality-scores). XS provides an efficient and convenient method for fast simulation of FASTQ files, such as those from Ion Torrent (currently uncovered by other simulators), Roche-454, Illumina and ABI-SOLiD sequencing machines. This tool is publicly available at http://bioinformatics.ua.pt/software/xs/.

MicroHH 1.0: a computational fluid dynamics code for direct numerical simulation and large-eddy simulation of atmospheric boundary layer flows

NASA Astrophysics Data System (ADS)

van Heerwaarden, Chiel C.; van Stratum, Bart J. H.; Heus, Thijs; Gibbs, Jeremy A.; Fedorovich, Evgeni; Mellado, Juan Pedro

2017-08-01

This paper describes MicroHH 1.0, a new and open-source (www.microhh.org) computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is primarily made for direct numerical simulation but also supports large-eddy simulation (LES). The paper covers the description of the governing equations, their numerical implementation, and the parameterizations included in the code. Furthermore, the paper presents the validation of the dynamical core in the form of convergence and conservation tests, and comparison of simulations of channel flows and slope flows against well-established test cases. The full numerical model, including the associated parameterizations for LES, has been tested for a set of cases under stable and unstable conditions, under the Boussinesq and anelastic approximations, and with dry and moist convection under stationary and time-varying boundary conditions. The paper presents performance tests showing good scaling from 256 to 32 768 processes. The graphical processing unit (GPU)-enabled version of the code can reach a speedup of more than an order of magnitude for simulations that fit in the memory of a single GPU.

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

PubMed Central

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close “neighborhood” of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa. PMID:26327290

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

PubMed

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

Accelerating sino-atrium computer simulations with graphic processing units.

PubMed

Zhang, Hong; Xiao, Zheng; Lin, Shien-fong

2015-01-01

Sino-atrial node cells (SANCs) play a significant role in rhythmic firing. To investigate their role in arrhythmia and interactions with the atrium, computer simulations based on cellular dynamic mathematical models are generally used. However, the large-scale computation usually makes research difficult, given the limited computational power of Central Processing Units (CPUs). In this paper, an accelerating approach with Graphic Processing Units (GPUs) is proposed in a simulation consisting of the SAN tissue and the adjoining atrium. By using the operator splitting method, the computational task was made parallel. Three parallelization strategies were then put forward. The strategy with the shortest running time was further optimized by considering block size, data transfer and partition. The results showed that for a simulation with 500 SANCs and 30 atrial cells, the execution time taken by the non-optimized program decreased 62% with respect to a serial program running on CPU. The execution time decreased by 80% after the program was optimized. The larger the tissue was, the more significant the acceleration became. The results demonstrated the effectiveness of the proposed GPU-accelerating methods and their promising applications in more complicated biological simulations.

Xyce parallel electronic simulator users guide, version 6.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, Eric R; Mei, Ting; Russo, Thomas V.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas; Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers; A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models; Device models that are specifically tailored to meet Sandia's needs, including some radiationaware devices (for Sandia users only); and Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase-a message passing parallel implementation-which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less

Xyce parallel electronic simulator users' guide, Version 6.0.1.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, Eric R; Mei, Ting; Russo, Thomas V.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandias needs, including some radiationaware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase a message passing parallel implementation which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less

Xyce parallel electronic simulator users guide, version 6.0.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, Eric R; Mei, Ting; Russo, Thomas V.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandias needs, including some radiationaware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase a message passing parallel implementation which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less

Resolving Properties of Polymers and Nanoparticle Assembly through Coarse-Grained Computational Studies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grest, Gary S.

2017-09-01

Coupled length and time scales determine the dynamic behavior of polymers and polymer nanocomposites and underlie their unique properties. To resolve the properties over large time and length scales it is imperative to develop coarse grained models which retain the atomistic specificity. Here we probe the degree of coarse graining required to simultaneously retain significant atomistic details a nd access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using polyethylene as a model system, we probe how the coarse - graining scale affects themore » measured dynamics with different number methylene group s per coarse - grained beads. Using these models we simulate polyethylene melts for times over 500 ms to study the viscoelastic properties of well - entangled polymer melts and large nanoparticle assembly as the nanoparticles are driven close enough to form nanostructures.« less

Simulating Nationwide Pandemics: Applying the Multi-scale Epidemiologic Simulation and Analysis System to Human Infectious Diseases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dombroski, M; Melius, C; Edmunds, T

2008-09-24

This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to humanmore » epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future work including validating the model against reliable historical disease data, improving contact rates, spread methods, and disease parameters through discussions with epidemiological experts, and incorporating realistic behavioral assumptions.« less

Multi-Scale Fusion of Information for Uncertainty Quantification and Management in Large-Scale Simulations

DTIC Science & Technology

2015-12-02

simplification of the equations but at the expense of introducing modeling errors. We have shown that the Wick solutions have accuracy comparable to...the system of equations for the coefficients of formal power series solutions . Moreover, the structure of this propagator is seemingly universal, i.e...the problem of computing the numerical solution to kinetic partial differential equa- tions involving many phase variables. These types of equations

A computational study on oblique shock wave-turbulent boundary layer interaction

NASA Astrophysics Data System (ADS)

Joy, Md. Saddam Hossain; Rahman, Saeedur; Hasan, A. B. M. Toufique; Ali, M.; Mitsutake, Y.; Matsuo, S.; Setoguchi, T.

2016-07-01

A numerical computation of an oblique shock wave incident on a turbulent boundary layer was performed for free stream flow of air at M∞ = 2.0 and Re1 = 10.5×106 m-1. The oblique shock wave was generated from a 8° wedge. Reynolds averaged Navier-Stokes (RANS) simulation with k-ω SST turbulence model was first utilized for two dimensional (2D) steady case. The results were compared with the experiment at the same flow conditions. Further, to capture the unsteadiness, a 2D Large Eddy Simulation (LES) with sub-grid scale model WMLES was performed which showed the unsteady effects. The frequency of the shock oscillation was computed and was found to be comparable with that of experimental measurement.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

TRANSITION FROM KINETIC TO MHD BEHAVIOR IN A COLLISIONLESS PLASMA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parashar, Tulasi N.; Matthaeus, William H.; Shay, Michael A.

The study of kinetic effects in heliospheric plasmas requires representation of dynamics at sub-proton scales, but in most cases the system is driven by magnetohydrodynamic (MHD) activity at larger scales. The latter requirement challenges available computational resources, which raises the question of how large such a system must be to exhibit MHD traits at large scales while kinetic behavior is accurately represented at small scales. Here we study this implied transition from kinetic to MHD-like behavior using particle-in-cell (PIC) simulations, initialized using an Orszag–Tang Vortex. The PIC code treats protons, as well as electrons, kinetically, and we address the questionmore » of interest by examining several different indicators of MHD-like behavior.« less

Discontinuous Galerkin Methods and High-Speed Turbulent Flows

NASA Astrophysics Data System (ADS)

Atak, Muhammed; Larsson, Johan; Munz, Claus-Dieter

2014-11-01

Discontinuous Galerkin methods gain increasing importance within the CFD community as they combine arbitrary high order of accuracy in complex geometries with parallel efficiency. Particularly the discontinuous Galerkin spectral element method (DGSEM) is a promising candidate for both the direct numerical simulation (DNS) and large eddy simulation (LES) of turbulent flows due to its excellent scaling attributes. In this talk, we present a DNS of a compressible turbulent boundary layer along a flat plate at a free-stream Mach number of M = 2.67 and assess the computational efficiency of the DGSEM at performing high-fidelity simulations of both transitional and turbulent boundary layers. We compare the accuracy of the results as well as the computational performance to results using a high order finite difference method.

An Engineering Solution for Solving Mesh Size Effects in the Simulation of Delamination with Cohesive Zone Models

NASA Technical Reports Server (NTRS)

Turon, A.; Davila, C. G.; Camanho, P. P.; Costa, J.

2007-01-01

This paper presents a methodology to determine the parameters to be used in the constitutive equations of Cohesive Zone Models employed in the simulation of delamination in composite materials by means of decohesion finite elements. A closed-form expression is developed to define the stiffness of the cohesive layer. A novel procedure that allows the use of coarser meshes of decohesion elements in large-scale computations is also proposed. The procedure ensures that the energy dissipated by the fracture process is computed correctly. It is shown that coarse-meshed models defined using the approach proposed here yield the same results as the models with finer meshes normally used for the simulation of fracture processes.

MPI implementation of PHOENICS: A general purpose computational fluid dynamics code

NASA Astrophysics Data System (ADS)

Simunovic, S.; Zacharia, T.; Baltas, N.; Spalding, D. B.

1995-03-01

PHOENICS is a suite of computational analysis programs that are used for simulation of fluid flow, heat transfer, and dynamical reaction processes. The parallel version of the solver EARTH for the Computational Fluid Dynamics (CFD) program PHOENICS has been implemented using Message Passing Interface (MPI) standard. Implementation of MPI version of PHOENICS makes this computational tool portable to a wide range of parallel machines and enables the use of high performance computing for large scale computational simulations. MPI libraries are available on several parallel architectures making the program usable across different architectures as well as on heterogeneous computer networks. The Intel Paragon NX and MPI versions of the program have been developed and tested on massively parallel supercomputers Intel Paragon XP/S 5, XP/S 35, and Kendall Square Research, and on the multiprocessor SGI Onyx computer at Oak Ridge National Laboratory. The preliminary testing results of the developed program have shown scalable performance for reasonably sized computational domains.

MPI implementation of PHOENICS: A general purpose computational fluid dynamics code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simunovic, S.; Zacharia, T.; Baltas, N.

1995-04-01

PHOENICS is a suite of computational analysis programs that are used for simulation of fluid flow, heat transfer, and dynamical reaction processes. The parallel version of the solver EARTH for the Computational Fluid Dynamics (CFD) program PHOENICS has been implemented using Message Passing Interface (MPI) standard. Implementation of MPI version of PHOENICS makes this computational tool portable to a wide range of parallel machines and enables the use of high performance computing for large scale computational simulations. MPI libraries are available on several parallel architectures making the program usable across different architectures as well as on heterogeneous computer networks. Themore » Intel Paragon NX and MPI versions of the program have been developed and tested on massively parallel supercomputers Intel Paragon XP/S 5, XP/S 35, and Kendall Square Research, and on the multiprocessor SGI Onyx computer at Oak Ridge National Laboratory. The preliminary testing results of the developed program have shown scalable performance for reasonably sized computational domains.« less

An atomic finite element model for biodegradable polymers. Part 1. Formulation of the finite elements.

PubMed

Gleadall, Andrew; Pan, Jingzhe; Ding, Lifeng; Kruft, Marc-Anton; Curcó, David

2015-11-01

Molecular dynamics (MD) simulations are widely used to analyse materials at the atomic scale. However, MD has high computational demands, which may inhibit its use for simulations of structures involving large numbers of atoms such as amorphous polymer structures. An atomic-scale finite element method (AFEM) is presented in this study with significantly lower computational demands than MD. Due to the reduced computational demands, AFEM is suitable for the analysis of Young's modulus of amorphous polymer structures. This is of particular interest when studying the degradation of bioresorbable polymers, which is the topic of an accompanying paper. AFEM is derived from the inter-atomic potential energy functions of an MD force field. The nonlinear MD functions were adapted to enable static linear analysis. Finite element formulations were derived to represent interatomic potential energy functions between two, three and four atoms. Validation of the AFEM was conducted through its application to atomic structures for crystalline and amorphous poly(lactide). Copyright © 2015 Elsevier Ltd. All rights reserved.

Internal variability of fine-scale components of meteorological fields in extended-range limited-area model simulations with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei

2015-09-01

Internal variability (IV) in dynamical downscaling with limited-area models (LAMs) represents a source of error inherent to the downscaled fields, which originates from the sensitive dependence of the models to arbitrarily small modifications. If IV is large it may impose the need for probabilistic verification of the downscaled information. Atmospheric spectral nudging (ASN) can reduce IV in LAMs as it constrains the large-scale components of LAM fields in the interior of the computational domain and thus prevents any considerable penetration of sensitively dependent deviations into the range of large scales. Using initial condition ensembles, the present study quantifies the impact of ASN on IV in LAM simulations in the range of fine scales that are not controlled by spectral nudging. Four simulation configurations that all include strong ASN but differ in the nudging settings are considered. In the fifth configuration, grid nudging of land surface variables toward high-resolution surface analyses is applied. The results show that the IV at scales larger than 300 km can be suppressed by selecting an appropriate ASN setup. At scales between 300 and 30 km, however, in all configurations, the hourly near-surface temperature, humidity, and winds are only partly reproducible. Nudging the land surface variables is found to have the potential to significantly reduce IV, particularly for fine-scale temperature and humidity. On the other hand, hourly precipitation accumulations at these scales are generally irreproducible in all configurations, and probabilistic approach to downscaling is therefore recommended.

Multi-scale modeling in cell biology

PubMed Central

Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

2009-01-01

Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808

Numerical Upscaling of Solute Transport in Fractured Porous Media Based on Flow Aligned Blocks

NASA Astrophysics Data System (ADS)

Leube, P.; Nowak, W.; Sanchez-Vila, X.

2013-12-01

High-contrast or fractured-porous media (FPM) pose one of the largest unresolved challenges for simulating large hydrogeological systems. The high contrast in advective transport between fast conduits and low-permeability rock matrix, including complex mass transfer processes, leads to the typical complex characteristics of early bulk arrivals and long tailings. Adequate direct representation of FPM requires enormous numerical resolutions. For large scales, e.g. the catchment scale, and when allowing for uncertainty in the fracture network architecture or in matrix properties, computational costs quickly reach an intractable level. In such cases, multi-scale simulation techniques have become useful tools. They allow decreasing the complexity of models by aggregating and transferring their parameters to coarser scales and so drastically reduce the computational costs. However, these advantages come at a loss of detail and accuracy. In this work, we develop and test a new multi-scale or upscaled modeling approach based on block upscaling. The novelty is that individual blocks are defined by and aligned with the local flow coordinates. We choose a multi-rate mass transfer (MRMT) model to represent the remaining sub-block non-Fickian behavior within these blocks on the coarse scale. To make the scale transition simple and to save computational costs, we capture sub-block features by temporal moments (TM) of block-wise particle arrival times to be matched with the MRMT model. By predicting spatial mass distributions of injected tracers in a synthetic test scenario, our coarse-scale solution matches reasonably well with the corresponding fine-scale reference solution. For predicting higher TM-orders (such as arrival time and effective dispersion), the prediction accuracy steadily decreases. This is compensated to some extent by the MRMT model. If the MRMT model becomes too complex, it loses its effect. We also found that prediction accuracy is sensitive to the choice of the effective dispersion coefficients and on the block resolution. A key advantage of the flow-aligned blocks is that the small-scale velocity field is reproduced quite accurately on the block-scale through their flow alignment. Thus, the block-scale transverse dispersivities remain in the similar magnitude as local ones, and they do not have to represent macroscopic uncertainty. Also, the flow-aligned blocks minimize numerical dispersion when solving the large-scale transport problem.

Validation of hydrogen gas stratification and mixing models

DOE PAGES

Wu, Hsingtzu; Zhao, Haihua

2015-05-26

Two validation benchmarks confirm that the BMIX++ code is capable of simulating unintended hydrogen release scenarios efficiently. The BMIX++ (UC Berkeley mechanistic MIXing code in C++) code has been developed to accurately and efficiently predict the fluid mixture distribution and heat transfer in large stratified enclosures for accident analyses and design optimizations. The BMIX++ code uses a scaling based one-dimensional method to achieve large reduction in computational effort compared to a 3-D computational fluid dynamics (CFD) simulation. Two BMIX++ benchmark models have been developed. One is for a single buoyant jet in an open space and another is for amore » large sealed enclosure with both a jet source and a vent near the floor. Both of them have been validated by comparisons with experimental data. Excellent agreements are observed. The entrainment coefficients of 0.09 and 0.08 are found to fit the experimental data for hydrogen leaks with the Froude number of 99 and 268 best, respectively. In addition, the BIX++ simulation results of the average helium concentration for an enclosure with a vent and a single jet agree with the experimental data within a margin of about 10% for jet flow rates ranging from 1.21 × 10⁻⁴ to 3.29 × 10⁻⁴ m³/s. In conclusion, computing time for each BMIX++ model with a normal desktop computer is less than 5 min.« less

A physics-motivated Centroidal Voronoi Particle domain decomposition method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fu, Lin, E-mail: lin.fu@tum.de; Hu, Xiangyu Y., E-mail: xiangyu.hu@tum.de; Adams, Nikolaus A., E-mail: nikolaus.adams@tum.de

2017-04-15

In this paper, we propose a novel domain decomposition method for large-scale simulations in continuum mechanics by merging the concepts of Centroidal Voronoi Tessellation (CVT) and Voronoi Particle dynamics (VP). The CVT is introduced to achieve a high-level compactness of the partitioning subdomains by the Lloyd algorithm which monotonically decreases the CVT energy. The number of computational elements between neighboring partitioning subdomains, which scales the communication effort for parallel simulations, is optimized implicitly as the generated partitioning subdomains are convex and simply connected with small aspect-ratios. Moreover, Voronoi Particle dynamics employing physical analogy with a tailored equation of state ismore » developed, which relaxes the particle system towards the target partition with good load balance. Since the equilibrium is computed by an iterative approach, the partitioning subdomains exhibit locality and the incremental property. Numerical experiments reveal that the proposed Centroidal Voronoi Particle (CVP) based algorithm produces high-quality partitioning with high efficiency, independently of computational-element types. Thus it can be used for a wide range of applications in computational science and engineering.« less

A physics-motivated Centroidal Voronoi Particle domain decomposition method

NASA Astrophysics Data System (ADS)

Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-04-01

In this paper, we propose a novel domain decomposition method for large-scale simulations in continuum mechanics by merging the concepts of Centroidal Voronoi Tessellation (CVT) and Voronoi Particle dynamics (VP). The CVT is introduced to achieve a high-level compactness of the partitioning subdomains by the Lloyd algorithm which monotonically decreases the CVT energy. The number of computational elements between neighboring partitioning subdomains, which scales the communication effort for parallel simulations, is optimized implicitly as the generated partitioning subdomains are convex and simply connected with small aspect-ratios. Moreover, Voronoi Particle dynamics employing physical analogy with a tailored equation of state is developed, which relaxes the particle system towards the target partition with good load balance. Since the equilibrium is computed by an iterative approach, the partitioning subdomains exhibit locality and the incremental property. Numerical experiments reveal that the proposed Centroidal Voronoi Particle (CVP) based algorithm produces high-quality partitioning with high efficiency, independently of computational-element types. Thus it can be used for a wide range of applications in computational science and engineering.

Large-eddy simulation of sand dune morphodynamics

NASA Astrophysics Data System (ADS)

Khosronejad, Ali; Sotiropoulos, Fotis; St. Anthony Falls Laboratory, University of Minnesota Team

2015-11-01

Sand dunes are natural features that form under complex interaction between turbulent flow and bed morphodynamics. We employ a fully-coupled 3D numerical model (Khosronejad and Sotiropoulos, 2014, Journal of Fluid Mechanics, 753:150-216) to perform high-resolution large-eddy simulations of turbulence and bed morphodynamics in a laboratory scale mobile-bed channel to investigate initiation, evolution and quasi-equilibrium of sand dunes (Venditti and Church, 2005, J. Geophysical Research, 110:F01009). We employ a curvilinear immersed boundary method along with convection-diffusion and bed-morphodynamics modules to simulate the suspended sediment and the bed-load transports respectively. The coupled simulation were carried out on a grid with more than 100 million grid nodes and simulated about 3 hours of physical time of dune evolution. The simulations provide the first complete description of sand dune formation and long-term evolution. The geometric characteristics of the simulated dunes are shown to be in excellent agreement with observed data obtained across a broad range of scales. This work was supported by NSF Grants EAR-0120914 (as part of the National Center for Earth-Surface Dynamics). Computational resources were provided by the University of Minnesota Supercomputing Institute.

Wakefield Computations for the CLIC PETS using the Parallel Finite Element Time-Domain Code T3P

DOE Office of Scientific and Technical Information (OSTI.GOV)

Candel, A; Kabel, A.; Lee, L.

In recent years, SLAC's Advanced Computations Department (ACD) has developed the high-performance parallel 3D electromagnetic time-domain code, T3P, for simulations of wakefields and transients in complex accelerator structures. T3P is based on advanced higher-order Finite Element methods on unstructured grids with quadratic surface approximation. Optimized for large-scale parallel processing on leadership supercomputing facilities, T3P allows simulations of realistic 3D structures with unprecedented accuracy, aiding the design of the next generation of accelerator facilities. Applications to the Compact Linear Collider (CLIC) Power Extraction and Transfer Structure (PETS) are presented.

Scaling up Planetary Dynamo Modeling to Massively Parallel Computing Systems: The Rayleigh Code at ALCF

NASA Astrophysics Data System (ADS)

Featherstone, N. A.; Aurnou, J. M.; Yadav, R. K.; Heimpel, M. H.; Soderlund, K. M.; Matsui, H.; Stanley, S.; Brown, B. P.; Glatzmaier, G.; Olson, P.; Buffett, B. A.; Hwang, L.; Kellogg, L. H.

2017-12-01

In the past three years, CIG's Dynamo Working Group has successfully ported the Rayleigh Code to the Argonne Leadership Computer Facility's Mira BG/Q device. In this poster, we present some our first results, showing simulations of 1) convection in the solar convection zone; 2) dynamo action in Earth's core and 3) convection in the jovian deep atmosphere. These simulations have made efficient use of 131 thousand cores, 131 thousand cores and 232 thousand cores, respectively, on Mira. In addition to our novel results, the joys and logistical challenges of carrying out such large runs will also be discussed.

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

PubMed

Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

2011-09-07

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, Alexey; Belov, Sergey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

2012-12-01

ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

GAPD: a GPU-accelerated atom-based polychromatic diffraction simulation code.

PubMed

E, J C; Wang, L; Chen, S; Zhang, Y Y; Luo, S N

2018-03-01

GAPD, a graphics-processing-unit (GPU)-accelerated atom-based polychromatic diffraction simulation code for direct, kinematics-based, simulations of X-ray/electron diffraction of large-scale atomic systems with mono-/polychromatic beams and arbitrary plane detector geometries, is presented. This code implements GPU parallel computation via both real- and reciprocal-space decompositions. With GAPD, direct simulations are performed of the reciprocal lattice node of ultralarge systems (∼5 billion atoms) and diffraction patterns of single-crystal and polycrystalline configurations with mono- and polychromatic X-ray beams (including synchrotron undulator sources), and validation, benchmark and application cases are presented.

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.