Community Petascale Project for Accelerator Science and Simulation: Advancing Computational Science for Future Accelerators and Accelerator Technologies

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

Spentzouris, P.; /Fermilab; Cary, J.

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors. ComPASS is in the first year of executing its plan to develop the next-generation HPC accelerator modeling tools. ComPASS aims to develop an integrated simulation environment that will utilize existing and new accelerator physics modules with petascale capabilities, by employing modern computing and solver technologies. The ComPASS vision is to deliver to accelerator scientists a virtual accelerator and virtual prototyping modeling environment, with the necessary multiphysics, multiscale capabilities. The plan for this development includes delivering accelerator modeling applications appropriate for each stage of the ComPASS software evolution. Such applications are already being used to address challenging problems in accelerator design and optimization. The ComPASS organization for software development and applications accounts for the natural domain areas (beam dynamics, electromagnetics, and advanced acceleration), and all areas depend on the enabling technologies activities, such as solvers and component technology, to deliver the desired performance and integrated simulation environment. The ComPASS applications focus on computationally challenging problems important for design or performance optimization to all major HEP, NP, and BES accelerator facilities. With the cost and complexity of particle accelerators rising, the use of computation to optimize their designs and find improved operating regimes becomes essential, potentially leading to significant cost savings with modest investment.« less

Theoretical and technological building blocks for an innovation accelerator

NASA Astrophysics Data System (ADS)

van Harmelen, F.; Kampis, G.; Börner, K.; van den Besselaar, P.; Schultes, E.; Goble, C.; Groth, P.; Mons, B.; Anderson, S.; Decker, S.; Hayes, C.; Buecheler, T.; Helbing, D.

2012-11-01

Modern science is a main driver of technological innovation. The efficiency of the scientific system is of key importance to ensure the competitiveness of a nation or region. However, the scientific system that we use today was devised centuries ago and is inadequate for our current ICT-based society: the peer review system encourages conservatism, journal publications are monolithic and slow, data is often not available to other scientists, and the independent validation of results is limited. The resulting scientific process is hence slow and sloppy. Building on the Innovation Accelerator paper by Helbing and Balietti [1], this paper takes the initial global vision and reviews the theoretical and technological building blocks that can be used for implementing an innovation (in first place: science) accelerator platform driven by re-imagining the science system. The envisioned platform would rest on four pillars: (i) Redesign the incentive scheme to reduce behavior such as conservatism, herding and hyping; (ii) Advance scientific publications by breaking up the monolithic paper unit and introducing other building blocks such as data, tools, experiment workflows, resources; (iii) Use machine readable semantics for publications, debate structures, provenance etc. in order to include the computer as a partner in the scientific process, and (iv) Build an online platform for collaboration, including a network of trust and reputation among the different types of stakeholders in the scientific system: scientists, educators, funding agencies, policy makers, students and industrial innovators among others. Any such improvements to the scientific system must support the entire scientific process (unlike current tools that chop up the scientific process into disconnected pieces), must facilitate and encourage collaboration and interdisciplinarity (again unlike current tools), must facilitate the inclusion of intelligent computing in the scientific process, must facilitate not only the core scientific process, but also accommodate other stakeholders such science policy makers, industrial innovators, and the general public. We first describe the current state of the scientific system together with up to a dozen new key initiatives, including an analysis of the role of science as an innovation accelerator. Our brief survey will show that there exist many separate ideas and concepts and diverse stand-alone demonstrator systems for different components of the ecosystem with many parts are still unexplored, and overall integration lacking. By analyzing a matrix of stakeholders vs. functionalities, we identify the required innovations. We (non-exhaustively) discuss a few of them: Publications that are meaningful to machines, innovative reviewing processes, data publication, workflow archiving and reuse, alternative impact metrics, tools for the detection of trends, community formation and emergence, as well as modular publications, citation objects and debate graphs. To summarize, the core idea behind the Innovation Accelerator is to develop new incentive models, rules, and interaction mechanisms to stimulate true innovation, revolutionizing the way in which we create knowledge and disseminate information.

Enabling large-scale viscoelastic calculations via neural network acceleration

NASA Astrophysics Data System (ADS)

Robinson DeVries, P.; Thompson, T. B.; Meade, B. J.

2017-12-01

One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity are the computational costs of large-scale viscoelastic earthquake cycle models. Deep artificial neural networks (ANNs) can be used to discover new, compact, and accurate computational representations of viscoelastic physics. Once found, these efficient ANN representations may replace computationally intensive viscoelastic codes and accelerate large-scale viscoelastic calculations by more than 50,000%. This magnitude of acceleration enables the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible. Perhaps most interestingly from a scientific perspective, ANN representations of viscoelastic physics may lead to basic advances in the understanding of the underlying model phenomenology. We demonstrate the potential of artificial neural networks to illuminate fundamental physical insights with specific examples.

The application of cloud computing to scientific workflows: a study of cost and performance.

PubMed

Berriman, G Bruce; Deelman, Ewa; Juve, Gideon; Rynge, Mats; Vöckler, Jens-S

2013-01-28

The current model of transferring data from data centres to desktops for analysis will soon be rendered impractical by the accelerating growth in the volume of science datasets. Processing will instead often take place on high-performance servers co-located with data. Evaluations of how new technologies such as cloud computing would support such a new distributed computing model are urgently needed. Cloud computing is a new way of purchasing computing and storage resources on demand through virtualization technologies. We report here the results of investigations of the applicability of commercial cloud computing to scientific computing, with an emphasis on astronomy, including investigations of what types of applications can be run cheaply and efficiently on the cloud, and an example of an application well suited to the cloud: processing a large dataset to create a new science product.

VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures

DOE PAGES

Moreland, Kenneth; Sewell, Christopher; Usher, William; ...

2016-05-09

Here, one of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.

VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures

DOE PAGES

Moreland, Kenneth; Sewell, Christopher; Usher, William; ...

2016-05-09

Execution on massively threaded processors is one of the most critical challenges for high-performance computing (HPC) scientific visualization. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Moreover, our current production scientific visualization software is not designed for these new types of architectures. In order to address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.

Novel 3D/VR interactive environment for MD simulations, visualization and analysis.

PubMed

Doblack, Benjamin N; Allis, Tim; Dávila, Lilian P

2014-12-18

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced.

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

PubMed Central

Doblack, Benjamin N.; Allis, Tim; Dávila, Lilian P.

2014-01-01

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced. PMID:25549300

Hermes: Seamless delivery of containerized bioinformatics workflows in hybrid cloud (HTC) environments

NASA Astrophysics Data System (ADS)

Kintsakis, Athanassios M.; Psomopoulos, Fotis E.; Symeonidis, Andreas L.; Mitkas, Pericles A.

Hermes introduces a new "describe once, run anywhere" paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.

Implementing Molecular Dynamics for Hybrid High Performance Computers - 1. Short Range Forces

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

Brown, W Michael; Wang, Peng; Plimpton, Steven J

The use of accelerators such as general-purpose graphics processing units (GPGPUs) have become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high performance computers, machines with more than one type of floating-point processor, are now becoming more prevalent due to these advantages. In this work, we discuss several important issues in porting a large molecular dynamics code for use on parallel hybrid machines - 1) choosing a hybrid parallel decomposition that works on central processing units (CPUs) with distributed memory and accelerator cores with shared memory,more » 2) minimizing the amount of code that must be ported for efficient acceleration, 3) utilizing the available processing power from both many-core CPUs and accelerators, and 4) choosing a programming model for acceleration. We present our solution to each of these issues for short-range force calculation in the molecular dynamics package LAMMPS. We describe algorithms for efficient short range force calculation on hybrid high performance machines. We describe a new approach for dynamic load balancing of work between CPU and accelerator cores. We describe the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators. Finally, we present results on a parallel test cluster containing 32 Fermi GPGPUs and 180 CPU cores.« less

A heterogeneous computing accelerated SCE-UA global optimization method using OpenMP, OpenCL, CUDA, and OpenACC.

PubMed

Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Liang, Ke; Hong, Yang

2017-10-01

The shuffled complex evolution optimization developed at the University of Arizona (SCE-UA) has been successfully applied in various kinds of scientific and engineering optimization applications, such as hydrological model parameter calibration, for many years. The algorithm possesses good global optimality, convergence stability and robustness. However, benchmark and real-world applications reveal the poor computational efficiency of the SCE-UA. This research aims at the parallelization and acceleration of the SCE-UA method based on powerful heterogeneous computing technology. The parallel SCE-UA is implemented on Intel Xeon multi-core CPU (by using OpenMP and OpenCL) and NVIDIA Tesla many-core GPU (by using OpenCL, CUDA, and OpenACC). The serial and parallel SCE-UA were tested based on the Griewank benchmark function. Comparison results indicate the parallel SCE-UA significantly improves computational efficiency compared to the original serial version. The OpenCL implementation obtains the best overall acceleration results however, with the most complex source code. The parallel SCE-UA has bright prospects to be applied in real-world applications.

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

Allada, Veerendra, Benjegerdes, Troy; Bode, Brett

Commodity clusters augmented with application accelerators are evolving as competitive high performance computing systems. The Graphical Processing Unit (GPU) with a very high arithmetic density and performance per price ratio is a good platform for the scientific application acceleration. In addition to the interconnect bottlenecks among the cluster compute nodes, the cost of memory copies between the host and the GPU device have to be carefully amortized to improve the overall efficiency of the application. Scientific applications also rely on efficient implementation of the BAsic Linear Algebra Subroutines (BLAS), among which the General Matrix Multiply (GEMM) is considered as themore » workhorse subroutine. In this paper, they study the performance of the memory copies and GEMM subroutines that are critical to port the computational chemistry algorithms to the GPU clusters. To that end, a benchmark based on the NetPIPE framework is developed to evaluate the latency and bandwidth of the memory copies between the host and the GPU device. The performance of the single and double precision GEMM subroutines from the NVIDIA CUBLAS 2.0 library are studied. The results have been compared with that of the BLAS routines from the Intel Math Kernel Library (MKL) to understand the computational trade-offs. The test bed is a Intel Xeon cluster equipped with NVIDIA Tesla GPUs.« less

Role of High-End Computing in Meeting NASA's Science and Engineering Challenges

NASA Technical Reports Server (NTRS)

Biswas, Rupak

2006-01-01

High-End Computing (HEC) has always played a major role in meeting the modeling and simulation needs of various NASA missions. With NASA's newest 62 teraflops Columbia supercomputer, HEC is having an even greater impact within the Agency and beyond. Significant cutting-edge science and engineering simulations in the areas of space exploration, Shuttle operations, Earth sciences, and aeronautics research, are already occurring on Columbia, demonstrating its ability to accelerate NASA s exploration vision. The talk will describe how the integrated supercomputing production environment 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.

Warp-X: A new exascale computing platform for beam–plasma simulations

DOE PAGES

Vay, J. -L.; Almgren, A.; Bell, J.; ...

2018-01-31

Turning the current experimental plasma accelerator state-of-the-art from a promising technology into mainstream scientific tools depends critically on high-performance, high-fidelity modeling of complex processes that develop over a wide range of space and time scales. As part of the U.S. Department of Energy's Exascale Computing Project, a team from Lawrence Berkeley National Laboratory, in collaboration with teams from SLAC National Accelerator Laboratory and Lawrence Livermore National Laboratory, is developing a new plasma accelerator simulation tool that will harness the power of future exascale supercomputers for high-performance modeling of plasma accelerators. We present the various components of the codes such asmore » the new Particle-In-Cell Scalable Application Resource (PICSAR) and the redesigned adaptive mesh refinement library AMReX, which are combined with redesigned elements of the Warp code, in the new WarpX software. Lastly, the code structure, status, early examples of applications and plans are discussed.« less

Warp-X: A new exascale computing platform for beam–plasma simulations

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

Vay, J. -L.; Almgren, A.; Bell, J.

Turning the current experimental plasma accelerator state-of-the-art from a promising technology into mainstream scientific tools depends critically on high-performance, high-fidelity modeling of complex processes that develop over a wide range of space and time scales. As part of the U.S. Department of Energy's Exascale Computing Project, a team from Lawrence Berkeley National Laboratory, in collaboration with teams from SLAC National Accelerator Laboratory and Lawrence Livermore National Laboratory, is developing a new plasma accelerator simulation tool that will harness the power of future exascale supercomputers for high-performance modeling of plasma accelerators. We present the various components of the codes such asmore » the new Particle-In-Cell Scalable Application Resource (PICSAR) and the redesigned adaptive mesh refinement library AMReX, which are combined with redesigned elements of the Warp code, in the new WarpX software. Lastly, the code structure, status, early examples of applications and plans are discussed.« less

Implementing Molecular Dynamics on Hybrid High Performance Computers - Particle-Particle Particle-Mesh

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

Brown, W Michael; Kohlmeyer, Axel; Plimpton, Steven J

The use of accelerators such as graphics processing units (GPUs) has become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high-performance computers, machines with nodes containing more than one type of floating-point processor (e.g. CPU and GPU), are now becoming more prevalent due to these advantages. In this paper, we present a continuation of previous work implementing algorithms for using accelerators into the LAMMPS molecular dynamics software for distributed memory parallel hybrid machines. In our previous work, we focused on acceleration for short-range models with anmore » approach intended to harness the processing power of both the accelerator and (multi-core) CPUs. To augment the existing implementations, we present an efficient implementation of long-range electrostatic force calculation for molecular dynamics. Specifically, we present an implementation of the particle-particle particle-mesh method based on the work by Harvey and De Fabritiis. We present benchmark results on the Keeneland InfiniBand GPU cluster. We provide a performance comparison of the same kernels compiled with both CUDA and OpenCL. We discuss limitations to parallel efficiency and future directions for improving performance on hybrid or heterogeneous computers.« less

White paper: A plan for cooperation between NASA and DARPA to establish a center for advanced architectures

NASA Technical Reports Server (NTRS)

Denning, P. J.; Adams, G. B., III; Brown, R. L.; Kanerva, P.; Leiner, B. M.; Raugh, M. R.

1986-01-01

Large, complex computer systems require many years of development. It is recognized that large scale systems are unlikely to be delivered in useful condition unless users are intimately involved throughout the design process. A mechanism is described that will involve users in the design of advanced computing systems and will accelerate the insertion of new systems into scientific research. This mechanism is embodied in a facility called the Center for Advanced Architectures (CAA). CAA would be a division of RIACS (Research Institute for Advanced Computer Science) and would receive its technical direction from a Scientific Advisory Board established by RIACS. The CAA described here is a possible implementation of a center envisaged in a proposed cooperation between NASA and DARPA.

Atomic Detail Visualization of Photosynthetic Membranes with GPU-Accelerated Ray Tracing

PubMed Central

Vandivort, Kirby L.; Barragan, Angela; Singharoy, Abhishek; Teo, Ivan; Ribeiro, João V.; Isralewitz, Barry; Liu, Bo; Goh, Boon Chong; Phillips, James C.; MacGregor-Chatwin, Craig; Johnson, Matthew P.; Kourkoutis, Lena F.; Hunter, C. Neil

2016-01-01

The cellular process responsible for providing energy for most life on Earth, namely photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers. PMID:27274603

Bringing Federated Identity to Grid Computing

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

Teheran, Jeny

The Fermi National Accelerator Laboratory (FNAL) is facing the challenge of providing scientific data access and grid submission to scientific collaborations that span the globe but are hosted at FNAL. Users in these collaborations are currently required to register as an FNAL user and obtain FNAL credentials to access grid resources to perform their scientific computations. These requirements burden researchers with managing additional authentication credentials, and put additional load on FNAL for managing user identities. Our design integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and MyProxy with the FNAL grid submission system to provide secure access formore » users from diverse experiments and collab orations without requiring each user to have authentication credentials from FNAL. The design automates the handling of certificates so users do not need to manage them manually. Although the initial implementation is for FNAL's grid submission system, the design and the core of the implementation are general and could be applied to other distributed computing systems.« less

US EPA - A*Star Partnership - Accelerating the Acceptance of Next-Generation Sciences and Their Application to Regulatory Risk Assessment (A*Star Symposium, Singapore)

EPA Science Inventory

The path for incorporating new alternative methods and technologies into quantitative chemical risk assessment poses a diverse set of scientific challenges. Some of these challenges include development of relevant and predictive test systems and computational models to integrate...

Atomic detail visualization of photosynthetic membranes with GPU-accelerated ray tracing

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

Stone, John E.; Sener, Melih; Vandivort, Kirby L.

The cellular process responsible for providing energy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. In this paper, we present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. Finally, we describemore » the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.« less

Atomic detail visualization of photosynthetic membranes with GPU-accelerated ray tracing

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

Stone, John E.; Sener, Melih; Vandivort, Kirby L.

The cellular process responsible for providing energy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that weremore » used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.« less

Atomic detail visualization of photosynthetic membranes with GPU-accelerated ray tracing

DOE PAGES

Stone, John E.; Sener, Melih; Vandivort, Kirby L.; ...

2015-12-12

The cellular process responsible for providing energy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. In this paper, we present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. Finally, we describemore » the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.« less

TADSim: Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

DOE PAGES

Mniszewski, Susan M.; Junghans, Christoph; Voter, Arthur F.; ...

2015-04-16

Next-generation high-performance computing will require more scalable and flexible performance prediction tools to evaluate software--hardware co-design choices relevant to scientific applications and hardware architectures. Here, we present a new class of tools called application simulators—parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation. Parameterized choices for the algorithmic method and hardware options provide a rich space for design exploration and allow us to quickly find well-performing software--hardware combinations. We demonstrate our approach with a TADSim simulator that models the temperature-accelerated dynamics (TAD) method, an algorithmically complex and parameter-rich member of the accelerated molecular dynamics (AMD) family ofmore » molecular dynamics methods. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We accomplish this by identifying the time-intensive elements, quantifying algorithm steps in terms of those elements, abstracting them out, and replacing them by the passage of time. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We extend TADSim to model algorithm extensions, such as speculative spawning of the compute-bound stages, and predict performance improvements without having to implement such a method. Validation against the actual TAD code shows close agreement for the evolution of an example physical system, a silver surface. Finally, focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights and suggested extensions.« less

Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data

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

Rubel, Oliver; Geddes, Cameron G.R.; Cormier-Michel, Estelle

2009-10-19

Numerical simulations of laser wakefield particle accelerators play a key role in the understanding of the complex acceleration process and in the design of expensive experimental facilities. As the size and complexity of simulation output grows, an increasingly acute challenge is the practical need for computational techniques that aid in scientific knowledge discovery. To that end, we present a set of data-understanding algorithms that work in concert in a pipeline fashion to automatically locate and analyze high energy particle bunches undergoing acceleration in very large simulation datasets. These techniques work cooperatively by first identifying features of interest in individual timesteps,more » then integrating features across timesteps, and based on the information derived perform analysis of temporally dynamic features. This combination of techniques supports accurate detection of particle beams enabling a deeper level of scientific understanding of physical phenomena than hasbeen possible before. By combining efficient data analysis algorithms and state-of-the-art data management we enable high-performance analysis of extremely large particle datasets in 3D. We demonstrate the usefulness of our methods for a variety of 2D and 3D datasets and discuss the performance of our analysis pipeline.« less

High performance hybrid functional Petri net simulations of biological pathway models on CUDA.

PubMed

Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.

Opportunities for Computational Discovery in Basic Energy Sciences

NASA Astrophysics Data System (ADS)

Pederson, Mark

2011-03-01

An overview of the broad-ranging support of computational physics and computational science within the Department of Energy Office of Science will be provided. Computation as the third branch of physics is supported by all six offices (Advanced Scientific Computing, Basic Energy, Biological and Environmental, Fusion Energy, High-Energy Physics, and Nuclear Physics). Support focuses on hardware, software and applications. Most opportunities within the fields of~condensed-matter physics, chemical-physics and materials sciences are supported by the Officeof Basic Energy Science (BES) or through partnerships between BES and the Office for Advanced Scientific Computing. Activities include radiation sciences, catalysis, combustion, materials in extreme environments, energy-storage materials, light-harvesting and photovoltaics, solid-state lighting and superconductivity.~ A summary of two recent reports by the computational materials and chemical communities on the role of computation during the next decade will be provided. ~In addition to materials and chemistry challenges specific to energy sciences, issues identified~include a focus on the role of the domain scientist in integrating, expanding and sustaining applications-oriented capabilities on evolving high-performance computing platforms and on the role of computation in accelerating the development of innovative technologies. ~~

Personal supercomputing by using transputer and Intel 80860 in plasma engineering

NASA Astrophysics Data System (ADS)

Ido, S.; Aoki, K.; Ishine, M.; Kubota, M.

1992-09-01

Transputer (T800) and 64-bit RISC Intel 80860 (i860) added on a personal computer can be used as an accelerator. When 32-bit T800s in a parallel system or 64-bit i860s are used, scientific calculations are carried out several ten times as fast as in the case of commonly used 32-bit personal computers or UNIX workstations. Benchmark tests and examples of physical simulations using T800s and i860 are reported.

Genten: Software for Generalized Tensor Decompositions v. 1.0.0

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

Phipps, Eric T.; Kolda, Tamara G.; Dunlavy, Daniel

Tensors, or multidimensional arrays, are a powerful mathematical means of describing multiway data. This software provides computational means for decomposing or approximating a given tensor in terms of smaller tensors of lower dimension, focusing on decomposition of large, sparse tensors. These techniques have applications in many scientific areas, including signal processing, linear algebra, computer vision, numerical analysis, data mining, graph analysis, neuroscience and more. The software is designed to take advantage of parallelism present emerging computer architectures such has multi-core CPUs, many-core accelerators such as the Intel Xeon Phi, and computation-oriented GPUs to enable efficient processing of large tensors.

A Modular Environment for Geophysical Inversion and Run-time Autotuning using Heterogeneous Computing Systems

NASA Astrophysics Data System (ADS)

Myre, Joseph M.

Heterogeneous computing systems have recently come to the forefront of the High-Performance Computing (HPC) community's interest. HPC computer systems that incorporate special purpose accelerators, such as Graphics Processing Units (GPUs), are said to be heterogeneous. Large scale heterogeneous computing systems have consistently ranked highly on the Top500 list since the beginning of the heterogeneous computing trend. By using heterogeneous computing systems that consist of both general purpose processors and special- purpose accelerators, the speed and problem size of many simulations could be dramatically increased. Ultimately this results in enhanced simulation capabilities that allows, in some cases for the first time, the execution of parameter space and uncertainty analyses, model optimizations, and other inverse modeling techniques that are critical for scientific discovery and engineering analysis. However, simplifying the usage and optimization of codes for heterogeneous computing systems remains a challenge. This is particularly true for scientists and engineers for whom understanding HPC architectures and undertaking performance analysis may not be primary research objectives. To enable scientists and engineers to remain focused on their primary research objectives, a modular environment for geophysical inversion and run-time autotuning on heterogeneous computing systems is presented. This environment is composed of three major components: 1) CUSH---a framework for reducing the complexity of programming heterogeneous computer systems, 2) geophysical inversion routines which can be used to characterize physical systems, and 3) run-time autotuning routines designed to determine configurations of heterogeneous computing systems in an attempt to maximize the performance of scientific and engineering codes. Using three case studies, a lattice-Boltzmann method, a non-negative least squares inversion, and a finite-difference fluid flow method, it is shown that this environment provides scientists and engineers with means to reduce the programmatic complexity of their applications, to perform geophysical inversions for characterizing physical systems, and to determine high-performing run-time configurations of heterogeneous computing systems using a run-time autotuner.

A feasibility study on porting the community land model onto accelerators using OpenACC

DOE PAGES

Wang, Dali; Wu, Wei; Winkler, Frank; ...

2014-01-01

As environmental models (such as Accelerated Climate Model for Energy (ACME), Parallel Reactive Flow and Transport Model (PFLOTRAN), Arctic Terrestrial Simulator (ATS), etc.) became more and more complicated, we are facing enormous challenges regarding to porting those applications onto hybrid computing architecture. OpenACC appears as a very promising technology, therefore, we have conducted a feasibility analysis on porting the Community Land Model (CLM), a terrestrial ecosystem model within the Community Earth System Models (CESM)). Specifically, we used automatic function testing platform to extract a small computing kernel out of CLM, then we apply this kernel into the actually CLM dataflowmore » procedure, and investigate the strategy of data parallelization and the benefit of data movement provided by current implementation of OpenACC. Even it is a non-intensive kernel, on a single 16-core computing node, the performance (based on the actual computation time using one GPU) of OpenACC implementation is 2.3 time faster than that of OpenMP implementation using single OpenMP thread, but it is 2.8 times slower than the performance of OpenMP implementation using 16 threads. On multiple nodes, MPI_OpenACC implementation demonstrated very good scalability on up to 128 GPUs on 128 computing nodes. This study also provides useful information for us to look into the potential benefits of “deep copy” capability and “routine” feature of OpenACC standards. In conclusion, we believe that our experience on the environmental model, CLM, can be beneficial to many other scientific research programs who are interested to porting their large scale scientific code using OpenACC onto high-end computers, empowered by hybrid computing architecture.« less

Explicit integration with GPU acceleration for large kinetic networks

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

Brock, Benjamin; Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830; Belt, Andrew

2015-12-01

We demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. This orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems inmore » various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.« less

Higher-order ice-sheet modelling accelerated by multigrid on graphics cards

NASA Astrophysics Data System (ADS)

Brædstrup, Christian; Egholm, David

2013-04-01

Higher-order ice flow modelling is a very computer intensive process owing primarily to the nonlinear influence of the horizontal stress coupling. When applied for simulating long-term glacial landscape evolution, the ice-sheet models must consider very long time series, while both high temporal and spatial resolution is needed to resolve small effects. The use of higher-order and full stokes models have therefore seen very limited usage in this field. However, recent advances in graphics card (GPU) technology for high performance computing have proven extremely efficient in accelerating many large-scale scientific computations. The general purpose GPU (GPGPU) technology is cheap, has a low power consumption and fits into a normal desktop computer. It could therefore provide a powerful tool for many glaciologists working on ice flow models. Our current research focuses on utilising the GPU as a tool in ice-sheet and glacier modelling. To this extent we have implemented the Integrated Second-Order Shallow Ice Approximation (iSOSIA) equations on the device using the finite difference method. To accelerate the computations, the GPU solver uses a non-linear Red-Black Gauss-Seidel iterator coupled with a Full Approximation Scheme (FAS) multigrid setup to further aid convergence. The GPU finite difference implementation provides the inherent parallelization that scales from hundreds to several thousands of cores on newer cards. We demonstrate the efficiency of the GPU multigrid solver using benchmark experiments.

Accelerating scientific discovery : 2007 annual report.

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

Beckman, P.; Dave, P.; Drugan, C.

2008-11-14

As a gateway for scientific discovery, the Argonne Leadership Computing Facility (ALCF) works hand in hand with the world's best computational scientists to advance research in a diverse span of scientific domains, ranging from chemistry, applied mathematics, and materials science to engineering physics and life sciences. Sponsored by the U.S. Department of Energy's (DOE) Office of Science, researchers are using the IBM Blue Gene/L supercomputer at the ALCF to study and explore key scientific problems that underlie important challenges facing our society. For instance, a research team at the University of California-San Diego/ SDSC is studying the molecular basis ofmore » Parkinson's disease. The researchers plan to use the knowledge they gain to discover new drugs to treat the disease and to identify risk factors for other diseases that are equally prevalent. Likewise, scientists from Pratt & Whitney are using the Blue Gene to understand the complex processes within aircraft engines. Expanding our understanding of jet engine combustors is the secret to improved fuel efficiency and reduced emissions. Lessons learned from the scientific simulations of jet engine combustors have already led Pratt & Whitney to newer designs with unprecedented reductions in emissions, noise, and cost of ownership. ALCF staff members provide in-depth expertise and assistance to those using the Blue Gene/L and optimizing user applications. Both the Catalyst and Applications Performance Engineering and Data Analytics (APEDA) teams support the users projects. In addition to working with scientists running experiments on the Blue Gene/L, we have become a nexus for the broader global community. In partnership with the Mathematics and Computer Science Division at Argonne National Laboratory, we have created an environment where the world's most challenging computational science problems can be addressed. Our expertise in high-end scientific computing enables us to provide guidance for applications that are transitioning to petascale as well as to produce software that facilitates their development, such as the MPICH library, which provides a portable and efficient implementation of the MPI standard--the prevalent programming model for large-scale scientific applications--and the PETSc toolkit that provides a programming paradigm that eases the development of many scientific applications on high-end computers.« less

Science in the cloud (SIC): A use case in MRI connectomics

PubMed Central

Gorgolewski, Krzysztof J.; Kleissas, Dean; Roncal, William Gray; Litt, Brian; Wandell, Brian; Poldrack, Russel A.; Wiener, Martin; Vogelstein, R. Jacob; Burns, Randal

2017-01-01

Abstract Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools that drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called ‘science in the cloud’ (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results that will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended. PMID:28327935

Science in the cloud (SIC): A use case in MRI connectomics.

PubMed

Kiar, Gregory; Gorgolewski, Krzysztof J; Kleissas, Dean; Roncal, William Gray; Litt, Brian; Wandell, Brian; Poldrack, Russel A; Wiener, Martin; Vogelstein, R Jacob; Burns, Randal; Vogelstein, Joshua T

2017-05-01

Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools that drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called 'science in the cloud' (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results that will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended. © The Author 2017. Published by Oxford University Press.

Simulating Hydrologic Flow and Reactive Transport with PFLOTRAN and PETSc on Emerging Fine-Grained Parallel Computer Architectures

NASA Astrophysics Data System (ADS)

Mills, R. T.; Rupp, K.; Smith, B. F.; Brown, J.; Knepley, M.; Zhang, H.; Adams, M.; Hammond, G. E.

2017-12-01

As the high-performance computing community pushes towards the exascale horizon, power and heat considerations have driven the increasing importance and prevalence of fine-grained parallelism in new computer architectures. High-performance computing centers have become increasingly reliant on GPGPU accelerators and "manycore" processors such as the Intel Xeon Phi line, and 512-bit SIMD registers have even been introduced in the latest generation of Intel's mainstream Xeon server processors. The high degree of fine-grained parallelism and more complicated memory hierarchy considerations of such "manycore" processors present several challenges to existing scientific software. Here, we consider how the massively parallel, open-source hydrologic flow and reactive transport code PFLOTRAN - and the underlying Portable, Extensible Toolkit for Scientific Computation (PETSc) library on which it is built - can best take advantage of such architectures. We will discuss some key features of these novel architectures and our code optimizations and algorithmic developments targeted at them, and present experiences drawn from working with a wide range of PFLOTRAN benchmark problems on these architectures.

Manycore Performance-Portability: Kokkos Multidimensional Array Library

DOE PAGES

Edwards, H. Carter; Sunderland, Daniel; Porter, Vicki; ...

2012-01-01

Large, complex scientific and engineering application code have a significant investment in computational kernels to implement their mathematical models. Porting these computational kernels to the collection of modern manycore accelerator devices is a major challenge in that these devices have diverse programming models, application programming interfaces (APIs), and performance requirements. The Kokkos Array programming model provides library-based approach to implement computational kernels that are performance-portable to CPU-multicore and GPGPU accelerator devices. This programming model is based upon three fundamental concepts: (1) manycore compute devices each with its own memory space, (2) data parallel kernels and (3) multidimensional arrays. Kernel executionmore » performance is, especially for NVIDIA® devices, extremely dependent on data access patterns. Optimal data access pattern can be different for different manycore devices – potentially leading to different implementations of computational kernels specialized for different devices. The Kokkos Array programming model supports performance-portable kernels by (1) separating data access patterns from computational kernels through a multidimensional array API and (2) introduce device-specific data access mappings when a kernel is compiled. An implementation of Kokkos Array is available through Trilinos [Trilinos website, http://trilinos.sandia.gov/, August 2011].« less

Evaluating Multi-core Architectures through Accelerating the Three-Dimensional Lax–Wendroff Correction

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

You, Yang; Fu, Haohuan; Song, Shuaiwen

2014-07-18

Wave propagation forward modeling is a widely used computational method in oil and gas exploration. The iterative stencil loops in such problems have broad applications in scientific computing. However, executing such loops can be highly time time-consuming, which greatly limits application’s performance and power efficiency. In this paper, we accelerate the forward modeling technique on the latest multi-core and many-core architectures such as Intel Sandy Bridge CPUs, NVIDIA Fermi C2070 GPU, NVIDIA Kepler K20x GPU, and the Intel Xeon Phi Co-processor. For the GPU platforms, we propose two parallel strategies to explore the performance optimization opportunities for our stencil kernels.more » For Sandy Bridge CPUs and MIC, we also employ various optimization techniques in order to achieve the best.« less

Explicit integration with GPU acceleration for large kinetic networks

DOE PAGES

Brock, Benjamin; Belt, Andrew; Billings, Jay Jay; ...

2015-09-15

In this study, we demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. In addition, this orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies thatmore » important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.« less

Forward and adjoint spectral-element simulations of seismic wave propagation using hardware accelerators

NASA Astrophysics Data System (ADS)

Peter, Daniel; Videau, Brice; Pouget, Kevin; Komatitsch, Dimitri

2015-04-01

Improving the resolution of tomographic images is crucial to answer important questions on the nature of Earth's subsurface structure and internal processes. Seismic tomography is the most prominent approach where seismic signals from ground-motion records are used to infer physical properties of internal structures such as compressional- and shear-wave speeds, anisotropy and attenuation. Recent advances in regional- and global-scale seismic inversions move towards full-waveform inversions which require accurate simulations of seismic wave propagation in complex 3D media, providing access to the full 3D seismic wavefields. However, these numerical simulations are computationally very expensive and need high-performance computing (HPC) facilities for further improving the current state of knowledge. During recent years, many-core architectures such as graphics processing units (GPUs) have been added to available large HPC systems. Such GPU-accelerated computing together with advances in multi-core central processing units (CPUs) can greatly accelerate scientific applications. There are mainly two possible choices of language support for GPU cards, the CUDA programming environment and OpenCL language standard. CUDA software development targets NVIDIA graphic cards while OpenCL was adopted mainly by AMD graphic cards. In order to employ such hardware accelerators for seismic wave propagation simulations, we incorporated a code generation tool BOAST into an existing spectral-element code package SPECFEM3D_GLOBE. This allows us to use meta-programming of computational kernels and generate optimized source code for both CUDA and OpenCL languages, running simulations on either CUDA or OpenCL hardware accelerators. We show here applications of forward and adjoint seismic wave propagation on CUDA/OpenCL GPUs, validating results and comparing performances for different simulations and hardware usages.

Solving global shallow water equations on heterogeneous supercomputers

PubMed Central

Fu, Haohuan; Gan, Lin; Yang, Chao; Xue, Wei; Wang, Lanning; Wang, Xinliang; Huang, Xiaomeng; Yang, Guangwen

2017-01-01

The scientific demand for more accurate modeling of the climate system calls for more computing power to support higher resolutions, inclusion of more component models, more complicated physics schemes, and larger ensembles. As the recent improvements in computing power mostly come from the increasing number of nodes in a system and the integration of heterogeneous accelerators, how to scale the computing problems onto more nodes and various kinds of accelerators has become a challenge for the model development. This paper describes our efforts on developing a highly scalable framework for performing global atmospheric modeling on heterogeneous supercomputers equipped with various accelerators, such as GPU (Graphic Processing Unit), MIC (Many Integrated Core), and FPGA (Field Programmable Gate Arrays) cards. We propose a generalized partition scheme of the problem domain, so as to keep a balanced utilization of both CPU resources and accelerator resources. With optimizations on both computing and memory access patterns, we manage to achieve around 8 to 20 times speedup when comparing one hybrid GPU or MIC node with one CPU node with 12 cores. Using a customized FPGA-based data-flow engines, we see the potential to gain another 5 to 8 times improvement on performance. On heterogeneous supercomputers, such as Tianhe-1A and Tianhe-2, our framework is capable of achieving ideally linear scaling efficiency, and sustained double-precision performances of 581 Tflops on Tianhe-1A (using 3750 nodes) and 3.74 Pflops on Tianhe-2 (using 8644 nodes). Our study also provides an evaluation on the programming paradigm of various accelerator architectures (GPU, MIC, FPGA) for performing global atmospheric simulation, to form a picture about both the potential performance benefits and the programming efforts involved. PMID:28282428

Compiling for Application Specific Computational Acceleration in Reconfigurable Architectures Final Report CRADA No. TSB-2033-01

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

De Supinski, B.; Caliga, D.

2017-09-28

The primary objective of this project was to develop memory optimization technology to efficiently deliver data to, and distribute data within, the SRC-6's Field Programmable Gate Array- ("FPGA") based Multi-Adaptive Processors (MAPs). The hardware/software approach was to explore efficient MAP configurations and generate the compiler technology to exploit those configurations. This memory accessing technology represents an important step towards making reconfigurable symmetric multi-processor (SMP) architectures that will be a costeffective solution for large-scale scientific computing.

Accelerating the Pace of Protein Functional Annotation With Intel Xeon Phi Coprocessors.

PubMed

Feinstein, Wei P; Moreno, Juana; Jarrell, Mark; Brylinski, Michal

2015-06-01

Intel Xeon Phi is a new addition to the family of powerful parallel accelerators. The range of its potential applications in computationally driven research is broad; however, at present, the repository of scientific codes is still relatively limited. In this study, we describe the development and benchmarking of a parallel version of eFindSite, a structural bioinformatics algorithm for the prediction of ligand-binding sites in proteins. Implemented for the Intel Xeon Phi platform, the parallelization of the structure alignment portion of eFindSite using pragma-based OpenMP brings about the desired performance improvements, which scale well with the number of computing cores. Compared to a serial version, the parallel code runs 11.8 and 10.1 times faster on the CPU and the coprocessor, respectively; when both resources are utilized simultaneously, the speedup is 17.6. For example, ligand-binding predictions for 501 benchmarking proteins are completed in 2.1 hours on a single Stampede node equipped with the Intel Xeon Phi card compared to 3.1 hours without the accelerator and 36.8 hours required by a serial version. In addition to the satisfactory parallel performance, porting existing scientific codes to the Intel Xeon Phi architecture is relatively straightforward with a short development time due to the support of common parallel programming models by the coprocessor. The parallel version of eFindSite is freely available to the academic community at www.brylinski.org/efindsite.

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study.

PubMed

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-03-28

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation.

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study

PubMed Central

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-01-01

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation. PMID:28350358

Artificial Intelligence and Virology - quo vadis

PubMed Central

Shapshak, Paul; Somboonwit, Charurut; Sinnott, John T.

2017-01-01

Artificial Intelligence (AI), robotics, co-robotics (cobots), quantum computers (QC), include surges of scientific endeavor to produce machines (mechanical and software) among numerous types and constructions that are accelerating progress to defeat infectious diseases. There is a plethora of additional applications and uses of these methodologies and technologies for the understanding of biomedicine through bioinformation discovery. Therefore, we briefly outline the use of such techniques in virology. PMID:29379259

Artificial Intelligence and Virology - quo vadis.

PubMed

Shapshak, Paul; Somboonwit, Charurut; Sinnott, John T

2017-01-01

Artificial Intelligence (AI), robotics, co-robotics (cobots), quantum computers (QC), include surges of scientific endeavor to produce machines (mechanical and software) among numerous types and constructions that are accelerating progress to defeat infectious diseases. There is a plethora of additional applications and uses of these methodologies and technologies for the understanding of biomedicine through bioinformation discovery. Therefore, we briefly outline the use of such techniques in virology.

Toward the Geoscience Paper of the Future: Best practices for documenting and sharing research from data to software to provenance

NASA Astrophysics Data System (ADS)

Gil, Yolanda; David, Cédric H.; Demir, Ibrahim; Essawy, Bakinam T.; Fulweiler, Robinson W.; Goodall, Jonathan L.; Karlstrom, Leif; Lee, Huikyo; Mills, Heath J.; Oh, Ji-Hyun; Pierce, Suzanne A.; Pope, Allen; Tzeng, Mimi W.; Villamizar, Sandra R.; Yu, Xuan

2016-10-01

Geoscientists now live in a world rich with digital data and methods, and their computational research cannot be fully captured in traditional publications. The Geoscience Paper of the Future (GPF) presents an approach to fully document, share, and cite all their research products including data, software, and computational provenance. This article proposes best practices for GPF authors to make data, software, and methods openly accessible, citable, and well documented. The publication of digital objects empowers scientists to manage their research products as valuable scientific assets in an open and transparent way that enables broader access by other scientists, students, decision makers, and the public. Improving documentation and dissemination of research will accelerate the pace of scientific discovery by improving the ability of others to build upon published work.

Accelerator Based Tools of Stockpile Stewardship

NASA Astrophysics Data System (ADS)

Seestrom, Susan

2017-01-01

The Manhattan Project had to solve difficult challenges in physics and materials science. During the cold war a large nuclear stockpile was developed. In both cases, the approach was largely empirical. Today that stockpile must be certified without nuclear testing, a task that becomes more difficult as the stockpile ages. I will discuss the role of modern accelerator based experiments, such as x-ray radiography, proton radiography, neutron and nuclear physics experiments, in stockpile stewardship. These new tools provide data of exceptional sensitivity and are answering questions about the stockpile, improving our scientific understanding, and providing validation for the computer simulations that are relied upon to certify todays' stockpile.

Medical Applications at CERN and the ENLIGHT Network

PubMed Central

Dosanjh, Manjit; Cirilli, Manuela; Myers, Steve; Navin, Sparsh

2016-01-01

State-of-the-art techniques derived from particle accelerators, detectors, and physics computing are routinely used in clinical practice and medical research centers: from imaging technologies to dedicated accelerators for cancer therapy and nuclear medicine, simulations, and data analytics. Principles of particle physics themselves are the foundation of a cutting edge radiotherapy technique for cancer treatment: hadron therapy. This article is an overview of the involvement of CERN, the European Organization for Nuclear Research, in medical applications, with specific focus on hadron therapy. It also presents the history, achievements, and future scientific goals of the European Network for Light Ion Hadron Therapy, whose co-ordination office is at CERN. PMID:26835422

Medical Applications at CERN and the ENLIGHT Network.

PubMed

Dosanjh, Manjit; Cirilli, Manuela; Myers, Steve; Navin, Sparsh

2016-01-01

State-of-the-art techniques derived from particle accelerators, detectors, and physics computing are routinely used in clinical practice and medical research centers: from imaging technologies to dedicated accelerators for cancer therapy and nuclear medicine, simulations, and data analytics. Principles of particle physics themselves are the foundation of a cutting edge radiotherapy technique for cancer treatment: hadron therapy. This article is an overview of the involvement of CERN, the European Organization for Nuclear Research, in medical applications, with specific focus on hadron therapy. It also presents the history, achievements, and future scientific goals of the European Network for Light Ion Hadron Therapy, whose co-ordination office is at CERN.

Implementing Molecular Dynamics on Hybrid High Performance Computers - Three-Body Potentials

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

Brown, W Michael; Yamada, Masako

The use of coprocessors or accelerators such as graphics processing units (GPUs) has become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power re- quirements. Hybrid high-performance computers, defined as machines with nodes containing more than one type of floating-point processor (e.g. CPU and GPU), are now becoming more prevalent due to these advantages. Although there has been extensive research into methods to efficiently use accelerators to improve the performance of molecular dynamics (MD) employing pairwise potential energy models, little is reported in the literature for models that includemore » many-body effects. 3-body terms are required for many popular potentials such as MEAM, Tersoff, REBO, AIREBO, Stillinger-Weber, Bond-Order Potentials, and others. Because the per-atom simulation times are much higher for models incorporating 3-body terms, there is a clear need for efficient algo- rithms usable on hybrid high performance computers. Here, we report a shared-memory force-decomposition for 3-body potentials that avoids memory conflicts to allow for a deterministic code with substantial performance improvements on hybrid machines. We describe modifications necessary for use in distributed memory MD codes and show results for the simulation of water with Stillinger-Weber on the hybrid Titan supercomputer. We compare performance of the 3-body model to the SPC/E water model when using accelerators. Finally, we demonstrate that our approach can attain a speedup of 5.1 with acceleration on Titan for production simulations to study water droplet freezing on a surface.« less

Advancing Capabilities for Understanding the Earth System Through Intelligent Systems, the NSF Perspective

NASA Astrophysics Data System (ADS)

Gil, Y.; Zanzerkia, E. E.; Munoz-Avila, H.

2015-12-01

The National Science Foundation (NSF) Directorate for Geosciences (GEO) and Directorate for Computer and Information Science (CISE) acknowledge the significant scientific challenges required to understand the fundamental processes of the Earth system, within the atmospheric and geospace, Earth, ocean and polar sciences, and across those boundaries. A broad view of the opportunities and directions for GEO are described in the report "Dynamic Earth: GEO imperative and Frontiers 2015-2020." Many of the aspects of geosciences research, highlighted both in this document and other community grand challenges, pose novel problems for researchers in intelligent systems. Geosciences research will require solutions for data-intensive science, advanced computational capabilities, and transformative concepts for visualizing, using, analyzing and understanding geo phenomena and data. Opportunities for the scientific community to engage in addressing these challenges are available and being developed through NSF's portfolio of investments and activities. The NSF-wide initiative, Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21), looks to accelerate research and education through new capabilities in data, computation, software and other aspects of cyberinfrastructure. EarthCube, a joint program between GEO and the Advanced Cyberinfrastructure Division, aims to create a well-connected and facile environment to share data and knowledge in an open, transparent, and inclusive manner, thus accelerating our ability to understand and predict the Earth system. EarthCube's mission opens an opportunity for collaborative research on novel information systems enhancing and supporting geosciences research efforts. NSF encourages true, collaborative partnerships between scientists in computer sciences and the geosciences to meet these challenges.

BarraCUDA - a fast short read sequence aligner using graphics processing units

PubMed Central

2012-01-01

Background With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. Findings Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. Conclusions BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available from http://seqbarracuda.sf.net PMID:22244497

A Secure Web Application Providing Public Access to High-Performance Data Intensive Scientific Resources - ScalaBLAST Web Application

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

Curtis, Darren S.; Peterson, Elena S.; Oehmen, Chris S.

2008-05-04

This work presents the ScalaBLAST Web Application (SWA), a web based application implemented using the PHP script language, MySQL DBMS, and Apache web server under a GNU/Linux platform. SWA is an application built as part of the Data Intensive Computer for Complex Biological Systems (DICCBS) project at the Pacific Northwest National Laboratory (PNNL). SWA delivers accelerated throughput of bioinformatics analysis via high-performance computing through a convenient, easy-to-use web interface. This approach greatly enhances emerging fields of study in biology such as ontology-based homology, and multiple whole genome comparisons which, in the absence of a tool like SWA, require a heroicmore » effort to overcome the computational bottleneck associated with genome analysis. The current version of SWA includes a user account management system, a web based user interface, and a backend process that generates the files necessary for the Internet scientific community to submit a ScalaBLAST parallel processing job on a dedicated cluster.« less

Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

NASA Astrophysics Data System (ADS)

Junghans, Christoph; Mniszewski, Susan; Voter, Arthur; Perez, Danny; Eidenbenz, Stephan

2014-03-01

We present an example of a new class of tools that we call application simulators, parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation (PDES). We demonstrate our approach with a TADSim application simulator that models the Temperature Accelerated Dynamics (TAD) method, which is an algorithmically complex member of the Accelerated Molecular Dynamics (AMD) family. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We further extend TADSim to model algorithm extensions to standard TAD, such as speculative spawning of the compute-bound stages of the algorithm, and predict performance improvements without having to implement such a method. Focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights into the TAD algorithm behavior and suggested extensions to the TAD method.

Predicting future discoveries from current scientific literature.

PubMed

Petrič, Ingrid; Cestnik, Bojan

2014-01-01

Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If enough scientific evidence is already published for the association of such findings, they can be considered as scientific hypotheses. In this chapter, we describe a method for the computer-aided generation of such hypotheses based on the existing scientific literature. Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.

Software Innovations Speed Scientific Computing

NASA Technical Reports Server (NTRS)

2012-01-01

To help reduce the time needed to analyze data from missions like those studying the Sun, Goddard Space Flight Center awarded SBIR funding to Tech-X Corporation of Boulder, Colorado. That work led to commercial technologies that help scientists accelerate their data analysis tasks. Thanks to its NASA work, the company doubled its number of headquarters employees to 70 and generated about $190,000 in revenue from its NASA-derived products.

!CHAOS: A cloud of controls

NASA Astrophysics Data System (ADS)

Angius, S.; Bisegni, C.; Ciuffetti, P.; Di Pirro, G.; Foggetta, L. G.; Galletti, F.; Gargana, R.; Gioscio, E.; Maselli, D.; Mazzitelli, G.; Michelotti, A.; Orrù, R.; Pistoni, M.; Spagnoli, F.; Spigone, D.; Stecchi, A.; Tonto, T.; Tota, M. A.; Catani, L.; Di Giulio, C.; Salina, G.; Buzzi, P.; Checcucci, B.; Lubrano, P.; Piccini, M.; Fattibene, E.; Michelotto, M.; Cavallaro, S. R.; Diana, B. F.; Enrico, F.; Pulvirenti, S.

2016-01-01

The paper is aimed to present the !CHAOS open source project aimed to develop a prototype of a national private Cloud Computing infrastructure, devoted to accelerator control systems and large experiments of High Energy Physics (HEP). The !CHAOS project has been financed by MIUR (Italian Ministry of Research and Education) and aims to develop a new concept of control system and data acquisition framework by providing, with a high level of aaabstraction, all the services needed for controlling and managing a large scientific, or non-scientific, infrastructure. A beta version of the !CHAOS infrastructure will be released at the end of December 2015 and will run on private Cloud infrastructures based on OpenStack.

IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research.

PubMed

Chen, Ying; Elenee Argentinis, J D; Weber, Griff

2016-04-01

Life sciences researchers are under pressure to innovate faster than ever. Big data offer the promise of unlocking novel insights and accelerating breakthroughs. Ironically, although more data are available than ever, only a fraction is being integrated, understood, and analyzed. The challenge lies in harnessing volumes of data, integrating the data from hundreds of sources, and understanding their various formats. New technologies such as cognitive computing offer promise for addressing this challenge because cognitive solutions are specifically designed to integrate and analyze big datasets. Cognitive solutions can understand different types of data such as lab values in a structured database or the text of a scientific publication. Cognitive solutions are trained to understand technical, industry-specific content and use advanced reasoning, predictive modeling, and machine learning techniques to advance research faster. Watson, a cognitive computing technology, has been configured to support life sciences research. This version of Watson includes medical literature, patents, genomics, and chemical and pharmacological data that researchers would typically use in their work. Watson has also been developed with specific comprehension of scientific terminology so it can make novel connections in millions of pages of text. Watson has been applied to a few pilot studies in the areas of drug target identification and drug repurposing. The pilot results suggest that Watson can accelerate identification of novel drug candidates and novel drug targets by harnessing the potential of big data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Institute for scientific computing research;fiscal year 1999 annual report

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

Keyes, D

2000-03-28

Large-scale scientific computation, and all of the disciplines that support it and help to validate it, have been placed at the focus of Lawrence Livermore National Laboratory by the Accelerated Strategic Computing Initiative (ASCI). The Laboratory operates the computer with the highest peak performance in the world and has undertaken some of the largest and most compute-intensive simulations ever performed. Computers at the architectural extremes, however, are notoriously difficult to use efficiently. Even such successes as the Laboratory's two Bell Prizes awarded in November 1999 only emphasize the need for much better ways of interacting with the results of large-scalemore » simulations. Advances in scientific computing research have, therefore, never been more vital to the core missions of the Laboratory than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, the Laboratory must engage researchers at many academic centers of excellence. In FY 1999, the Institute for Scientific Computing Research (ISCR) has expanded the Laboratory's bridge to the academic community in the form of collaborative subcontracts, visiting faculty, student internships, a workshop, and a very active seminar series. ISCR research participants are integrated almost seamlessly with the Laboratory's Center for Applied Scientific Computing (CASC), which, in turn, addresses computational challenges arising throughout the Laboratory. Administratively, the ISCR flourishes under the Laboratory's University Relations Program (URP). Together with the other four Institutes of the URP, it must navigate a course that allows the Laboratory to benefit from academic exchanges while preserving national security. Although FY 1999 brought more than its share of challenges to the operation of an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and well worth the continued effort. A change of administration for the ISCR occurred during FY 1999. Acting Director John Fitzgerald retired from LLNL in August after 35 years of service, including the last two at helm of the ISCR. David Keyes, who has been a regular visitor in conjunction with ASCI scalable algorithms research since October 1997, overlapped with John for three months and serves half-time as the new Acting Director.« less

Accelerating Science with the NERSC Burst Buffer Early User Program

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

Bhimji, Wahid; Bard, Debbie; Romanus, Melissa

NVRAM-based Burst Buffers are an important part of the emerging HPC storage landscape. The National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory recently installed one of the first Burst Buffer systems as part of its new Cori supercomputer, collaborating with Cray on the development of the DataWarp software. NERSC has a diverse user base comprised of over 6500 users in 700 different projects spanning a wide variety of scientific computing applications. The use-cases of the Burst Buffer at NERSC are therefore also considerable and diverse. We describe here performance measurements and lessons learned from the Burstmore » Buffer Early User Program at NERSC, which selected a number of research projects to gain early access to the Burst Buffer and exercise its capability to enable new scientific advancements. To the best of our knowledge this is the first time a Burst Buffer has been stressed at scale by diverse, real user workloads and therefore these lessons will be of considerable benefit to shaping the developing use of Burst Buffers at HPC centers.« less

GPU Acceleration of the Locally Selfconsistent Multiple Scattering Code for First Principles Calculation of the Ground State and Statistical Physics of Materials

NASA Astrophysics Data System (ADS)

Eisenbach, Markus

The Locally Self-consistent Multiple Scattering (LSMS) code solves the first principles Density Functional theory Kohn-Sham equation for a wide range of materials with a special focus on metals, alloys and metallic nano-structures. It has traditionally exhibited near perfect scalability on massively parallel high performance computer architectures. We present our efforts to exploit GPUs to accelerate the LSMS code to enable first principles calculations of O(100,000) atoms and statistical physics sampling of finite temperature properties. Using the Cray XK7 system Titan at the Oak Ridge Leadership Computing Facility we achieve a sustained performance of 14.5PFlop/s and a speedup of 8.6 compared to the CPU only code. This work has been sponsored by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Material Sciences and Engineering Division and by the Office of Advanced Scientific Computing. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

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.

An Accelerated Recursive Doubling Algorithm for Block Tridiagonal Systems

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

Seal, Sudip K

2014-01-01

Block tridiagonal systems of linear equations arise in a wide variety of scientific and engineering applications. Recursive doubling algorithm is a well-known prefix computation-based numerical algorithm that requires O(M^3(N/P + log P)) work to compute the solution of a block tridiagonal system with N block rows and block size M on P processors. In real-world applications, solutions of tridiagonal systems are most often sought with multiple, often hundreds and thousands, of different right hand sides but with the same tridiagonal matrix. Here, we show that a recursive doubling algorithm is sub-optimal when computing solutions of block tridiagonal systems with multiplemore » right hand sides and present a novel algorithm, called the accelerated recursive doubling algorithm, that delivers O(R) improvement when solving block tridiagonal systems with R distinct right hand sides. Since R is typically about 100 1000, this improvement translates to very significant speedups in practice. Detailed complexity analyses of the new algorithm with empirical confirmation of runtime improvements are presented. To the best of our knowledge, this algorithm has not been reported before in the literature.« less

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.

On improving the algorithm efficiency in the particle-particle force calculations

NASA Astrophysics Data System (ADS)

Kozynchenko, Alexander I.; Kozynchenko, Sergey A.

2016-09-01

The problem of calculating inter-particle forces in the particle-particle (PP) simulation models takes an important place in scientific computing. Such simulation models are used in diverse scientific applications arising in astrophysics, plasma physics, particle accelerators, etc., where the long-range forces are considered. The inverse-square laws such as Coulomb's law of electrostatic forces and Newton's law of universal gravitation are the examples of laws pertaining to the long-range forces. The standard naïve PP method outlined, for example, by Hockney and Eastwood [1] is straightforward, processing all pairs of particles in a double nested loop. The PP algorithm provides the best accuracy of all possible methods, but its computational complexity is O (Np2), where Np is a total number of particles involved. Too low efficiency of the PP algorithm seems to be the challenging issue in some cases where the high accuracy is required. An example can be taken from the charged particle beam dynamics where, under computing the own space charge of the beam, so-called macro-particles are used (see e.g., Humphries Jr. [2], Kozynchenko and Svistunov [3]).

Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2017-12-01

Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case studies to highlight how Cloud CI streamlines the process for setting up an interactive decision support system. Moreover, advances in artificial intelligence offer new techniques for old problems from integrating data to adaptive sensing or from interactive dashboards to optimizing multi-attribute problems. The combination of scientific expertise, flexible cloud computing solutions, and intelligent systems opens new research horizons.

Molecular dynamics simulations through GPU video games technologies

PubMed Central

Loukatou, Styliani; Papageorgiou, Louis; Fakourelis, Paraskevas; Filntisi, Arianna; Polychronidou, Eleftheria; Bassis, Ioannis; Megalooikonomou, Vasileios; Makałowski, Wojciech; Vlachakis, Dimitrios; Kossida, Sophia

2016-01-01

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations. PMID:27525251

Brookhaven highlights for fiscal year 1991, October 1, 1990--September 30, 1991

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

Rowe, M.S.; Cohen, A.; Greenberg, D.

1991-12-31

This report highlights Brookhaven National Laboratory`s activities for fiscal year 1991. Topics from the four research divisions: Computing and Communications, Instrumentation, Reactors, and Safety and Environmental Protection are presented. The research programs at Brookhaven are diverse, as is reflected by the nine different scientific departments: Accelerator Development, Alternating Gradient Synchrotron, Applied Science, Biology, Chemistry, Medical, National Synchrotron Light Source, Nuclear Energy, and Physics. Administrative and managerial information about Brookhaven are also disclosed. (GHH)

Brookhaven highlights for fiscal year 1991, October 1, 1990--September 30, 1991

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

Rowe, M.S.; Cohen, A.; Greenberg, D.

1991-01-01

This report highlights Brookhaven National Laboratory's activities for fiscal year 1991. Topics from the four research divisions: Computing and Communications, Instrumentation, Reactors, and Safety and Environmental Protection are presented. The research programs at Brookhaven are diverse, as is reflected by the nine different scientific departments: Accelerator Development, Alternating Gradient Synchrotron, Applied Science, Biology, Chemistry, Medical, National Synchrotron Light Source, Nuclear Energy, and Physics. Administrative and managerial information about Brookhaven are also disclosed. (GHH)

Automated and Assistive Tools for Accelerated Code migration of Scientific Computing on to Heterogeneous MultiCore Systems

DTIC Science & Technology

2017-04-13

modelling code, a parallel benchmark , and a communication avoiding version of the QR algorithm. Further, several improvements to the OmpSs model were...movement; and a port of the dynamic load balancing library to OmpSs. Finally, several updates to the tools infrastructure were accomplished, including: an...OmpSs: a basic algorithm on image processing applications, a mini application representative of an ocean modelling code, a parallel benchmark , and a

US EPA - A*Star Partnership - Accelerating the Acceptance of ...

EPA Pesticide Factsheets

The path for incorporating new alternative methods and technologies into quantitative chemical risk assessment poses a diverse set of scientific challenges. Some of these challenges include development of relevant and predictive test systems and computational models to integrate and extrapolate experimental data, and rapid characterization and acceptance of these systems and models. The series of presentations will highlight a collaborative effort between the U.S. Environmental Protection Agency (EPA) and the Agency for Science, Technology and Research (A*STAR) that is focused on developing and applying experimental and computational models for predicting chemical-induced liver and kidney toxicity, brain angiogenesis, and blood-brain-barrier formation. In addressing some of these challenges, the U.S. EPA and A*STAR collaboration will provide a glimpse of what chemical risk assessments could look like in the 21st century. Presentation on US EPA – A*STAR Partnership at international symposium on Accelerating the acceptance of next-generation sciences and their application to regulatory risk assessment in Singapore.

Virtual Observatory and Distributed Data Mining

NASA Astrophysics Data System (ADS)

Borne, Kirk D.

2012-03-01

New modes of discovery are enabled by the growth of data and computational resources (i.e., cyberinfrastructure) in the sciences. This cyberinfrastructure includes structured databases, virtual observatories (distributed data, as described in Section 20.2.1 of this chapter), high-performance computing (petascale machines), distributed computing (e.g., the Grid, the Cloud, and peer-to-peer networks), intelligent search and discovery tools, and innovative visualization environments. Data streams from experiments, sensors, and simulations are increasingly complex and growing in volume. This is true in most sciences, including astronomy, climate simulations, Earth observing systems, remote sensing data collections, and sensor networks. At the same time, we see an emerging confluence of new technologies and approaches to science, most clearly visible in the growing synergism of the four modes of scientific discovery: sensors-modeling-computing-data (Eastman et al. 2005). This has been driven by numerous developments, including the information explosion, development of large-array sensors, acceleration in high-performance computing (HPC) power, advances in algorithms, and efficient modeling techniques. Among these, the most extreme is the growth in new data. Specifically, the acquisition of data in all scientific disciplines is rapidly accelerating and causing a data glut (Bell et al. 2007). It has been estimated that data volumes double every year—for example, the NCSA (National Center for Supercomputing Applications) reported that their users cumulatively generated one petabyte of data over the first 19 years of NCSA operation, but they then generated their next one petabyte in the next year alone, and the data production has been growing by almost 100% each year after that (Butler 2008). The NCSA example is just one of many demonstrations of the exponential (annual data-doubling) growth in scientific data collections. In general, this putative data-doubling is an inevitable result of several compounding factors: the proliferation of data-generating devices, sensors, projects, and enterprises; the 18-month doubling of the digital capacity of these microprocessor-based sensors and devices (commonly referred to as "Moore’s law"); the move to digital for nearly all forms of information; the increase in human-generated data (both unstructured information on the web and structured data from experiments, models, and simulation); and the ever-expanding capability of higher density media to hold greater volumes of data (i.e., data production expands to fill the available storage space). These factors are consequently producing an exponential data growth rate, which will soon (if not already) become an insurmountable technical challenge even with the great advances in computation and algorithms. This technical challenge is compounded by the ever-increasing geographic dispersion of important data sources—the data collections are not stored uniformly at a single location, or with a single data model, or in uniform formats and modalities (e.g., images, databases, structured and unstructured files, and XML data sets)—the data are in fact large, distributed, heterogeneous, and complex. The greatest scientific research challenge with these massive distributed data collections is consequently extracting all of the rich information and knowledge content contained therein, thus requiring new approaches to scientific research. This emerging data-intensive and data-oriented approach to scientific research is sometimes called discovery informatics or X-informatics (where X can be any science, such as bio, geo, astro, chem, eco, or anything; Agresti 2003; Gray 2003; Borne 2010). This data-oriented approach to science is now recognized by some (e.g., Mahootian and Eastman 2009; Hey et al. 2009) as the fourth paradigm of research, following (historically) experiment/observation, modeling/analysis, and computational science.

Recent Advances in X-ray Cone-beam Computed Laminography.

PubMed

O'Brien, Neil S; Boardman, Richard P; Sinclair, Ian; Blumensath, Thomas

2016-10-06

X-ray computed tomography is an established volume imaging technique used routinely in medical diagnosis, industrial non-destructive testing, and a wide range of scientific fields. Traditionally, computed tomography uses scanning geometries with a single axis of rotation together with reconstruction algorithms specifically designed for this setup. Recently there has however been increasing interest in more complex scanning geometries. These include so called X-ray computed laminography systems capable of imaging specimens with large lateral dimensions or large aspect ratios, neither of which are well suited to conventional CT scanning procedures. Developments throughout this field have thus been rapid, including the introduction of novel system trajectories, the application and refinement of various reconstruction methods, and the use of recently developed computational hardware and software techniques to accelerate reconstruction times. Here we examine the advances made in the last several years and consider their impact on the state of the art.

[HyperPsych--resources for medicine and psychology on the World Wide Web].

PubMed

Laszig, P

1997-07-01

Progress in the research of interactive communication technology and the acceleration of processing and transmitting information have promoted the development of computer networks allowing global access to scientific information and services. The recently most well-known net is the internet. Based on its integrative structure as a communication-directed as well as an information-directed medium, the internet helps researchers design scientific research. Especially medicine and psychology as information-dependent scientific disciplines may profit by using this technological offer. As a method to coordinate to the vast amount of medical and psychological data around the globe and to communicate with researchers world-wide, it enhances innovative possibilities for research, diagnosis and therapy. Currently, the World Wide Web is regarded as the most user-friendly and practical of all the internet resources. Based on a systematic introduction to the applications of the WWW, this article discusses relevant resources, points out possibilities and limits of network-supported scientific research and proposes many uses of this new medium.

The Science DMZ: A Network Design Pattern for Data-Intensive Science

DOE PAGES

Dart, Eli; Rotman, Lauren; Tierney, Brian; ...

2014-01-01

The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The Science DMZ paradigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers andmore » research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.« less

Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations

PubMed Central

Gokmen, Tayfun; Vlasov, Yurii

2016-01-01

In recent years, deep neural networks (DNN) have demonstrated significant business impact in large scale analysis and classification tasks such as speech recognition, visual object detection, pattern extraction, etc. Training of large DNNs, however, is universally considered as time consuming and computationally intensive task that demands datacenter-scale computational resources recruited for many days. Here we propose a concept of resistive processing unit (RPU) devices that can potentially accelerate DNN training by orders of magnitude while using much less power. The proposed RPU device can store and update the weight values locally thus minimizing data movement during training and allowing to fully exploit the locality and the parallelism of the training algorithm. We evaluate the effect of various RPU device features/non-idealities and system parameters on performance in order to derive the device and system level specifications for implementation of an accelerator chip for DNN training in a realistic CMOS-compatible technology. For large DNNs with about 1 billion weights this massively parallel RPU architecture can achieve acceleration factors of 30, 000 × compared to state-of-the-art microprocessors while providing power efficiency of 84, 000 GigaOps∕s∕W. Problems that currently require days of training on a datacenter-size cluster with thousands of machines can be addressed within hours on a single RPU accelerator. A system consisting of a cluster of RPU accelerators will be able to tackle Big Data problems with trillions of parameters that is impossible to address today like, for example, natural speech recognition and translation between all world languages, real-time analytics on large streams of business and scientific data, integration, and analysis of multimodal sensory data flows from a massive number of IoT (Internet of Things) sensors. PMID:27493624

Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations.

PubMed

Gokmen, Tayfun; Vlasov, Yurii

2016-01-01

In recent years, deep neural networks (DNN) have demonstrated significant business impact in large scale analysis and classification tasks such as speech recognition, visual object detection, pattern extraction, etc. Training of large DNNs, however, is universally considered as time consuming and computationally intensive task that demands datacenter-scale computational resources recruited for many days. Here we propose a concept of resistive processing unit (RPU) devices that can potentially accelerate DNN training by orders of magnitude while using much less power. The proposed RPU device can store and update the weight values locally thus minimizing data movement during training and allowing to fully exploit the locality and the parallelism of the training algorithm. We evaluate the effect of various RPU device features/non-idealities and system parameters on performance in order to derive the device and system level specifications for implementation of an accelerator chip for DNN training in a realistic CMOS-compatible technology. For large DNNs with about 1 billion weights this massively parallel RPU architecture can achieve acceleration factors of 30, 000 × compared to state-of-the-art microprocessors while providing power efficiency of 84, 000 GigaOps∕s∕W. Problems that currently require days of training on a datacenter-size cluster with thousands of machines can be addressed within hours on a single RPU accelerator. A system consisting of a cluster of RPU accelerators will be able to tackle Big Data problems with trillions of parameters that is impossible to address today like, for example, natural speech recognition and translation between all world languages, real-time analytics on large streams of business and scientific data, integration, and analysis of multimodal sensory data flows from a massive number of IoT (Internet of Things) sensors.

Special issue on the "Consortium for Advanced Simulation of Light Water Reactors Research and Development Progress"

NASA Astrophysics Data System (ADS)

Turinsky, Paul J.; Martin, William R.

2017-04-01

In this special issue of the Journal of Computational Physics, the research and development completed at the time of manuscript submission by the Consortium for Advanced Simulation of Light Water Reactors (CASL) is presented. CASL is the first of several Energy Innovation Hubs that have been created by the Department of Energy. The Hubs are modeled after the strong scientific management characteristics of the Manhattan Project and AT&T Bell Laboratories, and function as integrated research centers that combine basic and applied research with engineering to accelerate scientific discovery that addresses critical energy issues. Lifetime of a Hub is expected to be five or ten years depending upon performance, with CASL being granted a ten year lifetime.

Developing science gateways for drug discovery in a grid environment.

PubMed

Pérez-Sánchez, Horacio; Rezaei, Vahid; Mezhuyev, Vitaliy; Man, Duhu; Peña-García, Jorge; den-Haan, Helena; Gesing, Sandra

2016-01-01

Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources. To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

The Center for Nanophase Materials Sciences

NASA Astrophysics Data System (ADS)

Lowndes, Douglas

2005-03-01

The Center for Nanophase Materials Sciences (CNMS) located at Oak Ridge National Laboratory (ORNL) will be the first DOE Nanoscale Science Research Center to begin operation, with construction to be completed in April 2005 and initial operations in October 2005. The CNMS' scientific program has been developed through workshops with the national community, with the goal of creating a highly collaborative research environment to accelerate discovery and drive technological advances. Research at the CNMS is organized under seven Scientific Themes selected to address challenges to understanding and to exploit particular ORNL strengths (see http://cnms.ornl.govhttp://cnms.ornl.gov). These include extensive synthesis and characterization capabilities for soft, hard, nanostructured, magnetic and catalytic materials and their composites; neutron scattering at the Spallation Neutron Source and High Flux Isotope Reactor; computational nanoscience in the CNMS' Nanomaterials Theory Institute and utilizing facilities and expertise of the Center for Computational Sciences and the new Leadership Scientific Computing Facility at ORNL; a new CNMS Nanofabrication Research Laboratory; and a suite of unique and state-of-the-art instruments to be made reliably available to the national community for imaging, manipulation, and properties measurements on nanoscale materials in controlled environments. The new research facilities will be described together with the planned operation of the user research program, the latter illustrated by the current ``jump start'' user program that utilizes existing ORNL/CNMS facilities.

Multilevel Summation of Electrostatic Potentials Using Graphics Processing Units*

PubMed Central

Hardy, David J.; Stone, John E.; Schulten, Klaus

2009-01-01

Physical and engineering practicalities involved in microprocessor design have resulted in flat performance growth for traditional single-core microprocessors. The urgent need for continuing increases in the performance of scientific applications requires the use of many-core processors and accelerators such as graphics processing units (GPUs). This paper discusses GPU acceleration of the multilevel summation method for computing electrostatic potentials and forces for a system of charged atoms, which is a problem of paramount importance in biomolecular modeling applications. We present and test a new GPU algorithm for the long-range part of the potentials that computes a cutoff pair potential between lattice points, essentially convolving a fixed 3-D lattice of “weights” over all sub-cubes of a much larger lattice. The implementation exploits the different memory subsystems provided on the GPU to stream optimally sized data sets through the multiprocessors. We demonstrate for the full multilevel summation calculation speedups of up to 26 using a single GPU and 46 using multiple GPUs, enabling the computation of a high-resolution map of the electrostatic potential for a system of 1.5 million atoms in under 12 seconds. PMID:20161132

Accelerating 3D Elastic Wave Equations on Knights Landing based Intel Xeon Phi processors

NASA Astrophysics Data System (ADS)

Sourouri, Mohammed; Birger Raknes, Espen

2017-04-01

In advanced imaging methods like reverse-time migration (RTM) and full waveform inversion (FWI) the elastic wave equation (EWE) is numerically solved many times to create the seismic image or the elastic parameter model update. Thus, it is essential to optimize the solution time for solving the EWE as this will have a major impact on the total computational cost in running RTM or FWI. From a computational point of view applications implementing EWEs are associated with two major challenges. The first challenge is the amount of memory-bound computations involved, while the second challenge is the execution of such computations over very large datasets. So far, multi-core processors have not been able to tackle these two challenges, which eventually led to the adoption of accelerators such as Graphics Processing Units (GPUs). Compared to conventional CPUs, GPUs are densely populated with many floating-point units and fast memory, a type of architecture that has proven to map well to many scientific computations. Despite its architectural advantages, full-scale adoption of accelerators has yet to materialize. First, accelerators require a significant programming effort imposed by programming models such as CUDA or OpenCL. Second, accelerators come with a limited amount of memory, which also require explicit data transfers between the CPU and the accelerator over the slow PCI bus. The second generation of the Xeon Phi processor based on the Knights Landing (KNL) architecture, promises the computational capabilities of an accelerator but require the same programming effort as traditional multi-core processors. The high computational performance is realized through many integrated cores (number of cores and tiles and memory varies with the model) organized in tiles that are connected via a 2D mesh based interconnect. In contrary to accelerators, KNL is a self-hosted system, meaning explicit data transfers over the PCI bus are no longer required. However, like most accelerators, KNL sports a memory subsystem consisting of low-level caches and 16GB of high-bandwidth MCDRAM memory. For capacity computing, up to 400GB of conventional DDR4 memory is provided. Such a strict hierarchical memory layout means that data locality is imperative if the true potential of this product is to be harnessed. In this work, we study a series of optimizations specifically targeting KNL for our EWE based application to reduce the time-to-solution time for the following 3D model sizes in grid points: 1283, 2563 and 5123. We compare the results with an optimized version for multi-core CPUs running on a dual-socket Xeon E5 2680v3 system using OpenMP. Our initial naive implementation on the KNL is roughly 20% faster than the multi-core version, but by using only one thread per core and careful memory placement using the memkind library, we could achieve higher speedups. Additionally, by using the MCDRAM as cache for problem sizes that are smaller than 16 GB further performance improvements were unlocked. Depending on the problem size, our overall results indicate that the KNL based system is approximately 2.2x faster than the 24-core Xeon E5 2680v3 system, with only modest changes to the code.

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus

PubMed Central

Karp, Peter D.; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-01-01

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida). PMID:26097686

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.

PubMed

Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-01-01

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida).

Gpu Implementation of a Viscous Flow Solver on Unstructured Grids

NASA Astrophysics Data System (ADS)

Xu, Tianhao; Chen, Long

2016-06-01

Graphics processing units have gained popularities in scientific computing over past several years due to their outstanding parallel computing capability. Computational fluid dynamics applications involve large amounts of calculations, therefore a latest GPU card is preferable of which the peak computing performance and memory bandwidth are much better than a contemporary high-end CPU. We herein focus on the detailed implementation of our GPU targeting Reynolds-averaged Navier-Stokes equations solver based on finite-volume method. The solver employs a vertex-centered scheme on unstructured grids for the sake of being capable of handling complex topologies. Multiple optimizations are carried out to improve the memory accessing performance and kernel utilization. Both steady and unsteady flow simulation cases are carried out using explicit Runge-Kutta scheme. The solver with GPU acceleration in this paper is demonstrated to have competitive advantages over the CPU targeting one.

A GPU accelerated and error-controlled solver for the unbounded Poisson equation in three dimensions

NASA Astrophysics Data System (ADS)

Exl, Lukas

2017-12-01

An efficient solver for the three dimensional free-space Poisson equation is presented. The underlying numerical method is based on finite Fourier series approximation. While the error of all involved approximations can be fully controlled, the overall computation error is driven by the convergence of the finite Fourier series of the density. For smooth and fast-decaying densities the proposed method will be spectrally accurate. The method scales with O(N log N) operations, where N is the total number of discretization points in the Cartesian grid. The majority of the computational costs come from fast Fourier transforms (FFT), which makes it ideal for GPU computation. Several numerical computations on CPU and GPU validate the method and show efficiency and convergence behavior. Tests are performed using the Vienna Scientific Cluster 3 (VSC3). A free MATLAB implementation for CPU and GPU is provided to the interested community.

Construction of Blaze at the University of Illinois at Chicago: A Shared, High-Performance, Visual Computer for Next-Generation Cyberinfrastructure-Accelerated Scientific, Engineering, Medical and Public Policy Research

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

Brown, Maxine D.; Leigh, Jason

2014-02-17

The Blaze high-performance visual computing system serves the high-performance computing research and education needs of University of Illinois at Chicago (UIC). Blaze consists of a state-of-the-art, networked, computer cluster and ultra-high-resolution visualization system called CAVE2(TM) that is currently not available anywhere in Illinois. This system is connected via a high-speed 100-Gigabit network to the State of Illinois' I-WIRE optical network, as well as to national and international high speed networks, such as the Internet2, and the Global Lambda Integrated Facility. This enables Blaze to serve as an on-ramp to national cyberinfrastructure, such as the National Science Foundation’s Blue Waters petascalemore » computer at the National Center for Supercomputing Applications at the University of Illinois at Chicago and the Department of Energy’s Argonne Leadership Computing Facility (ALCF) at Argonne National Laboratory. DOE award # DE-SC005067, leveraged with NSF award #CNS-0959053 for “Development of the Next-Generation CAVE Virtual Environment (NG-CAVE),” enabled us to create a first-of-its-kind high-performance visual computing system. The UIC Electronic Visualization Laboratory (EVL) worked with two U.S. companies to advance their commercial products and maintain U.S. leadership in the global information technology economy. New applications are being enabled with the CAVE2/Blaze visual computing system that is advancing scientific research and education in the U.S. and globally, and help train the next-generation workforce.« less

Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures

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

Arumugam, Kamesh

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore,more » these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.« less

A comparison of native GPU computing versus OpenACC for implementing flow-routing algorithms in hydrological applications

NASA Astrophysics Data System (ADS)

Rueda, Antonio J.; Noguera, José M.; Luque, Adrián

2016-02-01

In recent years GPU computing has gained wide acceptance as a simple low-cost solution for speeding up computationally expensive processing in many scientific and engineering applications. However, in most cases accelerating a traditional CPU implementation for a GPU is a non-trivial task that requires a thorough refactorization of the code and specific optimizations that depend on the architecture of the device. OpenACC is a promising technology that aims at reducing the effort required to accelerate C/C++/Fortran code on an attached multicore device. Virtually with this technology the CPU code only has to be augmented with a few compiler directives to identify the areas to be accelerated and the way in which data has to be moved between the CPU and GPU. Its potential benefits are multiple: better code readability, less development time, lower risk of errors and less dependency on the underlying architecture and future evolution of the GPU technology. Our aim with this work is to evaluate the pros and cons of using OpenACC against native GPU implementations in computationally expensive hydrological applications, using the classic D8 algorithm of O'Callaghan and Mark for river network extraction as case-study. We implemented the flow accumulation step of this algorithm in CPU, using OpenACC and two different CUDA versions, comparing the length and complexity of the code and its performance with different datasets. We advance that although OpenACC can not match the performance of a CUDA optimized implementation (×3.5 slower in average), it provides a significant performance improvement against a CPU implementation (×2-6) with by far a simpler code and less implementation effort.

Experimental evaluation of a flexible I/O architecture for accelerating workflow engines in ultrascale environments

DOE PAGES

Duro, Francisco Rodrigo; Blas, Javier Garcia; Isaila, Florin; ...

2016-10-06

The increasing volume of scientific data and the limited scalability and performance of storage systems are currently presenting a significant limitation for the productivity of the scientific workflows running on both high-performance computing (HPC) and cloud platforms. Clearly needed is better integration of storage systems and workflow engines to address this problem. This paper presents and evaluates a novel solution that leverages codesign principles for integrating Hercules—an in-memory data store—with a workflow management system. We consider four main aspects: workflow representation, task scheduling, task placement, and task termination. As a result, the experimental evaluation on both cloud and HPC systemsmore » demonstrates significant performance and scalability improvements over existing state-of-the-art approaches.« less

Controlling flexible robot arms using a high speed dynamics process

NASA Technical Reports Server (NTRS)

Jain, Abhinandan (Inventor); Rodriguez, Guillermo (Inventor)

1992-01-01

Described here is a robot controller for a flexible manipulator arm having plural bodies connected at respective movable hinges, and flexible in plural deformation modes. It is operated by computing articulated body qualities for each of the bodies from the respective modal spatial influence vectors, obtaining specified body forces for each of the bodies, and computing modal deformation accelerations of the nodes and hinge accelerations of the hinges from the specified body forces, from the articulated body quantities and from the modal spatial influence vectors. In one embodiment of the invention, the controller further operates by comparing the accelerations thus computed to desired manipulator motion to determine a motion discrepancy, and correcting the specified body forces so as to reduce the motion discrepancy. The manipulator bodies and hinges are characterized by respective vectors of deformation and hinge configuration variables. Computing modal deformation accelerations and hinge accelerations is carried out for each of the bodies, beginning with the outermost body by computing a residual body force from a residual body force of a previous body, computing a resultant hinge acceleration from the body force, and then, for each one of the bodies beginning with the innermost body, computing a modal body acceleration from a modal body acceleration of a previous body, computing a modal deformation acceleration and hinge acceleration from the resulting hinge acceleration and from the modal body acceleration.

Power to the People: Addressing Big Data Challenges in Neuroscience by Creating a New Cadre of Citizen Neuroscientists.

PubMed

Roskams, Jane; Popović, Zoran

2016-11-02

Global neuroscience projects are producing big data at an unprecedented rate that informatic and artificial intelligence (AI) analytics simply cannot handle. Online games, like Foldit, Eterna, and Eyewire-and now a new neuroscience game, Mozak-are fueling a people-powered research science (PPRS) revolution, creating a global community of "new experts" that over time synergize with computational efforts to accelerate scientific progress, empowering us to use our collective cerebral talents to drive our understanding of our brain. Copyright © 2016 Elsevier Inc. All rights reserved.

CERN-derived analysis of lunar radiation backgrounds

NASA Technical Reports Server (NTRS)

Wilson, Thomas L.; Svoboda, Robert

1993-01-01

The Moon produces radiation which background-limits scientific experiments there. Early analyses of these backgrounds have either failed to take into consideration the effect of charm in particle physics (because they pre-dated its discovery), or have used branching ratios which are no longer strictly valid (due to new accelerator data). We are presently investigating an analytical program for deriving muon and neutrino spectra generated by the Moon, converting an existing CERN computer program known as GEANT which does the same for the Earth. In so doing, this will (1) determine an accurate prompt neutrino spectrum produced by the lunar surface; (2) determine the lunar subsurface particle flux; (3) determine the consequence of charm production physics upon the lunar background radiation environment; and (4) provide an analytical tool for the NASA astrophysics community with which to begin an assessment of the Moon as a scientific laboratory versus its particle radiation environment. This will be done on a recurring basis with the latest experimental results of the particle data groups at Earth-based high-energy accelerators, in particular with the latest branching ratios for charmed meson decay. This will be accomplished for the first time as a full 3-dimensional simulation.

Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science

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

Crabtree, George; Glotzer, Sharon; McCurdy, Bill

This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. Newmore » materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of abating, has enabled the development of computer simulations and models of unprecedented fidelity. We are at the threshold of a new era where the integrated synthesis, characterization, and modeling of complex materials and chemical processes will transform our ability to understand and design new materials and chemistries with predictive power. In turn, this predictive capability will transform technological innovation by accelerating the development and deployment of new materials and processes in products and manufacturing. Harnessing the potential of computational science and engineering for the discovery and development of materials and chemical processes is essential to maintaining leadership in these foundational fields that underpin energy technologies and industrial competitiveness. Capitalizing on the opportunities presented by simulation-based engineering and science in materials and chemistry will require an integration of experimental capabilities with theoretical and computational modeling; the development of a robust and sustainable infrastructure to support the development and deployment of advanced computational models; and the assembly of a community of scientists and engineers to implement this integration and infrastructure. This community must extend to industry, where incorporating predictive materials science and chemistry into design tools can accelerate the product development cycle and drive economic competitiveness. The confluence of new theories, new materials synthesis capabilities, and new computer platforms has created an unprecedented opportunity to implement a "materials-by-design" paradigm with wide-ranging benefits in technological innovation and scientific discovery. The Workshop on Computational Materials Science and Chemistry for Innovation was convened in Bethesda, Maryland, on July 26-27, 2010. Sponsored by the Department of Energy (DOE) Offices of Advanced Scientific Computing Research and Basic Energy Sciences, the workshop brought together 160 experts in materials science, chemistry, and computational science representing more than 65 universities, laboratories, and industries, and four agencies. The workshop examined seven foundational challenge areas in materials science and chemistry: materials for extreme conditions, self-assembly, light harvesting, chemical reactions, designer fluids, thin films and interfaces, and electronic structure. Each of these challenge areas is critical to the development of advanced energy systems, and each can be accelerated by the integrated application of predictive capability with theory and experiment. The workshop concluded that emerging capabilities in predictive modeling and simulation have the potential to revolutionize the development of new materials and chemical processes. Coupled with world-leading materials characterization and nanoscale science facilities, this predictive capability provides the foundation for an innovation ecosystem that can accelerate the discovery, development, and deployment of new technologies, including advanced energy systems. Delivering on the promise of this innovation ecosystem requires the following: Integration of synthesis, processing, characterization, theory, and simulation and modeling. Many of the newly established Energy Frontier Research Centers and Energy Hubs are exploiting this integration. Achieving/strengthening predictive capability in foundational challenge areas. Predictive capability in the seven foundational challenge areas described in this report is critical to the development of advanced energy technologies. Developing validated computational approaches that span vast differences in time and length scales. This fundamental computational challenge crosscuts all of the foundational challenge areas. Similarly challenging is coupling of analytical data from multiple instruments and techniques that are required to link these length and time scales. Experimental validation and quantification of uncertainty in simulation and modeling. Uncertainty quantification becomes increasingly challenging as simulations become more complex. Robust and sustainable computational infrastructure, including software and applications. For modeling and simulation, software equals infrastructure. To validate the computational tools, software is critical infrastructure that effectively translates huge arrays of experimental data into useful scientific understanding. An integrated approach for managing this infrastructure is essential. Efficient transfer and incorporation of simulation-based engineering and science in industry. Strategies for bridging the gap between research and industrial applications and for widespread industry adoption of integrated computational materials engineering are needed.« less

Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

PubMed

Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W

2017-12-05

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.

Snowflake: A Lightweight Portable Stencil DSL

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

Zhang, Nathan; Driscoll, Michael; Markley, Charles

Stencil computations are not well optimized by general-purpose production compilers and the increased use of multicore, manycore, and accelerator-based systems makes the optimization problem even more challenging. In this paper we present Snowflake, a Domain Specific Language (DSL) for stencils that uses a 'micro-compiler' approach, i.e., small, focused, domain-specific code generators. The approach is similar to that used in image processing stencils, but Snowflake handles the much more complex stencils that arise in scientific computing, including complex boundary conditions, higher-order operators (larger stencils), higher dimensions, variable coefficients, non-unit-stride iteration spaces, and multiple input or output meshes. Snowflake is embedded inmore » the Python language, allowing it to interoperate with popular scientific tools like SciPy and iPython; it also takes advantage of built-in Python libraries for powerful dependence analysis as part of a just-in-time compiler. We demonstrate the power of the Snowflake language and the micro-compiler approach with a complex scientific benchmark, HPGMG, that exercises the generality of stencil support in Snowflake. By generating OpenMP comparable to, and OpenCL within a factor of 2x of hand-optimized HPGMG, Snowflake demonstrates that a micro-compiler can support diverse processor architectures and is performance-competitive whilst preserving a high-level Python implementation.« less

Snowflake: A Lightweight Portable Stencil DSL

DOE PAGES

Zhang, Nathan; Driscoll, Michael; Markley, Charles; ...

2017-05-01

Stencil computations are not well optimized by general-purpose production compilers and the increased use of multicore, manycore, and accelerator-based systems makes the optimization problem even more challenging. In this paper we present Snowflake, a Domain Specific Language (DSL) for stencils that uses a 'micro-compiler' approach, i.e., small, focused, domain-specific code generators. The approach is similar to that used in image processing stencils, but Snowflake handles the much more complex stencils that arise in scientific computing, including complex boundary conditions, higher-order operators (larger stencils), higher dimensions, variable coefficients, non-unit-stride iteration spaces, and multiple input or output meshes. Snowflake is embedded inmore » the Python language, allowing it to interoperate with popular scientific tools like SciPy and iPython; it also takes advantage of built-in Python libraries for powerful dependence analysis as part of a just-in-time compiler. We demonstrate the power of the Snowflake language and the micro-compiler approach with a complex scientific benchmark, HPGMG, that exercises the generality of stencil support in Snowflake. By generating OpenMP comparable to, and OpenCL within a factor of 2x of hand-optimized HPGMG, Snowflake demonstrates that a micro-compiler can support diverse processor architectures and is performance-competitive whilst preserving a high-level Python implementation.« less

Reducing Time to Science: Unidata and JupyterHub Technology Using the Jetstream Cloud

NASA Astrophysics Data System (ADS)

Chastang, J.; Signell, R. P.; Fischer, J. L.

2017-12-01

Cloud computing can accelerate scientific workflows, discovery, and collaborations by reducing research and data friction. We describe the deployment of Unidata and JupyterHub technologies on the NSF-funded XSEDE Jetstream cloud. With the aid of virtual machines and Docker technology, we deploy a Unidata JupyterHub server co-located with a Local Data Manager (LDM), THREDDS data server (TDS), and RAMADDA geoscience content management system. We provide Jupyter Notebooks and the pre-built Python environments needed to run them. The notebooks can be used for instruction and as templates for scientific experimentation and discovery. We also supply a large quantity of NCEP forecast model results to allow data-proximate analysis and visualization. In addition, users can transfer data using Globus command line tools, and perform their own data-proximate analysis and visualization with Notebook technology. These data can be shared with others via a dedicated TDS server for scientific distribution and collaboration. There are many benefits of this approach. Not only is the cloud computing environment fast, reliable and scalable, but scientists can analyze, visualize, and share data using only their web browser. No local specialized desktop software or a fast internet connection is required. This environment will enable scientists to spend less time managing their software and more time doing science.

Conference Committees: Conference Committees

NASA Astrophysics Data System (ADS)

2009-09-01

International Programm Committee (IPC) Harald Ade NCSU Sadao Aoki University Tsukuba David Attwood Lawrence Berkeley National Laboratory/CXRO Christian David Paul Scherrer Institut Peter Fischer Lawrence Berkeley National Laboratory Adam Hitchcock McMaster University Chris Jacobsen SUNY, Stony Brook Denis Joyeux Lab Charles Fabry de l'Institut d'Optique Yasushi Kagoshima University of Hyogo Hiroshi Kihara Kansai Medical University Janos Kirz SUNY Stony Brook Maya Kiskinova ELETTRA Ian McNulty Argonne National Lab/APS Alan Michette Kings College London Graeme Morrison Kings College London Keith Nugent University of Melbourne Zhu Peiping BSRF Institute of High Energy Physics Francois Polack Soleil Christoph Quitmann Paul Scherrer Institut Günther Schmahl University Göttingen Gerd Schneider Bessy Hyun-Joon Shin Pohang Accelerator Lab Jean Susini ESRF Mau-Tsu Tang NSRRC Tony Warwick Lawrence Berkeley Lab/ALS Local Organizing Committee Christoph Quitmann Chair, Scientific Program Charlotte Heer Secretary Christian David Scientific Program Frithjof Nolting Scientific Program Franz Pfeiffer Scientific Program Marco Stampanoni Scientific Program Robert Rudolph Sponsoring, Financials Alfred Waser Industry Exhibition Robert Keller Public Relation Markus Knecht Computing and WWW Annick Cavedon Proceedings and Excursions and Accompanying Persons Program Margrit Eichler Excursions and Accompanying Persons Program Kathy Eikenberry Excursions and Accompanying Persons Program Marlies Locher Excursions and Accompanying Persons Program

Role of High-End Computing in Meeting NASA's Science and Engineering Challenges

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Tu, Eugene L.; Van Dalsem, William R.

2006-01-01

Two years ago, NASA was on the verge of dramatically increasing its HEC capability and capacity. With the 10,240-processor supercomputer, Columbia, now in production for 18 months, HEC has an even greater impact within the Agency and extending to partner institutions. Advanced science and engineering simulations in space exploration, shuttle operations, Earth sciences, and fundamental aeronautics research are occurring on Columbia, demonstrating its ability to accelerate NASA s exploration vision. This talk describes how the integrated production environment fostered at the NASA Advanced Supercomputing (NAS) facility at Ames Research Center is accelerating scientific discovery, achieving parametric analyses of multiple scenarios, and enhancing safety for NASA missions. We focus on Columbia s impact on two key engineering and science disciplines: Aerospace, and Climate. We also discuss future mission challenges and plans for NASA s next-generation HEC environment.

Open Science in the Cloud: Towards a Universal Platform for Scientific and Statistical Computing

NASA Astrophysics Data System (ADS)

Chine, Karim

The UK, through the e-Science program, the US through the NSF-funded cyber infrastructure and the European Union through the ICT Calls aimed to provide "the technological solution to the problem of efficiently connecting data, computers, and people with the goal of enabling derivation of novel scientific theories and knowledge".1 The Grid (Foster, 2002; Foster; Kesselman, Nick, & Tuecke, 2002), foreseen as a major accelerator of discovery, didn't meet the expectations it had excited at its beginnings and was not adopted by the broad population of research professionals. The Grid is a good tool for particle physicists and it has allowed them to tackle the tremendous computational challenges inherent to their field. However, as a technology and paradigm for delivering computing on demand, it doesn't work and it can't be fixed. On one hand, "the abstractions that Grids expose - to the end-user, to the deployers and to application developers - are inappropriate and they need to be higher level" (Jha, Merzky, & Fox), and on the other hand, academic Grids are inherently economically unsustainable. They can't compete with a service outsourced to the Industry whose quality and price would be driven by market forces. The virtualization technologies and their corollary, the Infrastructure-as-a-Service (IaaS) style cloud, hold the promise to enable what the Grid failed to deliver: a sustainable environment for computational sciences that would lower the barriers for accessing federated computational resources, software tools and data; enable collaboration and resources sharing and provide the building blocks of a ubiquitous platform for traceable and reproducible computational research.

Modeling radiation forces acting on TOPEX/Poseidon for precision orbit determination

NASA Technical Reports Server (NTRS)

Marshall, J. A.; Luthcke, S. B.; Antreasian, P. G.; Rosborough, G. W.

1992-01-01

Geodetic satellites such as GEOSAT, SPOT, ERS-1, and TOPEX/Poseidon require accurate orbital computations to support the scientific data they collect. Until recently, gravity field mismodeling was the major source of error in precise orbit definition. However, albedo and infrared re-radiation, and spacecraft thermal imbalances produce in combination no more than a 6-cm radial root-mean-square (RMS) error over a 10-day period. This requires the development of nonconservative force models that take the satellite's complex geometry, attitude, and surface properties into account. For TOPEX/Poseidon, a 'box-wing' satellite form was investigated that models the satellite as a combination of flat plates arranged in a box shape with a connected solar array. The nonconservative forces acting on each of the eight surfaces are computed independently, yielding vector accelerations which are summed to compute the total aggregate effect on the satellite center-of-mass. In order to test the validity of this concept, 'micro-models' based on finite element analysis of TOPEX/Poseidon were used to generate acceleration histories in a wide variety of orbit orientations. These profiles are then compared to the box-wing model. The results of these simulations and their implication on the ability to precisely model the TOPEX/Poseidon orbit are discussed.

Nanoinformatics: developing new computing applications for nanomedicine

PubMed Central

Maojo, V.; Fritts, M.; Martin-Sanchez, F.; De la Iglesia, D.; Cachau, R.E.; Garcia-Remesal, M.; Crespo, J.; Mitchell, J.A.; Anguita, A.; Baker, N.; Barreiro, J.M.; Benitez, S. E.; De la Calle, G.; Facelli, J. C.; Ghazal, P.; Geissbuhler, A.; Gonzalez-Nilo, F.; Graf, N.; Grangeat, P.; Hermosilla, I.; Hussein, R.; Kern, J.; Koch, S.; Legre, Y.; Lopez-Alonso, V.; Lopez-Campos, G.; Milanesi, L.; Moustakis, V.; Munteanu, C.; Otero, P.; Pazos, A.; Perez-Rey, D.; Potamias, G.; Sanz, F.; Kulikowski, C.

2012-01-01

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended “nanotype” to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other –omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others. PMID:22942787

Costa - Introduction to 2015 Annual Report

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

Costa, James E.

In parallel with Sandia National Laboratories having two major locations (NM and CA), along with a number of smaller facilities across the nation, so too is the distribution of scientific, engineering and computing resources. As a part of Sandia’s Institutional Computing Program, CA site-based Sandia computer scientists and engineers have been providing mission and research staff with local CA resident expertise on computing options while also focusing on two growing high performance computing research problems. The first is how to increase system resilience to failure, as machines grow larger, more complex and heterogeneous. The second is how to ensure thatmore » computer hardware and configurations are optimized for specialized data analytical mission needs within the overall Sandia computing environment, including the HPC subenvironment. All of these activities support the larger Sandia effort in accelerating development and integration of high performance computing into national security missions. Sandia continues to both promote national R&D objectives, including the recent Presidential Executive Order establishing the National Strategic Computing Initiative and work to ensure that the full range of computing services and capabilities are available for all mission responsibilities, from national security to energy to homeland defense.« less

The Muon Collider

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

Zisman, Michael S

2010-05-17

We describe the scientific motivation for a new type of accelerator, the muon collider. This accelerator would permit an energy-frontier scientific program and yet would fit on the site of an existing laboratory. Such a device is quite challenging, and requires a substantial R&D program. After describing the ingredients of the facility, the ongoing R&D activities of the Muon Accelerator Program are discussed. A possible U.S. scenario that could lead to a muon collider at Fermilab is briefly mentioned.

The Muon Collider

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

Zisman, Michael S.

2011-01-05

We describe the scientific motivation for a new type of accelerator, the muon collider. This accelerator would permit an energy-frontier scientific program and yet would fit on the site of an existing laboratory. Such a device is quite challenging, and requires a substantial R&D program. After describing the ingredients of the facility, the ongoing R&D activities of the Muon Accelerator Program are discussed. A possible U.S. scenario that could lead to a muon collider at Fermilab is briefly mentioned.

Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics (LQCD)

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

Negele, John W.

Building on the success of two preceding generations of Scientific Discovery through Advanced Computing (SciDAC) projects, this grant supported the MIT component (P.I. John Negele) of a multi-institutional SciDAC-3 project that also included Brookhaven National Laboratory, the lead laboratory with P. I. Frithjof Karsch serving as Project Director, Thomas Jefferson National Accelerator Facility with P. I. David Richards serving as Co-director, University of Washington with P. I. Martin Savage, University of North Carolina with P. I. Rob Fowler, and College of William and Mary with P. I. Andreas Stathopoulos. Nationally, this multi-institutional project coordinated the software development effort that themore » nuclear physics lattice QCD community needs to ensure that lattice calculations can make optimal use of forthcoming leadership-class and dedicated hardware, including that at the national laboratories, and to exploit future computational resources in the Exascale era.« less

Modeling and Simulation of High Dimensional Stochastic Multiscale PDE Systems at the Exascale

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

Kevrekidis, Ioannis

2017-03-22

The thrust of the proposal was to exploit modern data-mining tools in a way that will create a systematic, computer-assisted approach to the representation of random media -- and also to the representation of the solutions of an array of important physicochemical processes that take place in/on such media. A parsimonious representation/parametrization of the random media links directly (via uncertainty quantification tools) to good sampling of the distribution of random media realizations. It also links directly to modern multiscale computational algorithms (like the equation-free approach that has been developed in our group) and plays a crucial role in accelerating themore » scientific computation of solutions of nonlinear PDE models (deterministic or stochastic) in such media – both solutions in particular realizations of the random media, and estimation of the statistics of the solutions over multiple realizations (e.g. expectations).« less

Acceleration Environment of the International Space Station

NASA Technical Reports Server (NTRS)

McPherson, Kevin; Kelly, Eric; Keller, Jennifer

2009-01-01

Measurement of the microgravity acceleration environment on the International Space Station has been accomplished by two accelerometer systems since 2001. The Microgravity Acceleration Measurement System records the quasi-steady microgravity environment, including the influences of aerodynamic drag, vehicle rotation, and venting effects. Measurement of the vibratory/transient regime, comprised of vehicle, crew, and equipment disturbances, has been accomplished by the Space Acceleration Measurement System-II. Until the arrival of the Columbus Orbital Facility and the Japanese Experiment Module, the location of these sensors, and therefore, the measurement of the microgravity acceleration environment, has been limited to within the United States Laboratory. Japanese Aerospace Exploration Agency has developed a vibratory acceleration measurement system called the Microgravity Measurement Apparatus which will be deployed within the Japanese Experiment Module to make distributed measurements of the Japanese Experiment Module's vibratory acceleration environment. Two Space Acceleration Measurement System sensors from the United States Laboratory will be re-deployed to support vibratory acceleration data measurement within the Columbus Orbital Facility. The additional measurement opportunities resulting from the arrival of these new laboratories allows Principal Investigators with facilities located in these International Space Station research laboratories to obtain microgravity acceleration data in support of their sensitive experiments. The Principal Investigator Microgravity Services project, at NASA Glenn Research Center, in Cleveland, Ohio, has supported acceleration measurement systems and the microgravity scientific community through the processing, characterization, distribution, and archival of the microgravity acceleration data obtained from the International Space Station acceleration measurement systems. This paper summarizes the PIMS capabilities available to the International Space Station scientific community, introduces plans for extending microgravity analysis results to the newly arrived scientific laboratories, and provides summary information for known microgravity environment disturbers.

Loci-STREAM Version 0.9

NASA Technical Reports Server (NTRS)

Wright, Jeffrey; Thakur, Siddharth

2006-01-01

Loci-STREAM is an evolving computational fluid dynamics (CFD) software tool for simulating possibly chemically reacting, possibly unsteady flows in diverse settings, including rocket engines, turbomachines, oil refineries, etc. Loci-STREAM implements a pressure- based flow-solving algorithm that utilizes unstructured grids. (The benefit of low memory usage by pressure-based algorithms is well recognized by experts in the field.) The algorithm is robust for flows at all speeds from zero to hypersonic. The flexibility of arbitrary polyhedral grids enables accurate, efficient simulation of flows in complex geometries, including those of plume-impingement problems. The present version - Loci-STREAM version 0.9 - includes an interface with the Portable, Extensible Toolkit for Scientific Computation (PETSc) library for access to enhanced linear-equation-solving programs therein that accelerate convergence toward a solution. The name "Loci" reflects the creation of this software within the Loci computational framework, which was developed at Mississippi State University for the primary purpose of simplifying the writing of complex multidisciplinary application programs to run in distributed-memory computing environments including clusters of personal computers. Loci has been designed to relieve application programmers of the details of programming for distributed-memory computers.

Checkpointing for a hybrid computing node

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

Cher, Chen-Yong

2016-03-08

According to an aspect, a method for checkpointing in a hybrid computing node includes executing a task in a processing accelerator of the hybrid computing node. A checkpoint is created in a local memory of the processing accelerator. The checkpoint includes state data to restart execution of the task in the processing accelerator upon a restart operation. Execution of the task is resumed in the processing accelerator after creating the checkpoint. The state data of the checkpoint are transferred from the processing accelerator to a main processor of the hybrid computing node while the processing accelerator is executing the task.

Gpufit: An open-source toolkit for GPU-accelerated curve fitting.

PubMed

Przybylski, Adrian; Thiel, Björn; Keller-Findeisen, Jan; Stock, Bernd; Bates, Mark

2017-11-16

We present a general purpose, open-source software library for estimation of non-linear parameters by the Levenberg-Marquardt algorithm. The software, Gpufit, runs on a Graphics Processing Unit (GPU) and executes computations in parallel, resulting in a significant gain in performance. We measured a speed increase of up to 42 times when comparing Gpufit with an identical CPU-based algorithm, with no loss of precision or accuracy. Gpufit is designed such that it is easily incorporated into existing applications or adapted for new ones. Multiple software interfaces, including to C, Python, and Matlab, ensure that Gpufit is accessible from most programming environments. The full source code is published as an open source software repository, making its function transparent to the user and facilitating future improvements and extensions. As a demonstration, we used Gpufit to accelerate an existing scientific image analysis package, yielding significantly improved processing times for super-resolution fluorescence microscopy datasets.

Highly Productive Application Development with ViennaCL for Accelerators

NASA Astrophysics Data System (ADS)

Rupp, K.; Weinbub, J.; Rudolf, F.

2012-12-01

The use of graphics processing units (GPUs) for the acceleration of general purpose computations has become very attractive over the last years, and accelerators based on many integrated CPU cores are about to hit the market. However, there are discussions about the benefit of GPU computing when comparing the reduction of execution times with the increased development effort [1]. To counter these concerns, our open-source linear algebra library ViennaCL [2,3] uses modern programming techniques such as generic programming in order to provide a convenient access layer for accelerator and GPU computing. Other GPU-accelerated libraries are primarily tuned for performance, but less tailored to productivity and portability: MAGMA [4] provides dense linear algebra operations via a LAPACK-comparable interface, but no dedicated matrix and vector types. Cusp [5] is closest in functionality to ViennaCL for sparse matrices, but is based on CUDA and thus restricted to devices from NVIDIA. However, no convenience layer for dense linear algebra is provided with Cusp. ViennaCL is written in C++ and uses OpenCL to access the resources of accelerators, GPUs and multi-core CPUs in a unified way. On the one hand, the library provides iterative solvers from the family of Krylov methods, including various preconditioners, for the solution of linear systems typically obtained from the discretization of partial differential equations. On the other hand, dense linear algebra operations are supported, including algorithms such as QR factorization and singular value decomposition. The user application interface of ViennaCL is compatible to uBLAS [6], which is part of the peer-reviewed Boost C++ libraries [7]. This allows to port existing applications based on uBLAS with a minimum of effort to ViennaCL. Conversely, the interface compatibility allows to use the iterative solvers from ViennaCL with uBLAS types directly, thus enabling code reuse beyond CPU-GPU boundaries. Out-of-the-box support for types from the Eigen library [8] and MTL 4 [9] are provided as well, enabling a seamless transition from single-core CPU to GPU and multi-core CPU computations. Case studies from the numerical solution of PDEs are given and isolated performance benchmarks are discussed. Also, pitfalls in scientific computing with GPUs and accelerators are addressed, allowing for a first evaluation of whether these novel devices can be mapped well to certain applications. References: [1] R. Bordawekar et al., Technical Report, IBM, 2010 [2] ViennaCL library. Online: http://viennacl.sourceforge.net/ [3] K. Rupp et al., GPUScA, 2010 [4] MAGMA library. Online: http://icl.cs.utk.edu/magma/ [5] Cusp library. Online: http://code.google.com/p/cusp-library/ [6] uBLAS library. Online: http://www.boost.org/libs/numeric/ublas/ [7] Boost C++ Libraries. Online: http://www.boost.org/ [8] Eigen library. Online: http://eigen.tuxfamily.org/ [9] MTL 4 Library. Online: http://www.mtl4.org/

Accelerating Pseudo-Random Number Generator for MCNP on GPU

NASA Astrophysics Data System (ADS)

Gong, Chunye; Liu, Jie; Chi, Lihua; Hu, Qingfeng; Deng, Li; Gong, Zhenghu

2010-09-01

Pseudo-random number generators (PRNG) are intensively used in many stochastic algorithms in particle simulations, artificial neural networks and other scientific computation. The PRNG in Monte Carlo N-Particle Transport Code (MCNP) requires long period, high quality, flexible jump and fast enough. In this paper, we implement such a PRNG for MCNP on NVIDIA's GTX200 Graphics Processor Units (GPU) using CUDA programming model. Results shows that 3.80 to 8.10 times speedup are achieved compared with 4 to 6 cores CPUs and more than 679.18 million double precision random numbers can be generated per second on GPU.

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.

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

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

Ruebel, Oliver

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research coveredmore » in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle acceleration, physicists model LWFAs computationally. The datasets produced by LWFA simulations are (i) extremely large, (ii) of varying spatial and temporal resolution, (iii) heterogeneous, and (iv) high-dimensional, making analysis and knowledge discovery from complex LWFA simulation data a challenging task. To address these challenges this thesis describes the integration of the visualization system VisIt and the state-of-the-art index/query system FastBit, enabling interactive visual exploration of extremely large three-dimensional particle datasets. Researchers are especially interested in beams of high-energy particles formed during the course of a simulation. This thesis describes novel methods for automatic detection and analysis of particle beams enabling a more accurate and efficient data analysis process. By integrating these automated analysis methods with visualization, this research enables more accurate, efficient, and effective analysis of LWFA simulation data than previously possible.« less

Sloshing dynamics on rotating helium dewar tank

NASA Technical Reports Server (NTRS)

Hung, R. J.

1993-01-01

The generalized mathematical formulation of sloshing dynamics for partially filled liquid of cryogenic superfluid helium II in dewar containers driven by both the gravity gradient and jitter accelerations applicable to scientific spacecraft which is eligible to carry out spinning motion and/or slew motion for the purpose to perform scientific observation during the normal spacecraft operation are investigated. An example is given with Gravity Probe-B (GP-B) spacecraft which is responsible for the sloshing dynamics. The jitter accelerations include slew motion, spinning motion, atmospheric drag on the spacecraft, spacecraft attitude motions arising from machinery vibrations, thruster firing, pointing control of spacecraft, crew motion, etc. Explicit mathematical expressions to cover these forces acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics were based on the non-inertia frame spacecraft bound coordinate, and solve time dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. The explicit mathematical expressions of boundary conditions to cover capillary force effect on the liquid vapor interface in microgravity environments are also derived. The formulations of fluid moment and angular moment fluctuations in fluid profiles induced by the sloshing dynamics, together with fluid stress and moment fluctuations exerted on the spacecraft dewar containers were derived. Results were widely published in the open journals.

Numerical studies of the surface tension effect of cryogenic liquid helium

NASA Technical Reports Server (NTRS)

Hung, R. J.

1994-01-01

The generalized mathematical formulation of sloshing dynamics for partially filled liquid of cryogenic superfluid helium II in dewar containers driven by both the gravity gradient and jitter accelerations applicable to scientific spacecraft which is eligible to carry out spinning motion and/or slew motion for the purpose of performing scientific observation during the normal spacecraft operation is investigated. An example is given with Gravity Probe-B (GP-B) spacecraft which is responsible for the sloshing dynamics. The jitter accelerations include slew motion, spinning motion, atmospheric drag on the spacecraft, spacecraft attitude motions arising from machinery vibrations, thruster firing, pointing control of spacecraft, crew motion, etc. Explicit mathematical expressions to cover these forces acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics has been based on the non-inertia frame spacecraft bound coordinate, and solve time-dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. The explicit mathematical expressions of boundary conditions to cover capillary force effect on the liquid vapor interface in microgravity environments are also derived. The formulations of fluid moment and angular moment fluctuations in fluid profiles induced by the sloshing dynamics, together with fluid stress and moment fluctuations exerted on the spacecraft dewar containers, have been derived.

Low-Cost Alternative for Signal Generators in the Physics Laboratory

NASA Astrophysics Data System (ADS)

Pathare, Shirish Rajan; Raghavendra, M. K.; Huli, Saurabhee

2017-05-01

Recently devices such as the optical mouse of a computer, webcams, Wii remote, and digital cameras have been used to record and analyze different physical phenomena quantitatively. Devices like tablets and smartphones are also becoming popular. Different scientific applications available at Google Play (Android devices) or the App Store (iOS devices) make them versatile. One can find many websites that provide information regarding various scientific applications compatible with these systems. A variety of smartphones/tablets are available with different types of sensors embedded. Some of them have sensors that are capable of measuring intensity of light, sound, and magnetic field. The camera of these devices has been used to study projectile motion, and the same device, along with a sensor, has been used to study the physical pendulum. Accelerometers have been used to study free and damped harmonic oscillations and to measure acceleration due to gravity. Using accelerometers and gyroscopes, angular velocity and centripetal acceleration have been measured. The coefficient of restitution for a ball bouncing on the floor has been measured using the application Oscilloscope on the iPhone. In this article, we present the use of an Android device as a low-cost alternative for a signal generator. We use the Signal Generator application installed on the Android device along with an amplifier circuit.

Accelerator Science: Circular vs. Linear

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

Lincoln, Don

Particle accelerator are scientific instruments that allow scientists to collide particles together at incredible energies to study the secrets of the universe. However, there are many manners in which particle accelerators can be constructed. In this video, Fermilab’s Dr. Don Lincoln explains the pros and cons of circular and linear accelerators.

Message from the ISCB: ISCB Ebola award for important future research on the computational biology of Ebola virus.

PubMed

Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-02-15

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains and three-dimensional protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology 2016, Orlando, FL). dkovats@iscb.org or rost@in.tum.de. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

sbv IMPROVER: Modern Approach to Systems Biology.

PubMed

Guryanova, Svetlana; Guryanova, Anna

2017-01-01

The increasing amount and variety of data in biosciences call for innovative methods of visualization, scientific verification, and pathway analysis. Novel approaches to biological networks and research quality control are important because of their role in development of new products, improvement, and acceleration of existing health policies and research for novel ways of solving scientific challenges. One such approach is sbv IMPROVER. It is a platform that uses crowdsourcing and verification to create biological networks with easy public access. It contains 120 networks built in Biological Expression Language (BEL) to interpret data from PubMed articles with high-quality verification available for free on the CBN database. Computable, human-readable biological networks with a structured syntax are a powerful way of representing biological information generated from high-density data. This article presents sbv IMPROVER, a crowd-verification approach for the visualization and expansion of biological networks.

White House announces “big data” initiative

NASA Astrophysics Data System (ADS)

Showstack, Randy

2012-04-01

The world is now generating zetabytes—which is 10 to the 21st power, or a billion trillion bytess—of information every year, according to John Holdren, director of the White House Office of Science and Technology Policy. With data volumes growing exponentially from a variety of sources such as computers running large-scale models, scientific instruments including telescopes and particle accelerators, and even online retail transactions, a key challenge is to better manage and utilize the data. The Big Data Research and Development Initiative, launched by the White House at a 29 March briefing, initially includes six federal departments and agencies providing more than $200 million in new commitments to improve tools and techniques for better accessing, organizing, and using data for scientific advances. The agencies and departments include the National Science Foundation (NSF), Department of Energy, U.S. Geological Survey (USGS), National Institutes of Health (NIH), Department of Defense, and Defense Advanced Research Projects Agency.

Limiting technologies for particle beams and high energy physics

NASA Astrophysics Data System (ADS)

Panofsky, W. K. H.

1985-07-01

Since 1930 the energy of accelerators had grown by an order of magnitude roughly every 7 years. Like all exponential growths, be they human population, the size of computers, or anything else, this eventually will have to come to an end. When will this happen to the growth of the energy of particle accelerators and colliders? Fortunately, as the energy of accelerators has grown the cost per unit energy has decreased almost as fast as has the increase in energy. The result is that while the energy has increased so dramatically the cost per new installation has increased only by roughly an order of magnitude since the 1930's (corrected for inflation), while the number of accelerators operating at the frontier of the field has shrunk. As is shown in the by now familiar Livingston chart this dramatic decrease in cost has been achieved largely by a succession of new technologies, in addition to the more moderate gains in efficiency due to improved design, economies of scale, etc. We are therefore facing two questions: (1) Is there good reason scientifically to maintain the exponential growth, and (2) Are there new technologies in sight which promise continued decreases in unit costs. The answer to the first question is definitely yes; the answer to the second question is maybe.

Active Storage with Analytics Capabilities and I/O Runtime System for Petascale Systems

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

Choudhary, Alok

Computational scientists must understand results from experimental, observational and computational simulation generated data to gain insights and perform knowledge discovery. As systems approach the petascale range, problems that were unimaginable a few years ago are within reach. With the increasing volume and complexity of data produced by ultra-scale simulations and high-throughput experiments, understanding the science is largely hampered by the lack of comprehensive I/O, storage, acceleration of data manipulation, analysis, and mining tools. Scientists require techniques, tools and infrastructure to facilitate better understanding of their data, in particular the ability to effectively perform complex data analysis, statistical analysis and knowledgemore » discovery. The goal of this work is to enable more effective analysis of scientific datasets through the integration of enhancements in the I/O stack, from active storage support at the file system layer to MPI-IO and high-level I/O library layers. We propose to provide software components to accelerate data analytics, mining, I/O, and knowledge discovery for large-scale scientific applications, thereby increasing productivity of both scientists and the systems. Our approaches include 1) design the interfaces in high-level I/O libraries, such as parallel netCDF, for applications to activate data mining operations at the lower I/O layers; 2) Enhance MPI-IO runtime systems to incorporate the functionality developed as a part of the runtime system design; 3) Develop parallel data mining programs as part of runtime library for server-side file system in PVFS file system; and 4) Prototype an active storage cluster, which will utilize multicore CPUs, GPUs, and FPGAs to carry out the data mining workload.« less

76 FR 41234 - Advanced Scientific Computing Advisory Committee Charter Renewal

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-13

... Secretariat, General Services Administration, notice is hereby given that the Advanced Scientific Computing... advice and recommendations concerning the Advanced Scientific Computing program in response only to... Advanced Scientific Computing Research program and recommendations based thereon; --Advice on the computing...

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.

Accelerator Science: Circular vs. Linear

ScienceCinema

Lincoln, Don

2018-06-12

Particle accelerator are scientific instruments that allow scientists to collide particles together at incredible energies to study the secrets of the universe. However, there are many manners in which particle accelerators can be constructed. In this video, Fermilab’s Dr. Don Lincoln explains the pros and cons of circular and linear accelerators.

Management, Analysis, and Visualization of Experimental and Observational Data – The Convergence of Data and Computing

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

Bethel, E. Wes; Greenwald, Martin; Kleese van Dam, Kerstin

Scientific user facilities—particle accelerators, telescopes, colliders, supercomputers, light sources, sequencing facilities, and more—operated by the U.S. Department of Energy (DOE) Office of Science (SC) generate ever increasing volumes of data at unprecedented rates from experiments, observations, and simulations. At the same time there is a growing community of experimentalists that require real-time data analysis feedback, to enable them to steer their complex experimental instruments to optimized scientific outcomes and new discoveries. Recent efforts in DOE-SC have focused on articulating the data-centric challenges and opportunities facing these science communities. Key challenges include difficulties coping with data size, rate, and complexity inmore » the context of both real-time and post-experiment data analysis and interpretation. Solutions will require algorithmic and mathematical advances, as well as hardware and software infrastructures that adequately support data-intensive scientific workloads. This paper presents the summary findings of a workshop held by DOE-SC in September 2015, convened to identify the major challenges and the research that is needed to meet those challenges.« less

Management, Analysis, and Visualization of Experimental and Observational Data -- The Convergence of Data and Computing

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

Bethel, E. Wes; Greenwald, Martin; Kleese van Dam, Kersten

Scientific user facilities---particle accelerators, telescopes, colliders, supercomputers, light sources, sequencing facilities, and more---operated by the U.S. Department of Energy (DOE) Office of Science (SC) generate ever increasing volumes of data at unprecedented rates from experiments, observations, and simulations. At the same time there is a growing community of experimentalists that require real-time data analysis feedback, to enable them to steer their complex experimental instruments to optimized scientific outcomes and new discoveries. Recent efforts in DOE-SC have focused on articulating the data-centric challenges and opportunities facing these science communities. Key challenges include difficulties coping with data size, rate, and complexity inmore » the context of both real-time and post-experiment data analysis and interpretation. Solutions will require algorithmic and mathematical advances, as well as hardware and software infrastructures that adequately support data-intensive scientific workloads. This paper presents the summary findings of a workshop held by DOE-SC in September 2015, convened to identify the major challenges and the research that is needed to meet those challenges.« less

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

Perumalla, Kalyan S.; Yoginath, Srikanth B.

Problems such as fault tolerance and scalable synchronization can be efficiently solved using reversibility of applications. Making applications reversible by relying on computation rather than on memory is ideal for large scale parallel computing, especially for the next generation of supercomputers in which memory is expensive in terms of latency, energy, and price. In this direction, a case study is presented here in reversing a computational core, namely, Basic Linear Algebra Subprograms, which is widely used in scientific applications. A new Reversible BLAS (RBLAS) library interface has been designed, and a prototype has been implemented with two modes: (1) amore » memory-mode in which reversibility is obtained by checkpointing to memory in forward and restoring from memory in reverse, and (2) a computational-mode in which nothing is saved in the forward, but restoration is done entirely via inverse computation in reverse. The article is focused on detailed performance benchmarking to evaluate the runtime dynamics and performance effects, comparing reversible computation with checkpointing on both traditional CPU platforms and recent GPU accelerator platforms. For BLAS Level-1 subprograms, data indicates over an order of magnitude better speed of reversible computation compared to checkpointing. For BLAS Level-2 and Level-3, a more complex tradeoff is observed between reversible computation and checkpointing, depending on computational and memory complexities of the subprograms.« less

On the use of reverse Brownian motion to accelerate hybrid simulations

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

Bakarji, Joseph; Tartakovsky, Daniel M., E-mail: tartakovsky@stanford.edu

Multiscale and multiphysics simulations are two rapidly developing fields of scientific computing. Efficient coupling of continuum (deterministic or stochastic) constitutive solvers with their discrete (stochastic, particle-based) counterparts is a common challenge in both kinds of simulations. We focus on interfacial, tightly coupled simulations of diffusion that combine continuum and particle-based solvers. The latter employs the reverse Brownian motion (rBm), a Monte Carlo approach that allows one to enforce inhomogeneous Dirichlet, Neumann, or Robin boundary conditions and is trivially parallelizable. We discuss numerical approaches for improving the accuracy of rBm in the presence of inhomogeneous Neumann boundary conditions and alternative strategiesmore » for coupling the rBm solver with its continuum counterpart. Numerical experiments are used to investigate the convergence, stability, and computational efficiency of the proposed hybrid algorithm.« less

plasmaFoam: An OpenFOAM framework for computational plasma physics and chemistry

NASA Astrophysics Data System (ADS)

Venkattraman, Ayyaswamy; Verma, Abhishek Kumar

2016-09-01

As emphasized in the 2012 Roadmap for low temperature plasmas (LTP), scientific computing has emerged as an essential tool for the investigation and prediction of the fundamental physical and chemical processes associated with these systems. While several in-house and commercial codes exist, with each having its own advantages and disadvantages, a common framework that can be developed by researchers from all over the world will likely accelerate the impact of computational studies on advances in low-temperature plasma physics and chemistry. In this regard, we present a finite volume computational toolbox to perform high-fidelity simulations of LTP systems. This framework, primarily based on the OpenFOAM solver suite, allows us to enhance our understanding of multiscale plasma phenomenon by performing massively parallel, three-dimensional simulations on unstructured meshes using well-established high performance computing tools that are widely used in the computational fluid dynamics community. In this talk, we will present preliminary results obtained using the OpenFOAM-based solver suite with benchmark three-dimensional simulations of microplasma devices including both dielectric and plasma regions. We will also discuss the future outlook for the solver suite.

OCCAM: a flexible, multi-purpose and extendable HPC cluster

NASA Astrophysics Data System (ADS)

Aldinucci, M.; Bagnasco, S.; Lusso, S.; Pasteris, P.; Rabellino, S.; Vallero, S.

2017-10-01

The Open Computing Cluster for Advanced data Manipulation (OCCAM) is a multipurpose flexible HPC cluster designed and operated by a collaboration between the University of Torino and the Sezione di Torino of the Istituto Nazionale di Fisica Nucleare. It is aimed at providing a flexible, reconfigurable and extendable infrastructure to cater to a wide range of different scientific computing use cases, including ones from solid-state chemistry, high-energy physics, computer science, big data analytics, computational biology, genomics and many others. Furthermore, it will serve as a platform for R&D activities on computational technologies themselves, with topics ranging from GPU acceleration to Cloud Computing technologies. A heterogeneous and reconfigurable system like this poses a number of challenges related to the frequency at which heterogeneous hardware resources might change their availability and shareability status, which in turn affect methods and means to allocate, manage, optimize, bill, monitor VMs, containers, virtual farms, jobs, interactive bare-metal sessions, etc. This work describes some of the use cases that prompted the design and construction of the HPC cluster, its architecture and resource provisioning model, along with a first characterization of its performance by some synthetic benchmark tools and a few realistic use-case tests.

Massive Exploration of Perturbed Conditions of the Blood Coagulation Cascade through GPU Parallelization

PubMed Central

Cazzaniga, Paolo; Nobile, Marco S.; Besozzi, Daniela; Bellini, Matteo; Mauri, Giancarlo

2014-01-01

The introduction of general-purpose Graphics Processing Units (GPUs) is boosting scientific applications in Bioinformatics, Systems Biology, and Computational Biology. In these fields, the use of high-performance computing solutions is motivated by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the capability of standard desktop computers. In this work we present coagSODA, a CUDA-powered computational tool that was purposely developed for the analysis of a large mechanistic model of the blood coagulation cascade (BCC), defined according to both mass-action kinetics and Hill functions. coagSODA allows the execution of parallel simulations of the dynamics of the BCC by automatically deriving the system of ordinary differential equations and then exploiting the numerical integration algorithm LSODA. We present the biological results achieved with a massive exploration of perturbed conditions of the BCC, carried out with one-dimensional and bi-dimensional parameter sweep analysis, and show that GPU-accelerated parallel simulations of this model can increase the computational performances up to a 181× speedup compared to the corresponding sequential simulations. PMID:25025072

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.

Advanced Computing Tools and Models for Accelerator Physics

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

Ryne, Robert; Ryne, Robert D.

2008-06-11

This paper is based on a transcript of my EPAC'08 presentation on advanced computing tools for accelerator physics. Following an introduction I present several examples, provide a history of the development of beam dynamics capabilities, and conclude with thoughts on the future of large scale computing in accelerator physics.

76 FR 31945 - Advanced Scientific Computing Advisory Committee

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2011-06-02

... DEPARTMENT OF ENERGY Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy... teleconference meeting of the Advanced Scientific Computing Advisory Committee (ASCAC). The Federal [email protected] . FOR FURTHER INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing...

Preface: SciDAC 2006

NASA Astrophysics Data System (ADS)

Tang, William M., Dr.

2006-01-01

The second annual Scientific Discovery through Advanced Computing (SciDAC) Conference was held from June 25-29, 2006 at the new Hyatt Regency Hotel in Denver, Colorado. This conference showcased outstanding SciDAC-sponsored computational science results achieved during the past year across many scientific domains, with an emphasis on science at scale. Exciting computational science that has been accomplished outside of the SciDAC program both nationally and internationally was also featured to help foster communication between SciDAC computational scientists and those funded by other agencies. This was illustrated by many compelling examples of how domain scientists collaborated productively with applied mathematicians and computer scientists to effectively take advantage of terascale computers (capable of performing trillions of calculations per second) not only to accelerate progress in scientific discovery in a variety of fields but also to show great promise for being able to utilize the exciting petascale capabilities in the near future. The SciDAC program was originally conceived as an interdisciplinary computational science program based on the guiding principle that strong collaborative alliances between domain scientists, applied mathematicians, and computer scientists are vital to accelerated progress and associated discovery on the world's most challenging scientific problems. Associated verification and validation are essential in this successful program, which was funded by the US Department of Energy Office of Science (DOE OS) five years ago. As is made clear in many of the papers in these proceedings, SciDAC has fundamentally changed the way that computational science is now carried out in response to the exciting challenge of making the best use of the rapid progress in the emergence of more and more powerful computational platforms. In this regard, Dr. Raymond Orbach, Energy Undersecretary for Science at the DOE and Director of the OS has stated: `SciDAC has strengthened the role of high-end computing in furthering science. It is defining whole new fields for discovery.' (SciDAC Review, Spring 2006, p8). Application domains within the SciDAC 2006 conference agenda encompassed a broad range of science including: (i) the DOE core mission of energy research involving combustion studies relevant to fuel efficiency and pollution issues faced today and magnetic fusion investigations impacting prospects for future energy sources; (ii) fundamental explorations into the building blocks of matter, ranging from quantum chromodynamics - the basic theory that describes how quarks make up the protons and neutrons of all matter - to the design of modern high-energy accelerators; (iii) the formidable challenges of predicting and controlling the behavior of molecules in quantum chemistry and the complex biomolecules determining the evolution of biological systems; (iv) studies of exploding stars for insights into the nature of the universe; and (v) integrated climate modeling to enable realistic analysis of earth's changing climate. Associated research has made it quite clear that advanced computation is often the only means by which timely progress is feasible when dealing with these complex, multi-component physical, chemical, and biological systems operating over huge ranges of temporal and spatial scales. Working with the domain scientists, applied mathematicians and computer scientists have continued to develop the discretizations of the underlying equations and the complementary algorithms to enable improvements in solutions on modern parallel computing platforms as they evolve from the terascale toward the petascale regime. Moreover, the associated tremendous growth of data generated from the terabyte to the petabyte range demands not only the advanced data analysis and visualization methods to harvest the scientific information but also the development of efficient workflow strategies which can deal with the data input/output, management, movement, and storage challenges. If scientific discovery is expected to keep apace with the continuing progression from tera- to petascale platforms, the vital alliance between domain scientists, applied mathematicians, and computer scientists will be even more crucial. During the SciDAC 2006 Conference, some of the future challenges and opportunities in interdisciplinary computational science were emphasized in the Advanced Architectures Panel and by Dr. Victor Reis, Senior Advisor to the Secretary of Energy, who gave a featured presentation on `Simulation, Computation, and the Global Nuclear Energy Partnership.' Overall, the conference provided an excellent opportunity to highlight the rising importance of computational science in the scientific enterprise and to motivate future investment in this area. As Michael Strayer, SciDAC Program Director, has noted: `While SciDAC may have started out as a specific program, Scientific Discovery through Advanced Computing has become a powerful concept for addressing some of the biggest challenges facing our nation and our world.' Looking forward to next year, the SciDAC 2007 Conference will be held from June 24-28 at the Westin Copley Plaza in Boston, Massachusetts. Chairman: David Keyes, Columbia University. The Organizing Committee for the SciDAC 2006 Conference would like to acknowledge the individuals whose talents and efforts were essential to the success of the meeting. Special thanks go to Betsy Riley for her leadership in building the infrastructure support for the conference, for identifying and then obtaining contributions from our corporate sponsors, for coordinating all media communications, and for her efforts in organizing and preparing the conference proceedings for publication; to Tim Jones for handling the hotel scouting, subcontracts, and exhibits and stage production; to Angela Harris for handling supplies, shipping, and tracking, poster sessions set-up, and for her efforts in coordinating and scheduling the promotional activities that took place during the conference; to John Bui and John Smith for their superb wireless networking and A/V set-up and support; to Cindy Latham for Web site design, graphic design, and quality control of proceedings submissions; and to Pamelia Nixon-Hartje of Ambassador for budget and quality control of catering. We are grateful for the highly professional dedicated efforts of all of these individuals, who were the cornerstones of the SciDAC 2006 Conference. Thanks also go to Angela Beach of the ORNL Conference Center for her efforts in executing the contracts with the hotel, Carolyn James of Colorado State for on-site registration supervision, Lora Wolfe and Brittany Hagen for administrative support at ORNL, and Dami Rich and Andrew Sproles for graphic design and production. We are also most grateful to the Oak Ridge National Laboratory, especially Jeff Nichols, and to our corporate sponsors, Data Direct Networks, Cray, IBM, SGI, and Institute of Physics Publishing for their support. We especially express our gratitude to the featured speakers, invited oral speakers, invited poster presenters, session chairs, and advanced architecture panelists and chair for their excellent contributions on behalf of SciDAC 2006. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas, Margaret Smith, and the production team of Institute of Physics Publishing, who worked tirelessly to publish the final conference proceedings in a timely manner. Finally, heartfelt thanks are extended to Michael Strayer, Associate Director for OASCR and SciDAC Director, and to the DOE program managers associated with SciDAC for their continuing enthusiasm and strong support for the annual SciDAC Conferences as a special venue to showcase the exciting scientific discovery achievements enabled by the interdisciplinary collaborations championed by the SciDAC program.

Exploiting on-node heterogeneity for in-situ analytics of climate simulations via a functional partitioning framework

NASA Astrophysics Data System (ADS)

Sapra, Karan; Gupta, Saurabh; Atchley, Scott; Anantharaj, Valentine; Miller, Ross; Vazhkudai, Sudharshan

2016-04-01

Efficient resource utilization is critical for improved end-to-end computing and workflow of scientific applications. Heterogeneous node architectures, such as the GPU-enabled Titan supercomputer at the Oak Ridge Leadership Computing Facility (OLCF), present us with further challenges. In many HPC applications on Titan, the accelerators are the primary compute engines while the CPUs orchestrate the offloading of work onto the accelerators, and moving the output back to the main memory. On the other hand, applications that do not exploit GPUs, the CPU usage is dominant while the GPUs idle. We utilized Heterogenous Functional Partitioning (HFP) runtime framework that can optimize usage of resources on a compute node to expedite an application's end-to-end workflow. This approach is different from existing techniques for in-situ analyses in that it provides a framework for on-the-fly analysis on-node by dynamically exploiting under-utilized resources therein. We have implemented in the Community Earth System Model (CESM) a new concurrent diagnostic processing capability enabled by the HFP framework. Various single variate statistics, such as means and distributions, are computed in-situ by launching HFP tasks on the GPU via the node local HFP daemon. Since our current configuration of CESM does not use GPU resources heavily, we can move these tasks to GPU using the HFP framework. Each rank running the atmospheric model in CESM pushes the variables of of interest via HFP function calls to the HFP daemon. This node local daemon is responsible for receiving the data from main program and launching the designated analytics tasks on the GPU. We have implemented these analytics tasks in C and use OpenACC directives to enable GPU acceleration. This methodology is also advantageous while executing GPU-enabled configurations of CESM when the CPUs will be idle during portions of the runtime. In our implementation results, we demonstrate that it is more efficient to use HFP framework to offload the tasks to GPUs instead of doing it in the main application. We observe increased resource utilization and overall productivity in this approach by using HFP framework for end-to-end workflow.

BioPig: a Hadoop-based analytic toolkit for large-scale sequence data.

PubMed

Nordberg, Henrik; Bhatia, Karan; Wang, Kai; Wang, Zhong

2013-12-01

The recent revolution in sequencing technologies has led to an exponential growth of sequence data. As a result, most of the current bioinformatics tools become obsolete as they fail to scale with data. To tackle this 'data deluge', here we introduce the BioPig sequence analysis toolkit as one of the solutions that scale to data and computation. We built BioPig on the Apache's Hadoop MapReduce system and the Pig data flow language. Compared with traditional serial and MPI-based algorithms, BioPig has three major advantages: first, BioPig's programmability greatly reduces development time for parallel bioinformatics applications; second, testing BioPig with up to 500 Gb sequences demonstrates that it scales automatically with size of data; and finally, BioPig can be ported without modification on many Hadoop infrastructures, as tested with Magellan system at National Energy Research Scientific Computing Center and the Amazon Elastic Compute Cloud. In summary, BioPig represents a novel program framework with the potential to greatly accelerate data-intensive bioinformatics analysis.

Accelerating Scientific Advancement for Pediatric Rare Lung Disease Research. Report from a National Institutes of Health-NHLBI Workshop, September 3 and 4, 2015.

PubMed

Young, Lisa R; Trapnell, Bruce C; Mandl, Kenneth D; Swarr, Daniel T; Wambach, Jennifer A; Blaisdell, Carol J

2016-12-01

Pediatric rare lung disease (PRLD) is a term that refers to a heterogeneous group of rare disorders in children. In recent years, this field has experienced significant progress marked by scientific discoveries, multicenter and interdisciplinary collaborations, and efforts of patient advocates. Although genetic mechanisms underlie many PRLDs, pathogenesis remains uncertain for many of these disorders. Furthermore, epidemiology and natural history are insufficiently defined, and therapies are limited. To develop strategies to accelerate scientific advancement for PRLD research, the NHLBI of the National Institutes of Health convened a strategic planning workshop on September 3 and 4, 2015. The workshop brought together a group of scientific experts, intramural and extramural investigators, and advocacy groups with the following objectives: (1) to discuss the current state of PRLD research; (2) to identify scientific gaps and barriers to increasing research and improving outcomes for PRLDs; (3) to identify technologies, tools, and reagents that could be leveraged to accelerate advancement of research in this field; and (4) to develop priorities for research aimed at improving patient outcomes and quality of life. This report summarizes the workshop discussion and provides specific recommendations to guide future research in PRLD.

Finite-element approach to Brownian dynamics of polymers.

PubMed

Cyron, Christian J; Wall, Wolfgang A

2009-12-01

In the last decades simulation tools for Brownian dynamics of polymers have attracted more and more interest. Such simulation tools have been applied to a large variety of problems and accelerated the scientific progress significantly. However, the currently most frequently used explicit bead models exhibit severe limitations, especially with respect to time step size, the necessity of artificial constraints and the lack of a sound mathematical foundation. Here we present a framework for simulations of Brownian polymer dynamics based on the finite-element method. This approach allows simulating a wide range of physical phenomena at a highly attractive computational cost on the basis of a far-developed mathematical background.

75 FR 9887 - Advanced Scientific Computing Advisory Committee

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2010-03-04

... DEPARTMENT OF ENERGY Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy... Advanced Scientific Computing Advisory Committee (ASCAC). Federal Advisory Committee Act (Pub. L. 92-463... INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building...

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2011-02-22

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2010-10-20

... DEPARTMENT OF ENERGY DOE/Advanced Scientific Computing Advisory Committee AGENCY: Department of... the Advanced Scientific Computing Advisory Committee (ASCAC). Federal Advisory Committee Act (Pub. L.... FOR FURTHER INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21...

Computing through Scientific Abstractions in SysBioPS

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

Chin, George; Stephan, Eric G.; Gracio, Deborah K.

2004-10-13

Today, biologists and bioinformaticists have a tremendous amount of computational power at their disposal. With the availability of supercomputers, burgeoning scientific databases and digital libraries such as GenBank and PubMed, and pervasive computational environments such as the Grid, biologists have access to a wealth of computational capabilities and scientific data at hand. Yet, the rapid development of computational technologies has far exceeded the typical biologist’s ability to effectively apply the technology in their research. Computational sciences research and development efforts such as the Biology Workbench, BioSPICE (Biological Simulation Program for Intra-Cellular Evaluation), and BioCoRE (Biological Collaborative Research Environment) are importantmore » in connecting biologists and their scientific problems to computational infrastructures. On the Computational Cell Environment and Heuristic Entity-Relationship Building Environment projects at the Pacific Northwest National Laboratory, we are jointly developing a new breed of scientific problem solving environment called SysBioPSE that will allow biologists to access and apply computational resources in the scientific research context. In contrast to other computational science environments, SysBioPSE operates as an abstraction layer above a computational infrastructure. The goal of SysBioPSE is to allow biologists to apply computational resources in the context of the scientific problems they are addressing and the scientific perspectives from which they conduct their research. More specifically, SysBioPSE allows biologists to capture and represent scientific concepts and theories and experimental processes, and to link these views to scientific applications, data repositories, and computer systems.« less

A unified perspective on ankle push-off in human walking

PubMed Central

Adamczyk, Peter G.

2016-01-01

ABSTRACT Muscle–tendon units about the ankle joint generate a burst of positive power during the step-to-step transition in human walking, termed ankle push-off, but there is no scientific consensus on its functional role. A central question embodied in the biomechanics literature is: does ankle push-off primarily contribute to leg swing, or to center of mass (COM) acceleration? This question has been debated in various forms for decades. However, it actually presents a false dichotomy, as these two possibilities are not mutually exclusive. If we ask either question independently, the answer is the same: yes! (1) Does ankle push-off primarily contribute to leg swing acceleration? Yes. (2) Does ankle push-off primarily contribute to COM acceleration? Yes. Here, we summarize the historical debate, then synthesize the seemingly polarized perspectives and demonstrate that both descriptions are valid. The principal means by which ankle push-off affects COM mechanics is by a localized action that increases the speed and kinetic energy of the trailing push-off limb. Because the limb is included in body COM computations, this localized segmental acceleration also accelerates the COM, and most of the segmental energy change also appears as COM energy change. Interpretation of ankle mechanics should abandon an either/or contrast of leg swing versus COM acceleration. Instead, ankle push-off should be interpreted in light of both mutually consistent effects. This unified perspective informs our fundamental understanding of the role of ankle push-off, and has important implications for the design of clinical interventions (e.g. prostheses, orthoses) intended to restore locomotor function to individuals with disabilities. PMID:27903626

75 FR 43518 - Advanced Scientific Computing Advisory Committee; Meeting

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2010-07-26

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Choosing experiments to accelerate collective discovery

DOE PAGES

Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.; ...

2015-11-24

Scientists perform a tiny subset of all possible experiments. What characterizes the experiments they choose? What are the consequences of those choices for the pace of scientific discovery? We model scientific knowledge as a network and science as a sequence of experiments designed to gradually uncover it. By analyzing millions of biomedical articles published over 30 y, we find that biomedical scientists pursue conservative research strategies exploring the local neighborhood of central, important molecules. Although such strategies probably serve scientific careers, we show that they slow scientific advance, especially in mature fields, where more risk and less redundant experimentation wouldmore » accelerate discovery of the network. Lastly, we also consider institutional arrangements that could help science pursue these more efficient strategies.« less

Accelerated Application Development: The ORNL Titan Experience

DOE PAGES

Joubert, Wayne; Archibald, Richard K.; Berrill, Mark A.; ...

2015-05-09

The use of computational accelerators such as NVIDIA GPUs and Intel Xeon Phi processors is now widespread in the high performance computing community, with many applications delivering impressive performance gains. However, programming these systems for high performance, performance portability and software maintainability has been a challenge. In this paper we discuss experiences porting applications to the Titan system. Titan, which began planning in 2009 and was deployed for general use in 2013, was the first multi-petaflop system based on accelerator hardware. To ready applications for accelerated computing, a preparedness effort was undertaken prior to delivery of Titan. In this papermore » we report experiences and lessons learned from this process and describe how users are currently making use of computational accelerators on Titan.« less

Accelerated application development: The ORNL Titan experience

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

Joubert, Wayne; Archibald, Rick; Berrill, Mark

2015-08-01

The use of computational accelerators such as NVIDIA GPUs and Intel Xeon Phi processors is now widespread in the high performance computing community, with many applications delivering impressive performance gains. However, programming these systems for high performance, performance portability and software maintainability has been a challenge. In this paper we discuss experiences porting applications to the Titan system. Titan, which began planning in 2009 and was deployed for general use in 2013, was the first multi-petaflop system based on accelerator hardware. To ready applications for accelerated computing, a preparedness effort was undertaken prior to delivery of Titan. In this papermore » we report experiences and lessons learned from this process and describe how users are currently making use of computational accelerators on Titan.« less

Particle acceleration, transport and turbulence in cosmic and heliospheric physics

NASA Technical Reports Server (NTRS)

Matthaeus, W.

1992-01-01

In this progress report, the long term goals, recent scientific progress, and organizational activities are described. The scientific focus of this annual report is in three areas: first, the physics of particle acceleration and transport, including heliospheric modulation and transport, shock acceleration and galactic propagation and reacceleration of cosmic rays; second, the development of theories of the interaction of turbulence and large scale plasma and magnetic field structures, as in winds and shocks; third, the elucidation of the nature of magnetohydrodynamic turbulence processes and the role such turbulence processes might play in heliospheric, galactic, cosmic ray physics, and other space physics applications.

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

PubMed Central

Manconi, Andrea; Orro, Alessandro; Manca, Emanuele; Armano, Giuliano; Milanesi, Luciano

2014-01-01

Cytosine DNA methylation is an epigenetic mark implicated in several biological processes. Bisulfite treatment of DNA is acknowledged as the gold standard technique to study methylation. This technique introduces changes in the genomic DNA by converting cytosines to uracils while 5-methylcytosines remain nonreactive. During PCR amplification 5-methylcytosines are amplified as cytosine, whereas uracils and thymines as thymine. To detect the methylation levels, reads treated with the bisulfite must be aligned against a reference genome. Mapping these reads to a reference genome represents a significant computational challenge mainly due to the increased search space and the loss of information introduced by the treatment. To deal with this computational challenge we devised GPU-BSM, a tool based on modern Graphics Processing Units. Graphics Processing Units are hardware accelerators that are increasingly being used successfully to accelerate general-purpose scientific applications. GPU-BSM is a tool able to map bisulfite-treated reads from whole genome bisulfite sequencing and reduced representation bisulfite sequencing, and to estimate methylation levels, with the goal of detecting methylation. Due to the massive parallelization obtained by exploiting graphics cards, GPU-BSM aligns bisulfite-treated reads faster than other cutting-edge solutions, while outperforming most of them in terms of unique mapped reads. PMID:24842718

Fully accelerating quantum Monte Carlo simulations of real materials on GPU clusters

NASA Astrophysics Data System (ADS)

Esler, Kenneth

2011-03-01

Quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles, combining very high accuracy with extreme parallel scalability. By solving the many-body Schrödinger equation through a stochastic projection, it achieves greater accuracy than mean-field methods and better scaling with system size than quantum chemical methods, enabling scientific discovery across a broad spectrum of disciplines. In recent years, graphics processing units (GPUs) have provided a high-performance and low-cost new approach to scientific computing, and GPU-based supercomputers are now among the fastest in the world. The multiple forms of parallelism afforded by QMC algorithms make the method an ideal candidate for acceleration in the many-core paradigm. We present the results of porting the QMCPACK code to run on GPU clusters using the NVIDIA CUDA platform. Using mixed precision on GPUs and MPI for intercommunication, we observe typical full-application speedups of approximately 10x to 15x relative to quad-core CPUs alone, while reproducing the double-precision CPU results within statistical error. We discuss the algorithm modifications necessary to achieve good performance on this heterogeneous architecture and present the results of applying our code to molecules and bulk materials. Supported by the U.S. DOE under Contract No. DOE-DE-FG05-08OR23336 and by the NSF under No. 0904572.

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-09-01

Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in exascale simulations.

Chaste: An Open Source C++ Library for Computational Physiology and Biology

PubMed Central

Mirams, Gary R.; Arthurs, Christopher J.; Bernabeu, Miguel O.; Bordas, Rafel; Cooper, Jonathan; Corrias, Alberto; Davit, Yohan; Dunn, Sara-Jane; Fletcher, Alexander G.; Harvey, Daniel G.; Marsh, Megan E.; Osborne, James M.; Pathmanathan, Pras; Pitt-Francis, Joe; Southern, James; Zemzemi, Nejib; Gavaghan, David J.

2013-01-01

Chaste — Cancer, Heart And Soft Tissue Environment — is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to ‘re-invent the wheel’ with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials. PMID:23516352

The rise of machine consciousness: studying consciousness with computational models.

PubMed

Reggia, James A

2013-08-01

Efforts to create computational models of consciousness have accelerated over the last two decades, creating a field that has become known as artificial consciousness. There have been two main motivations for this controversial work: to develop a better scientific understanding of the nature of human/animal consciousness and to produce machines that genuinely exhibit conscious awareness. This review begins by briefly explaining some of the concepts and terminology used by investigators working on machine consciousness, and summarizes key neurobiological correlates of human consciousness that are particularly relevant to past computational studies. Models of consciousness developed over the last twenty years are then surveyed. These models are largely found to fall into five categories based on the fundamental issue that their developers have selected as being most central to consciousness: a global workspace, information integration, an internal self-model, higher-level representations, or attention mechanisms. For each of these five categories, an overview of past work is given, a representative example is presented in some detail to illustrate the approach, and comments are provided on the contributions and limitations of the methodology. Three conclusions are offered about the state of the field based on this review: (1) computational modeling has become an effective and accepted methodology for the scientific study of consciousness, (2) existing computational models have successfully captured a number of neurobiological, cognitive, and behavioral correlates of conscious information processing as machine simulations, and (3) no existing approach to artificial consciousness has presented a compelling demonstration of phenomenal machine consciousness, or even clear evidence that artificial phenomenal consciousness will eventually be possible. The paper concludes by discussing the importance of continuing work in this area, considering the ethical issues it raises, and making predictions concerning future developments. Copyright © 2013 Elsevier Ltd. All rights reserved.

Software for Managing Parametric Studies

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; McCann, Karen M.; DeVivo, Adrian

2003-01-01

The Information Power Grid Virtual Laboratory (ILab) is a Practical Extraction and Reporting Language (PERL) graphical-user-interface computer program that generates shell scripts to facilitate parametric studies performed on the Grid. (The Grid denotes a worldwide network of supercomputers used for scientific and engineering computations involving data sets too large to fit on desktop computers.) Heretofore, parametric studies on the Grid have been impeded by the need to create control language scripts and edit input data files painstaking tasks that are necessary for managing multiple jobs on multiple computers. ILab reflects an object-oriented approach to automation of these tasks: All data and operations are organized into packages in order to accelerate development and debugging. A container or document object in ILab, called an experiment, contains all the information (data and file paths) necessary to define a complex series of repeated, sequenced, and/or branching processes. For convenience and to enable reuse, this object is serialized to and from disk storage. At run time, the current ILab experiment is used to generate required input files and shell scripts, create directories, copy data files, and then both initiate and monitor the execution of all computational processes.

GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

NASA Astrophysics Data System (ADS)

Spiechowicz, J.; Kostur, M.; Machura, L.

2015-06-01

This work presents an updated and extended guide on methods of a proper acceleration of the Monte Carlo integration of stochastic differential equations with the commonly available NVIDIA Graphics Processing Units using the CUDA programming environment. We outline the general aspects of the scientific computing on graphics cards and demonstrate them with two models of a well known phenomenon of the noise induced transport of Brownian motors in periodic structures. As a source of fluctuations in the considered systems we selected the three most commonly occurring noises: the Gaussian white noise, the white Poissonian noise and the dichotomous process also known as a random telegraph signal. The detailed discussion on various aspects of the applied numerical schemes is also presented. The measured speedup can be of the astonishing order of about 3000 when compared to a typical CPU. This number significantly expands the range of problems solvable by use of stochastic simulations, allowing even an interactive research in some cases.

High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics

DOE PAGES

Amundson, James; Macridin, Alexandru; Spentzouris, Panagiotis

2014-07-28

The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable ofmore » handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.« less

Acceleration and Velocity Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truax, Roger

2015-01-01

A simple approach for computing acceleration and velocity of a structure from the strain is proposed in this study. First, deflection and slope of the structure are computed from the strain using a two-step theory. Frequencies of the structure are computed from the time histories of strain using a parameter estimation technique together with an autoregressive moving average model. From deflection, slope, and frequencies of the structure, acceleration and velocity of the structure can be obtained using the proposed approach. Simple harmonic motion is assumed for the acceleration computations, and the central difference equation with a linear autoregressive model is used for the computations of velocity. A cantilevered rectangular wing model is used to validate the simple approach. Quality of the computed deflection, acceleration, and velocity values are independent of the number of fibers. The central difference equation with a linear autoregressive model proposed in this study follows the target response with reasonable accuracy. Therefore, the handicap of the backward difference equation, phase shift, is successfully overcome.

Parallelization of combinatorial search when solving knapsack optimization problem on computing systems based on multicore processors

NASA Astrophysics Data System (ADS)

Rahman, P. A.

2018-05-01

This scientific paper deals with the model of the knapsack optimization problem and method of its solving based on directed combinatorial search in the boolean space. The offered by the author specialized mathematical model of decomposition of the search-zone to the separate search-spheres and the algorithm of distribution of the search-spheres to the different cores of the multi-core processor are also discussed. The paper also provides an example of decomposition of the search-zone to the several search-spheres and distribution of the search-spheres to the different cores of the quad-core processor. Finally, an offered by the author formula for estimation of the theoretical maximum of the computational acceleration, which can be achieved due to the parallelization of the search-zone to the search-spheres on the unlimited number of the processor cores, is also given.

The Materials Commons: A Collaboration Platform and Information Repository for the Global Materials Community

NASA Astrophysics Data System (ADS)

Puchala, Brian; Tarcea, Glenn; Marquis, Emmanuelle. A.; Hedstrom, Margaret; Jagadish, H. V.; Allison, John E.

2016-08-01

Accelerating the pace of materials discovery and development requires new approaches and means of collaborating and sharing information. To address this need, we are developing the Materials Commons, a collaboration platform and information repository for use by the structural materials community. The Materials Commons has been designed to be a continuous, seamless part of the scientific workflow process. Researchers upload the results of experiments and computations as they are performed, automatically where possible, along with the provenance information describing the experimental and computational processes. The Materials Commons website provides an easy-to-use interface for uploading and downloading data and data provenance, as well as for searching and sharing data. This paper provides an overview of the Materials Commons. Concepts are also outlined for integrating the Materials Commons with the broader Materials Information Infrastructure that is evolving to support the Materials Genome Initiative.

Towards reversible basic linear algebra subprograms: A performance study

DOE PAGES

Perumalla, Kalyan S.; Yoginath, Srikanth B.

2014-12-06

Problems such as fault tolerance and scalable synchronization can be efficiently solved using reversibility of applications. Making applications reversible by relying on computation rather than on memory is ideal for large scale parallel computing, especially for the next generation of supercomputers in which memory is expensive in terms of latency, energy, and price. In this direction, a case study is presented here in reversing a computational core, namely, Basic Linear Algebra Subprograms, which is widely used in scientific applications. A new Reversible BLAS (RBLAS) library interface has been designed, and a prototype has been implemented with two modes: (1) amore » memory-mode in which reversibility is obtained by checkpointing to memory in forward and restoring from memory in reverse, and (2) a computational-mode in which nothing is saved in the forward, but restoration is done entirely via inverse computation in reverse. The article is focused on detailed performance benchmarking to evaluate the runtime dynamics and performance effects, comparing reversible computation with checkpointing on both traditional CPU platforms and recent GPU accelerator platforms. For BLAS Level-1 subprograms, data indicates over an order of magnitude better speed of reversible computation compared to checkpointing. For BLAS Level-2 and Level-3, a more complex tradeoff is observed between reversible computation and checkpointing, depending on computational and memory complexities of the subprograms.« less

Accelerating Scientific Advancement for Pediatric Rare Lung Disease Research. Report from a National Institutes of Health–NHLBI Workshop, September 3 and 4, 2015

PubMed Central

Young, Lisa R.; Trapnell, Bruce C.; Mandl, Kenneth D.; Swarr, Daniel T.; Wambach, Jennifer A.

2016-01-01

Pediatric rare lung disease (PRLD) is a term that refers to a heterogeneous group of rare disorders in children. In recent years, this field has experienced significant progress marked by scientific discoveries, multicenter and interdisciplinary collaborations, and efforts of patient advocates. Although genetic mechanisms underlie many PRLDs, pathogenesis remains uncertain for many of these disorders. Furthermore, epidemiology and natural history are insufficiently defined, and therapies are limited. To develop strategies to accelerate scientific advancement for PRLD research, the NHLBI of the National Institutes of Health convened a strategic planning workshop on September 3 and 4, 2015. The workshop brought together a group of scientific experts, intramural and extramural investigators, and advocacy groups with the following objectives: (1) to discuss the current state of PRLD research; (2) to identify scientific gaps and barriers to increasing research and improving outcomes for PRLDs; (3) to identify technologies, tools, and reagents that could be leveraged to accelerate advancement of research in this field; and (4) to develop priorities for research aimed at improving patient outcomes and quality of life. This report summarizes the workshop discussion and provides specific recommendations to guide future research in PRLD. PMID:27925785

Controlling Flexible Robot Arms Using High Speed Dynamics Process

NASA Technical Reports Server (NTRS)

Jain, Abhinandan (Inventor)

1996-01-01

A robot manipulator controller for a flexible manipulator arm having plural bodies connected at respective movable hinges and flexible in plural deformation modes corresponding to respective modal spatial influence vectors relating deformations of plural spaced nodes of respective bodies to the plural deformation modes, operates by computing articulated body quantities for each of the bodies from respective modal spatial influence vectors, obtaining specified body forces for each of the bodies, and computing modal deformation accelerations of the nodes and hinge accelerations of the hinges from the specified body forces, from the articulated body quantities and from the modal spatial influence vectors. In one embodiment of the invention, the controller further operates by comparing the accelerations thus computed to desired manipulator motion to determine a motion discrepancy, and correcting the specified body forces so as to reduce the motion discrepancy. The manipulator bodies and hinges are characterized by respective vectors of deformation and hinge configuration variables, and computing modal deformation accelerations and hinge accelerations is carried out for each one of the bodies beginning with the outermost body by computing a residual body force from a residual body force of a previous body and from the vector of deformation and hinge configuration variables, computing a resultant hinge acceleration from the body force, the residual body force and the articulated hinge inertia, and revising the residual body force modal body acceleration.

A call for virtual experiments: accelerating the scientific process.

PubMed

Cooper, Jonathan; Vik, Jon Olav; Waltemath, Dagmar

2015-01-01

Experimentation is fundamental to the scientific method, whether for exploration, description or explanation. We argue that promoting the reuse of virtual experiments (the in silico analogues of wet-lab or field experiments) would vastly improve the usefulness and relevance of computational models, encouraging critical scrutiny of models and serving as a common language between modellers and experimentalists. We review the benefits of reusable virtual experiments: in specifying, assaying, and comparing the behavioural repertoires of models; as prerequisites for reproducible research; to guide model reuse and composition; and for quality assurance in the translational application of models. A key step towards achieving this is that models and experimental protocols should be represented separately, but annotated so as to facilitate the linking of models to experiments and data. Lastly, we outline how the rigorous, streamlined confrontation between experimental datasets and candidate models would enable a "continuous integration" of biological knowledge, transforming our approach to systems biology. Copyright © 2014 Elsevier Ltd. All rights reserved.

NIH/NSF accelerate biomedical research innovations

Cancer.gov

A collaboration between the National Science Foundation and the National Institutes of Health will give NIH-funded researchers training to help them evaluate their scientific discoveries for commercial potential, with the aim of accelerating biomedical in

A unified perspective on ankle push-off in human walking.

PubMed

Zelik, Karl E; Adamczyk, Peter G

2016-12-01

Muscle-tendon units about the ankle joint generate a burst of positive power during the step-to-step transition in human walking, termed ankle push-off, but there is no scientific consensus on its functional role. A central question embodied in the biomechanics literature is: does ankle push-off primarily contribute to leg swing, or to center of mass (COM) acceleration? This question has been debated in various forms for decades. However, it actually presents a false dichotomy, as these two possibilities are not mutually exclusive. If we ask either question independently, the answer is the same: yes! (1) Does ankle push-off primarily contribute to leg swing acceleration? Yes. (2) Does ankle push-off primarily contribute to COM acceleration? Yes. Here, we summarize the historical debate, then synthesize the seemingly polarized perspectives and demonstrate that both descriptions are valid. The principal means by which ankle push-off affects COM mechanics is by a localized action that increases the speed and kinetic energy of the trailing push-off limb. Because the limb is included in body COM computations, this localized segmental acceleration also accelerates the COM, and most of the segmental energy change also appears as COM energy change. Interpretation of ankle mechanics should abandon an either/or contrast of leg swing versus COM acceleration. Instead, ankle push-off should be interpreted in light of both mutually consistent effects. This unified perspective informs our fundamental understanding of the role of ankle push-off, and has important implications for the design of clinical interventions (e.g. prostheses, orthoses) intended to restore locomotor function to individuals with disabilities. © 2016. Published by The Company of Biologists Ltd.

Acceleration technologies for charged particles: an introduction

NASA Astrophysics Data System (ADS)

Carter, Richard G.

2011-01-01

Particle accelerators have many important uses in scientific experiments, in industry and in medicine. This paper reviews the variety of technologies which are used to accelerate charged particles to high energies. It aims to show how the capabilities and limitations of these technologies are related to underlying physical principles. The paper emphasises the way in which different technologies are used together to convey energy from the electrical supply to the accelerated particles.

FastBit: Interactively Searching Massive Data

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

Wu, Kesheng; Ahern, Sean; Bethel, E. Wes

2009-06-23

As scientific instruments and computer simulations produce more and more data, the task of locating the essential information to gain insight becomes increasingly difficult. FastBit is an efficient software tool to address this challenge. In this article, we present a summary of the key underlying technologies, namely bitmap compression, encoding, and binning. Together these techniques enable FastBit to answer structured (SQL) queries orders of magnitude faster than popular database systems. To illustrate how FastBit is used in applications, we present three examples involving a high-energy physics experiment, a combustion simulation, and an accelerator simulation. In each case, FastBit significantly reducesmore » the response time and enables interactive exploration on terabytes of data.« less

A comparison of acceleration methods for solving the neutron transport k-eigenvalue problem

NASA Astrophysics Data System (ADS)

Willert, Jeffrey; Park, H.; Knoll, D. A.

2014-10-01

Over the past several years a number of papers have been written describing modern techniques for numerically computing the dominant eigenvalue of the neutron transport criticality problem. These methods fall into two distinct categories. The first category of methods rewrite the multi-group k-eigenvalue problem as a nonlinear system of equations and solve the resulting system using either a Jacobian-Free Newton-Krylov (JFNK) method or Nonlinear Krylov Acceleration (NKA), a variant of Anderson Acceleration. These methods are generally successful in significantly reducing the number of transport sweeps required to compute the dominant eigenvalue. The second category of methods utilize Moment-Based Acceleration (or High-Order/Low-Order (HOLO) Acceleration). These methods solve a sequence of modified diffusion eigenvalue problems whose solutions converge to the solution of the original transport eigenvalue problem. This second class of methods is, in our experience, always superior to the first, as most of the computational work is eliminated by the acceleration from the LO diffusion system. In this paper, we review each of these methods. Our computational results support our claim that the choice of which nonlinear solver to use, JFNK or NKA, should be secondary. The primary computational savings result from the implementation of a HOLO algorithm. We display computational results for a series of challenging multi-dimensional test problems.

Accelerating Climate Simulations Through Hybrid Computing

NASA Technical Reports Server (NTRS)

Zhou, Shujia; Sinno, Scott; Cruz, Carlos; Purcell, Mark

2009-01-01

Unconventional multi-core processors (e.g., IBM Cell B/E and NYIDIDA GPU) have emerged as accelerators in climate simulation. However, climate models typically run on parallel computers with conventional processors (e.g., Intel and AMD) using MPI. Connecting accelerators to this architecture efficiently and easily becomes a critical issue. When using MPI for connection, we identified two challenges: (1) identical MPI implementation is required in both systems, and; (2) existing MPI code must be modified to accommodate the accelerators. In response, we have extended and deployed IBM Dynamic Application Virtualization (DAV) in a hybrid computing prototype system (one blade with two Intel quad-core processors, two IBM QS22 Cell blades, connected with Infiniband), allowing for seamlessly offloading compute-intensive functions to remote, heterogeneous accelerators in a scalable, load-balanced manner. Currently, a climate solar radiation model running with multiple MPI processes has been offloaded to multiple Cell blades with approx.10% network overhead.

Advances in PCR technology.

PubMed

Lauerman, Lloyd H

2004-12-01

Since the discovery of the polymerase chain reaction (PCR) 20 years ago, an avalanche of scientific publications have reported major developments and changes in specialized equipment, reagents, sample preparation, computer programs and techniques, generated through business, government and university research. The requirement for genetic sequences for primer selection and validation has been greatly facilitated by the development of new sequencing techniques, machines and computer programs. Genetic libraries, such as GenBank, EMBL and DDBJ continue to accumulate a wealth of genetic sequence information for the development and validation of molecular-based diagnostic procedures concerning human and veterinary disease agents. The mechanization of various aspects of the PCR assay, such as robotics, microfluidics and nanotechnology, has made it possible for the rapid advancement of new procedures. Real-time PCR, DNA microarray and DNA chips utilize these newer techniques in conjunction with computer and computer programs. Instruments for hand-held PCR assays are being developed. The PCR and reverse transcription-PCR (RT-PCR) assays have greatly accelerated the speed and accuracy of diagnoses of human and animal disease, especially of the infectious agents that are difficult to isolate or demonstrate. The PCR has made it possible to genetically characterize a microbial isolate inexpensively and rapidly for identification, typing and epidemiological comparison.

Computer Assistance in Information Work. Part I: Conceptual Framework for Improving the Computer/User Interface in Information Work. Part II: Catalog of Acceleration, Augmentation, and Delegation Functions in Information Work.

ERIC Educational Resources Information Center

Paisley, William; Butler, Matilda

This study of the computer/user interface investigated the role of the computer in performing information tasks that users now perform without computer assistance. Users' perceptual/cognitive processes are to be accelerated or augmented by the computer; a long term goal is to delegate information tasks entirely to the computer. Cybernetic and…

Big Data Processing for a Central Texas Groundwater Case Study

NASA Astrophysics Data System (ADS)

Cantu, A.; Rivera, O.; Martínez, A.; Lewis, D. H.; Gentle, J. N., Jr.; Fuentes, G.; Pierce, S. A.

2016-12-01

As computational methods improve, scientists are able to expand the level and scale of experimental simulation and testing that is completed for case studies. This study presents a comparative analysis of multiple models for the Barton Springs segment of the Edwards aquifer. Several numerical simulations using state-mandated MODFLOW models ran on Stampede, a High Performance Computing system housed at the Texas Advanced Computing Center, were performed for multiple scenario testing. One goal of this multidisciplinary project aims to visualize and compare the output data of the groundwater model using the statistical programming language R to find revealing data patterns produced by different pumping scenarios. Presenting data in a friendly post-processing format is covered in this paper. Visualization of the data and creating workflows applicable to the management of the data are tasks performed after data extraction. Resulting analyses provide an example of how supercomputing can be used to accelerate evaluation of scientific uncertainty and geological knowledge in relation to policy and management decisions. Understanding the aquifer behavior helps policy makers avoid negative impact on the endangered species, environmental services and aids in maximizing the aquifer yield.

Big Machines and Big Science: 80 Years of Accelerators at Stanford

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

Loew, Gregory

2008-12-16

Longtime SLAC physicist Greg Loew will present a trip through SLAC's origins, highlighting its scientific achievements, and provide a glimpse of the lab's future in 'Big Machines and Big Science: 80 Years of Accelerators at Stanford.'

Design of FastQuery: How to Generalize Indexing and Querying System for Scientific Data

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

Wu, Jerry; Wu, Kesheng

2011-04-18

Modern scientific datasets present numerous data management and analysis challenges. State-of-the-art index and query technologies such as FastBit are critical for facilitating interactive exploration of large datasets. These technologies rely on adding auxiliary information to existing datasets to accelerate query processing. To use these indices, we need to match the relational data model used by the indexing systems with the array data model used by most scientific data, and to provide an efficient input and output layer for reading and writing the indices. In this work, we present a flexible design that can be easily applied to most scientific datamore » formats. We demonstrate this flexibility by applying it to two of the most commonly used scientific data formats, HDF5 and NetCDF. We present two case studies using simulation data from the particle accelerator and climate simulation communities. To demonstrate the effectiveness of the new design, we also present a detailed performance study using both synthetic and real scientific workloads.« less

Opening Remarks: SciDAC 2007

NASA Astrophysics Data System (ADS)

Strayer, Michael

2007-09-01

Good morning. Welcome to Boston, the home of the Red Sox, Celtics and Bruins, baked beans, tea parties, Robert Parker, and SciDAC 2007. A year ago I stood before you to share the legacy of the first SciDAC program and identify the challenges that we must address on the road to petascale computing—a road E E Cummins described as `. . . never traveled, gladly beyond any experience.' Today, I want to explore the preparations for the rapidly approaching extreme scale (X-scale) generation. These preparations are the first step propelling us along the road of burgeoning scientific discovery enabled by the application of X- scale computing. We look to petascale computing and beyond to open up a world of discovery that cuts across scientific fields and leads us to a greater understanding of not only our world, but our universe. As part of the President's America Competitiveness Initiative, the ASCR Office has been preparing a ten year vision for computing. As part of this planning the LBNL together with ORNL and ANL hosted three town hall meetings on Simulation and Modeling at the Exascale for Energy, Ecological Sustainability and Global Security (E3). The proposed E3 initiative is organized around four programmatic themes: Engaging our top scientists, engineers, computer scientists and applied mathematicians; investing in pioneering large-scale science; developing scalable analysis algorithms, and storage architectures to accelerate discovery; and accelerating the build-out and future development of the DOE open computing facilities. It is clear that we have only just started down the path to extreme scale computing. Plan to attend Thursday's session on the out-briefing and discussion of these meetings. The road to the petascale has been at best rocky. In FY07, the continuing resolution provided 12% less money for Advanced Scientific Computing than either the President, the Senate, or the House. As a consequence, many of you had to absorb a no cost extension for your SciDAC work. I am pleased that the President's FY08 budget restores the funding for SciDAC. Quoting from Advanced Scientific Computing Research description in the House Energy and Water Development Appropriations Bill for FY08, "Perhaps no other area of research at the Department is so critical to sustaining U.S. leadership in science and technology, revolutionizing the way science is done and improving research productivity." As a society we need to revolutionize our approaches to energy, environmental and global security challenges. As we go forward along the road to the X-scale generation, the use of computation will continue to be a critical tool along with theory and experiment in understanding the behavior of the fundamental components of nature as well as for fundamental discovery and exploration of the behavior of complex systems. The foundation to overcome these societal challenges will build from the experiences and knowledge gained as you, members of our SciDAC research teams, work together to attack problems at the tera- and peta- scale. If SciDAC is viewed as an experiment for revolutionizing scientific methodology, then a strategic goal of ASCR program must be to broaden the intellectual base prepared to address the challenges of the new X-scale generation of computing. We must focus our computational science experiences gained over the past five years on the opportunities introduced with extreme scale computing. Our facilities are on a path to provide the resources needed to undertake the first part of our journey. Using the newly upgraded 119 teraflop Cray XT system at the Leadership Computing Facility, SciDAC research teams have in three days performed a 100-year study of the time evolution of the atmospheric CO2 concentration originating from the land surface. The simulation of the El Nino/Southern Oscillation which was part of this study has been characterized as `the most impressive new result in ten years' gained new insight into the behavior of superheated ionic gas in the ITER reactor as a result of an AORSA run on 22,500 processors that achieved over 87 trillion calculations per second (87 teraflops) which is 74% of the system's theoretical peak. Tomorrow, Argonne and IBM will announce that the first IBM Blue Gene/P, a 100 teraflop system, will be shipped to the Argonne Leadership Computing Facility later this fiscal year. By the end of FY2007 ASCR high performance and leadership computing resources will include the 114 teraflop IBM Blue Gene/P; a 102 teraflop Cray XT4 at NERSC and a 119 teraflop Cray XT system at Oak Ridge. Before ringing in the New Year, Oak Ridge will upgrade to 250 teraflops with the replacement of the dual core processors with quad core processors and Argonne will upgrade to between 250-500 teraflops, and next year, a petascale Cray Baker system is scheduled for delivery at Oak Ridge. The multidisciplinary teams in our SciDAC Centers for Enabling Technologies and our SciDAC Institutes must continue to work with our Scientific Application teams to overcome the barriers that prevent effective use of these new systems. These challenges include: the need for new algorithms as well as operating system and runtime software and tools which scale to parallel systems composed of hundreds of thousands processors; program development environments and tools which scale effectively and provide ease of use for developers and scientific end users; and visualization and data management systems that support moving, storing, analyzing, manipulating and visualizing multi-petabytes of scientific data and objects. The SciDAC Centers, located primarily at our DOE national laboratories will take the lead in ensuring that critical computer science and applied mathematics issues are addressed in a timely and comprehensive fashion and to address issues associated with research software lifecycle. In contrast, the SciDAC Institutes, which are university-led centers of excellence, will have more flexibility to pursue new research topics through a range of research collaborations. The Institutes will also work to broaden the intellectual and researcher base—conducting short courses and summer schools to take advantage of new high performance computing capabilities. The SciDAC Outreach Center at Lawrence Berkeley National Laboratory complements the outreach efforts of the SciDAC Institutes. The Outreach Center is our clearinghouse for SciDAC activities and resources and will communicate with the high performance computing community in part to understand their needs for workshops, summer schools and institutes. SciDAC is not ASCR's only effort to broaden the computational science community needed to meet the challenges of the new X-scale generation. I hope that you were able to attend the Computational Science Graduate Fellowship poster session last night. ASCR developed the fellowship in 1991 to meet the nation's growing need for scientists and technology professionals with advanced computer skills. CSGF, now jointly funded between ASCR and NNSA, is more than a traditional academic fellowship. It has provided more than 200 of the best and brightest graduate students with guidance, support and community in preparing them as computational scientists. Today CSGF alumni are bringing their diverse top-level skills and knowledge to research teams at DOE laboratories and in industries such as Proctor and Gamble, Lockheed Martin and Intel. At universities they are working to train the next generation of computational scientists. To build on this success, we intend to develop a wholly new Early Career Principal Investigator's (ECPI) program. Our objective is to stimulate academic research in scientific areas within ASCR's purview especially among faculty in early stages of their academic careers. Last February, we lost Ken Kennedy, one of the leading lights of our community. As we move forward into the extreme computing generation, his vision and insight will be greatly missed. In memorial to Ken Kennedy, we shall designate the ECPI grants to beginning faculty in Computer Science as the Ken Kennedy Fellowship. Watch the ASCR website for more information about ECPI and other early career programs in the computational sciences. We look to you, our scientists, researchers, and visionaries to take X-scale computing and use it to explode scientific discovery in your fields. We at SciDAC will work to ensure that this tool is the sharpest and most precise and efficient instrument to carve away the unknown and reveal the most exciting secrets and stimulating scientific discoveries of our time. The partnership between research and computing is the marriage that will spur greater discovery, and as Spencer said to Susan in Robert Parker's novel, `Sudden Mischief', `We stick together long enough, and we may get as smart as hell'. Michael Strayer

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

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

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

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

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem. Mid-year report FY16 Q2

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

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

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

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

Collaborative Research: Tomographic imaging of laser-plasma structures

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

Downer, Michael

The interaction of intense short laser pulses with ionized gases, or plasmas, underlies many applications such as acceleration of elementary particles, production of energy by laser fusion, generation of x-ray and far-infrared “terahertz” pulses for medical and materials probing, remote sensing of explosives and pollutants, and generation of guide stars. Such laser-plasma interactions create tiny electron density structures (analogous to the wake behind a boat) inside the plasma in the shape of waves, bubbles and filaments that move at the speed of light, and evolve as they propagate. Prior to recent work by the PI of this proposal, detailed knowledgemore » of such structures came exclusively from intensive computer simulations. Now “snapshots” of these elusive, light-velocity structures can be taken in the laboratory using dynamic variant of holography, the technique used to produce ID cards and DVDs, and dynamic variant of tomography, the technique used in medicine to image internal bodily organs. These fast visualization techniques are important for understanding, improving and scaling the above-mentioned applications of laser-plasma interactions. In this project, we accomplished three things: 1) We took holographic pictures of a laser-driven plasma-wave in the act of accelerating electrons to high energy, and used computer simulations to understand the pictures. 2) Using results from this experiment to optimize the performance of the accelerator, and the brightness of x-rays that it emits. These x-rays will be useful for medical and materials science applications. 3) We made technical improvements to the holographic technique that enables us to see finer details in the recorded pictures. Four refereed journal papers were published, and two students earned PhDs and moved on to scientific careers in US National Laboratories based on their work under this project.« less

[Technical Gap of Chinese Medical Accelerator and Its Development Path].

PubMed

Tian, Xinzhi

2017-11-30

With the reform and opening up the tide through nearly four decades of development, our medical accelerator business isfacing new era demands now, in this new historical opportunity in front of the younger generation of medical accelerator staff must assume the older generation of scientific research personnel are different of the historical responsibility. Based on the development of the predecessors, we try to analyze the current situation of the domestic accelerator, establish the new development ideas of the domestic medical accelerator, and directly face and solve the dilemma facing the development of the domestic accelerator.

Mechanisms and Effects of Transcranial Direct Current Stimulation

PubMed Central

Giordano, James; Bikson, Marom; Kappenman, Emily S.; Clark, Vincent P.; Coslett, H. Branch; Hamblin, Michael R.; Hamilton, Roy; Jankord, Ryan; Kozumbo, Walter J.; McKinley, R. Andrew; Nitsche, Michael A.; Reilly, J. Patrick; Richardson, Jessica; Wurzman, Rachel

2017-01-01

The US Air Force Office of Scientific Research convened a meeting of researchers in the fields of neuroscience, psychology, engineering, and medicine to discuss most pressing issues facing ongoing research in the field of transcranial direct current stimulation (tDCS) and related techniques. In this study, we present opinions prepared by participants of the meeting, focusing on the most promising areas of research, immediate and future goals for the field, and the potential for hormesis theory to inform tDCS research. Scientific, medical, and ethical considerations support the ongoing testing of tDCS in healthy and clinical populations, provided best protocols are used to maximize safety. Notwithstanding the need for ongoing research, promising applications include enhancing vigilance/attention in healthy volunteers, which can accelerate training and support learning. Commonly, tDCS is used as an adjunct to training/rehabilitation tasks with the goal of leftward shift in the learning/treatment effect curves. Although trials are encouraging, elucidating the basic mechanisms of tDCS will accelerate validation and adoption. To this end, biomarkers (eg, clinical neuroimaging and findings from animal models) can support hypotheses linking neurobiological mechanisms and behavioral effects. Dosage can be optimized using computational models of current flow and understanding dose–response. Both biomarkers and dosimetry should guide individualized interventions with the goal of reducing variability. Insights from other applied energy domains, including ionizing radiation, transcranial magnetic stimulation, and low-level laser (light) therapy, can be prudently leveraged. PMID:28210202

160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA)

PubMed Central

Li, Isaac TS; Shum, Warren; Truong, Kevin

2007-01-01

Background To infer homology and subsequently gene function, the Smith-Waterman (SW) algorithm is used to find the optimal local alignment between two sequences. When searching sequence databases that may contain hundreds of millions of sequences, this algorithm becomes computationally expensive. Results In this paper, we focused on accelerating the Smith-Waterman algorithm by using FPGA-based hardware that implemented a module for computing the score of a single cell of the SW matrix. Then using a grid of this module, the entire SW matrix was computed at the speed of field propagation through the FPGA circuit. These modifications dramatically accelerated the algorithm's computation time by up to 160 folds compared to a pure software implementation running on the same FPGA with an Altera Nios II softprocessor. Conclusion This design of FPGA accelerated hardware offers a new promising direction to seeking computation improvement of genomic database searching. PMID:17555593

160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA).

PubMed

Li, Isaac T S; Shum, Warren; Truong, Kevin

2007-06-07

To infer homology and subsequently gene function, the Smith-Waterman (SW) algorithm is used to find the optimal local alignment between two sequences. When searching sequence databases that may contain hundreds of millions of sequences, this algorithm becomes computationally expensive. In this paper, we focused on accelerating the Smith-Waterman algorithm by using FPGA-based hardware that implemented a module for computing the score of a single cell of the SW matrix. Then using a grid of this module, the entire SW matrix was computed at the speed of field propagation through the FPGA circuit. These modifications dramatically accelerated the algorithm's computation time by up to 160 folds compared to a pure software implementation running on the same FPGA with an Altera Nios II softprocessor. This design of FPGA accelerated hardware offers a new promising direction to seeking computation improvement of genomic database searching.

Computing Models for FPGA-Based Accelerators

PubMed Central

Herbordt, Martin C.; Gu, Yongfeng; VanCourt, Tom; Model, Josh; Sukhwani, Bharat; Chiu, Matt

2011-01-01

Field-programmable gate arrays are widely considered as accelerators for compute-intensive applications. A critical phase of FPGA application development is finding and mapping to the appropriate computing model. FPGA computing enables models with highly flexible fine-grained parallelism and associative operations such as broadcast and collective response. Several case studies demonstrate the effectiveness of using these computing models in developing FPGA applications for molecular modeling. PMID:21603152

Cloud Computing and Validated Learning for Accelerating Innovation in IoT

ERIC Educational Resources Information Center

Suciu, George; Todoran, Gyorgy; Vulpe, Alexandru; Suciu, Victor; Bulca, Cristina; Cheveresan, Romulus

2015-01-01

Innovation in Internet of Things (IoT) requires more than just creation of technology and use of cloud computing or big data platforms. It requires accelerated commercialization or aptly called go-to-market processes. To successfully accelerate, companies need a new type of product development, the so-called validated learning process.…

Analysis of ballistic transport in nanoscale devices by using an accelerated finite element contact block reduction approach

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

Li, H.; Li, G., E-mail: gli@clemson.edu

2014-08-28

An accelerated Finite Element Contact Block Reduction (FECBR) approach is presented for computational analysis of ballistic transport in nanoscale electronic devices with arbitrary geometry and unstructured mesh. Finite element formulation is developed for the theoretical CBR/Poisson model. The FECBR approach is accelerated through eigen-pair reduction, lead mode space projection, and component mode synthesis techniques. The accelerated FECBR is applied to perform quantum mechanical ballistic transport analysis of a DG-MOSFET with taper-shaped extensions and a DG-MOSFET with Si/SiO{sub 2} interface roughness. The computed electrical transport properties of the devices obtained from the accelerated FECBR approach and associated computational cost as amore » function of system degrees of freedom are compared with those obtained from the original CBR and direct inversion methods. The performance of the accelerated FECBR in both its accuracy and efficiency is demonstrated.« less

The accelerator neutron source for boron neutron capture therapy

NASA Astrophysics Data System (ADS)

Kasatov, D.; Koshkarev, A.; Kuznetsov, A.; Makarov, A.; Ostreinov, Yu; Shchudlo, I.; Sorokin, I.; Sycheva, T.; Taskaev, S.; Zaidi, L.

2016-11-01

The accelerator based epithermal neutron source for Boron Neutron Capture Therapy (BNCT) is proposed, created and used in the Budker Institute of Nuclear Physics. In 2014, with the support of the Russian Science Foundation created the BNCT laboratory for the purpose to the end of 2016 get the neutron flux, suitable for BNCT. For getting 3 mA 2.3 MeV proton beam, was created a new type accelerator - tandem accelerator with vacuum isolation. On this moment, we have a stationary proton beam with 2.3 MeV and current 1.75 mA. Generation of neutrons is carried out by dropping proton beam on to lithium target as a result of threshold reaction 7Li(p,n)7Be. Established facility is a unique scientific installation. It provides a generating of neutron flux, including a monochromatic energy neutrons, gamma radiation, alpha-particles and positrons, and may be used by other research groups for carrying out scientific researches. The article describes an accelerator neutron source, presents and discusses the result of experiments and declares future plans.

Considerations on the Use of Custom Accelerators for Big Data Analytics

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

Castellana, Vito G.; Tumeo, Antonino; Minutoli, Marco

Accelerators, including Graphic Processing Units (GPUs) for gen- eral purpose computation, many-core designs with wide vector units (e.g., Intel Phi), have become a common component of many high performance clusters. The appearance of more stable and reliable tools tools that can automatically convert code written in high-level specifications with annotations (such as C or C++) to hardware de- scription languages (High-Level Synthesis - HLS), is also setting the stage for a broader use of reconfigurable devices (e.g., Field Pro- grammable Gate Arrays - FPGAs) in high performance system for the implementation of custom accelerators, helped by the fact that newmore » processors include advanced cache-coherent interconnects for these components. In this chapter, we briefly survey the status of the use of accelerators in high performance systems targeted at big data analytics applications. We argue that, although the progress in the use of accelerators for this class of applications has been sig- nificant, differently from scientific simulations there still are gaps to close. This is particularly true for the ”irregular” behaviors exhibited by no-SQL, graph databases. We focus our attention on the limits of HLS tools for data analytics and graph methods, and discuss a new architectural template that better fits the requirement of this class of applications. We validate the new architectural templates by mod- ifying the Graph Engine for Multithreaded System (GEMS) frame- work to support accelerators generated with such a methodology, and testing with queries coming from the Lehigh University Benchmark (LUBM). The architectural template enables better supporting the task and memory level parallelism present in graph methods by sup- porting a new control model and a enhanced memory interface. We show that out solution allows generating parallel accelerators, pro- viding speed ups with respect to conventional HLS flows. We finally draw conclusions and present a perspective on the use of reconfig- urable devices and Design Automation tools for data analytics.« less

Upgrades of DARWIN, a dose and spectrum monitoring system applicable to various types of radiation over wide energy ranges

NASA Astrophysics Data System (ADS)

Sato, Tatsuhiko; Satoh, Daiki; Endo, Akira; Shigyo, Nobuhiro; Watanabe, Fusao; Sakurai, Hiroki; Arai, Yoichi

2011-05-01

A dose and spectrum monitoring system applicable to neutrons, photons and muons over wide ranges of energy, designated as DARWIN, has been developed for radiological protection in high-energy accelerator facilities. DARWIN consists of a phoswitch-type scintillation detector, a data-acquisition (DAQ) module for digital waveform analysis, and a personal computer equipped with a graphical-user-interface (GUI) program for controlling the system. The system was recently upgraded by introducing an original DAQ module based on a field programmable gate array, FPGA, and also by adding a function for estimating neutron and photon spectra based on an unfolding technique without requiring any specific scientific background of the user. The performance of the upgraded DARWIN was examined in various radiation fields, including an operational field in J-PARC. The experiments revealed that the dose rates and spectra measured by the upgraded DARWIN are quite reasonable, even in radiation fields with peak structures in terms of both spectrum and time variation. These results clearly demonstrate the usefulness of DARWIN for improving radiation safety in high-energy accelerator facilities.

The Accelerated O.D. Program: Graduates of the First Ten Years.

ERIC Educational Resources Information Center

Chauncey, Depew M.

1988-01-01

A survey of the practice patterns, licensing, and distribution of graduates of the New England College of Optometry's accelerated doctor of optometry program indicates its success as a source of optometric educators with advanced expertise in scientific research. (Author/MSE)

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

NASA Astrophysics Data System (ADS)

Strayer, Michael

2005-01-01

Good morning. Welcome to SciDAC 2005 and San Francisco. SciDAC is all about computational science and scientific discovery. In a large sense, computational science characterizes SciDAC and its intent is change. It transforms both our approach and our understanding of science. It opens new doors and crosses traditional boundaries while seeking discovery. In terms of twentieth century methodologies, computational science may be said to be transformational. There are a number of examples to this point. First are the sciences that encompass climate modeling. The application of computational science has in essence created the field of climate modeling. This community is now international in scope and has provided precision results that are challenging our understanding of our environment. A second example is that of lattice quantum chromodynamics. Lattice QCD, while adding precision and insight to our fundamental understanding of strong interaction dynamics, has transformed our approach to particle and nuclear science. The individual investigator approach has evolved to teams of scientists from different disciplines working side-by-side towards a common goal. SciDAC is also undergoing a transformation. This meeting is a prime example. Last year it was a small programmatic meeting tracking progress in SciDAC. This year, we have a major computational science meeting with a variety of disciplines and enabling technologies represented. SciDAC 2005 should position itself as a new corner stone for Computational Science and its impact on science. As we look to the immediate future, FY2006 will bring a new cycle to SciDAC. Most of the program elements of SciDAC will be re-competed in FY2006. The re-competition will involve new instruments for computational science, new approaches for collaboration, as well as new disciplines. There will be new opportunities for virtual experiments in carbon sequestration, fusion, and nuclear power and nuclear waste, as well as collaborations with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds immense promise. In this environment, I believe it is necessary to institute a system of science based performance metrics to help quantify our progress towards science goals and scientific computing. As a final comment I would like to reaffirm that the shifting landscapes of science will force changes to our computational sciences, and leave you with the quote from Richard Hamming, 'The purpose of computing is insight, not numbers'.

Center for Center for Technology for Advanced Scientific Component Software (TASCS)

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

Kostadin, Damevski

A resounding success of the Scientific Discovery through Advanced Computing (SciDAC) program is that high-performance computational science is now universally recognized as a critical aspect of scientific discovery [71], complementing both theoretical and experimental research. As scientific communities prepare to exploit unprecedented computing capabilities of emerging leadership-class machines for multi-model simulations at the extreme scale [72], it is more important than ever to address the technical and social challenges of geographically distributed teams that combine expertise in domain science, applied mathematics, and computer science to build robust and flexible codes that can incorporate changes over time. The Center for Technologymore » for Advanced Scientific Component Software (TASCS)1 tackles these these issues by exploiting component-based software development to facilitate collaborative high-performance scientific computing.« less

Computational Science: A Research Methodology for the 21st Century

NASA Astrophysics Data System (ADS)

Orbach, Raymond L.

2004-03-01

Computational simulation - a means of scientific discovery that employs computer systems to simulate a physical system according to laws derived from theory and experiment - has attained peer status with theory and experiment. Important advances in basic science are accomplished by a new "sociology" for ultrascale scientific computing capability (USSCC), a fusion of sustained advances in scientific models, mathematical algorithms, computer architecture, and scientific software engineering. Expansion of current capabilities by factors of 100 - 1000 open up new vistas for scientific discovery: long term climatic variability and change, macroscopic material design from correlated behavior at the nanoscale, design and optimization of magnetic confinement fusion reactors, strong interactions on a computational lattice through quantum chromodynamics, and stellar explosions and element production. The "virtual prototype," made possible by this expansion, can markedly reduce time-to-market for industrial applications such as jet engines and safer, more fuel efficient cleaner cars. In order to develop USSCC, the National Energy Research Scientific Computing Center (NERSC) announced the competition "Innovative and Novel Computational Impact on Theory and Experiment" (INCITE), with no requirement for current DOE sponsorship. Fifty nine proposals for grand challenge scientific problems were submitted for a small number of awards. The successful grants, and their preliminary progress, will be described.

A Survey of Memristive Threshold Logic Circuits.

PubMed

Maan, Akshay Kumar; Jayadevi, Deepthi Anirudhan; James, Alex Pappachen

2017-08-01

In this paper, we review different memristive threshold logic (MTL) circuits that are inspired from the synaptic action of the flow of neurotransmitters in the biological brain. The brainlike generalization ability and the area minimization of these threshold logic circuits aim toward crossing Moore's law boundaries at device, circuits, and systems levels. Fast switching memory, signal processing, control systems, programmable logic, image processing, reconfigurable computing, and pattern recognition are identified as some of the potential applications of MTL systems. The physical realization of nanoscale devices with memristive behavior from materials, such as TiO 2 , ferroelectrics, silicon, and polymers, has accelerated research effort in these application areas, inspiring the scientific community to pursue the design of high-speed, low-cost, low-power, and high-density neuromorphic architectures.

Transitioning Rationally Designed Catalytic Materials to Real 'Working' Catalysts Produced at Commercial Scale: Nanoparticle Materials

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

Schaidle, Joshua A.; Habas, Susan E.; Baddour, Frederick G.

Catalyst design, from idea to commercialization, requires multi-disciplinary scientific and engineering research and development over 10-20 year time periods. Historically, the identification of new or improved catalyst materials has largely been an empirical trial-and-error process. However, advances in computational capabilities (new tools and increased processing power) coupled with new synthetic techniques have started to yield rationally-designed catalysts with controlled nano-structures and tailored properties. This technological advancement represents an opportunity to accelerate the catalyst development timeline and to deliver new materials that outperform existing industrial catalysts or enable new applications, once a number of unique challenges associated with the scale-up ofmore » nano-structured materials are overcome.« less

Architectural requirements for the Red Storm computing system.

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

Camp, William J.; Tomkins, James Lee

This report is based on the Statement of Work (SOW) describing the various requirements for delivering 3 new supercomputer system to Sandia National Laboratories (Sandia) as part of the Department of Energy's (DOE) Accelerated Strategic Computing Initiative (ASCI) program. This system is named Red Storm and will be a distributed memory, massively parallel processor (MPP) machine built primarily out of commodity parts. The requirements presented here distill extensive architectural and design experience accumulated over a decade and a half of research, development and production operation of similar machines at Sandia. Red Storm will have an unusually high bandwidth, low latencymore » interconnect, specially designed hardware and software reliability features, a light weight kernel compute node operating system and the ability to rapidly switch major sections of the machine between classified and unclassified computing environments. Particular attention has been paid to architectural balance in the design of Red Storm, and it is therefore expected to achieve an atypically high fraction of its peak speed of 41 TeraOPS on real scientific computing applications. In addition, Red Storm is designed to be upgradeable to many times this initial peak capability while still retaining appropriate balance in key design dimensions. Installation of the Red Storm computer system at Sandia's New Mexico site is planned for 2004, and it is expected that the system will be operated for a minimum of five years following installation.« less

Big Data Smart Socket (BDSS): a system that abstracts data transfer habits from end users.

PubMed

Watts, Nicholas A; Feltus, Frank A

2017-02-15

The ability to centralize and store data for long periods on an end user's computational resources is increasingly difficult for many scientific disciplines. For example, genomics data is increasingly large and distributed, and the data needs to be moved into workflow execution sites ranging from lab workstations to the cloud. However, the typical user is not always informed on emerging network technology or the most efficient methods to move and share data. Thus, the user defaults to using inefficient methods for transfer across the commercial internet. To accelerate large data transfer, we created a tool called the Big Data Smart Socket (BDSS) that abstracts data transfer methodology from the user. The user provides BDSS with a manifest of datasets stored in a remote storage repository. BDSS then queries a metadata repository for curated data transfer mechanisms and optimal path to move each of the files in the manifest to the site of workflow execution. BDSS functions as a standalone tool or can be directly integrated into a computational workflow such as provided by the Galaxy Project. To demonstrate applicability, we use BDSS within a biological context, although it is applicable to any scientific domain. BDSS is available under version 2 of the GNU General Public License at https://github.com/feltus/BDSS . ffeltus@clemson.edu. © The Author 2016. Published by Oxford University Press.

Big Data Smart Socket (BDSS): a system that abstracts data transfer habits from end users

PubMed Central

Watts, Nicholas A.

2017-01-01

Motivation: The ability to centralize and store data for long periods on an end user’s computational resources is increasingly difficult for many scientific disciplines. For example, genomics data is increasingly large and distributed, and the data needs to be moved into workflow execution sites ranging from lab workstations to the cloud. However, the typical user is not always informed on emerging network technology or the most efficient methods to move and share data. Thus, the user defaults to using inefficient methods for transfer across the commercial internet. Results: To accelerate large data transfer, we created a tool called the Big Data Smart Socket (BDSS) that abstracts data transfer methodology from the user. The user provides BDSS with a manifest of datasets stored in a remote storage repository. BDSS then queries a metadata repository for curated data transfer mechanisms and optimal path to move each of the files in the manifest to the site of workflow execution. BDSS functions as a standalone tool or can be directly integrated into a computational workflow such as provided by the Galaxy Project. To demonstrate applicability, we use BDSS within a biological context, although it is applicable to any scientific domain. Availability and Implementation: BDSS is available under version 2 of the GNU General Public License at https://github.com/feltus/BDSS. Contact: ffeltus@clemson.edu PMID:27797780

The Common Data Acquisition Platform in the Helmholtz Association

NASA Astrophysics Data System (ADS)

Kaever, P.; Balzer, M.; Kopmann, A.; Zimmer, M.; Rongen, H.

2017-04-01

Various centres of the German Helmholtz Association (HGF) started in 2012 to develop a modular data acquisition (DAQ) platform, covering the entire range from detector readout to data transfer into parallel computing environments. This platform integrates generic hardware components like the multi-purpose HGF-Advanced Mezzanine Card or a smart scientific camera framework, adding user value with Linux drivers and board support packages. Technically the scope comprises the DAQ-chain from FPGA-modules to computing servers, notably frontend-electronics-interfaces, microcontrollers and GPUs with their software plus high-performance data transmission links. The core idea is a generic and component-based approach, enabling the implementation of specific experiment requirements with low effort. This so called DTS-platform will support standards like MTCA.4 in hard- and software to ensure compatibility with commercial components. Its capability to deploy on other crate standards or FPGA-boards with PCI express or Ethernet interfaces remains an essential feature. Competences of the participating centres are coordinated in order to provide a solid technological basis for both research topics in the Helmholtz Programme ``Matter and Technology'': ``Detector Technology and Systems'' and ``Accelerator Research and Development''. The DTS-platform aims at reducing costs and development time and will ensure access to latest technologies for the collaboration. Due to its flexible approach, it has the potential to be applied in other scientific programs.

A Bridge for Accelerating Materials by Design

DOE PAGES

Sumpter, Bobby G.; Vasudevan, Rama K.; Potok, Thomas E.; ...

2015-11-25

Recent technical advances in the area of nanoscale imaging, spectroscopy, and scattering/diffraction have led to unprecedented capabilities for investigating materials structural, dynamical and functional characteristics. In addition, recent advances in computational algorithms and computer capacities that are orders of magnitude larger/faster have enabled large-scale simulations of materials properties starting with nothing but the identity of the atomic species and the basic principles of quantum- and statistical-mechanics and thermodynamics. Along with these advances, an explosion of high-resolution data has emerged. This confluence of capabilities and rise of big data offer grand opportunities for advancing materials sciences but also introduce several challenges.more » In this editorial we identify challenges impeding progress towards advancing materials by design (e.g., the design/discovery of materials with improved properties/performance), possible solutions, and provide examples of scientific issues that can be addressed by using a tightly integrated approach where theory and experiments are linked through big-deep data.« less

Exploratory of society

NASA Astrophysics Data System (ADS)

Cederman, L.-E.; Conte, R.; Helbing, D.; Nowak, A.; Schweitzer, F.; Vespignani, A.

2012-11-01

A huge flow of quantitative social, demographic and behavioral data is becoming available that traces the activities and interactions of individuals, social patterns, transportation infrastructures and travel fluxes. This has caused, together with innovative computational techniques and methods for modeling social actions in hybrid (natural and artificial) societies, a qualitative change in the ways we model socio-technical systems. For the first time, society can be studied in a comprehensive fashion that addresses social and behavioral complexity. In other words we are in the position to envision the development of large data and computational cyber infrastructure defining an exploratory of society that provides quantitative anticipatory, explanatory and scenario analysis capabilities ranging from emerging infectious disease to conflict and crime surges. The goal of the exploratory of society is to provide the basic infrastructure embedding the framework of tools and knowledge needed for the design of forecast/anticipatory/crisis management approaches to socio technical systems, supporting future decision making procedures by accelerating the scientific cycle that goes from data generation to predictions.

A coarse-grid projection method for accelerating incompressible flow computations

NASA Astrophysics Data System (ADS)

San, Omer; Staples, Anne E.

2013-01-01

We present a coarse-grid projection (CGP) method for accelerating incompressible flow computations, which is applicable to methods involving Poisson equations as incompressibility constraints. The CGP methodology is a modular approach that facilitates data transfer with simple interpolations and uses black-box solvers for the Poisson and advection-diffusion equations in the flow solver. After solving the Poisson equation on a coarsened grid, an interpolation scheme is used to obtain the fine data for subsequent time stepping on the full grid. A particular version of the method is applied here to the vorticity-stream function, primitive variable, and vorticity-velocity formulations of incompressible Navier-Stokes equations. We compute several benchmark flow problems on two-dimensional Cartesian and non-Cartesian grids, as well as a three-dimensional flow problem. The method is found to accelerate these computations while retaining a level of accuracy close to that of the fine resolution field, which is significantly better than the accuracy obtained for a similar computation performed solely using a coarse grid. A linear acceleration rate is obtained for all the cases we consider due to the linear-cost elliptic Poisson solver used, with reduction factors in computational time between 2 and 42. The computational savings are larger when a suboptimal Poisson solver is used. We also find that the computational savings increase with increasing distortion ratio on non-Cartesian grids, making the CGP method a useful tool for accelerating generalized curvilinear incompressible flow solvers.

Computational Accelerator Physics. Proceedings

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

Bisognano, J.J.; Mondelli, A.A.

1997-04-01

The sixty two papers appearing in this volume were presented at CAP96, the Computational Accelerator Physics Conference held in Williamsburg, Virginia from September 24{minus}27,1996. Science Applications International Corporation (SAIC) and the Thomas Jefferson National Accelerator Facility (Jefferson lab) jointly hosted CAP96, with financial support from the U.S. department of Energy`s Office of Energy Research and the Office of Naval reasearch. Topics ranged from descriptions of specific codes to advanced computing techniques and numerical methods. Update talks were presented on nearly all of the accelerator community`s major electromagnetic and particle tracking codes. Among all papers, thirty of them are abstracted formore » the Energy Science and Technology database.(AIP)« less

Joint the Center for Applied Scientific Computing

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

Gamblin, Todd; Bremer, Timo; Van Essen, Brian

The Center for Applied Scientific Computing serves as Livermore Lab’s window to the broader computer science, computational physics, applied mathematics, and data science research communities. In collaboration with academic, industrial, and other government laboratory partners, we conduct world-class scientific research and development on problems critical to national security. CASC applies the power of high-performance computing and the efficiency of modern computational methods to the realms of stockpile stewardship, cyber and energy security, and knowledge discovery for intelligence applications.

Quantum Accelerators for High-performance Computing Systems

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

Humble, Travis S.; Britt, Keith A.; Mohiyaddin, Fahd A.

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, themore » prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.« less

Acceleration of Cherenkov angle reconstruction with the new Intel Xeon/FPGA compute platform for the particle identification in the LHCb Upgrade

NASA Astrophysics Data System (ADS)

Faerber, Christian

2017-10-01

The LHCb experiment at the LHC will upgrade its detector by 2018/2019 to a ‘triggerless’ readout scheme, where all the readout electronics and several sub-detector parts will be replaced. The new readout electronics will be able to readout the detector at 40 MHz. This increases the data bandwidth from the detector down to the Event Filter farm to 40 TBit/s, which also has to be processed to select the interesting proton-proton collision for later storage. The architecture of such a computing farm, which can process this amount of data as efficiently as possible, is a challenging task and several compute accelerator technologies are being considered for use inside the new Event Filter farm. In the high performance computing sector more and more FPGA compute accelerators are used to improve the compute performance and reduce the power consumption (e.g. in the Microsoft Catapult project and Bing search engine). Also for the LHCb upgrade the usage of an experimental FPGA accelerated computing platform in the Event Building or in the Event Filter farm is being considered and therefore tested. This platform from Intel hosts a general CPU and a high performance FPGA linked via a high speed link which is for this platform a QPI link. On the FPGA an accelerator is implemented. The used system is a two socket platform from Intel with a Xeon CPU and an FPGA. The FPGA has cache-coherent memory access to the main memory of the server and can collaborate with the CPU. As a first step, a computing intensive algorithm to reconstruct Cherenkov angles for the LHCb RICH particle identification was successfully ported in Verilog to the Intel Xeon/FPGA platform and accelerated by a factor of 35. The same algorithm was ported to the Intel Xeon/FPGA platform with OpenCL. The implementation work and the performance will be compared. Also another FPGA accelerator the Nallatech 385 PCIe accelerator with the same Stratix V FPGA were tested for performance. The results show that the Intel Xeon/FPGA platforms, which are built in general for high performance computing, are also very interesting for the High Energy Physics community.

The Geoscience Paper of the Future: Best Practices for Documenting and Sharing Research from Data to Software to Provenance

NASA Astrophysics Data System (ADS)

Gil, Y.; Yu, X.; David, C. H.; Demir, I.; Essawy, B.; Fulweiler, R. W.; Goodall, J. L.; Karlstrom, L.; Lee, H.; Mills, H. J.; Pierce, S. A.; Pope, A.; Tzeng, M.; Villamizar, S. R.

2016-12-01

Geoscientists live in a world rich with digital data and methods, and their computational research cannot be fully captured in traditional publications. The Geoscience Paper of the Future (GPF) proposes best practices for GPF authors to make data, software, and methods openly accessible, citable, and well documented. Those best practices come from recommendations by both scholars and organizations concerning open science, reproducible publications, and digital scholarship. The publication of digital objects empowers scientists to manage their research products as valuable scientific assets in an open and transparent way that enables broader access by other scientists, students, decision makers, and the public. Improving documentation and dissemination of research will accelerate the pace of scientific discovery by improving the ability of others to build upon published work. This presentation summarizes these best practices, as well as the practical experiences of several GPF authors in different geosciences disciplines. It will also discuss existing challenges for authors and publishers to produce GPFs in practice, and the opportunities to develop new approaches and infrastructure to implement those best practices. The adoption of GPF recommendations requires awareness and social change in the scientific community, including clear communication of the benefits and best practices that may be new to geoscientists.

Design of Linear Accelerator (LINAC) tanks for proton therapy via Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) approaches

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

Castellano, T.; De Palma, L.; Laneve, D.

2015-07-01

A homemade computer code for designing a Side- Coupled Linear Accelerator (SCL) is written. It integrates a simplified model of SCL tanks with the Particle Swarm Optimization (PSO) algorithm. The computer code main aim is to obtain useful guidelines for the design of Linear Accelerator (LINAC) resonant cavities. The design procedure, assisted via the aforesaid approach seems very promising, allowing future improvements towards the optimization of actual accelerating geometries. (authors)

ITK: enabling reproducible research and open science

PubMed Central

McCormick, Matthew; Liu, Xiaoxiao; Jomier, Julien; Marion, Charles; Ibanez, Luis

2014-01-01

Reproducibility verification is essential to the practice of the scientific method. Researchers report their findings, which are strengthened as other independent groups in the scientific community share similar outcomes. In the many scientific fields where software has become a fundamental tool for capturing and analyzing data, this requirement of reproducibility implies that reliable and comprehensive software platforms and tools should be made available to the scientific community. The tools will empower them and the public to verify, through practice, the reproducibility of observations that are reported in the scientific literature. Medical image analysis is one of the fields in which the use of computational resources, both software and hardware, are an essential platform for performing experimental work. In this arena, the introduction of the Insight Toolkit (ITK) in 1999 has transformed the field and facilitates its progress by accelerating the rate at which algorithmic implementations are developed, tested, disseminated and improved. By building on the efficiency and quality of open source methodologies, ITK has provided the medical image community with an effective platform on which to build a daily workflow that incorporates the true scientific practices of reproducibility verification. This article describes the multiple tools, methodologies, and practices that the ITK community has adopted, refined, and followed during the past decade, in order to become one of the research communities with the most modern reproducibility verification infrastructure. For example, 207 contributors have created over 2400 unit tests that provide over 84% code line test coverage. The Insight Journal, an open publication journal associated with the toolkit, has seen over 360,000 publication downloads. The median normalized closeness centrality, a measure of knowledge flow, resulting from the distributed peer code review system was high, 0.46. PMID:24600387

ITK: enabling reproducible research and open science.

PubMed

McCormick, Matthew; Liu, Xiaoxiao; Jomier, Julien; Marion, Charles; Ibanez, Luis

2014-01-01

Reproducibility verification is essential to the practice of the scientific method. Researchers report their findings, which are strengthened as other independent groups in the scientific community share similar outcomes. In the many scientific fields where software has become a fundamental tool for capturing and analyzing data, this requirement of reproducibility implies that reliable and comprehensive software platforms and tools should be made available to the scientific community. The tools will empower them and the public to verify, through practice, the reproducibility of observations that are reported in the scientific literature. Medical image analysis is one of the fields in which the use of computational resources, both software and hardware, are an essential platform for performing experimental work. In this arena, the introduction of the Insight Toolkit (ITK) in 1999 has transformed the field and facilitates its progress by accelerating the rate at which algorithmic implementations are developed, tested, disseminated and improved. By building on the efficiency and quality of open source methodologies, ITK has provided the medical image community with an effective platform on which to build a daily workflow that incorporates the true scientific practices of reproducibility verification. This article describes the multiple tools, methodologies, and practices that the ITK community has adopted, refined, and followed during the past decade, in order to become one of the research communities with the most modern reproducibility verification infrastructure. For example, 207 contributors have created over 2400 unit tests that provide over 84% code line test coverage. The Insight Journal, an open publication journal associated with the toolkit, has seen over 360,000 publication downloads. The median normalized closeness centrality, a measure of knowledge flow, resulting from the distributed peer code review system was high, 0.46.

Minimum time acceleration of aircraft turbofan engines by using an algorithm based on nonlinear programming

NASA Technical Reports Server (NTRS)

Teren, F.

1977-01-01

Minimum time accelerations of aircraft turbofan engines are presented. The calculation of these accelerations was made by using a piecewise linear engine model, and an algorithm based on nonlinear programming. Use of this model and algorithm allows such trajectories to be readily calculated on a digital computer with a minimal expenditure of computer time.

Convergence acceleration of viscous flow computations

NASA Technical Reports Server (NTRS)

Johnson, G. M.

1982-01-01

A multiple-grid convergence acceleration technique introduced for application to the solution of the Euler equations by means of Lax-Wendroff algorithms is extended to treat compressible viscous flow. Computational results are presented for the solution of the thin-layer version of the Navier-Stokes equations using the explicit MacCormack algorithm, accelerated by a convective coarse-grid scheme. Extensions and generalizations are mentioned.

Effective correlator for RadioAstron project

NASA Astrophysics Data System (ADS)

Sergeev, Sergey

This paper presents the implementation of programme FX-correlator for Very Long Baseline Interferometry, adapted for the project "RadioAstron". Software correlator implemented for heterogeneous computing systems using graphics accelerators. It is shown that for the task interferometry implementation of the graphics hardware has a high efficiency. The host processor of heterogeneous computing system, performs the function of forming the data flow for graphics accelerators, the number of which corresponds to the number of frequency channels. So, for the Radioastron project, such channels is seven. Each accelerator is perform correlation matrix for all bases for a single frequency channel. Initial data is converted to the floating-point format, is correction for the corresponding delay function and computes the entire correlation matrix simultaneously. Calculation of the correlation matrix is performed using the sliding Fourier transform. Thus, thanks to the compliance of a solved problem for architecture graphics accelerators, managed to get a performance for one processor platform Kepler, which corresponds to the performance of this task, the computing cluster platforms Intel on four nodes. This task successfully scaled not only on a large number of graphics accelerators, but also on a large number of nodes with multiple accelerators.

Acceleration and torque feedback for robotic control - Experimental results

NASA Technical Reports Server (NTRS)

Mclnroy, John E.; Saridis, George N.

1990-01-01

Gross motion control of robotic manipulators typically requires significant on-line computations to compensate for nonlinear dynamics due to gravity, Coriolis, centripetal, and friction nonlinearities. One controller proposed by Luo and Saridis avoids these computations by feeding back joint acceleration and torque. This study implements the controller on a Puma 600 robotic manipulator. Joint acceleration measurement is obtained by measuring linear accelerations of each joint, and deriving a computationally efficient transformation from the linear measurements to the angular accelerations. Torque feedback is obtained by using the previous torque sent to the joints. The implementation has stability problems on the Puma 600 due to the extremely high gains inherent in the feedback structure. Since these high gains excite frequency modes in the Puma 600, the algorithm is modified to decrease the gain inherent in the feedback structure. The resulting compensator is stable and insensitive to high frequency unmodeled dynamics. Moreover, a second compensator is proposed which uses acceleration and torque feedback, but still allows nonlinear terms to be fed forward. Thus, by feeding the increment in the easily calculated gravity terms forward, improved responses are obtained. Both proposed compensators are implemented, and the real time results are compared to those obtained with the computed torque algorithm.

78 FR 41046 - Advanced Scientific Computing Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-09

... Services Administration, notice is hereby given that the Advanced Scientific Computing Advisory Committee will be renewed for a two-year period beginning on July 1, 2013. The Committee will provide advice to the Director, Office of Science (DOE), on the Advanced Scientific Computing Research Program managed...

Effects of different computer typing speeds on acceleration and peak contact pressure of the fingertips during computer typing.

PubMed

Yoo, Won-Gyu

2015-01-01

[Purpose] This study showed the effects of different computer typing speeds on acceleration and peak contact pressure of the fingertips during computer typing. [Subjects] Twenty-one male computer workers voluntarily consented to participate in this study. They consisted of 7 workers who could type 200-300 characteristics/minute, 7 workers who could type 300-400 characteristics/minute, and 7 workers who could type 400-500 chracteristics/minute. [Methods] This study was used to measure the acceleration and peak contact pressure of the fingertips for different typing speed groups using an accelerometer and CONFORMat system. [Results] The fingertip contact pressure was increased in the high typing speed group compared with the low and medium typing speed groups. The fingertip acceleration was increased in the high typing speed group compared with the low and medium typing speed groups. [Conclusion] The results of the present study indicate that a fast typing speed cause continuous pressure stress to be applied to the fingers, thereby creating pain in the fingers.

Combining Acceleration and Displacement Dependent Modal Frequency Responses Using an MSC/NASTRAN DMAP Alter

NASA Technical Reports Server (NTRS)

Barnett, Alan R.; Widrick, Timothy W.; Ludwiczak, Damian R.

1996-01-01

Solving for dynamic responses of free-free launch vehicle/spacecraft systems acted upon by buffeting winds is commonly performed throughout the aerospace industry. Due to the unpredictable nature of this wind loading event, these problems are typically solved using frequency response random analysis techniques. To generate dynamic responses for spacecraft with statically-indeterminate interfaces, spacecraft contractors prefer to develop models which have response transformation matrices developed for mode acceleration data recovery. This method transforms spacecraft boundary accelerations and displacements into internal responses. Unfortunately, standard MSC/NASTRAN modal frequency response solution sequences cannot be used to combine acceleration- and displacement-dependent responses required for spacecraft mode acceleration data recovery. External user-written computer codes can be used with MSC/NASTRAN output to perform such combinations, but these methods can be labor and computer resource intensive. Taking advantage of the analytical and computer resource efficiencies inherent within MS C/NASTRAN, a DMAP Alter has been developed to combine acceleration- and displacement-dependent modal frequency responses for performing spacecraft mode acceleration data recovery. The Alter has been used successfully to efficiently solve a common aerospace buffeting wind analysis.

Acceleration and Velocity Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truax, Roger

2016-01-01

A simple approach for computing acceleration and velocity of a structure from the strain is proposed in this study. First, deflection and slope of the structure are computed from the strain using a two-step theory. Frequencies of the structure are computed from the time histories of strain using a parameter estimation technique together with an Autoregressive Moving Average model. From deflection, slope, and frequencies of the structure, acceleration and velocity of the structure can be obtained using the proposed approach. shape sensing, fiber optic strain sensor, system equivalent reduction and expansion process.

ISEES: an institute for sustainable software to accelerate environmental science

NASA Astrophysics Data System (ADS)

Jones, M. B.; Schildhauer, M.; Fox, P. A.

2013-12-01

Software is essential to the full science lifecycle, spanning data acquisition, processing, quality assessment, data integration, analysis, modeling, and visualization. Software runs our meteorological sensor systems, our data loggers, and our ocean gliders. Every aspect of science is impacted by, and improved by, software. Scientific advances ranging from modeling climate change to the sequencing of the human genome have been rendered possible in the last few decades due to the massive improvements in the capabilities of computers to process data through software. This pivotal role of software in science is broadly acknowledged, while simultaneously being systematically undervalued through minimal investments in maintenance and innovation. As a community, we need to embrace the creation, use, and maintenance of software within science, and address problems such as code complexity, openness,reproducibility, and accessibility. We also need to fully develop new skills and practices in software engineering as a core competency in our earth science disciplines, starting with undergraduate and graduate education and extending into university and agency professional positions. The Institute for Sustainable Earth and Environmental Software (ISEES) is being envisioned as a community-driven activity that can facilitate and galvanize activites around scientific software in an analogous way to synthesis centers such as NCEAS and NESCent that have stimulated massive advances in ecology and evolution. We will describe the results of six workshops (Science Drivers, Software Lifecycles, Software Components, Workforce Development and Training, Sustainability and Governance, and Community Engagement) that have been held in 2013 to envision such an institute. We will present community recommendations from these workshops and our strategic vision for how ISEES will address the technical issues in the software lifecycle, sustainability of the whole software ecosystem, and the critical issue of computational training for the scientific community. Process for envisioning ISEES.

The RTE inversion on FPGA aboard the solar orbiter PHI instrument

NASA Astrophysics Data System (ADS)

Cobos Carrascosa, J. P.; Aparicio del Moral, B.; Ramos Mas, J. L.; Balaguer, M.; López Jiménez, A. C.; del Toro Iniesta, J. C.

2016-07-01

In this work we propose a multiprocessor architecture to reach high performance in floating point operations by using radiation tolerant FPGA devices, and under narrow time and power constraints. This architecture is used in the PHI instrument that carries out the scientific analysis aboard the ESA's Solar Orbiter mission. The proposed architecture, in a SIMD flavor, is aimed to be an accelerator within the Data Processing Unit (it is composed by a main Leon processor and two FPGAs) for carrying out the RTE inversion on board the spacecraft using a relatively slow FPGA device - Xilinx XQR4VSX55-. The proposed architecture squeezes the FPGA resources in order to reach the computational requirements and improves the ground-based system performance based on commercial CPUs regarding time and power consumption. In this work we demonstrate the feasibility of using this FPGA devices embedded in the SO/PHI instrument. With that goal in mind, we perform tests to evaluate the scientific results and to measure the processing time and power consumption for carrying out the RTE inversion.

Mathematical Model of Bubble Sloshing Dynamics for Cryogenic Liquid Helium in Orbital Spacecraft Dewar Container

NASA Technical Reports Server (NTRS)

Hung, R. J.; Pan, H. L.

1995-01-01

A generalized mathematical model is investigated of sloshing dynamics for dewar containers, partially filled with a liquid of cryogenic superfluid helium 2, driven by both gravity gradient and jitter accelerations applicable to two types of scientific spacecrafts, which are eligible to carry out spinning motion and/or slew motion to perform scientific observations during normal spacecraft operation. Two examples are given for the Gravity Probe-B (GP-B) with spinning motion, and the Advanced X-Ray Astrophysics Facility-Spectroscopy (AXAF-S) with slew motion, which are responsible for the sloshing dynamics. Explicit mathematical expressions for the modelling of sloshing dynamics to cover these forces acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics will be based on the noninertial frame spacecraft bound coordinate, and we will solve the time-dependent three-dimensional formulations of partial differential equations subject to initial and boundary conditions. Explicit mathematical expressions of boundary conditions lo cover capillary force effects on the liquid-vapor interface in microgravity environments are also derived. Results of the simulations of the mathematical model are illustrated.

A Summary of the NASA Fusion Propulsion Workshop 2000

NASA Technical Reports Server (NTRS)

Thio, Y. C. Francis; Turchi, Peter J.; Santarius, John F.; Schafer, Charles (Technical Monitor)

2001-01-01

A NASA Fusion Propulsion Workshop was held on Nov. 8 and 9, 2000 at Marshall Space Flight Center (MSFC) in Huntsville, Alabama. A total of 43 papers were presented at the Workshop orally or by posters, covering a broad spectrum of issues related to applying fusion to propulsion. The status of fusion research was reported at the Workshop showing the outstanding scientific research that has been accomplished worldwide in the fusion energy research program. The international fusion research community has demonstrated the scientific principles of fusion creating plasmas with conditions for fusion burn with a gain of order unity: 0.25 in Princeton TFTR, 0.65 in the Joint European Torus, and a Q-equivalent of 1.25 in Japan's JT-60. This research has developed an impressive range of physics and technological capabilities that may be applied effectively to the research of possibly new propulsion-oriented fusion schemes. The pertinent physics capabilities include the plasma computational tools, the experimental plasma facilities, the diagnostics techniques, and the theoretical understanding. The enabling technologies include the various plasma heating, acceleration, and the pulsed power technologies.

Novel hybrid GPU-CPU implementation of parallelized Monte Carlo parametric expectation maximization estimation method for population pharmacokinetic data analysis.

PubMed

Ng, C M

2013-10-01

The development of a population PK/PD model, an essential component for model-based drug development, is both time- and labor-intensive. A graphical-processing unit (GPU) computing technology has been proposed and used to accelerate many scientific computations. The objective of this study was to develop a hybrid GPU-CPU implementation of parallelized Monte Carlo parametric expectation maximization (MCPEM) estimation algorithm for population PK data analysis. A hybrid GPU-CPU implementation of the MCPEM algorithm (MCPEMGPU) and identical algorithm that is designed for the single CPU (MCPEMCPU) were developed using MATLAB in a single computer equipped with dual Xeon 6-Core E5690 CPU and a NVIDIA Tesla C2070 GPU parallel computing card that contained 448 stream processors. Two different PK models with rich/sparse sampling design schemes were used to simulate population data in assessing the performance of MCPEMCPU and MCPEMGPU. Results were analyzed by comparing the parameter estimation and model computation times. Speedup factor was used to assess the relative benefit of parallelized MCPEMGPU over MCPEMCPU in shortening model computation time. The MCPEMGPU consistently achieved shorter computation time than the MCPEMCPU and can offer more than 48-fold speedup using a single GPU card. The novel hybrid GPU-CPU implementation of parallelized MCPEM algorithm developed in this study holds a great promise in serving as the core for the next-generation of modeling software for population PK/PD analysis.

GPU-accelerated adjoint algorithmic differentiation

NASA Astrophysics Data System (ADS)

Gremse, Felix; Höfter, Andreas; Razik, Lukas; Kiessling, Fabian; Naumann, Uwe

2016-03-01

Many scientific problems such as classifier training or medical image reconstruction can be expressed as minimization of differentiable real-valued cost functions and solved with iterative gradient-based methods. Adjoint algorithmic differentiation (AAD) enables automated computation of gradients of such cost functions implemented as computer programs. To backpropagate adjoint derivatives, excessive memory is potentially required to store the intermediate partial derivatives on a dedicated data structure, referred to as the ;tape;. Parallelization is difficult because threads need to synchronize their accesses during taping and backpropagation. This situation is aggravated for many-core architectures, such as Graphics Processing Units (GPUs), because of the large number of light-weight threads and the limited memory size in general as well as per thread. We show how these limitations can be mediated if the cost function is expressed using GPU-accelerated vector and matrix operations which are recognized as intrinsic functions by our AAD software. We compare this approach with naive and vectorized implementations for CPUs. We use four increasingly complex cost functions to evaluate the performance with respect to memory consumption and gradient computation times. Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity. The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation. The GPU version achieved an additional speedup of 7.5 ± 4.4, showing that the processing power of GPUs can be utilized for AAD using this concept. Furthermore, we show how this software can be systematically extended for more complex problems such as nonlinear absorption reconstruction for fluorescence-mediated tomography.

GPU-Accelerated Adjoint Algorithmic Differentiation.

PubMed

Gremse, Felix; Höfter, Andreas; Razik, Lukas; Kiessling, Fabian; Naumann, Uwe

2016-03-01

Many scientific problems such as classifier training or medical image reconstruction can be expressed as minimization of differentiable real-valued cost functions and solved with iterative gradient-based methods. Adjoint algorithmic differentiation (AAD) enables automated computation of gradients of such cost functions implemented as computer programs. To backpropagate adjoint derivatives, excessive memory is potentially required to store the intermediate partial derivatives on a dedicated data structure, referred to as the "tape". Parallelization is difficult because threads need to synchronize their accesses during taping and backpropagation. This situation is aggravated for many-core architectures, such as Graphics Processing Units (GPUs), because of the large number of light-weight threads and the limited memory size in general as well as per thread. We show how these limitations can be mediated if the cost function is expressed using GPU-accelerated vector and matrix operations which are recognized as intrinsic functions by our AAD software. We compare this approach with naive and vectorized implementations for CPUs. We use four increasingly complex cost functions to evaluate the performance with respect to memory consumption and gradient computation times. Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity. The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation. The GPU version achieved an additional speedup of 7.5 ± 4.4, showing that the processing power of GPUs can be utilized for AAD using this concept. Furthermore, we show how this software can be systematically extended for more complex problems such as nonlinear absorption reconstruction for fluorescence-mediated tomography.

GPU-Accelerated Adjoint Algorithmic Differentiation

PubMed Central

Gremse, Felix; Höfter, Andreas; Razik, Lukas; Kiessling, Fabian; Naumann, Uwe

2015-01-01

Many scientific problems such as classifier training or medical image reconstruction can be expressed as minimization of differentiable real-valued cost functions and solved with iterative gradient-based methods. Adjoint algorithmic differentiation (AAD) enables automated computation of gradients of such cost functions implemented as computer programs. To backpropagate adjoint derivatives, excessive memory is potentially required to store the intermediate partial derivatives on a dedicated data structure, referred to as the “tape”. Parallelization is difficult because threads need to synchronize their accesses during taping and backpropagation. This situation is aggravated for many-core architectures, such as Graphics Processing Units (GPUs), because of the large number of light-weight threads and the limited memory size in general as well as per thread. We show how these limitations can be mediated if the cost function is expressed using GPU-accelerated vector and matrix operations which are recognized as intrinsic functions by our AAD software. We compare this approach with naive and vectorized implementations for CPUs. We use four increasingly complex cost functions to evaluate the performance with respect to memory consumption and gradient computation times. Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity. The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation. The GPU version achieved an additional speedup of 7.5 ± 4.4, showing that the processing power of GPUs can be utilized for AAD using this concept. Furthermore, we show how this software can be systematically extended for more complex problems such as nonlinear absorption reconstruction for fluorescence-mediated tomography. PMID:26941443

Whole earth modeling: developing and disseminating scientific software for computational geophysics.

NASA Astrophysics Data System (ADS)

Kellogg, L. H.

2016-12-01

Historically, a great deal of specialized scientific software for modeling and data analysis has been developed by individual researchers or small groups of scientists working on their own specific research problems. As the magnitude of available data and computer power has increased, so has the complexity of scientific problems addressed by computational methods, creating both a need to sustain existing scientific software, and expand its development to take advantage of new algorithms, new software approaches, and new computational hardware. To that end, communities like the Computational Infrastructure for Geodynamics (CIG) have been established to support the use of best practices in scientific computing for solid earth geophysics research and teaching. Working as a scientific community enables computational geophysicists to take advantage of technological developments, improve the accuracy and performance of software, build on prior software development, and collaborate more readily. The CIG community, and others, have adopted an open-source development model, in which code is developed and disseminated by the community in an open fashion, using version control and software repositories like Git. One emerging issue is how to adequately identify and credit the intellectual contributions involved in creating open source scientific software. The traditional method of disseminating scientific ideas, peer reviewed publication, was not designed for review or crediting scientific software, although emerging publication strategies such software journals are attempting to address the need. We are piloting an integrated approach in which authors are identified and credited as scientific software is developed and run. Successful software citation requires integration with the scholarly publication and indexing mechanisms as well, to assign credit, ensure discoverability, and provide provenance for software.

Observed differences in upper extremity forces, muscle efforts, postures, velocities and accelerations across computer activities in a field study of office workers.

PubMed

Bruno Garza, J L; Eijckelhof, B H W; Johnson, P W; Raina, S M; Rynell, P W; Huysmans, M A; van Dieën, J H; van der Beek, A J; Blatter, B M; Dennerlein, J T

2012-01-01

This study, a part of the PRedicting Occupational biomechanics in OFfice workers (PROOF) study, investigated whether there are differences in field-measured forces, muscle efforts, postures, velocities and accelerations across computer activities. These parameters were measured continuously for 120 office workers performing their own work for two hours each. There were differences in nearly all forces, muscle efforts, postures, velocities and accelerations across keyboard, mouse and idle activities. Keyboard activities showed a 50% increase in the median right trapezius muscle effort when compared to mouse activities. Median shoulder rotation changed from 25 degrees internal rotation during keyboard use to 15 degrees external rotation during mouse use. Only keyboard use was associated with median ulnar deviations greater than 5 degrees. Idle activities led to the greatest variability observed in all muscle efforts and postures measured. In future studies, measurements of computer activities could be used to provide information on the physical exposures experienced during computer use. Practitioner Summary: Computer users may develop musculoskeletal disorders due to their force, muscle effort, posture and wrist velocity and acceleration exposures during computer use. We report that many physical exposures are different across computer activities. This information may be used to estimate physical exposures based on patterns of computer activities over time.

Controlling under-actuated robot arms using a high speed dynamics process

NASA Technical Reports Server (NTRS)

Jain, Abhinandan (Inventor); Rodriguez, Guillermo (Inventor)

1994-01-01

The invention controls an under-actuated manipulator by first obtaining predetermined active joint accelerations of the active joints and the passive joint friction forces of the passive joints, then computing articulated body qualities for each of the joints from the current positions of the links, and finally computing from the articulated body qualities and from the active joint accelerations and the passive joint forces, active joint forces of the active joints. Ultimately, the invention transmits servo commands to the active joint forces thus computed to the respective ones of the joint servos. The computation of the active joint forces is accomplished using a recursive dynamics algorithm. In this computation, an inward recursion is first carried out for each link, beginning with the outermost link in order to compute the residual link force of each link from the active joint acceleration if the corresponding joint is active, or from the known passive joint force if the corresponding joint is passive. Then, an outward recursion is carried out for each link in which the active joint force is computed from the residual link force if the corresponding joint is active or the passive joint acceleration is computed from the residual link force if the corresponding joint is passive.

Accelerating scientific publication in biology

PubMed Central

Vale, Ronald D.

2015-01-01

Scientific publications enable results and ideas to be transmitted throughout the scientific community. The number and type of journal publications also have become the primary criteria used in evaluating career advancement. Our analysis suggests that publication practices have changed considerably in the life sciences over the past 30 years. More experimental data are now required for publication, and the average time required for graduate students to publish their first paper has increased and is approaching the desirable duration of PhD training. Because publication is generally a requirement for career progression, schemes to reduce the time of graduate student and postdoctoral training may be difficult to implement without also considering new mechanisms for accelerating communication of their work. The increasing time to publication also delays potential catalytic effects that ensue when many scientists have access to new information. The time has come for life scientists, funding agencies, and publishers to discuss how to communicate new findings in a way that best serves the interests of the public and the scientific community. PMID:26508643

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

Clendenin, James E

The International Committee supported the proposal of the Chairman of the XVIII International Linac Conference to issue a new Compendium of linear accelerators. The last one was published in 1976. The Local Organizing Committee of Linac96 decided to set up a sub-committee for this purpose. Contrary to the catalogues of the High Energy Accelerators which compile accelerators with energies above 1 GeV, we have not defined a specific limit in energy. Microtrons and cyclotrons are not in this compendium. Also data from thousands of medical and industrial linacs has not been collected. Therefore, only scientific linacs are listed in themore » present compendium. Each linac found in this research and involved in a physics context was considered. It could be used, for example, either as an injector for high energy accelerators, or in nuclear physics, materials physics, free electron lasers or synchrotron light machines. Linear accelerators are developed in three continents only: America, Asia, and Europe. This geographical distribution is kept as a basis. The compendium contains the parameters and status of scientific linacs. Most of these linacs are operational. However, many facilities under construction or design studies are also included. A special mention has been made at the end for the studies of future linear colliders.« less

Behind the Scenes of the Spallation Neutron Source – The Linear Accelerator

ScienceCinema

Galambos, John

2018-06-25

The Spallation Neutron Source at Oak Ridge National Laboratory is a one-of-a-kind research facility that provides the most intense pulsed neutron beams in the world for scientific research and industrial development. Take a look inside the facility's linear accelerator.

Computing Principal Eigenvectors of Large Web Graphs: Algorithms and Accelerations Related to PageRank and HITS

ERIC Educational Resources Information Center

Nagasinghe, Iranga

2010-01-01

This thesis investigates and develops a few acceleration techniques for the search engine algorithms used in PageRank and HITS computations. PageRank and HITS methods are two highly successful applications of modern Linear Algebra in computer science and engineering. They constitute the essential technologies accounted for the immense growth and…

Can Accelerators Accelerate Learning?

NASA Astrophysics Data System (ADS)

Santos, A. C. F.; Fonseca, P.; Coelho, L. F. S.

2009-03-01

The 'Young Talented' education program developed by the Brazilian State Funding Agency (FAPERJ) [1] makes it possible for high-schools students from public high schools to perform activities in scientific laboratories. In the Atomic and Molecular Physics Laboratory at Federal University of Rio de Janeiro (UFRJ), the students are confronted with modern research tools like the 1.7 MV ion accelerator. Being a user-friendly machine, the accelerator is easily manageable by the students, who can perform simple hands-on activities, stimulating interest in physics, and getting the students close to modern laboratory techniques.

Integrating Data Base into the Elementary School Science Program.

ERIC Educational Resources Information Center

Schlenker, Richard M.

This document describes seven science activities that combine scientific principles and computers. The objectives for the activities are to show students how the computer can be used as a tool to store and arrange scientific data, provide students with experience using the computer as a tool to manage scientific data, and provide students with…

A high performance scientific cloud computing environment for materials simulations

NASA Astrophysics Data System (ADS)

Jorissen, K.; Vila, F. D.; Rehr, J. J.

2012-09-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

Unaligned instruction relocation

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

Bertolli, Carlo; O'Brien, John K.; Sallenave, Olivier H.

In one embodiment, a computer-implemented method includes receiving source code to be compiled into an executable file for an unaligned instruction set architecture (ISA). Aligned assembled code is generated, by a computer processor. The aligned assembled code complies with an aligned ISA and includes aligned processor code for a processor and aligned accelerator code for an accelerator. A first linking pass is performed on the aligned assembled code, including relocating a first relocation target in the aligned accelerator code that refers to a first object outside the aligned accelerator code. Unaligned assembled code is generated in accordance with the unalignedmore » ISA and includes unaligned accelerator code for the accelerator and unaligned processor code for the processor. A second linking pass is performed on the unaligned assembled code, including relocating a second relocation target outside the unaligned accelerator code that refers to an object in the unaligned accelerator code.« less

Unaligned instruction relocation

DOEpatents

Bertolli, Carlo; O'Brien, John K.; Sallenave, Olivier H.; Sura, Zehra N.

2018-01-23

In one embodiment, a computer-implemented method includes receiving source code to be compiled into an executable file for an unaligned instruction set architecture (ISA). Aligned assembled code is generated, by a computer processor. The aligned assembled code complies with an aligned ISA and includes aligned processor code for a processor and aligned accelerator code for an accelerator. A first linking pass is performed on the aligned assembled code, including relocating a first relocation target in the aligned accelerator code that refers to a first object outside the aligned accelerator code. Unaligned assembled code is generated in accordance with the unaligned ISA and includes unaligned accelerator code for the accelerator and unaligned processor code for the processor. A second linking pass is performed on the unaligned assembled code, including relocating a second relocation target outside the unaligned accelerator code that refers to an object in the unaligned accelerator code.

Status Report on the Development of Research Campaigns

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

Baer, Donald R.; Baker, Scott E.; Washton, Nancy M.

2013-06-30

Research campaigns were conceived as a means to focus EMSL research on specific scientific questions. Campaign will help fulfill the Environmental Molecular Sciences Laboratory (EMSL) strategic vision to develop and integrate, for use by the scientific community, world leading capabilities that transform understanding in the environmental molecular sciences and accelerate discoveries relevant to the Department of Energy’s (DOE’s) missions. Campaigns are multi-institutional multi-disciplinary projects with scope beyond those of normal EMSL user projects. The goal of research campaigns is to have EMSL scientists and users team on the projects in the effort to accelerate progress and increase impact in specificmore » scientific areas by focusing user research, EMSL resources, and expertise in those areas. This report will give a history and update on the progress of those campaigns.« less

Avi Purkayastha | NREL

Science.gov Websites

Austin, from 2001 to 2007. There he was principal in HPC applications and user support, as well as in research and development in large-scale scientific applications and different HPC systems and technologies Interests HPC applications performance and optimizations|HPC systems and accelerator technologies|Scientific

Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

ERIC Educational Resources Information Center

Pallant, Amy; Lee, Hee-Sun

2015-01-01

Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students (N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation…

Parallel processing for scientific computations

NASA Technical Reports Server (NTRS)

Alkhatib, Hasan S.

1995-01-01

The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.

Accelerating Climate and Weather Simulations through Hybrid Computing

NASA Technical Reports Server (NTRS)

Zhou, Shujia; Cruz, Carlos; Duffy, Daniel; Tucker, Robert; Purcell, Mark

2011-01-01

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

Neuro-prosthetic interplay. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by M. Santello et al.

NASA Astrophysics Data System (ADS)

Schieber, Marc H.

2016-07-01

Control of the human hand has been both difficult to understand scientifically and difficult to emulate technologically. The article by Santello and colleagues in the current issue of Physics of Life Reviews[1] highlights the accelerating pace of interaction between the neuroscience of controlling body movement and the engineering of robotic hands that can be used either autonomously or as part of a motor neuroprosthesis, an artificial body part that moves under control from a human subject's own nervous system. Motor neuroprostheses typically involve a brain-computer interface (BCI) that takes signals from the subject's nervous system or muscles, interprets those signals through a decoding algorithm, and then applies the resulting output to control the artificial device.

Non-Rocket Missile Rope Launcher

NASA Technical Reports Server (NTRS)

Bolonkin, Alexander

2002-01-01

The method, installation, and estimation for delivering payload and missiles into outer space are presented. This method uses, in general, the engines and straight or closed-loop cables disposed on a planet surface. The installation consists of a space apparatus, power drive stations located along trajectory of the apparatus, the cables connected to the apparatus and to the power stations, a system for suspending the cable, and disconnected device. The drive stations accelerate the apparatus up to hypersonic speed. The estimations and computations show the possibility of making these projects a reality in a short period of time (see attached project: launcher for missiles and loads). The launch will be very cheap $1-$2 per LB. We need only light strong cable, which can be made from artificial fibers, whiskers, nanotubes, which exist in industry and scientific laboratories.

78 FR 66018 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-04

... Panel, Accelerator Mass Spectrometry Facility. Date: December 2-3, 2013. Time: 8:00 a.m. to 6:00 p.m... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Center for Scientific Review... personal privacy. Name of Committee: AIDS and Related Research Integrated Review Group, AIDS-associated...

The Institutional Challenges of Cyberinfrastructure and E-Research

ERIC Educational Resources Information Center

Lynch, Clifford

2008-01-01

In thinking about how best to support the changes in scholarly and scientific work and also to accelerate these changes as a way of advancing scientific progress, science funding agencies began speaking about the need to systematically invest in what they called "cyberinfrastructure." This included not just information technologies but…

Accelerating artificial intelligence with reconfigurable computing

NASA Astrophysics Data System (ADS)

Cieszewski, Radoslaw

Reconfigurable computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated by placing the computationally intense portions of an algorithm into reconfigurable hardware. Reconfigurable computing combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be changed over the lifetime of the system. Similar to an ASIC, reconfigurable systems provide a method to map circuits into hardware. Reconfigurable systems therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Such a field, where there is many different algorithms which can be accelerated, is an artificial intelligence. This paper presents example hardware implementations of Artificial Neural Networks, Genetic Algorithms and Expert Systems.

Consortium for Mathematics in the Geosciences (CMG++): Promoting the application of mathematics, statistics, and computational sciences to the geosciences

NASA Astrophysics Data System (ADS)

Mead, J.; Wright, G. B.

2013-12-01

The collection of massive amounts of high quality data from new and greatly improved observing technologies and from large-scale numerical simulations are drastically improving our understanding and modeling of the earth system. However, these datasets are also revealing important knowledge gaps and limitations of our current conceptual models for explaining key aspects of these new observations. These limitations are impeding progress on questions that have both fundamental scientific and societal significance, including climate and weather, natural disaster mitigation, earthquake and volcano dynamics, earth structure and geodynamics, resource exploration, and planetary evolution. New conceptual approaches and numerical methods for characterizing and simulating these systems are needed - methods that can handle processes which vary through a myriad of scales in heterogeneous, complex environments. Additionally, as certain aspects of these systems may be observable only indirectly or not at all, new statistical methods are also needed. This type of research will demand integrating the expertise of geoscientist together with that of mathematicians, statisticians, and computer scientists. If the past is any indicator, this interdisciplinary research will no doubt lead to advances in all these fields in addition to vital improvements in our ability to predict the behavior of the planetary environment. The Consortium for Mathematics in the Geosciences (CMG++) arose from two scientific workshops held at Northwestern and Princeton in 2011 and 2012 with participants from mathematics, statistics, geoscience and computational science. The mission of CMG++ is to accelerate the traditional interaction between people in these disciplines through the promotion of both collaborative research and interdisciplinary education. We will discuss current activities, describe how people can get involved, and solicit input from the broader AGU community.

Teaching Electromagnetism to High-School Students Using Particle Accelerators

ERIC Educational Resources Information Center

Sinflorio, D. A.; Fonseca, P.; Coelho, L. F. S.; Santos, A. C. F.

2006-01-01

In this article we describe two simple experiments using an ion accelerator as an aid to the teaching of electromagnetism to high-school students. This is part of a programme developed by a Brazilian State funding agency (FAPERJ) which aims to help scientifically minded students take their first steps in research.

Diagnosis of Acceleration, Reconnection, Turbulence, and Heating

NASA Astrophysics Data System (ADS)

Dufor, Mikal T.; Jemiolo, Andrew J.; Keesee, Amy; Cassak, Paul; Tu, Weichao; Scime, Earl E.

2017-10-01

The DARTH (Diagnosis of Acceleration, Reconnection, Turbulence, and Heating) experiment is an intermediate-scale, experimental facility designed to study magnetic reconnection at and below the kinetic scale of ions and electrons. The experiment will have non-perturbative diagnostics with high temporal and three-dimensional spatial resolution, giving it the capability to investigate kinetic-scale physics. Of specific scientific interest are particle acceleration, plasma heating, turbulence and energy dissipation during reconnection. Here we will describe the magnetic field system and the two plasma guns used to create flux ropes that then merge through magnetic reconnection. We will also describe the key diagnostic systems: laser induced fluorescence (LIF) for ion vdf measurements, a 300 GHz microwave scattering system for sub-mm wavelength fluctuation measurements and a Thomson scattering laser for electron vdf measurements. The vacuum chamber is designed to provide unparalleled access for these particle diagnostics. The scientific goals of DARTH are to examine particle acceleration and heating during, the role of three-dimensional instabilities during reconnection, how reconnection ceases, and the role of impurities and asymmetries in reconnection. This work was supported by the by the O'Brien Energy Research Fund.

Space Acceleration Measurement System-II: Microgravity Instrumentation for the International Space Station Research Community

NASA Technical Reports Server (NTRS)

Sutliff, Thomas J.

1999-01-01

The International Space Station opens for business in the year 2000, and with the opening, science investigations will take advantage of the unique conditions it provides as an on-orbit laboratory for research. With initiation of scientific studies comes a need to understand the environment present during research. The Space Acceleration Measurement System-II provides researchers a consistent means to understand the vibratory conditions present during experimentation on the International Space Station. The Space Acceleration Measurement System-II, or SAMS-II, detects vibrations present while the space station is operating. SAMS-II on-orbit hardware is comprised of two basic building block elements: a centralized control unit and multiple Remote Triaxial Sensors deployed to measure the acceleration environment at the point of scientific research, generally within a research rack. Ground Operations Equipment is deployed to complete the command, control and data telemetry elements of the SAMS-II implementation. Initially, operations consist of user requirements development, measurement sensor deployment and use, and data recovery on the ground. Future system enhancements will provide additional user functionality and support more simultaneous users.

Introduction to the LaRC central scientific computing complex

NASA Technical Reports Server (NTRS)

Shoosmith, John N.

1993-01-01

The computers and associated equipment that make up the Central Scientific Computing Complex of the Langley Research Center are briefly described. The electronic networks that provide access to the various components of the complex and a number of areas that can be used by Langley and contractors staff for special applications (scientific visualization, image processing, software engineering, and grid generation) are also described. Flight simulation facilities that use the central computers are described. Management of the complex, procedures for its use, and available services and resources are discussed. This document is intended for new users of the complex, for current users who wish to keep appraised of changes, and for visitors who need to understand the role of central scientific computers at Langley.

OMPC: an Open-Source MATLAB®-to-Python Compiler

PubMed Central

Jurica, Peter; van Leeuwen, Cees

2008-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB®, the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB®-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB® functions into Python programs. The imported MATLAB® modules will run independently of MATLAB®, relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB®. OMPC is available at http://ompc.juricap.com. PMID:19225577

Scientific Computing Paradigm

NASA Technical Reports Server (NTRS)

VanZandt, John

1994-01-01

The usage model of supercomputers for scientific applications, such as computational fluid dynamics (CFD), has changed over the years. Scientific visualization has moved scientists away from looking at numbers to looking at three-dimensional images, which capture the meaning of the data. This change has impacted the system models for computing. This report details the model which is used by scientists at NASA's research centers.

Commentary: Considerations in Pedagogy and Assessment in the Use of Computers to Promote Learning about Scientific Models

ERIC Educational Resources Information Center

Adams, Stephen T.

2004-01-01

Although one role of computers in science education is to help students learn specific science concepts, computers are especially intriguing as a vehicle for fostering the development of epistemological knowledge about the nature of scientific knowledge--what it means to "know" in a scientific sense (diSessa, 1985). In this vein, the…

High-End Scientific Computing

EPA Pesticide Factsheets

EPA uses high-end scientific computing, geospatial services and remote sensing/imagery analysis to support EPA's mission. The Center for Environmental Computing (CEC) assists the Agency's program offices and regions to meet staff needs in these areas.

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

McCaskey, Alexander J.

Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.

The Talent Development Middle School. An Elective Replacement Approach to Providing Extra Help in Math--The CATAMA Program (Computer- and Team-Assisted Mathematics Acceleration). Report No. 21.

ERIC Educational Resources Information Center

Mac Iver, Douglas J.; Balfanz, Robert; Plank, Stephen B.

In Talent Development Middle Schools, students needing extra help in mathematics participate in the Computer- and Team-Assisted Mathematics Acceleration (CATAMA) course. CATAMA is an innovative combination of computer-assisted instruction and structured cooperative learning that students receive in addition to their regular math course for about…

Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations.

PubMed

Neylon, J; Min, Y; Kupelian, P; Low, D A; Santhanam, A

2017-04-01

In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies. An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network. Inter-process communication methods were optimized to facilitate resource distribution and minimize data transfers over the server interconnect. The analytically predicted computation time predicted matched experimentally observations within 1-5 %. MGCS performance approached a theoretical limit of acceleration proportional to the number of GPUs utilized when computational tasks far outweighed memory operations. The MGCS implementation reproduced ground-truth dose computations with negligible differences, by distributing the work among several processes and implemented optimization strategies. The results showed that a cloud-based computation engine was a feasible solution for enabling clinics to make use of fast dose calculations for advanced treatment planning and adaptive radiotherapy. The cloud-based system was able to exceed the performance of a local machine even for optimized calculations, and provided significant acceleration for computationally intensive tasks. Such a framework can provide access to advanced technology and computational methods to many clinics, providing an avenue for standardization across institutions without the requirements of purchasing, maintaining, and continually updating hardware.

Computer simulation of the CSPAD, ePix10k, and RayonixMX170HS X-ray detectors

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

Tina, Adrienne

2015-08-21

The invention of free-electron lasers (FELs) has opened a door to an entirely new level of scientific research. The Linac Coherent Light Source (LCLS) at SLAC National Accelerator Laboratory is an X-ray FEL that houses several instruments, each with its own unique X-ray applications. This light source is revolutionary in that while its properties allow for a whole new range of scientific opportunities, it also poses numerous challenges. For example, the intensity of a focused X-ray beam is enough to damage a sample in one mere pulse; however, the pulse speed and extreme brightness of the source together are enoughmore » to obtain enough information about that sample, so that no further measurements are necessary. An important device in the radiation detection process, particularly for X-ray imaging, is the detector. The power of the LCLS X-rays has instigated a need for better performing detectors. The research conducted for this project consisted of the study of X-ray detectors to imitate their behaviors in a computer program. The analysis of the Rayonix MX170-HS, CSPAD, and ePix10k in particular helped to understand their properties. This program simulated the interaction of X-ray photons with these detectors to discern the patterns of their responses. A scientist’s selection process of a detector for a specific experiment is simplified from the characterization of the detectors in the program.« less

gpuPOM: a GPU-based Princeton Ocean Model

NASA Astrophysics Data System (ADS)

Xu, S.; Huang, X.; Zhang, Y.; Fu, H.; Oey, L.-Y.; Xu, F.; Yang, G.

2014-11-01

Rapid advances in the performance of the graphics processing unit (GPU) have made the GPU a compelling solution for a series of scientific applications. However, most existing GPU acceleration works for climate models are doing partial code porting for certain hot spots, and can only achieve limited speedup for the entire model. In this work, we take the mpiPOM (a parallel version of the Princeton Ocean Model) as our starting point, design and implement a GPU-based Princeton Ocean Model. By carefully considering the architectural features of the state-of-the-art GPU devices, we rewrite the full mpiPOM model from the original Fortran version into a new Compute Unified Device Architecture C (CUDA-C) version. We take several accelerating methods to further improve the performance of gpuPOM, including optimizing memory access in a single GPU, overlapping communication and boundary operations among multiple GPUs, and overlapping input/output (I/O) between the hybrid Central Processing Unit (CPU) and the GPU. Our experimental results indicate that the performance of the gpuPOM on a workstation containing 4 GPUs is comparable to a powerful cluster with 408 CPU cores and it reduces the energy consumption by 6.8 times.

GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method

NASA Astrophysics Data System (ADS)

Gong, Chunye; Liu, Jie; Chi, Lihua; Huang, Haowei; Fang, Jingyue; Gong, Zhenghu

2011-07-01

Graphics Processing Unit (GPU), originally developed for real-time, high-definition 3D graphics in computer games, now provides great faculty in solving scientific applications. The basis of particle transport simulation is the time-dependent, multi-group, inhomogeneous Boltzmann transport equation. The numerical solution to the Boltzmann equation involves the discrete ordinates ( Sn) method and the procedure of source iteration. In this paper, we present a GPU accelerated simulation of one energy group time-independent deterministic discrete ordinates particle transport in 3D Cartesian geometry (Sweep3D). The performance of the GPU simulations are reported with the simulations of vacuum boundary condition. The discussion of the relative advantages and disadvantages of the GPU implementation, the simulation on multi GPUs, the programming effort and code portability are also reported. The results show that the overall performance speedup of one NVIDIA Tesla M2050 GPU ranges from 2.56 compared with one Intel Xeon X5670 chip to 8.14 compared with one Intel Core Q6600 chip for no flux fixup. The simulation with flux fixup on one M2050 is 1.23 times faster than on one X5670.

Approaching the exa-scale: a real-world evaluation of rendering extremely large data sets

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

Patchett, John M; Ahrens, James P; Lo, Li - Ta

2010-10-15

Extremely large scale analysis is becoming increasingly important as supercomputers and their simulations move from petascale to exascale. The lack of dedicated hardware acceleration for rendering on today's supercomputing platforms motivates our detailed evaluation of the possibility of interactive rendering on the supercomputer. In order to facilitate our understanding of rendering on the supercomputing platform, we focus on scalability of rendering algorithms and architecture envisioned for exascale datasets. To understand tradeoffs for dealing with extremely large datasets, we compare three different rendering algorithms for large polygonal data: software based ray tracing, software based rasterization and hardware accelerated rasterization. We presentmore » a case study of strong and weak scaling of rendering extremely large data on both GPU and CPU based parallel supercomputers using Para View, a parallel visualization tool. Wc use three different data sets: two synthetic and one from a scientific application. At an extreme scale, algorithmic rendering choices make a difference and should be considered while approaching exascale computing, visualization, and analysis. We find software based ray-tracing offers a viable approach for scalable rendering of the projected future massive data sizes.« less

Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

PubMed Central

Shang, Yizi; Shang, Ling; Gao, Chuanchang; Lu, Guiming; Ye, Yuntao; Jia, Dongdong

2014-01-01

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. PMID:24574931

Fermilab | Tritium at Fermilab | Frequently asked questions

Science.gov Websites

computing Quantum initiatives Research and development Key discoveries Benefits of particle physics Particle Accelerators Leading accelerator technology Accelerator complex Illinois Accelerator Research Center Fermilab questions about tritium Tritium in surface water Indian Creek Kress Creek Ferry Creek Tritium in sanitary

Computed lateral rate and acceleration power spectral response of conventional and STOL airplanes to atmospheric turbulence

NASA Technical Reports Server (NTRS)

Lichtenstein, J. H.

1975-01-01

Power-spectral-density calculations were made of the lateral responses to atmospheric turbulence for several conventional and short take-off and landing (STOL) airplanes. The turbulence was modeled as three orthogonal velocity components, which were uncorrelated, and each was represented with a one-dimensional power spectrum. Power spectral densities were computed for displacements, rates, and accelerations in roll, yaw, and sideslip. In addition, the power spectral density of the transverse acceleration was computed. Evaluation of ride quality based on a specific ride quality criterion was also made. The results show that the STOL airplanes generally had larger values for the rate and acceleration power spectra (and, consequently, larger corresponding root-mean-square values) than the conventional airplanes. The ride quality criterion gave poorer ratings to the STOL airplanes than to the conventional airplanes.

Accelerating Vaccine Formulation Development Using Design of Experiment Stability Studies.

PubMed

Ahl, Patrick L; Mensch, Christopher; Hu, Binghua; Pixley, Heidi; Zhang, Lan; Dieter, Lance; Russell, Ryann; Smith, William J; Przysiecki, Craig; Kosinski, Mike; Blue, Jeffrey T

2016-10-01

Vaccine drug product thermal stability often depends on formulation input factors and how they interact. Scientific understanding and professional experience typically allows vaccine formulators to accurately predict the thermal stability output based on formulation input factors such as pH, ionic strength, and excipients. Thermal stability predictions, however, are not enough for regulators. Stability claims must be supported by experimental data. The Quality by Design approach of Design of Experiment (DoE) is well suited to describe formulation outputs such as thermal stability in terms of formulation input factors. A DoE approach particularly at elevated temperatures that induce accelerated degradation can provide empirical understanding of how vaccine formulation input factors and interactions affect vaccine stability output performance. This is possible even when clear scientific understanding of particular formulation stability mechanisms are lacking. A DoE approach was used in an accelerated 37(°)C stability study of an aluminum adjuvant Neisseria meningitidis serogroup B vaccine. Formulation stability differences were identified after only 15 days into the study. We believe this study demonstrates the power of combining DoE methodology with accelerated stress stability studies to accelerate and improve vaccine formulation development programs particularly during the preformulation stage. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Defining Computational Thinking for Mathematics and Science Classrooms

ERIC Educational Resources Information Center

Weintrop, David; Beheshti, Elham; Horn, Michael; Orton, Kai; Jona, Kemi; Trouille, Laura; Wilensky, Uri

2016-01-01

Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include "computational thinking" as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new…

Ermittlung von Wortstaemmen in russischen wissenschaftlichen Fachsprachen mit Hilfe des Computers (Establishing Word Stems in Scientific Russian With the Aid of a Computer)

ERIC Educational Resources Information Center

Halbauer, Siegfried

1976-01-01

It was considered that students of intensive scientific Russian courses could learn vocabulary more efficiently if they were taught word stems and how to combine them with prefixes and suffixes to form scientific words. The computer programs developed to identify the most important stems is discussed. (Text is in German.) (FB)

Scientific Visualization: The Modern Oscilloscope for "Seeing the Unseeable" (LBNL Summer Lecture Series)

ScienceCinema

Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division and Scientific Visualization Group

2018-05-07

Summer Lecture Series 2008: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

Proceedings of RIKEN BNL Research Center Workshop

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

Samios, Nicholas P.

The twelfth evaluation of the RIKEN BNL Research Center (RBRC) took place on November 6 – 8, 2012 at Brookhaven National Laboratory. The members of the Scientific Review Committee (SRC), present at the meeting, were: Prof. Wit Busza, Prof. Miklos Gyulassy, Prof. Kenichi Imai, Prof. Richard Milner (Chair), Prof. Alfred Mueller, Prof. Charles Young Prescott, and Prof. Akira Ukawa. We are pleased that Dr. Hideto En’yo, the Director of the Nishina Institute of RIKEN, Japan, participated in this meeting both in informing the committee of the activities of the RIKEN Nishina Center for Accelerator- Based Science and the role ofmore » RBRC and as an observer of this review. In order to illustrate the breadth and scope of the RBRC program, each member of the Center made a presentation on his/her research efforts. This encompassed three major areas of investigation: theoretical, experimental and computational physics. In addition, the committee met privately with the fellows and postdocs to ascertain their opinions and concerns. Although the main purpose of this review is a report to RIKEN management on the health, scientific value, management and future prospects of the Center, the RBRC management felt that a compendium of the scientific presentations are of sufficient quality and interest that they warrant a wider distribution. Therefore we have made this compilation and present it to the community for its information and enlightenment.« less

Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method

NASA Astrophysics Data System (ADS)

Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Hong, Yang; Zuo, Depeng; Ren, Minglei; Lei, Tianjie; Liang, Ke

2018-01-01

Hydrological model calibration has been a hot issue for decades. The shuffled complex evolution method developed at the University of Arizona (SCE-UA) has been proved to be an effective and robust optimization approach. However, its computational efficiency deteriorates significantly when the amount of hydrometeorological data increases. In recent years, the rise of heterogeneous parallel computing has brought hope for the acceleration of hydrological model calibration. This study proposed a parallel SCE-UA method and applied it to the calibration of a watershed rainfall-runoff model, the Xinanjiang model. The parallel method was implemented on heterogeneous computing systems using OpenMP and CUDA. Performance testing and sensitivity analysis were carried out to verify its correctness and efficiency. Comparison results indicated that heterogeneous parallel computing-accelerated SCE-UA converged much more quickly than the original serial version and possessed satisfactory accuracy and stability for the task of fast hydrological model calibration.

Further Studies of the NRL Collective Particle Accelerator VIA Numerical Modeling with the MAGIC Code.

DTIC Science & Technology

1984-08-01

COLLFCTIVF PAPTTCLE ACCELERATOR VIA NUMERICAL MODFLINC WITH THF MAGIC CODE Robert 1. Darker Auqust 19F4 Final Report for Period I April. qI84 - 30...NUMERICAL MODELING WITH THE MAGIC CODE Robert 3. Barker August 1984 Final Report for Period 1 April 1984 - 30 September 1984 Prepared for: Scientific...Collective Final Report Particle Accelerator VIA Numerical Modeling with April 1 - September-30, 1984 MAGIC Code. 6. PERFORMING ORG. REPORT NUMBER MRC/WDC-R

Jefferson Lab Virtual Tour

ScienceCinema

None

2018-01-16

Take a virtual tour of the campus of Thomas Jefferson National Accelerator Facility. You can see inside our two accelerators, three experimental areas, accelerator component fabrication and testing areas, high-performance computing areas and laser labs.

Scientific Visualization, Seeing the Unseeable

ScienceCinema

LBNL

2017-12-09

June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in bo... June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

Generation of nanosecond neutron pulses in vacuum accelerating tubes

NASA Astrophysics Data System (ADS)

Didenko, A. N.; Shikanov, A. E.; Rashchikov, V. I.; Ryzhkov, V. I.; Shatokhin, V. L.

2014-06-01

The generation of neutron pulses with a duration of 1-100 ns using small vacuum accelerating tubes is considered. Two physical models of acceleration of short deuteron bunches in pulse neutron generators are described. The dependences of an instantaneous neutron flux in accelerating tubes on the parameters of pulse neutron generators are obtained using computer simulation. The results of experimental investigation of short-pulse neutron generators based on the accelerating tube with a vacuum-arc deuteron source, connected in the circuit with a discharge peaker, and an accelerating tube with a laser deuteron source, connected according to the Arkad'ev-Marx circuit, are given. In the experiments, the neutron yield per pulse reached 107 for a pulse duration of 10-100 ns. The resultant experimental data are in satisfactory agreement with the results of computer simulation.

Research for the Fluid Field of the Centrifugal Compressor Impeller in Accelerating Startup

NASA Astrophysics Data System (ADS)

Li, Xiaozhu; Chen, Gang; Zhu, Changyun; Qin, Guoliang

2013-03-01

In order to study the flow field in the impeller in the accelerating start-up process of centrifugal compressor, the 3-D and 1-D transient accelerated flow governing equations along streamline in the impeller of the centrifugal compressor are derived in detail, the assumption of pressure gradient distribution is presented, and the solving method for 1-D transient accelerating flow field is given based on the assumption. The solving method is achieved by programming and the computing result is obtained. It is obtained by comparison that the computing method is met with the test result. So the feasibility and effectiveness for solving accelerating start-up problem of centrifugal compressor by the solving method in this paper is proven.

The charged particle accelerators subsystems modeling

NASA Astrophysics Data System (ADS)

Averyanov, G. P.; Kobylyatskiy, A. V.

2017-01-01

Presented web-based resource for information support the engineering, science and education in Electrophysics, containing web-based tools for simulation subsystems charged particle accelerators. Formulated the development motivation of Web-Environment for Virtual Electrophysical Laboratories. Analyzes the trends of designs the dynamic web-environments for supporting of scientific research and E-learning, within the framework of Open Education concept.

Fundamentals of Radiation Physics

DTIC Science & Technology

2008-07-01

Sources of Ionizing Radiation Electrically generated • Charged particle accelerators • Van de Graaff generator , cyclotron linear accelerator ...Presented at the Armed Forces Radiobiology Research Institute Scientific Medical Effects of Ionizing Radiation Course July 28 through August 1, 2008...conducted once a year, focuses on the latest research about the medical effects of ionizing radiation to help clinicians, health physicists, and

76 FR 63311 - Center for Scientific Review Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-12

... Panel PAR-10-018: Accelerating the Pace of Drug Abuse Research Using Existing Epidemiology, Prevention, and Treatment Research Data. Date:November 1-2, 2011 Time: 10 a.m. to 5 p.m. Agenda: To review and... Scientific Review Special Emphasis Panel; Small Business: Orthopedic and Skeletal Biology. Date: November 7...

Reforming system of professional training of future specialists by taking into account production automation requirements

NASA Astrophysics Data System (ADS)

Saigushev, N. Y.; Vedeneeva, O. A.; Melekhova, Yu B.

2018-05-01

The accelerating scientific development, equipment upgrade, emergence of new technologies and intensive growth and use of nano-, robotic, bio- and other perspective technologies require the formation of scientific and technological potential in Russia which is suitable for present-day challenges of the global technological growth.

Visual Language for the Expression of Scientific Concepts

ERIC Educational Resources Information Center

Zender, Mike; Crutcher, Keith A.

2007-01-01

The accelerating rate of data generation and resulting publications are taxing the ability of scientific investigators to stay current with the emerging literature. This problem, acute in science, is not uncommon in other areas. New approaches to managing this explosion of information are needed. While it is only possible to read one paper or…

77 FR 59200 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-26

... Panel; PAR 10-018: Accelerating the Pace of Drug Abuse Research Using Existing Epidemiology, Prevention, and Treatment Research Data. Date: October 24, 2012. Time: 2 p.m. to 4 p.m. Agenda: To review and...: Center for Scientific Review Special Emphasis Panel; PA:12-006: Academic Research Enhancement Award...

Deep learning for computational chemistry

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

Goh, Garrett B.; Hodas, Nathan O.; Vishnu, Abhinav

The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. Inmore » this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.« less

Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers

PubMed Central

Filipovic, Nenad D.

2017-01-01

Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. In this paper, the implementation of the already existing algorithm for region-of-interest based image segmentation for mammogram images on High-Performance Reconfigurable Dataflow Computers (HPRDCs) is proposed. As a dataflow engine (DFE) of such HPRDC, Maxeler's acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable Dataflow Computers (RDCs) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave a different acceleration value of algorithm execution. Those acceleration values are presented and experimental results showed good acceleration. PMID:28611851

Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers.

PubMed

Milankovic, Ivan L; Mijailovic, Nikola V; Filipovic, Nenad D; Peulic, Aleksandar S

2017-01-01

Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. In this paper, the implementation of the already existing algorithm for region-of-interest based image segmentation for mammogram images on High-Performance Reconfigurable Dataflow Computers (HPRDCs) is proposed. As a dataflow engine (DFE) of such HPRDC, Maxeler's acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable Dataflow Computers (RDCs) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave a different acceleration value of algorithm execution. Those acceleration values are presented and experimental results showed good acceleration.

Energy Innovation Hubs: A Home for Scientific Collaboration

ScienceCinema

Chu, Steven

2017-12-11

Secretary Chu will host a live, streaming Q&A session with the directors of the Energy Innovation Hubs on Tuesday, March 6, at 2:15 p.m. EST. The directors will be available for questions regarding their teams' work and the future of American energy. Ask your questions in the comments below, or submit them on Facebook, Twitter (@energy), or send an e-mail to newmedia@hq.doe.gov, prior or during the live event. Dr. Hank Foley is the director of the Greater Philadelphia Innovation Cluster for Energy-Efficient Buildings, which is pioneering new data intensive techniques for designing and operating energy efficient buildings, including advanced computer modeling. Dr. Douglas Kothe is the director of the Consortium for Advanced Simulation of Light Water Reactors, which uses powerful supercomputers to create "virtual" reactors that will help improve the safety and performance of both existing and new nuclear reactors. Dr. Nathan Lewis is the director of the Joint Center for Artificial Photosynthesis, which focuses on how to produce fuels from sunlight, water, and carbon dioxide. The Energy Innovation Hubs are major integrated research centers, with researchers from many different institutions and technical backgrounds. Each hub is focused on a specific high priority goal, rapidly accelerating scientific discoveries and shortening the path from laboratory innovation to technological development and commercial deployment of critical energy technologies. Ask your questions in the comments below, or submit them on Facebook, Twitter (@energy), or send an e-mail to newmedia@energy.gov, prior or during the live event. The Energy Innovation Hubs are major integrated research centers, with researchers from many different institutions and technical backgrounds. Each Hub is focused on a specific high priority goal, rapidly accelerating scientific discoveries and shortening the path from laboratory innovation to technological development and commercial deployment of critical energy technologies. Dr. Hank Holey is the director of the Greater Philadelphia Innovation Cluster for Energy-Efficient Buildings, which is pioneering new data intensive techniques for designing and operating energy efficient buildings, including advanced computer modeling. Dr. Douglas Kothe is the director of the Modeling and Simulation for Nuclear Reactors Hub, which uses powerful supercomputers to create "virtual" reactors that will help improve the safety and performance of both existing and new nuclear reactors. Dr. Nathan Lewis is the director of the Joint Center for Artificial Photosynthesis Hub, which focuses on how to produce biofuels from sunlight, water, and carbon dioxide.

galario: Gpu Accelerated Library for Analyzing Radio Interferometer Observations

NASA Astrophysics Data System (ADS)

Tazzari, Marco; Beaujean, Frederik; Testi, Leonardo

2017-10-01

The galario library exploits the computing power of modern graphic cards (GPUs) to accelerate the comparison of model predictions to radio interferometer observations. It speeds up the computation of the synthetic visibilities given a model image (or an axisymmetric brightness profile) and their comparison to the observations.

Computer-Assisted Learning in Elementary Reading: A Randomized Control Trial

ERIC Educational Resources Information Center

Shannon, Lisa Cassidy; Styers, Mary Koenig; Wilkerson, Stephanie Baird; Peery, Elizabeth

2015-01-01

This study evaluated the efficacy of Accelerated Reader, a computer-based learning program, at improving student reading. Accelerated Reader is a progress-monitoring, assessment, and practice tool that supports classroom instruction and guides independent reading. Researchers used a randomized controlled trial to evaluate the program with 344…

OMPC: an Open-Source MATLAB-to-Python Compiler.

PubMed

Jurica, Peter; van Leeuwen, Cees

2009-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

Parallel computing works

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

Not Available

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of manymore » computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.« less

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.

Exploring Cloud Computing for Large-scale Scientific Applications

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

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

Computational Benefits Using an Advanced Concatenation Scheme Based on Reduced Order Models for RF Structures

NASA Astrophysics Data System (ADS)

Heller, Johann; Flisgen, Thomas; van Rienen, Ursula

The computation of electromagnetic fields and parameters derived thereof for lossless radio frequency (RF) structures filled with isotropic media is an important task for the design and operation of particle accelerators. Unfortunately, these computations are often highly demanding with regard to computational effort. The entire computational demand of the problem can be reduced using decomposition schemes in order to solve the field problems on standard workstations. This paper presents one of the first detailed comparisons between the recently proposed state-space concatenation approach (SSC) and a direct computation for an accelerator cavity with coupler-elements that break the rotational symmetry.

Llewellyn Hilleth Thomas: An appraisal of an under-appreciated polymath

NASA Astrophysics Data System (ADS)

Jackson, John David

2010-02-01

Llewellyn Hilleth Thomas was born in 1903 and died in 1992 at the age of 88. His name is known by most for only two things, Thomas precession and the Thomas-Fermi atom. The many other facets of his career - astrophysics, atomic and molecular physics, nonlinear problems, accelerator physics, magnetohydrodynamics, computer design principles and software and hardware - are largely unknown or forgotten. I review his whole career - his early schooling, his time at Cambridge, then Copenhagen in 1925-26, and back to Cambridge, his move to the US as an assistant professor at Ohio State University in 1929, his wartime years at the Ballistic Research Laboratory, Aberdeen Proving Grounds, then in 1946 his new career as a unique resource at IBM's Watson Scientific Computing Laboratory and Columbia University until his first retirement in 1968, and his twilight years at North Carolina State University. Although the Thomas precession and the Thomas-Fermi atom may be the jewels in his crown, his many other accomplishments add to our appreciation of this consummate applied mathematician and physicist. )

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

It Takes a Village: Documenting the Contributions of Non-Scientific Staff to Scientific Research

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

Higgins, Valerie

Documenting the Contributions of Non-Scientific Staff to Scientific Research Science, especially large-scale basic research, is a collaborative endeavor, often drawing on the skills of people from a wide variety of disciplines. These people include not just scientists, but also administrators, engineers, and many others. Fermilab, a Department of Energy National Laboratory and the United States’ premier particle physics laboratory, exemplifies this kind of research; many of its high-energy physics experiments involve hundreds of collaborators from all over the world. The Fermilab Archives seeks to document the history of the lab and the unique scientific research its staff and visitors perform.more » Adequately documenting the lab’s work often requires us to go far beyond things like the writings and correspondence of scientists to also capture the administrative and social histories of the experiments and the context in which they were performed. At Fermilab, we have sought to capture these elements of the lab’s activities through an oral history program that focuses on support staff as well as physicists and collection development choices that recognize the importance of records documenting the cultural life of the lab. These materials are not merely supplementary, but rather essential documentation of the many types of labor that go into the planning and execution of an experiment or the construction of an accelerator and the context in which this work is performed. Any picture of these experiments and accelerators that did not include this type of information would be incomplete. While the importance and richness of this material is especially pronounced at Fermilab due to the massive size of its experiments and accelerator facilities and its vibrant cultural life, the fruitfulness of these collecting efforts at Fermilab suggests that other archives documenting modern STEM research should also make sure the contributions of non-technical and non-scientific staff are preserved and that researchers interested in this subject should not neglect such sources.« less

Particle tracking acceleration via signed distance fields in direct-accelerated geometry Monte Carlo

DOE PAGES

Shriwise, Patrick C.; Davis, Andrew; Jacobson, Lucas J.; ...

2017-08-26

Computer-aided design (CAD)-based Monte Carlo radiation transport is of value to the nuclear engineering community for its ability to conduct transport on high-fidelity models of nuclear systems, but it is more computationally expensive than native geometry representations. This work describes the adaptation of a rendering data structure, the signed distance field, as a geometric query tool for accelerating CAD-based transport in the direct-accelerated geometry Monte Carlo toolkit. Demonstrations of its effectiveness are shown for several problems. The beginnings of a predictive model for the data structure's utilization based on various problem parameters is also introduced.

An Overview of the Computational Physics and Methods Group at Los Alamos National Laboratory

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

Baker, Randal Scott

CCS Division was formed to strengthen the visibility and impact of computer science and computational physics research on strategic directions for the Laboratory. Both computer science and computational science are now central to scientific discovery and innovation. They have become indispensable tools for all other scientific missions at the Laboratory. CCS Division forms a bridge between external partners and Laboratory programs, bringing new ideas and technologies to bear on today’s important problems and attracting high-quality technical staff members to the Laboratory. The Computational Physics and Methods Group CCS-2 conducts methods research and develops scientific software aimed at the latest andmore » emerging HPC systems.« less

[Earth Science Technology Office's Computational Technologies Project

NASA Technical Reports Server (NTRS)

Fischer, James (Technical Monitor); Merkey, Phillip

2005-01-01

This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

Superfluid helium sloshing dynamics induced oscillations and fluctuations of angular momentum, force and moment actuated on spacecraft driven by gravity gradient or jitter acceleration associated with slew motion

NASA Technical Reports Server (NTRS)

Hung, R. J.

1994-01-01

The generalized mathematical formulation of sloshing dynamics for partially filled liquid of cryogenic superfluid helium II in dewar containers driven by the gravity gradient and jitter accelerations associated with slew motion for the purpose to perform scientific observation during the normal spacecraft operation are investigated. An example is given with the Advanced X-Ray Astrophysics Facility-Spectroscopy (AXAF-S) for slew motion which is responsible for the sloshing dynamics. The jitter accelerations include slew motion, spinning motion, atmospheric drag on the spacecraft, spacecraft attitude motions arising from machinery vibrations, thruster firing, pointing control of spacecraft, crew motion, etc. Explicit mathematical expressions to cover these forces acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics is based on the non-inertia frame spacecraft bound coordinate, and solve time-dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. The explicit mathematical expressions of boundary conditions to cover capillary force effect on the liquid-vapor interface in microgravity environments are also derived. The formulations of fluid moment and angular moment fluctuations in fluid profiles induced by the sloshing dynamics, together with fluid stress and moment fluctuations exerted on the spacecraft dewar containers have also been derived. Examples are also given for cases applicable to the AXAF-S spacecraft sloshing dynamics associated with slew motion.

Software package for modeling spin-orbit motion in storage rings

NASA Astrophysics Data System (ADS)

Zyuzin, D. V.

2015-12-01

A software package providing a graphical user interface for computer experiments on the motion of charged particle beams in accelerators, as well as analysis of obtained data, is presented. The software package was tested in the framework of the international project on electric dipole moment measurement JEDI (Jülich Electric Dipole moment Investigations). The specific features of particle spin motion imply the requirement to use a cyclic accelerator (storage ring) consisting of electrostatic elements, which makes it possible to preserve horizontal polarization for a long time. Computer experiments study the dynamics of 106-109 particles in a beam during 109 turns in an accelerator (about 1012-1015 integration steps for the equations of motion). For designing an optimal accelerator structure, a large number of computer experiments on polarized beam dynamics are required. The numerical core of the package is COSY Infinity, a program for modeling spin-orbit dynamics.

An acceleration framework for synthetic aperture radar algorithms

NASA Astrophysics Data System (ADS)

Kim, Youngsoo; Gloster, Clay S.; Alexander, Winser E.

2017-04-01

Algorithms for radar signal processing, such as Synthetic Aperture Radar (SAR) are computationally intensive and require considerable execution time on a general purpose processor. Reconfigurable logic can be used to off-load the primary computational kernel onto a custom computing machine in order to reduce execution time by an order of magnitude as compared to kernel execution on a general purpose processor. Specifically, Field Programmable Gate Arrays (FPGAs) can be used to accelerate these kernels using hardware-based custom logic implementations. In this paper, we demonstrate a framework for algorithm acceleration. We used SAR as a case study to illustrate the potential for algorithm acceleration offered by FPGAs. Initially, we profiled the SAR algorithm and implemented a homomorphic filter using a hardware implementation of the natural logarithm. Experimental results show a linear speedup by adding reasonably small processing elements in Field Programmable Gate Array (FPGA) as opposed to using a software implementation running on a typical general purpose processor.

Computers and Computation. Readings from Scientific American.

ERIC Educational Resources Information Center

Fenichel, Robert R.; Weizenbaum, Joseph

A collection of articles from "Scientific American" magazine has been put together at this time because the current period in computer science is one of consolidation rather than innovation. A few years ago, computer science was moving so swiftly that even the professional journals were more archival than informative; but today it is…

Final Report on Institutional Computing Project s15_hilaserion, “Kinetic Modeling of Next-Generation High-Energy, High-Intensity Laser-Ion Accelerators as an Enabling Capability”

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

Albright, Brian James; Yin, Lin; Stark, David James

This proposal sought of order 1M core-hours of Institutional Computing time intended to enable computing by a new LANL Postdoc (David Stark) working under LDRD ER project 20160472ER (PI: Lin Yin) on laser-ion acceleration. The project was “off-cycle,” initiating in June of 2016 with a postdoc hire.

On-the-fly data assessment for high-throughput x-ray diffraction measurements

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

Ren, Fang; Pandolfi, Ronald; Van Campen, Douglas

Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for the discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through the development of an approach that makes routine data assessment automatic and instantaneous. By extracting and visualizing customized attributesmore » in real time, data quality and coverage, as well as other scientifically relevant information contained in large data sets, is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize the usage of expensive characterization resources by prioritizing measurements of the highest scientific impact. We anticipate our approach will become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. Finally, with these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition.« less

On-the-fly data assessment for high-throughput x-ray diffraction measurements

DOE PAGES

Ren, Fang; Pandolfi, Ronald; Van Campen, Douglas; ...

2017-05-02

Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for the discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through the development of an approach that makes routine data assessment automatic and instantaneous. By extracting and visualizing customized attributesmore » in real time, data quality and coverage, as well as other scientifically relevant information contained in large data sets, is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize the usage of expensive characterization resources by prioritizing measurements of the highest scientific impact. We anticipate our approach will become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. Finally, with these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition.« less

Imagining tomorrow's university in an era of open science.

PubMed

Howe, Adina; Howe, Michael; Kaleita, Amy L; Raman, D Raj

2017-01-01

As part of a recent workshop entitled "Imagining Tomorrow's University", we were asked to visualize the future of universities as research becomes increasingly data- and computation-driven, and identify a set of principles characterizing pertinent opportunities and obstacles presented by this shift. In order to establish a holistic view, we take a multilevel approach and examine the impact of open science on individual scholars and how this impacts as well as on the university as a whole. At the university level, open science presents a double-edged sword: when well executed, open science can accelerate the rate of scientific inquiry across the institution and beyond; however, haphazard or half-hearted efforts are likely to squander valuable resources, diminish university productivity and prestige, and potentially do more harm than good. We present our perspective on the role of open science at the university.

Accuracy of the lattice-Boltzmann method using the Cell processor

NASA Astrophysics Data System (ADS)

Harvey, M. J.; de Fabritiis, G.; Giupponi, G.

2008-11-01

Accelerator processors like the new Cell processor are extending the traditional platforms for scientific computation, allowing orders of magnitude more floating-point operations per second (flops) compared to standard central processing units. However, they currently lack double-precision support and support for some IEEE 754 capabilities. In this work, we develop a lattice-Boltzmann (LB) code to run on the Cell processor and test the accuracy of this lattice method on this platform. We run tests for different flow topologies, boundary conditions, and Reynolds numbers in the range Re=6 350 . In one case, simulation results show a reduced mass and momentum conservation compared to an equivalent double-precision LB implementation. All other cases demonstrate the utility of the Cell processor for fluid dynamics simulations. Benchmarks on two Cell-based platforms are performed, the Sony Playstation3 and the QS20/QS21 IBM blade, obtaining a speed-up factor of 7 and 21, respectively, compared to the original PC version of the code, and a conservative sustained performance of 28 gigaflops per single Cell processor. Our results suggest that choice of IEEE 754 rounding mode is possibly as important as double-precision support for this specific scientific application.

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

UCSB FEL user-mode adaption project. Final report, 1 Jan 86-31 Dec 90

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

Jaccarino, V.

1992-04-14

This research sponsored by the SDIO Biomedical and Materials Sciences FEL Program held the following objectives. Provide a facility in which in-house and outside user research in the materials and biological sciences can be carried out in the Far Infrared using-the unique properties of the UCSB electrostatic accelerator-driven FEL. Develop and implement new FEL concepts and FIR technology and encourage the transfer and application of this research. Train graduate students, post doctoral researchers and technical personnel in varied aspects of scientific user disciplines, FEL science and FIR technology in a cooperative, interdisciplinary environment. In summary, a free electron laser facilitymore » has been developed which is operational from 200 GH z, (6.6 cm -1), to 4.8 THz, (160 cm-1) tunable under computer control and able to deliver kilowatts of millimeter wave and far-infrared power. This facility has a well equipped user lab that has been used to perform ground breaking experiments in scientific areas as diverse as bio-physics. Nine graduate students and post doctoral researchers have been trained in the operation, use and application of these free-electron lasers.« less

PRISM software—Processing and review interface for strong-motion data

USGS Publications Warehouse

Jones, Jeanne M.; Kalkan, Erol; Stephens, Christopher D.; Ng, Peter

2017-11-28

Rapidly available and accurate ground-motion acceleration time series (seismic recordings) and derived data products are essential to quickly providing scientific and engineering analysis and advice after an earthquake. To meet this need, the U.S. Geological Survey National Strong Motion Project has developed a software package called PRISM (Processing and Review Interface for Strong-Motion data). PRISM automatically processes strong-motion acceleration records, producing compatible acceleration, velocity, and displacement time series; acceleration, velocity, and displacement response spectra; Fourier amplitude spectra; and standard earthquake-intensity measures. PRISM is intended to be used by strong-motion seismic networks, as well as by earthquake engineers and seismologists.

Modern Computational Techniques for the HMMER Sequence Analysis

PubMed Central

2013-01-01

This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detailed performance comparison of sequence analysis tools on various computing platforms recently developed in the bioinformatics society. The characteristics of the sequence analysis, such as data and compute-intensive natures, make it very attractive to optimize and parallelize by using both traditional software approach and innovated hardware acceleration technologies. PMID:25937944

DeepX: Deep Learning Accelerator for Restricted Boltzmann Machine Artificial Neural Networks.

PubMed

Kim, Lok-Won

2018-05-01

Although there have been many decades of research and commercial presence on high performance general purpose processors, there are still many applications that require fully customized hardware architectures for further computational acceleration. Recently, deep learning has been successfully used to learn in a wide variety of applications, but their heavy computation demand has considerably limited their practical applications. This paper proposes a fully pipelined acceleration architecture to alleviate high computational demand of an artificial neural network (ANN) which is restricted Boltzmann machine (RBM) ANNs. The implemented RBM ANN accelerator (integrating network size, using 128 input cases per batch, and running at a 303-MHz clock frequency) integrated in a state-of-the art field-programmable gate array (FPGA) (Xilinx Virtex 7 XC7V-2000T) provides a computational performance of 301-billion connection-updates-per-second and about 193 times higher performance than a software solution running on general purpose processors. Most importantly, the architecture enables over 4 times (12 times in batch learning) higher performance compared with a previous work when both are implemented in an FPGA device (XC2VP70).

Method for computationally efficient design of dielectric laser accelerator structures

DOE PAGES

Hughes, Tyler; Veronis, Georgios; Wootton, Kent P.; ...

2017-06-22

Here, dielectric microstructures have generated much interest in recent years as a means of accelerating charged particles when powered by solid state lasers. The acceleration gradient (or particle energy gain per unit length) is an important figure of merit. To design structures with high acceleration gradients, we explore the adjoint variable method, a highly efficient technique used to compute the sensitivity of an objective with respect to a large number of parameters. With this formalism, the sensitivity of the acceleration gradient of a dielectric structure with respect to its entire spatial permittivity distribution is calculated by the use of onlymore » two full-field electromagnetic simulations, the original and ‘adjoint’. The adjoint simulation corresponds physically to the reciprocal situation of a point charge moving through the accelerator gap and radiating. Using this formalism, we perform numerical optimizations aimed at maximizing acceleration gradients, which generate fabricable structures of greatly improved performance in comparison to previously examined geometries.« less

ILU industrial electron accelerators for medical-product sterilization and food treatment

NASA Astrophysics Data System (ADS)

Bezuglov, V. V.; Bryazgin, A. A.; Vlasov, A. Yu.; Voronin, L. A.; Panfilov, A. D.; Radchenko, V. M.; Tkachenko, V. O.; Shtarklev, E. A.

2016-12-01

Pulse linear electron accelerators of the ILU type have been developed and produced by the Institute of Nuclear Physics, Siberian Branch, Russian Academy of Sciences, for more than 30 years. Their distinctive features are simplicity of design, convenience in operation, and reliability during long work under conditions of industrial production. ILU accelerators have a range of energy of 0.7-10 MeV at a power of accelerated beam of up to 100 kW and they are optimally suitable for use as universal sterilizing complexes. The scientific novelty of these accelerators consists of their capability to work both in the electron-treatment mode of production and in the bremsstrahlung generation mode, which has high penetrating power.

Harnessing the crowd to accelerate molecular medicine research.

PubMed

Smith, Robert J; Merchant, Raina M

2015-07-01

Crowdsourcing presents a novel approach to solving complex problems within molecular medicine. By leveraging the expertise of fellow scientists across the globe, broadcasting to and engaging the public for idea generation, harnessing a scalable workforce for quick data management, and fundraising for research endeavors, crowdsourcing creates novel opportunities for accelerating scientific progress. Copyright © 2015 Elsevier Ltd. All rights reserved.

Muscle contributions to the acceleration of the whole body centre of mass during recovery from forward loss of balance by stepping in young and older adults.

PubMed

Graham, David F; Carty, Christopher P; Lloyd, David G; Barrett, Rod S

2017-01-01

The purpose of this study was to determine the muscular contributions to the acceleration of the whole body centre of mass (COM) of older compared to younger adults that were able to recover from forward loss of balance with a single step. Forward loss of balance was achieved by releasing participants (14 older adults and 6 younger adults) from a static whole-body forward lean angle of approximately 18 degrees. 10 older adults and 6 younger adults were able to recover with a single step and included in subsequent analysis. A scalable anatomical model consisting of 36 degrees-of-freedom was used to compute kinematics and joint moments from motion capture and force plate data. Forces for 92 muscle actuators were computed using Static Optimisation and Induced Acceleration Analysis was used to compute individual muscle contributions to the three-dimensional acceleration of the whole body COM. There were no significant differences between older and younger adults in step length, step time, 3D COM accelerations or muscle contributions to 3D COM accelerations. The stance and stepping leg Gastrocnemius and Soleus muscles were primarily responsible for the vertical acceleration experienced by the COM. The Gastrocnemius and Soleus from the stance side leg together with bilateral Hamstrings accelerated the COM forwards throughout balance recovery while the Vasti and Soleus of the stepping side leg provided the majority of braking accelerations following foot contact. The Hip Abductor muscles provided the greatest contribution to medial-lateral accelerations of the COM. Deficits in the neuromuscular control of the Gastrocnemius, Soleus, Vasti and Hip Abductors in particular could adversely influence balance recovery and may be important targets in interventions to improve balance recovery performance.

Muscle contributions to the acceleration of the whole body centre of mass during recovery from forward loss of balance by stepping in young and older adults

PubMed Central

Graham, David F.; Carty, Christopher P.; Lloyd, David G.

2017-01-01

The purpose of this study was to determine the muscular contributions to the acceleration of the whole body centre of mass (COM) of older compared to younger adults that were able to recover from forward loss of balance with a single step. Forward loss of balance was achieved by releasing participants (14 older adults and 6 younger adults) from a static whole-body forward lean angle of approximately 18 degrees. 10 older adults and 6 younger adults were able to recover with a single step and included in subsequent analysis. A scalable anatomical model consisting of 36 degrees-of-freedom was used to compute kinematics and joint moments from motion capture and force plate data. Forces for 92 muscle actuators were computed using Static Optimisation and Induced Acceleration Analysis was used to compute individual muscle contributions to the three-dimensional acceleration of the whole body COM. There were no significant differences between older and younger adults in step length, step time, 3D COM accelerations or muscle contributions to 3D COM accelerations. The stance and stepping leg Gastrocnemius and Soleus muscles were primarily responsible for the vertical acceleration experienced by the COM. The Gastrocnemius and Soleus from the stance side leg together with bilateral Hamstrings accelerated the COM forwards throughout balance recovery while the Vasti and Soleus of the stepping side leg provided the majority of braking accelerations following foot contact. The Hip Abductor muscles provided the greatest contribution to medial-lateral accelerations of the COM. Deficits in the neuromuscular control of the Gastrocnemius, Soleus, Vasti and Hip Abductors in particular could adversely influence balance recovery and may be important targets in interventions to improve balance recovery performance. PMID:29069097

On the upscaling of process-based models in deltaic applications

NASA Astrophysics Data System (ADS)

Li, L.; Storms, J. E. A.; Walstra, D. J. R.

2018-03-01

Process-based numerical models are increasingly used to study the evolution of marine and terrestrial depositional environments. Whilst a detailed description of small-scale processes provides an accurate representation of reality, application on geological timescales is restrained by the associated increase in computational time. In order to reduce the computational time, a number of acceleration methods are combined and evaluated for a schematic supply-driven delta (static base level) and an accommodation-driven delta (variable base level). The performance of the combined acceleration methods is evaluated by comparing the morphological indicators such as distributary channel networking and delta volumes derived from the model predictions for various levels of acceleration. The results of the accelerated models are compared to the outcomes from a series of simulations to capture autogenic variability. Autogenic variability is quantified by re-running identical models on an initial bathymetry with 1 cm added noise. The overall results show that the variability of the accelerated models fall within the autogenic variability range, suggesting that the application of acceleration methods does not significantly affect the simulated delta evolution. The Time-scale compression method (the acceleration method introduced in this paper) results in an increased computational efficiency of 75% without adversely affecting the simulated delta evolution compared to a base case. The combination of the Time-scale compression method with the existing acceleration methods has the potential to extend the application range of process-based models towards geologic timescales.

Preface: SciDAC 2007

NASA Astrophysics Data System (ADS)

Keyes, David E.

2007-09-01

It takes a village to perform a petascale computation—domain scientists, applied mathematicians, computer scientists, computer system vendors, program managers, and support staff—and the village was assembled during 24-28 June 2007 in Boston's Westin Copley Place for the third annual Scientific Discovery through Advanced Computing (SciDAC) 2007 Conference. Over 300 registered participants networked around 76 posters, focused on achievements and challenges in 36 plenary talks, and brainstormed in two panels. In addition, with an eye to spreading the vision for simulation at the petascale and to growing the workforce, 115 participants—mostly doctoral students and post-docs complementary to the conferees—were gathered on 29 June 2007 in classrooms of the Massachusetts Institute of Technology for a full day of tutorials on the use of SciDAC software. Eleven SciDAC-sponsored research groups presented their software at an introductory level, in both lecture and hands-on formats that included live runs on a local BlueGene/L. Computation has always been about garnering insight into the behavior of systems too complex to explore satisfactorily by theoretical means alone. Today, however, computation is about much more: scientists and decision makers expect quantitatively reliable predictions from simulations ranging in scale from that of the Earth's climate, down to quarks, and out to colliding black holes. Predictive simulation lies at the heart of policy choices in energy and environment affecting billions of lives and expenditures of trillions of dollars. It is also at the heart of scientific debates on the nature of matter and the origin of the universe. The petascale is barely adequate for such demands and we are barely established at the levels of resolution and throughput that this new scale of computation affords. However, no scientific agenda worldwide is pushing the petascale frontier on all its fronts as vigorously as SciDAC. The breadth of this conference archive reflects the philosophy of the SciDAC program, which was introduced as a collaboration of all of the program offices in the Office of Science of the U.S. Department of Energy (DOE) in Fall 2001 and was renewed for a second period of five years in Fall 2006, with additional support in certain areas from the DOE's National Nuclear Security Administration (NNSA) and the U.S. National Science Foundation (NSF). All of the projects in the SciDAC portfolio were represented at the conference and most are captured in this volume. In addition, the Organizing Committee incorporated into the technical program a number of computational science highlights from outside of SciDAC, and, indeed, from outside of the United States. As implied by the title, scientific discovery is the driving deliverable of the SciDAC program, spanning the full range of the DOE Office of Science: accelerator design, astrophysics, chemistry and materials science, climate science, combustion, life science, nuclear physics, plasma physics, and subsurface physics. As articulated in the eponymous report that launched SciDAC, the computational challenges of these diverse areas are remarkably common. Each is profoundly multiscale in space and time and therefore continues to benefit at any margin from access to the largest and fastest computers available. Optimality of representation and execution requires adaptive, scalable mathematical algorithms in both continuous (geometrically complex domain) and discrete (mesh and graph) aspects. Programmability and performance optimality require software environments that both manage the intricate details of the underlying hardware and abstract them for scientific users. Running effectively on remote specialized hardware requires transparent workflow systems. Comprehending the petascale data sets generated in such simulations requires automated tools for data exploration and visualization. Archiving and sharing access to this data within the inevitably distributed community of leading scientists requires networked collaborative environments. Each of these elements is a research and development project in its own right. SciDAC does not replace theoretical programs oriented towards long-term basic research, but harvests them for contemporary, complementary state-of-the-art computational campaigns. By clustering researchers from applications and enabling technologies into coordinated, mission-driven projects, SciDAC accomplishes two ends with remarkable effectiveness: (1) it enriches the scientific perspective of both applications and enabling communities through mutual interaction and (2) it leverages between applications solutions and effort encapsulated in software. Though SciDAC is unique, its objective of multiscale science at extreme computational scale is shared and approached through different programmatic mechanisms, notably NNSA's ASC program, NSF's Cyberinfrastructure program, and DoD's CREATE program in the U.S., and RIKEN's computational simulation programs in Japan. Representatives of each of these programs were given the podium at SciDAC 2007 and communication occurred that will be valuable towards the ends of complementarity, leverage, and promulgation of best practices. The 2007 conference was graced with additional welcome program announcements. Michael Strayer announced a new program of postdoctoral research fellowships in the enabling technologies. (The computer science post-docs will be named after the late Professor Ken Kennedy, who briefly led the SciDAC project Center for Scalable Application Development Software (CScADS) until his untimely death in February 2007.) IBM announced its petascale BlueGene/P system on June 26. Meanwhile, at ISC07 in Dresden, the semi-annual posting of a revised Top 500 list on June 27 showed several new Top 10 systems accessible to various SciDAC participants. While SciDAC is dominated in 2007 by the classical scientific pursuit of understanding through reduction to components and isolation of causes and effects, simulation at scale is beginning to offer something even more tantalizing: synthesis and integration of multiple interacting phenomena in complex systems. Indeed, the design-oriented elements of SciDAC, such as accelerator and tokamak modeling, area already emphasizing multiphysics coupling, and climate science has been doing so for years in the coupling of models of the ocean, atmosphere, ice, and land. In one of the panels at SciDAC 2007, leaders of a three-stage `progressive workshop' on exascale simulation for energy and environment (E3), considered prospects for whole-system modeling in a variety of scientific areas within the domain of DOE related to energy, environmental, and global security. Computer vendors were invited to comment on the prospects for delivering exascale computing systems in another panel. The daunting nature of this challenge is summarized with the observation that the peak processing power of the entire Top 500 list of June 2007 is only 0.0052 exaflop/s. It takes the combined power of most of the computers on the internet today worldwide to reach 1 exaflop/s or 1018 floating point operations per second. The program of SciDAC 2007 followed a template honed by its predecessor meetings in San Francisco in 2005 and Denver in 2006. The Boston venue permitted outreach to a number of universities in the immediate region and throughout southern New England, including SciDAC campuses of Boston University, Harvard, and MIT, and a dozen others including most of the Ivy League. Altogether 55 universities, 20 laboratories, 14 private companies, 5 agencies, and 4 countries were represented among the conference and tutorial workshop participants. Approximately 47% of the conference participants were from government laboratories, 37% from universities, 9% from federal program offices, and 7% from industry. Keys to the success of SciDAC 2007 were the informal poster receptions, coffee breaks, working breakfasts and lunches, and even the `Right-brain Night' featuring artistic statements, both reverent and irreverent, by computational scientists, inspired by their work. The organizers thank the sponsors for their generosity in attracting participants to these informal occasions with sumptuous snacks and beverages: AMD, Cray, DataDirect, IBM, SGI, SiCortex, and the Institute of Physics. A conference as logistically complex as SciDAC 2007 cannot possibly and should not be executed primarily by the scientists, themselves. It is a great pleasure to acknowledge the many talented staff that contributed to a productive time for all participants and nearperfect adherence to schedule. Chief among them is Betsy Riley, currently detailed from ORNL to the program office in Germantown, with degrees in mathematics and computer science, but a passion for organizing interdisciplinary scientific programs. Betsy staffed the organizing committee during the year of telecon meetings leading up to the conference and masterminded sponsorship, invitations, and the compilation of the proceedings. Assisting her from ORNL in managing the program were Daniel Pack, Angela Beach, and Angela Fincher. Cynthia Latham of ORNL performed admirably in website and graphic design for all aspects of the online and printed materials of the meeting. John Bui, John Smith, and Missy Smith of ORNL ran their customary tight ship with respect to audio-visual execution and capture, assisted by Eric Ecklund and Keith Quinn of the Westin. Pamelia Nixon-Hartje of Ambassador Services was personally invaluable in getting the most out of the hotel and its staff. We thank Jeff Nichols of ORNL for managing the primary subcontract for the meeting. The SciDAC tutorial program was a joint effort of Professor John Negele of MIT, David Skinner, PI of the SciDAC Outreach Center, and the SciDAC 2007 Chair. Sponsorship from the Outreach Center in the form of travel scholarships for students, and of the local area SciDAC university delegation of BU, Harvard, and MIT for food and facilities is gratefully acknowledged. Of course, the archival success of a scientific meeting rests with the willingness of the presenters to make the extra effort to package their field-leading science in a form suitable for interaction with colleagues from other disciplines rather than fellow specialists. This goal, oft-stated in the run up to the meeting, was achieved to an admirable degree, both in the live presentations and in these proceedings. This effort is its own reward, since it leads to enhanced communication and accelerated scientific progress. Our greatest thanks are reserved for Michael Strayer, Associate Director for OASCR and the Director of SciDAC, for envisioning this celebratory meeting three years ago, and sustaining it with his own enthusiasm, in order to provide a highly visible manifestation of the fruits of SciDAC. He and the other Office of Science program managers in attendance and working in Washington, DC to communicate the opportunities afforded by SciDAC deserve the gratitude of a new virtual scientific village created and cemented under the vision of scientific discovery through advanced computing. David E Keyes Fu Foundation Professor of Applied Mathematics

Unsteady Aerodynamic Force Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2016-01-01

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm. A cantilevered rectangular wing built and tested at the NASA Langley Research Center (Hampton, Virginia, USA) in 1959 is used to validate the simple approach. Unsteady aerodynamic forces as well as wing deflections, velocities, accelerations, and strains are computed using the CFL3D computational fluid dynamics (CFD) code and an MSC/NASTRAN code (MSC Software Corporation, Newport Beach, California, USA), and these CFL3D-based results are assumed as measured quantities. Based on the measured strains, wing deflections, velocities, accelerations, and aerodynamic forces are computed using the proposed approach. These computed deflections, velocities, accelerations, and unsteady aerodynamic forces are compared with the CFL3D/NASTRAN-based results. In general, computed aerodynamic forces based on the lifting surface theory in subsonic speeds are in good agreement with the target aerodynamic forces generated using CFL3D code with the Euler equation. Excellent aeroelastic responses are obtained even with unsteady strain data under the signal to noise ratio of -9.8dB. The deflections, velocities, and accelerations at each sensor location are independent of structural and aerodynamic models. Therefore, the distributed strain data together with the current proposed approaches can be used as distributed deflection, velocity, and acceleration sensors. This research demonstrates the feasibility of obtaining induced drag and lift forces through the use of distributed sensor technology with measured strain data. An active induced drag control system thus can be designed using the two computed aerodynamic forces, induced drag and lift, to improve the fuel efficiency of an aircraft. Interpolation elements between structural finite element grids and the CFD grids and centroids are successfully incorporated with the unsteady aeroelastic computation scheme. The most critical technology for the success of the proposed approach is the robust on-line parameter estimator, since the least-squares curve fitting method depends heavily on aeroelastic system frequencies and damping factors.

MeV electron acceleration at 1 kHz with <10 mJ laser pulses

NASA Astrophysics Data System (ADS)

Salehi, Fatholah; Goers, Andy; Hine, George; Feder, Linus; Kuk, Donghoon; Miao, Bo; Woodbury, Daniel; Kim, Ki-Yong; Milchberg, Howard

2017-01-01

We demonstrate laser driven acceleration of electrons to MeV-scale energies at 1 kHz repetition rate using <10 mJ pulses focused on near-critical density He and H2 gas jets. Using the H2 gas jet, electron acceleration to 0.5 MeV in 10 fC bunches was observed with laser pulse energy as low as 1.3 mJ. Increasing the pulse energy to 10 mJ, we measure 1pC charge bunches with >1 MeV energy for both He and H gas jets. Such a high repetition rate, high flux ultrafast source has immediate application to time resolved probing of matter for scientific, medical, or security applications, either using the electrons directly or using a high-Z foil converter to generate ultrafast γ-rays. This work is supported by the US Department of Energy, the National Science Foundation, and the Air Force Office of Scientific Research.

Particle Identification on an FPGA Accelerated Compute Platform for the LHCb Upgrade

NASA Astrophysics Data System (ADS)

Fäerber, Christian; Schwemmer, Rainer; Machen, Jonathan; Neufeld, Niko

2017-07-01

The current LHCb readout system will be upgraded in 2018 to a “triggerless” readout of the entire detector at the Large Hadron Collider collision rate of 40 MHz. The corresponding bandwidth from the detector down to the foreseen dedicated computing farm (event filter farm), which acts as the trigger, has to be increased by a factor of almost 100 from currently 500 Gb/s up to 40 Tb/s. The event filter farm will preanalyze the data and will select the events on an event by event basis. This will reduce the bandwidth down to a manageable size to write the interesting physics data to tape. The design of such a system is a challenging task, and the reason why different new technologies are considered and have to be investigated for the different parts of the system. For the usage in the event building farm or in the event filter farm (trigger), an experimental field programmable gate array (FPGA) accelerated computing platform is considered and, therefore, tested. FPGA compute accelerators are used more and more in standard servers such as for Microsoft Bing search or Baidu search. The platform we use hosts a general Intel CPU and a high-performance FPGA linked via the high-speed Intel QuickPath Interconnect. An accelerator is implemented on the FPGA. It is very likely that these platforms, which are built, in general, for high-performance computing, are also very interesting for the high-energy physics community. First, the performance results of smaller test cases performed at the beginning are presented. Afterward, a part of the existing LHCb RICH particle identification is tested and is ported to the experimental FPGA accelerated platform. We have compared the performance of the LHCb RICH particle identification running on a normal CPU with the performance of the same algorithm, which is running on the Xeon-FPGA compute accelerator platform.

Optimizations of Human Restraint Systems for Short-Period Acceleration

NASA Technical Reports Server (NTRS)

Payne, P. R.

1963-01-01

A restraint system's main function is to restrain its occupant when his vehicle is subjected to acceleration. If the restraint system is rigid and well-fitting (to eliminate slack) then it will transmit the vehicle acceleration to its occupant without modifying it in any way. Few present-day restraint systems are stiff enough to give this one-to-one transmission characteristic, and depending upon their dynamic characteristics and the nature of the vehicle's acceleration-time history, they will either magnify or attenuate the acceleration. Obviously an optimum restraint system will give maximum attenuation of an input acceleration. In the general case of an arbitrary acceleration input, a computer must be used to determine the optimum dynamic characteristics for the restraint system. Analytical solutions can be obtained for certain simple cases, however, and these cases are considered in this paper, after the concept of dynamic models of the human body is introduced. The paper concludes with a description of an analog computer specially developed for the Air Force to handle completely general mechanical restraint optimization programs of this type, where the acceleration input may be any arbitrary function of time.

Scientific Inquiry Self-Efficacy and Computer Game Self-Efficacy as Predictors and Outcomes of Middle School Boys' and Girls' Performance in a Science Assessment in a Virtual Environment

NASA Astrophysics Data System (ADS)

Bergey, Bradley W.; Ketelhut, Diane Jass; Liang, Senfeng; Natarajan, Uma; Karakus, Melissa

2015-10-01

The primary aim of the study was to examine whether performance on a science assessment in an immersive virtual environment was associated with changes in scientific inquiry self-efficacy. A secondary aim of the study was to examine whether performance on the science assessment was equitable for students with different levels of computer game self-efficacy, including whether gender differences were observed. We examined 407 middle school students' scientific inquiry self-efficacy and computer game self-efficacy before and after completing a computer game-like assessment about a science mystery. Results from path analyses indicated that prior scientific inquiry self-efficacy predicted achievement on end-of-module questions, which in turn predicted change in scientific inquiry self-efficacy. By contrast, computer game self-efficacy was neither predictive of nor predicted by performance on the science assessment. While boys had higher computer game self-efficacy compared to girls, multi-group analyses suggested only minor gender differences in how efficacy beliefs related to performance. Implications for assessments with virtual environments and future design and research are discussed.

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

Hules, John

This 1998 annual report from the National Scientific Energy Research Computing Center (NERSC) presents the year in review of the following categories: Computational Science; Computer Science and Applied Mathematics; and Systems and Services. Also presented are science highlights in the following categories: Basic Energy Sciences; Biological and Environmental Research; Fusion Energy Sciences; High Energy and Nuclear Physics; and Advanced Scientific Computing Research and Other Projects.

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond

PubMed Central

Gama-Castro, Socorro; Salgado, Heladia; Santos-Zavaleta, Alberto; Ledezma-Tejeida, Daniela; Muñiz-Rascado, Luis; García-Sotelo, Jair Santiago; Alquicira-Hernández, Kevin; Martínez-Flores, Irma; Pannier, Lucia; Castro-Mondragón, Jaime Abraham; Medina-Rivera, Alejandra; Solano-Lira, Hilda; Bonavides-Martínez, César; Pérez-Rueda, Ernesto; Alquicira-Hernández, Shirley; Porrón-Sotelo, Liliana; López-Fuentes, Alejandra; Hernández-Koutoucheva, Anastasia; Moral-Chávez, Víctor Del; Rinaldi, Fabio; Collado-Vides, Julio

2016-01-01

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for ‘neighborhood’ genes to known operons and regulons, and computational developments. PMID:26527724

Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

ERIC Educational Resources Information Center

Wolf, Michael Maclean

2009-01-01

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

The Versatile Terminal.

ERIC Educational Resources Information Center

Evans, C. D.

This paper describes the experiences of the industrial research laboratory of Kodak Ltd. in finding and providing a computer terminal most suited to its very varied requirements. These requirements include bibliographic and scientific data searching and access to a number of worldwide computing services for scientific computing work. The provision…

Deep learning for computational chemistry.

PubMed

Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

2017-06-15

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A redshift survey of IRAS galaxies. V - The acceleration on the Local Group

NASA Technical Reports Server (NTRS)

Strauss, Michael A.; Yahil, Amos; Davis, Marc; Huchra, John P.; Fisher, Karl

1992-01-01

The acceleration on the Local Group is calculated based on a full-sky redshift survey of 5288 galaxies detected by IRAS. A formalism is developed to compute the distribution function of the IRAS acceleration for a given power spectrum of initial perturbations. The computed acceleration on the Local Group points 18-28 deg from the direction of the Local Group peculiar velocity vector. The data suggest that the CMB dipole is indeed due to the motion of the Local Group, that this motion is gravitationally induced, and that the distribution of IRAS galaxies on large scales is related to that of dark matter by a simple linear biasing model.

Correlated histogram representation of Monte Carlo derived medical accelerator photon-output phase space

DOEpatents

Schach Von Wittenau, Alexis E.

2003-01-01

A method is provided to represent the calculated phase space of photons emanating from medical accelerators used in photon teletherapy. The method reproduces the energy distributions and trajectories of the photons originating in the bremsstrahlung target and of photons scattered by components within the accelerator head. The method reproduces the energy and directional information from sources up to several centimeters in radial extent, so it is expected to generalize well to accelerators made by different manufacturers. The method is computationally both fast and efficient overall sampling efficiency of 80% or higher for most field sizes. The computational cost is independent of the number of beams used in the treatment plan.

Processing of Swarm Accelerometer Data into Thermospheric Neutral Densities

NASA Astrophysics Data System (ADS)

Doornbos, E.; Siemes, C.; Encarnacao, J.; Peřestý, R.; Grunwaldt, L.; Kraus, J.; Holmdahl Olsen, P. E.; van den IJssel, J.; Flury, J.; Apelbaum, G.

2015-12-01

The Swarm satellites were launched on 22 November 2013 and carry accelerometers and GPS receivers as part of their scientific payload. The GPS receivers are not only used for locating the position and time of the magnetic measurements, but also for determining non-gravitational forces like drag and radiation pressure acting on the spacecraft. The accelerometers measure these forces directly, at much finer resolution than the GPS receivers, from which thermospheric neutral densities and potentially winds can be derived. Unfortunately, the acceleration measurements suffer from a variety of disturbances, the most prominent being slow temperature-induced bias variations and sudden bias changes. These disturbances have caused a significant delay of the accelerometer data release. In this presentation, we describe the new three-stage processing that is required for transforming the disturbed acceleration measurements into scientifically valuable thermospheric neutral densities. In the first stage, the sudden bias changes in the acceleration measurements are removed using a dedicated software tool. The second stage is the calibration of the accelerometer measurements against the non-gravitational accelerations derived from the GPS receiver, which includes the correction for the slow temperature-induced bias variations. The third stage consists of transforming the corrected and calibrated accelerations into thermospheric neutral densities. We describe the methods used in each stage, highlight the difficulties encountered, and comment on the quality of the thermospheric neutral density data set, which covers the geomagnetic storm on 17 March 2015.

Accelerating Astronomy & Astrophysics in the New Era of Parallel Computing: GPUs, Phi and Cloud Computing

NASA Astrophysics Data System (ADS)

Ford, Eric B.; Dindar, Saleh; Peters, Jorg

2015-08-01

The realism of astrophysical simulations and statistical analyses of astronomical data are set by the available computational resources. Thus, astronomers and astrophysicists are constantly pushing the limits of computational capabilities. For decades, astronomers benefited from massive improvements in computational power that were driven primarily by increasing clock speeds and required relatively little attention to details of the computational hardware. For nearly a decade, increases in computational capabilities have come primarily from increasing the degree of parallelism, rather than increasing clock speeds. Further increases in computational capabilities will likely be led by many-core architectures such as Graphical Processing Units (GPUs) and Intel Xeon Phi. Successfully harnessing these new architectures, requires significantly more understanding of the hardware architecture, cache hierarchy, compiler capabilities and network network characteristics.I will provide an astronomer's overview of the opportunities and challenges provided by modern many-core architectures and elastic cloud computing. The primary goal is to help an astronomical audience understand what types of problems are likely to yield more than order of magnitude speed-ups and which problems are unlikely to parallelize sufficiently efficiently to be worth the development time and/or costs.I will draw on my experience leading a team in developing the Swarm-NG library for parallel integration of large ensembles of small n-body systems on GPUs, as well as several smaller software projects. I will share lessons learned from collaborating with computer scientists, including both technical and soft skills. Finally, I will discuss the challenges of training the next generation of astronomers to be proficient in this new era of high-performance computing, drawing on experience teaching a graduate class on High-Performance Scientific Computing for Astrophysics and organizing a 2014 advanced summer school on Bayesian Computing for Astronomical Data Analysis with support of the Penn State Center for Astrostatistics and Institute for CyberScience.

Amplify scientific discovery with artificial intelligence

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

Gil, Yolanda; Greaves, Mark T.; Hendler, James

Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automatedmore » language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.« less

A distributed computing environment with support for constraint-based task scheduling and scientific experimentation

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

Ahrens, J.P.; Shapiro, L.G.; Tanimoto, S.L.

1997-04-01

This paper describes a computing environment which supports computer-based scientific research work. Key features include support for automatic distributed scheduling and execution and computer-based scientific experimentation. A new flexible and extensible scheduling technique that is responsive to a user`s scheduling constraints, such as the ordering of program results and the specification of task assignments and processor utilization levels, is presented. An easy-to-use constraint language for specifying scheduling constraints, based on the relational database query language SQL, is described along with a search-based algorithm for fulfilling these constraints. A set of performance studies show that the environment can schedule and executemore » program graphs on a network of workstations as the user requests. A method for automatically generating computer-based scientific experiments is described. Experiments provide a concise method of specifying a large collection of parameterized program executions. The environment achieved significant speedups when executing experiments; for a large collection of scientific experiments an average speedup of 3.4 on an average of 5.5 scheduled processors was obtained.« less

Initial characterization of the microgravity environment of the international space station: increments 2 through 4

NASA Technical Reports Server (NTRS)

Jules, Kenol; McPherson, Kevin; Hrovat, Kenneth; Kelly, Eric

2004-01-01

The primary objective of the International Space Station (ISS) is to provide a long-term quiescent environment for the conduct of scientific research for a variety of microgravity science disciplines. This paper reports to the microgravity scientific community the results of an initial characterization of the microgravity environment on the International Space Station for increments 2 through 4. During that period almost 70,000 hours of station operations and scientific experiments were conducted. 720 hours of crew research time were logged aboard the orbiting laboratory and over half a terabyte of acceleration data were recorded and much of that was analyzed. The results discussed in this paper cover both the quasi-steady and vibratory acceleration environment of the station during its first year of scientific operation. For the quasi-steady environment, results are presented and discussed for the following: the space station attitudes Torque Equilibrium Attitude and the X-Axis Perpendicular to the Orbital Plane; station docking attitude maneuvers; Space Shuttle joint operation with the station; cabin de-pressurizations and the station water dumps. For the vibratory environment, results are presented for the following: crew exercise, docking events, and the activation/de-activation of both station life support system hardware and experiment hardware. Finally, a grand summary of all the data collected aboard the station during the 1-year period is presented showing where the overall quasi-steady and vibratory acceleration magnitude levels fall over that period of time using a 95th percentile benchmark. Published by Elsevier Ltd.

Large-Scale Calculations for Material Sciences Using Accelerators to Improve Time- and Energy-to-Solution

DOE PAGES

Eisenbach, Markus

2017-01-01

A major impediment to deploying next-generation high-performance computational systems is the required electrical power, often measured in units of megawatts. The solution to this problem is driving the introduction of novel machine architectures, such as those employing many-core processors and specialized accelerators. In this article, we describe the use of a hybrid accelerated architecture to achieve both reduced time to solution and the associated reduction in the electrical cost for a state-of-the-art materials science computation.

Hardware accelerated high performance neutron transport computation based on AGENT methodology

NASA Astrophysics Data System (ADS)

Xiao, Shanjie

The spatial heterogeneity of the next generation Gen-IV nuclear reactor core designs brings challenges to the neutron transport analysis. The Arbitrary Geometry Neutron Transport (AGENT) AGENT code is a three-dimensional neutron transport analysis code being developed at the Laboratory for Neutronics and Geometry Computation (NEGE) at Purdue University. It can accurately describe the spatial heterogeneity in a hierarchical structure through the R-function solid modeler. The previous version of AGENT coupled the 2D transport MOC solver and the 1D diffusion NEM solver to solve the three dimensional Boltzmann transport equation. In this research, the 2D/1D coupling methodology was expanded to couple two transport solvers, the radial 2D MOC solver and the axial 1D MOC solver, for better accuracy. The expansion was benchmarked with the widely applied C5G7 benchmark models and two fast breeder reactor models, and showed good agreement with the reference Monte Carlo results. In practice, the accurate neutron transport analysis for a full reactor core is still time-consuming and thus limits its application. Therefore, another content of my research is focused on designing a specific hardware based on the reconfigurable computing technique in order to accelerate AGENT computations. It is the first time that the application of this type is used to the reactor physics and neutron transport for reactor design. The most time consuming part of the AGENT algorithm was identified. Moreover, the architecture of the AGENT acceleration system was designed based on the analysis. Through the parallel computation on the specially designed, highly efficient architecture, the acceleration design on FPGA acquires high performance at the much lower working frequency than CPUs. The whole design simulations show that the acceleration design would be able to speedup large scale AGENT computations about 20 times. The high performance AGENT acceleration system will drastically shortening the computation time for 3D full-core neutron transport analysis, making the AGENT methodology unique and advantageous, and thus supplies the possibility to extend the application range of neutron transport analysis in either industry engineering or academic research.

MALVAC 2012 scientific forum: accelerating development of second-generation malaria vaccines

PubMed Central

2012-01-01

The World Health Organization (WHO) convened a malaria vaccines committee (MALVAC) scientific forum from 20 to 21 February 2012 in Geneva, Switzerland, to review the global malaria vaccine portfolio, to gain consensus on approaches to accelerate second-generation malaria vaccine development, and to discuss the need to update the vision and strategic goal of the Malaria Vaccine Technology Roadmap. This article summarizes the forum, which included reviews of leading Plasmodium falciparum vaccine candidates for pre-erythrocytic vaccines, blood-stage vaccines, and transmission-blocking vaccines. Other major topics included vaccine candidates against Plasmodium vivax, clinical trial site capacity development in Africa, trial design considerations for a second-generation malaria vaccine, adjuvant selection, and regulatory oversight functions including vaccine licensure. PMID:23140365

Experiences with Deriva: An Asset Management Platform for Accelerating eScience.

PubMed

Bugacov, Alejandro; Czajkowski, Karl; Kesselman, Carl; Kumar, Anoop; Schuler, Robert E; Tangmunarunkit, Hongsuda

2017-10-01

The pace of discovery in eScience is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. It is all too common for investigators to spend inordinate amounts of time developing ad hoc procedures to manage their data. In previous work, we presented Deriva, a Scientific Asset Management System, designed to accelerate data driven discovery. In this paper, we report on the use of Deriva in a number of substantial and diverse eScience applications. We describe the lessons we have learned, both from the perspective of the Deriva technology, as well as the ability and willingness of scientists to incorporate Scientific Asset Management into their daily workflows.

Computer-Supported Aids to Making Sense of Scientific Articles: Cognitive, Motivational, and Attitudinal Effects

ERIC Educational Resources Information Center

Gegner, Julie A.; Mackay, Donald H. J.; Mayer, Richard E.

2009-01-01

High school students can access original scientific research articles on the Internet, but may have trouble understanding them. To address this problem of online literacy, the authors developed a computer-based prototype for guiding students' comprehension of scientific articles. High school students were asked to read an original scientific…

Scientific Computing for Chemists: An Undergraduate Course in Simulations, Data Processing, and Visualization

ERIC Educational Resources Information Center

Weiss, Charles J.

2017-01-01

The Scientific Computing for Chemists course taught at Wabash College teaches chemistry students to use the Python programming language, Jupyter notebooks, and a number of common Python scientific libraries to process, analyze, and visualize data. Assuming no prior programming experience, the course introduces students to basic programming and…

Computational chemistry in pharmaceutical research: at the crossroads.

PubMed

Bajorath, Jürgen

2012-01-01

Computational approaches are an integral part of pharmaceutical research. However, there are many of unsolved key questions that limit the scientific progress in the still evolving computational field and its impact on drug discovery. Importantly, a number of these questions are not new but date back many years. Hence, it might be difficult to conclusively answer them in the foreseeable future. Moreover, the computational field as a whole is characterized by a high degree of heterogeneity and so is, unfortunately, the quality of its scientific output. In light of this situation, it is proposed that changes in scientific standards and culture should be seriously considered now in order to lay a foundation for future progress in computational research.

[Earth and Space Sciences Project Services for NASA HPCC

NASA Technical Reports Server (NTRS)

Merkey, Phillip

2002-01-01

This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

Scholarly literature and the press: scientific impact and social perception of physics computing

NASA Astrophysics Data System (ADS)

Pia, M. G.; Basaglia, T.; Bell, Z. W.; Dressendorfer, P. V.

2014-06-01

The broad coverage of the search for the Higgs boson in the mainstream media is a relative novelty for high energy physics (HEP) research, whose achievements have traditionally been limited to scholarly literature. This paper illustrates the results of a scientometric analysis of HEP computing in scientific literature, institutional media and the press, and a comparative overview of similar metrics concerning representative particle physics measurements. The picture emerging from these scientometric data documents the relationship between the scientific impact and the social perception of HEP physics research versus that of HEP computing. The results of this analysis suggest that improved communication of the scientific and social role of HEP computing via press releases from the major HEP laboratories would be beneficial to the high energy physics community.

Software Reuse Methods to Improve Technological Infrastructure for e-Science

NASA Technical Reports Server (NTRS)

Marshall, James J.; Downs, Robert R.; Mattmann, Chris A.

2011-01-01

Social computing has the potential to contribute to scientific research. Ongoing developments in information and communications technology improve capabilities for enabling scientific research, including research fostered by social computing capabilities. The recent emergence of e-Science practices has demonstrated the benefits from improvements in the technological infrastructure, or cyber-infrastructure, that has been developed to support science. Cloud computing is one example of this e-Science trend. Our own work in the area of software reuse offers methods that can be used to improve new technological development, including cloud computing capabilities, to support scientific research practices. In this paper, we focus on software reuse and its potential to contribute to the development and evaluation of information systems and related services designed to support new capabilities for conducting scientific research.

Recent Developments in Young-Earth Creationist Geology

NASA Astrophysics Data System (ADS)

Heaton, Timothy H.

2009-10-01

Young-earth creationism has undergone a shift in emphasis toward building of historical models that incorporate Biblical and scientific evidence and the acceptance of scientific conclusions that were formerly rejected. The RATE Group admitted that massive amounts of radioactive decay occurred during earth history but proposed a period of accelerated decay during Noah’s Flood to fit the resulting history into a young-earth timeframe. Finding a mechanism for the acceleration and dealing with the excessive heat and radiation it would generate posed major problems for the project. Catastrophic plate tectonics was proposed to explain continental movements in a short timeframe and serve as a trigger for Noah’s Flood, but other creationists rejected the idea citing hopeless chronological problems. Creationists have also sought to explain the order of the fossil record and the Ice Age in a young-earth timeframe. An examination of these efforts demonstrates the anti-scientific nature of using the Bible as a non-negotiable framework for earth history.

Advancing Water Science through Improved Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Koch, B. J.; Miles, B.; Rai, A.; Ahalt, S.; Band, L. E.; Minsker, B.; Palmer, M.; Williams, M. R.; Idaszak, R.; Whitton, M. C.

2012-12-01

Major scientific advances are needed to help address impacts of climate change and increasing human-mediated environmental modification on the water cycle at global and local scales. However, such advances within the water sciences are limited in part by inadequate information infrastructures. For example, cyberinfrastructure (CI) includes the integrated computer hardware, software, networks, sensors, data, and human capital that enable scientific workflows to be carried out within and among individual research efforts and across varied disciplines. A coordinated transformation of existing CI and development of new CI could accelerate the productivity of water science by enabling greater discovery, access, and interoperability of data and models, and by freeing scientists to do science rather than create and manage technological tools. To elucidate specific ways in which improved CI could advance water science, three challenges confronting the water science community were evaluated: 1) How does ecohydrologic patch structure affect nitrogen transport and fate in watersheds?, 2) How can human-modified environments emulate natural water and nutrient cycling to enhance both human and ecosystem well-being?, 3) How do changes in climate affect water availability to support biodiversity and human needs? We assessed the approaches used by researchers to address components of these challenges, identified barriers imposed by limitations of current CI, and interviewed leaders in various water science subdisciplines to determine the most recent CI tools employed. Our preliminary findings revealed four areas where CI improvements are likely to stimulate scientific advances: 1) sensor networks, 2) data quality assurance/quality control, 3) data and modeling standards, 4) high performance computing. In addition, the full potential of a re-envisioned water science CI cannot be realized without a substantial training component. In light of these findings, we suggest that CI industry-proven practices such as open-source community architecture, agile development methodologies, and sound software engineering methods offer a promising pathway to a transformed water science CI capable of meeting the demands of both individual scientists and community-wide research initiatives.

Multidimensional Environmental Data Resource Brokering on Computational Grids and Scientific Clouds

NASA Astrophysics Data System (ADS)

Montella, Raffaele; Giunta, Giulio; Laccetti, Giuliano

Grid computing has widely evolved over the past years, and its capabilities have found their way even into business products and are no longer relegated to scientific applications. Today, grid computing technology is not restricted to a set of specific grid open source or industrial products, but rather it is comprised of a set of capabilities virtually within any kind of software to create shared and highly collaborative production environments. These environments are focused on computational (workload) capabilities and the integration of information (data) into those computational capabilities. An active grid computing application field is the fully virtualization of scientific instruments in order to increase their availability and decrease operational and maintaining costs. Computational and information grids allow to manage real-world objects in a service-oriented way using industrial world-spread standards.

78 FR 6087 - Advanced Scientific Computing Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-29

... INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building... Theory and Experiment (INCITE) Public Comment (10-minute rule) Public Participation: The meeting is open...

Computational Science in Armenia (Invited Talk)

NASA Astrophysics Data System (ADS)

Marandjian, H.; Shoukourian, Yu.

This survey is devoted to the development of informatics and computer science in Armenia. The results in theoretical computer science (algebraic models, solutions to systems of general form recursive equations, the methods of coding theory, pattern recognition and image processing), constitute the theoretical basis for developing problem-solving-oriented environments. As examples can be mentioned: a synthesizer of optimized distributed recursive programs, software tools for cluster-oriented implementations of two-dimensional cellular automata, a grid-aware web interface with advanced service trading for linear algebra calculations. In the direction of solving scientific problems that require high-performance computing resources, examples of completed projects include the field of physics (parallel computing of complex quantum systems), astrophysics (Armenian virtual laboratory), biology (molecular dynamics study of human red blood cell membrane), meteorology (implementing and evaluating the Weather Research and Forecast Model for the territory of Armenia). The overview also notes that the Institute for Informatics and Automation Problems of the National Academy of Sciences of Armenia has established a scientific and educational infrastructure, uniting computing clusters of scientific and educational institutions of the country and provides the scientific community with access to local and international computational resources, that is a strong support for computational science in Armenia.

Research and development for electropolishing of Nb for ILC accelerator cavities

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

Kelley, Michael J.

The objectives of this project are to 1, Expand the scientific and technological understanding of the effect of post-treatment (electropolish, buffered chemical polish, low-temperature baking) on the surface of niobium; 2, Relate the knowledge to the performance of niobium superconducting radiofrequency accelerator cavities; and, 3, Thereby design and demonstrate an electropolish process that can be applied to complete cavities.

ATLAS with CARIBU: A laboratory portrait

DOE PAGES

Pardo, Richard C.; Savard, Guy; Janssens, Robert V. F.

2016-03-21

The Argonne Tandem Linac Accelerator System (ATLAS) is the world's first superconducting accelerator for projectiles heavier than the electron. This unique system is a U.S. Department of Energy (DOE) national user research facility open to scientists from all over the world. Here, it is located within the Physics Division at Argonne National Laboratory and is one of five large scientific user facilities located at the laboratory.

The Light Ion Pulsed Power Induction Accelerator for ETF

DTIC Science & Technology

1995-07-01

the technical development necessary to demonstrate scientific and engineering feasibility for fusion energy production with a reprated driver. In...order for ETF to be cost effective, the accelerator system must be able to drive several target chambers which will test various Inertial Fusion ... Energy (IFE) reactor technologies. We envision an elevator system positioning and removing multiple target chambers from the center area of the ion beam

Highly parallel computation

NASA Technical Reports Server (NTRS)

Denning, Peter J.; Tichy, Walter F.

1990-01-01

Highly parallel computing architectures are the only means to achieve the computation rates demanded by advanced scientific problems. A decade of research has demonstrated the feasibility of such machines and current research focuses on which architectures designated as multiple instruction multiple datastream (MIMD) and single instruction multiple datastream (SIMD) have produced the best results to date; neither shows a decisive advantage for most near-homogeneous scientific problems. For scientific problems with many dissimilar parts, more speculative architectures such as neural networks or data flow may be needed.

78 FR 30930 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-23

... Panel; Small Business: Radiation Therapy and Biology. Date: June 18-19, 2013. Time: 9:00 a.m. to 8:00 p...: Accelerating the Pace of Drug Abuse Research Using Existing Data. Date: June 20, 2013. Time: 1:00 p.m. to 4:00...: Center for Scientific Review Special Emphasis Panel; PA-12-139: Pilot and Feasibility Clinical Research...

ASCR Cybersecurity for Scientific Computing Integrity - Research Pathways and Ideas Workshop

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

Peisert, Sean; Potok, Thomas E.; Jones, Todd

At the request of the U.S. Department of Energy's (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program office, a workshop was held June 2-3, 2015, in Gaithersburg, MD, to identify potential long term (10 to +20 year) cybersecurity fundamental basic research and development challenges, strategies and roadmap facing future high performance computing (HPC), networks, data centers, and extreme-scale scientific user facilities. This workshop was a follow-on to the workshop held January 7-9, 2015, in Rockville, MD, that examined higher level ideas about scientific computing integrity specific to the mission of the DOE Office of Science. Issues includedmore » research computation and simulation that takes place on ASCR computing facilities and networks, as well as network-connected scientific instruments, such as those run by various DOE Office of Science programs. Workshop participants included researchers and operational staff from DOE national laboratories, as well as academic researchers and industry experts. Participants were selected based on the submission of abstracts relating to the topics discussed in the previous workshop report [1] and also from other ASCR reports, including "Abstract Machine Models and Proxy Architectures for Exascale Computing" [27], the DOE "Preliminary Conceptual Design for an Exascale Computing Initiative" [28], and the January 2015 machine learning workshop [29]. The workshop was also attended by several observers from DOE and other government agencies. The workshop was divided into three topic areas: (1) Trustworthy Supercomputing, (2) Extreme-Scale Data, Knowledge, and Analytics for Understanding and Improving Cybersecurity, and (3) Trust within High-end Networking and Data Centers. Participants were divided into three corresponding teams based on the category of their abstracts. The workshop began with a series of talks from the program manager and workshop chair, followed by the leaders for each of the three topics and a representative of each of the four major DOE Office of Science Advanced Scientific Computing Research Facilities: the Argonne Leadership Computing Facility (ALCF), the Energy Sciences Network (ESnet), the National Energy Research Scientific Computing Center (NERSC), and the Oak Ridge Leadership Computing Facility (OLCF). The rest of the workshop consisted of topical breakout discussions and focused writing periods that produced much of this report.« less

CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

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

Miller, David; Agarwal, Deborah A.; Sun, Xin

2011-09-01

The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

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

Miller, D.; Agarwal, D.; Sun, X.

2011-01-01

The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

Accelerated Reader.

ERIC Educational Resources Information Center

Education Commission of the States, Denver, CO.

This paper provides an overview of Accelerated Reader, a system of computerized testing and record-keeping that supplements the regular classroom reading program. Accelerated Reader's primary goal is to increase literature-based reading practice. The program offers a computer-aided reading comprehension and management program intended to motivate…

Convergence acceleration of the Proteus computer code with multigrid methods

NASA Technical Reports Server (NTRS)

Demuren, A. O.; Ibraheem, S. O.

1992-01-01

Presented here is the first part of a study to implement convergence acceleration techniques based on the multigrid concept in the Proteus computer code. A review is given of previous studies on the implementation of multigrid methods in computer codes for compressible flow analysis. Also presented is a detailed stability analysis of upwind and central-difference based numerical schemes for solving the Euler and Navier-Stokes equations. Results are given of a convergence study of the Proteus code on computational grids of different sizes. The results presented here form the foundation for the implementation of multigrid methods in the Proteus code.

Building Cognition: The Construction of Computational Representations for Scientific Discovery

ERIC Educational Resources Information Center

Chandrasekharan, Sanjay; Nersessian, Nancy J.

2015-01-01

Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a…

DOE Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee Report on Scientific and Technical Information

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

Hey, Tony; Agarwal, Deborah; Borgman, Christine

The Advanced Scientific Computing Advisory Committee (ASCAC) was charged to form a standing subcommittee to review the Department of Energy’s Office of Scientific and Technical Information (OSTI) and to begin by assessing the quality and effectiveness of OSTI’s recent and current products and services and to comment on its mission and future directions in the rapidly changing environment for scientific publication and data. The Committee met with OSTI staff and reviewed available products, services and other materials. This report summaries their initial findings and recommendations.

A new IBA-AMS laboratory at the Comenius University in Bratislava (Slovakia)

NASA Astrophysics Data System (ADS)

Povinec, Pavel P.; Masarik, Jozef; Kúš, Peter; Holý, Karol; Ješkovský, Miroslav; Breier, Robert; Staníček, Jaroslav; Šivo, Alexander; Richtáriková, Marta; Kováčik, Andrej; Szarka, Ján; Steier, Peter; Priller, Alfred

2015-01-01

A Centre for Nuclear and Accelerator Technologies (CENTA) has been established at the Comenius University in Bratislava comprising of a tandem laboratory designed for Ion Beam Analysis (IBA), Ion Beam Modification (IBM) of materials and Accelerator Mass Spectrometry (AMS). The main equipment of the laboratory, i.e. Alphatross and MC-SNICS ion sources, 3 MV Pelletron tandem accelerator, and analyzers of accelerated ions are described. Optimization of ion beam characteristics for different ion sources with gas and solid targets, for transmission of accelerated ions with different energy and charge state, for different parameters of the high-energy ion analyzers, as well as first AMS results are presented. The scientific program of the CENTA will be devoted mainly to nuclear, environmental, life and material sciences.

Laboratory directed research and development fy1999 annual report

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

Al-Ayat, R A

2000-04-11

The Lawrence Livermore National Laboratory (LLNL) was founded in 1952 and has been managed since its inception by the University of California (UC) for the U.S. Department of Energy (DOE). Because of this long association with UC, the Laboratory has been able to recruit a world-class workforce, establish an atmosphere of intellectual freedom and innovation, and achieve recognition in relevant fields of knowledge as a scientific and technological leader. This environment and reputation are essential for sustained scientific and technical excellence. As a DOE national laboratory with about 7,000 employees, LLNL has an essential and compelling primary mission to ensuremore » that the nation's nuclear weapons remain safe, secure, and reliable and to prevent the spread and use of nuclear weapons worldwide. The Laboratory receives funding from the DOE Assistant Secretary for Defense Programs, whose focus is stewardship of our nuclear weapons stockpile. Funding is also provided by the Deputy Administrator for Defense Nuclear Nonproliferation, many Department of Defense sponsors, other federal agencies, and the private sector. As a multidisciplinary laboratory, LLNL has applied its considerable skills in high-performance computing, advanced engineering, and the management of large research and development projects to become the science and technology leader in those areas of its mission responsibility. The Laboratory Directed Research and Development (LDRD) Program was authorized by the U.S. Congress in 1984. The Program allows the Director of each DOE laboratory to fund advanced, creative, and innovative research and development (R&D) activities that will ensure scientific and technical vitality in the continually evolving mission areas at DOE and the Laboratory. In addition, the LDRD Program provides LLNL with the flexibility to nurture and enrich essential scientific and technical competencies, which attract the most qualified scientists and engineers. The LDRD Program also enables many collaborations with the scientific community in academia, national and international laboratories, and industry. The projects in the FY1999 LDRD portfolio were carefully selected to continue vigorous support of the strategic vision and the long-term goals of DOE and the Laboratory. Projects chosen for LDRD funding undergo stringent selection processes, which look for high-potential scientific return, emphasize strategic relevance, and feature technical peer reviews by external and internal experts. The FY1999 projects described in this annual report focus on supporting the Laboratory's national security needs: stewardship of the U.S. nuclear weapons stockpile, responsibility for the counter- and nonproliferation of weapons of mass destruction, development of high-performance computing, and support of DOE environmental research and waste management programs. In the past, LDRD investments have significantly enhanced LLNL scientific capabilities and greatly contributed to the Laboratory's ability to meet its national security programmatic requirements. Examples of past investments include technical precursors to the Accelerated Strategic Computing Initiative (ASCI), special-materials processing and characterization, and biodefense. Our analysis of the FY1999 portfolio shows that it strongly supports the Laboratory's national security mission. About 95% of the LDRD dollars have directly supported LLNL's national security activities in FY1999, which far exceeds the portion of LLNL's overall budget supported by National Security Programs, which is 63% for FY1999.« less

Report for the Office of Scientific and Technical Information: Population Modeling of the Emergence and Development of Scientific Fields

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

Bettencourt, L. M. A.; Castillo-Chavez, C.; Kaiser, D.

2006-10-04

The accelerated development of digital libraries and archives, in tandem with efficient search engines and the computational ability to retrieve and parse massive amounts of information, are making it possible to quantify the time evolution of scientific literatures. These data are but one piece of the tangible recorded evidence of the processes whereby scientists create and exchange information in their journeys towards the generation of knowledge. As such, these tools provide a proxy with which to study our ability to innovate. Innovation has often been linked with prosperity and growth and, consequently, trying to understand what drives scientific innovation ismore » of extreme interest. Identifying sets of population characteristics, factors, and mechanisms that enable scientific communities to remain at the cutting edge, accelerate their growth, or increase their ability to re-organize around new themes or research topics is therefore of special significance. Yet generating a quantitative understanding of the factors that make scientific fields arise and/or become more or less productive is still in its infancy. This is precisely the type of knowledge most needed for promoting and sustaining innovation. Ideally, the efficient and strategic allocation of resources on the part of funding agencies and corporations would be driven primarily by knowledge of this type. Early steps have been taken toward such a quantitative understanding of scientific innovation. Some have focused on characterizing the broad properties of relevant time series, such as numbers of publications and authors in a given field. Others have focused on the structure and evolution of networks of coauthorship and citation. Together these types of studies provide much needed statistical analyses of the structure and evolution of scientific communities. Despite these efforts, however, crucial elements of prediction have remained elusive. Building on many of these earlier insights, we provide here a coarse-grained approach to modeling the time-evolution of scientific fields mathematically, through adaptive models of contagion. That is, our models are inspired by epidemic contact processes, but take into account the social interactions and processes whereby scientific ideas spread - social interactions gleaned from close empirical study of historical cases. Variations in model parameters can increase or hamper the speed at which a field develops. In this way, models for the spread of 'infectious' ideas can be used to identify pressure points in the process of innovation that may allow for the evaluation of possible interventions by those responsible for promoting innovation, such as funding agencies. This report is organized as follows: Section 2 introduces and discusses the population model used here to describe the dynamics behind the establishment of scientific fields. The approach is based on a succinct (coarse) description of contact processes between scientists, and is a simplified version of a general class of models developed in the course of this work. We selected this model based primarily on its ability to treat a wide range of data patterns efficiently, across several different scientific fields. We also describe our methods for estimating parameter values, our optimization techniques used to match the model to data, and our method of generating error estimates. Section 3 presents brief accounts of six case studies of scientific evolution, measured by the growth in number of active authors over time, and shows the results of fitting our model to these data, including extrapolations to the near future. Section 4 discusses these results and provides some perspectives on the values and limitations of the models used. We also discuss topics for further research which should improve our ability to predict (and perhaps influence) the course of future scientific research. Section 5 provides more detail on the broad class of epidemic models developed as part of this project.« less

Where We Now Stand

ERIC Educational Resources Information Center

Lumsden, Keith G.

1969-01-01

Noting the acceleration of scientific evaluation, the author focuses his attention on where we now stand in the evaluation of two methods of instruction: programed learning materials and television. (Editor)

Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

ERIC Educational Resources Information Center

Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

2016-01-01

In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

ERIC Educational Resources Information Center

Hulshof, Casper D.; de Jong, Ton

2006-01-01

Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

Software package for modeling spin–orbit motion in storage rings

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

Zyuzin, D. V., E-mail: d.zyuzin@fz-juelich.de

2015-12-15

A software package providing a graphical user interface for computer experiments on the motion of charged particle beams in accelerators, as well as analysis of obtained data, is presented. The software package was tested in the framework of the international project on electric dipole moment measurement JEDI (Jülich Electric Dipole moment Investigations). The specific features of particle spin motion imply the requirement to use a cyclic accelerator (storage ring) consisting of electrostatic elements, which makes it possible to preserve horizontal polarization for a long time. Computer experiments study the dynamics of 10{sup 6}–10{sup 9} particles in a beam during 10{supmore » 9} turns in an accelerator (about 10{sup 12}–10{sup 15} integration steps for the equations of motion). For designing an optimal accelerator structure, a large number of computer experiments on polarized beam dynamics are required. The numerical core of the package is COSY Infinity, a program for modeling spin–orbit dynamics.« less

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

USGS Publications Warehouse

Dietze, Michael C.; Fox, Andrew; Beck-Johnson, Lindsay; Betancourt, Julio L.; Hooten, Mevin B.; Jarnevich, Catherine S.; Keitt, Timothy H.; Kenney, Melissa A.; Laney, Christine M.; Larsen, Laurel G.; Loescher, Henry W.; Lunch, Claire K.; Pijanowski, Bryan; Randerson, James T.; Read, Emily; Tredennick, Andrew T.; Vargas, Rodrigo; Weathers, Kathleen C.; White, Ethan P.

2018-01-01

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Iterative near-term ecological forecasting: Needs, opportunities, and challenges.

PubMed

Dietze, Michael C; Fox, Andrew; Beck-Johnson, Lindsay M; Betancourt, Julio L; Hooten, Mevin B; Jarnevich, Catherine S; Keitt, Timothy H; Kenney, Melissa A; Laney, Christine M; Larsen, Laurel G; Loescher, Henry W; Lunch, Claire K; Pijanowski, Bryan C; Randerson, James T; Read, Emily K; Tredennick, Andrew T; Vargas, Rodrigo; Weathers, Kathleen C; White, Ethan P

2018-02-13

Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Accelerated spike resampling for accurate multiple testing controls.

PubMed

Harrison, Matthew T

2013-02-01

Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

Derivation of improved load transformation matrices for launchers-spacecraft coupled analysis, and direct computation of margins of safety

NASA Technical Reports Server (NTRS)

Klein, M.; Reynolds, J.; Ricks, E.

1989-01-01

Load and stress recovery from transient dynamic studies are improved upon using an extended acceleration vector in the modal acceleration technique applied to structural analysis. Extension of the normal LTM (load transformation matrices) stress recovery to automatically compute margins of safety is presented with an application to the Hubble space telescope.

The application of artificial intelligent techniques to accelerator operations at McMaster University

NASA Astrophysics Data System (ADS)

Poehlman, W. F. S.; Garland, Wm. J.; Stark, J. W.

1993-06-01

In an era of downsizing and a limited pool of skilled accelerator personnel from which to draw replacements for an aging workforce, the impetus to integrate intelligent computer automation into the accelerator operator's repertoire is strong. However, successful deployment of an "Operator's Companion" is not trivial. Both graphical and human factors need to be recognized as critical areas that require extra care when formulating the Companion. They include interactive graphical user's interface that mimics, for the operator, familiar accelerator controls; knowledge of acquisition phases during development must acknowledge the expert's mental model of machine operation; and automated operations must be seen as improvements to the operator's environment rather than threats of ultimate replacement. Experiences with the PACES Accelerator Operator Companion developed at two sites over the past three years are related and graphical examples are given. The scale of the work involves multi-computer control of various start-up/shutdown and tuning procedures for Model FN and KN Van de Graaff accelerators. The response from licensing agencies has been encouraging.

Utilizing GPUs to Accelerate Turbomachinery CFD Codes

NASA Technical Reports Server (NTRS)

MacCalla, Weylin; Kulkarni, Sameer

2016-01-01

GPU computing has established itself as a way to accelerate parallel codes in the high performance computing world. This work focuses on speeding up APNASA, a legacy CFD code used at NASA Glenn Research Center, while also drawing conclusions about the nature of GPU computing and the requirements to make GPGPU worthwhile on legacy codes. Rewriting and restructuring of the source code was avoided to limit the introduction of new bugs. The code was profiled and investigated for parallelization potential, then OpenACC directives were used to indicate parallel parts of the code. The use of OpenACC directives was not able to reduce the runtime of APNASA on either the NVIDIA Tesla discrete graphics card, or the AMD accelerated processing unit. Additionally, it was found that in order to justify the use of GPGPU, the amount of parallel work being done within a kernel would have to greatly exceed the work being done by any one portion of the APNASA code. It was determined that in order for an application like APNASA to be accelerated on the GPU, it should not be modular in nature, and the parallel portions of the code must contain a large portion of the code's computation time.

GPU Accelerated Prognostics

NASA Technical Reports Server (NTRS)

Gorospe, George E., Jr.; Daigle, Matthew J.; Sankararaman, Shankar; Kulkarni, Chetan S.; Ng, Eley

2017-01-01

Prognostic methods enable operators and maintainers to predict the future performance for critical systems. However, these methods can be computationally expensive and may need to be performed each time new information about the system becomes available. In light of these computational requirements, we have investigated the application of graphics processing units (GPUs) as a computational platform for real-time prognostics. Recent advances in GPU technology have reduced cost and increased the computational capability of these highly parallel processing units, making them more attractive for the deployment of prognostic software. We present a survey of model-based prognostic algorithms with considerations for leveraging the parallel architecture of the GPU and a case study of GPU-accelerated battery prognostics with computational performance results.

Graduate Student Program in Materials and Engineering Research and Development for Future Accelerators

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

Spentzouris, Linda

The objective of the proposal was to develop graduate student training in materials and engineering research relevant to the development of particle accelerators. Many components used in today's accelerators or storage rings are at the limit of performance. The path forward in many cases requires the development of new materials or fabrication techniques, or a novel engineering approach. Often, accelerator-based laboratories find it difficult to get top-level engineers or materials experts with the motivation to work on these problems. The three years of funding provided by this grant was used to support development of accelerator components through a multidisciplinary approachmore » that cut across the disciplinary boundaries of accelerator physics, materials science, and surface chemistry. The following results were achieved: (1) significant scientific results on fabrication of novel photocathodes, (2) application of surface science and superconducting materials expertise to accelerator problems through faculty involvement, (3) development of instrumentation for fabrication and characterization of materials for accelerator components, (4) student involvement with problems at the interface of material science and accelerator physics.« less

News | Computing

Science.gov Websites

Support News Publications Computing for Experiments Computing for Neutrino and Muon Physics Computing for Collider Experiments Computing for Astrophysics Research and Development Accelerator Modeling ComPASS - Impact of Detector Simulation on Particle Physics Collider Experiments Daniel Elvira's paper "Impact

GPU accelerated dynamic functional connectivity analysis for functional MRI data.

PubMed

Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu

2015-07-01

Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spectral turning bands for efficient Gaussian random fields generation on GPUs and accelerators

NASA Astrophysics Data System (ADS)

Hunger, L.; Cosenza, B.; Kimeswenger, S.; Fahringer, T.

2015-11-01

A random field (RF) is a set of correlated random variables associated with different spatial locations. RF generation algorithms are of crucial importance for many scientific areas, such as astrophysics, geostatistics, computer graphics, and many others. Current approaches commonly make use of 3D fast Fourier transform (FFT), which does not scale well for RF bigger than the available memory; they are also limited to regular rectilinear meshes. We introduce random field generation with the turning band method (RAFT), an RF generation algorithm based on the turning band method that is optimized for massively parallel hardware such as GPUs and accelerators. Our algorithm replaces the 3D FFT with a lower-order, one-dimensional FFT followed by a projection step and is further optimized with loop unrolling and blocking. RAFT can easily generate RF on non-regular (non-uniform) meshes and efficiently produce fields with mesh sizes bigger than the available device memory by using a streaming, out-of-core approach. Our algorithm generates RF with the correct statistical behavior and is tested on a variety of modern hardware, such as NVIDIA Tesla, AMD FirePro and Intel Phi. RAFT is faster than the traditional methods on regular meshes and has been successfully applied to two real case scenarios: planetary nebulae and cosmological simulations.

Ultrasound window-modulated compounding Nakagami imaging: Resolution improvement and computational acceleration for liver characterization.

PubMed

Ma, Hsiang-Yang; Lin, Ying-Hsiu; Wang, Chiao-Yin; Chen, Chiung-Nien; Ho, Ming-Chih; Tsui, Po-Hsiang

2016-08-01

Ultrasound Nakagami imaging is an attractive method for visualizing changes in envelope statistics. Window-modulated compounding (WMC) Nakagami imaging was reported to improve image smoothness. The sliding window technique is typically used for constructing ultrasound parametric and Nakagami images. Using a large window overlap ratio may improve the WMC Nakagami image resolution but reduces computational efficiency. Therefore, the objectives of this study include: (i) exploring the effects of the window overlap ratio on the resolution and smoothness of WMC Nakagami images; (ii) proposing a fast algorithm that is based on the convolution operator (FACO) to accelerate WMC Nakagami imaging. Computer simulations and preliminary clinical tests on liver fibrosis samples (n=48) were performed to validate the FACO-based WMC Nakagami imaging. The results demonstrated that the width of the autocorrelation function and the parameter distribution of the WMC Nakagami image reduce with the increase in the window overlap ratio. One-pixel shifting (i.e., sliding the window on the image data in steps of one pixel for parametric imaging) as the maximum overlap ratio significantly improves the WMC Nakagami image quality. Concurrently, the proposed FACO method combined with a computational platform that optimizes the matrix computation can accelerate WMC Nakagami imaging, allowing the detection of liver fibrosis-induced changes in envelope statistics. FACO-accelerated WMC Nakagami imaging is a new-generation Nakagami imaging technique with an improved image quality and fast computation. Copyright © 2016 Elsevier B.V. All rights reserved.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

NASA Astrophysics Data System (ADS)

Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

Data-driven Ontology Development: A Case Study at NASA's Atmospheric Science Data Center

NASA Astrophysics Data System (ADS)

Hertz, J.; Huffer, E.; Kusterer, J.

2012-12-01

Well-founded ontologies are key to enabling transformative semantic technologies and accelerating scientific research. One example is semantically enabled search and discovery, making scientific data accessible and more understandable by accurately modeling a complex domain. The ontology creation process remains a challenge for many anxious to pursue semantic technologies. The key may be that the creation process -- whether formal, community-based, automated or semi-automated -- should encompass not only a foundational core and supplemental resources but also a focus on the purpose or mission the ontology is created to support. Are there tools or processes to de-mystify, assess or enhance the resulting ontology? We suggest that comparison and analysis of a domain-focused ontology can be made using text engineering tools for information extraction, tokenizers, named entity transducers and others. The results are analyzed to ensure the ontology reflects the core purpose of the domain's mission and that the ontology integrates and describes the supporting data in the language of the domain - how the science is analyzed and discussed among all users of the data. Commonalities and relationships among domain resources describing the Clouds and Earth's Radiant Energy (CERES) Bi-Directional Scan (BDS) datasets from NASA's Atmospheric Science Data Center are compared. The domain resources include: a formal ontology created for CERES; scientific works such as papers, conference proceedings and notes; information extracted from the datasets (i.e., header metadata); and BDS scientific documentation (Algorithm Theoretical Basis Documents, collection guides, data quality summaries and others). These resources are analyzed using the open source software General Architecture for Text Engineering, a mature framework for computational tasks involving human language.

An Interdisciplinary Guided Inquiry on Estuarine Transport Using a Computer Model in High School Classrooms

ERIC Educational Resources Information Center

Chan, Kit Yu Karen; Yang, Sylvia; Maliska, Max E.; Grunbaum, Daniel

2012-01-01

The National Science Education Standards have highlighted the importance of active learning and reflection for contemporary scientific methods in K-12 classrooms, including the use of models. Computer modeling and visualization are tools that researchers employ in their scientific inquiry process, and often computer models are used in…

Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

ERIC Educational Resources Information Center

Younge, Andrew J.

2016-01-01

With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their scientific computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for…

An Analysis on the Effect of Computer Self-Efficacy over Scientific Research Self-Efficacy and Information Literacy Self-Efficacy

ERIC Educational Resources Information Center

Tuncer, Murat

2013-01-01

Present research investigates reciprocal relations amidst computer self-efficacy, scientific research and information literacy self-efficacy. Research findings have demonstrated that according to standardized regression coefficients, computer self-efficacy has a positive effect on information literacy self-efficacy. Likewise it has been detected…

The Impact of Three-Dimensional Computational Modeling on Student Understanding of Astronomical Concepts: A Quantitative Analysis

ERIC Educational Resources Information Center

Hansen, John; Barnett, Michael; MaKinster, James; Keating, Thomas

2004-01-01

The increased availability of computational modeling software has created opportunities for students to engage in scientific inquiry through constructing computer-based models of scientific phenomena. However, despite the growing trend of integrating technology into science curricula, educators need to understand what aspects of these technologies…

Accelerator on a Chip

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

England, Joel

2014-06-30

SLAC's Joel England explains how the same fabrication techniques used for silicon computer microchips allowed their team to create the new laser-driven particle accelerator chips. (SLAC Multimedia Communications)

Accelerator on a Chip

ScienceCinema

England, Joel

2018-01-16

SLAC's Joel England explains how the same fabrication techniques used for silicon computer microchips allowed their team to create the new laser-driven particle accelerator chips. (SLAC Multimedia Communications)

Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; VanderWijngaart, Rob

2003-01-01

The growing gap between sustained and peak performance for scientific applications has become a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to bridge this gap for a significant number of computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines a full spectrum of low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks using some simple optimizations. Finally, we evaluate the perfor- mance of several numerical codes from key scientific computing domains. Overall results demonstrate that the SX6 achieves high performance on a large fraction of our application suite and in many cases significantly outperforms the RISC-based architectures. However, certain classes of applications are not easily amenable to vectorization and would likely require extensive reengineering of both algorithm and implementation to utilize the SX6 effectively.

Accelerating execution of the integrated TIGER series Monte Carlo radiation transport codes

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

Smith, L.M.; Hochstedler, R.D.

1997-02-01

Execution of the integrated TIGER series (ITS) of coupled electron/photon Monte Carlo radiation transport codes has been accelerated by modifying the FORTRAN source code for more efficient computation. Each member code of ITS was benchmarked and profiled with a specific test case that directed the acceleration effort toward the most computationally intensive subroutines. Techniques for accelerating these subroutines included replacing linear search algorithms with binary versions, replacing the pseudo-random number generator, reducing program memory allocation, and proofing the input files for geometrical redundancies. All techniques produced identical or statistically similar results to the original code. Final benchmark timing of themore » accelerated code resulted in speed-up factors of 2.00 for TIGER (the one-dimensional slab geometry code), 1.74 for CYLTRAN (the two-dimensional cylindrical geometry code), and 1.90 for ACCEPT (the arbitrary three-dimensional geometry code).« less

NOTE: Acceleration of Monte Carlo-based scatter compensation for cardiac SPECT

NASA Astrophysics Data System (ADS)

Sohlberg, A.; Watabe, H.; Iida, H.

2008-07-01

Single proton emission computed tomography (SPECT) images are degraded by photon scatter making scatter compensation essential for accurate reconstruction. Reconstruction-based scatter compensation with Monte Carlo (MC) modelling of scatter shows promise for accurate scatter correction, but it is normally hampered by long computation times. The aim of this work was to accelerate the MC-based scatter compensation using coarse grid and intermittent scatter modelling. The acceleration methods were compared to un-accelerated implementation using MC-simulated projection data of the mathematical cardiac torso (MCAT) phantom modelling 99mTc uptake and clinical myocardial perfusion studies. The results showed that when combined the acceleration methods reduced the reconstruction time for 10 ordered subset expectation maximization (OS-EM) iterations from 56 to 11 min without a significant reduction in image quality indicating that the coarse grid and intermittent scatter modelling are suitable for MC-based scatter compensation in cardiac SPECT.

Extended Task Space Control for Robotic Manipulators

NASA Technical Reports Server (NTRS)

Backes, Paul G. (Inventor); Long, Mark K. (Inventor)

1996-01-01

The invention is a method of operating a robot in successive sampling intervals to perform a task, the robot having joints and joint actuators with actuator control loops, by decomposing the task into behavior forces, accelerations, velocities and positions of plural behaviors to be exhibited by the robot simultaneously, computing actuator accelerations of the joint actuators for the current sampling interval from both behavior forces, accelerations velocities and positions of the current sampling interval and actuator velocities and positions of the previous sampling interval, computing actuator velocities and positions of the joint actuators for the current sampling interval from the actuator velocities and positions of the previous sampling interval, and, finally, controlling the actuators in accordance with the actuator accelerations, velocities and positions of the current sampling interval. The actuator accelerations, velocities and positions of the current sampling interval are stored for use during the next sampling interval.

Covariant Uniform Acceleration

NASA Astrophysics Data System (ADS)

Friedman, Yaakov; Scarr, Tzvi

2013-04-01

We derive a 4D covariant Relativistic Dynamics Equation. This equation canonically extends the 3D relativistic dynamics equation , where F is the 3D force and p = m0γv is the 3D relativistic momentum. The standard 4D equation is only partially covariant. To achieve full Lorentz covariance, we replace the four-force F by a rank 2 antisymmetric tensor acting on the four-velocity. By taking this tensor to be constant, we obtain a covariant definition of uniformly accelerated motion. This solves a problem of Einstein and Planck. We compute explicit solutions for uniformly accelerated motion. The solutions are divided into four Lorentz-invariant types: null, linear, rotational, and general. For null acceleration, the worldline is cubic in the time. Linear acceleration covariantly extends 1D hyperbolic motion, while rotational acceleration covariantly extends pure rotational motion. We use Generalized Fermi-Walker transport to construct a uniformly accelerated family of inertial frames which are instantaneously comoving to a uniformly accelerated observer. We explain the connection between our approach and that of Mashhoon. We show that our solutions of uniformly accelerated motion have constant acceleration in the comoving frame. Assuming the Weak Hypothesis of Locality, we obtain local spacetime transformations from a uniformly accelerated frame K' to an inertial frame K. The spacetime transformations between two uniformly accelerated frames with the same acceleration are Lorentz. We compute the metric at an arbitrary point of a uniformly accelerated frame. We obtain velocity and acceleration transformations from a uniformly accelerated system K' to an inertial frame K. We introduce the 4D velocity, an adaptation of Horwitz and Piron s notion of "off-shell." We derive the general formula for the time dilation between accelerated clocks. We obtain a formula for the angular velocity of a uniformly accelerated object. Every rest point of K' is uniformly accelerated, and its acceleration is a function of the observer's acceleration and its position. We obtain an interpretation of the Lorentz-Abraham-Dirac equation as an acceleration transformation from K' to K.

Climate Informatics

NASA Technical Reports Server (NTRS)

Monteleoni, Claire; Schmidt, Gavin A.; Alexander, Francis J.; Niculescu-Mizil, Alexandru; Steinhaeuser, Karsten; Tippett, Michael; Banerjee, Arindam; Blumenthal, M. Benno; Ganguly, Auroop R.; Smerdon, Jason E.;

Neuromorphic photonic networks using silicon photonic weight banks.

PubMed

Tait, Alexander N; de Lima, Thomas Ferreira; Zhou, Ellen; Wu, Allie X; Nahmias, Mitchell A; Shastri, Bhavin J; Prucnal, Paul R

2017-08-07

Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

USRA/RIACS

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1992-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under a cooperative agreement with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing; Advanced Methods for Scientific Computing; Learning Systems; High Performance Networks and Technology; Graphics, Visualization, and Virtual Environments.

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

NASA Astrophysics Data System (ADS)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

Max 1991: Flare Research at the Next Solar Maximum. Workshop 1: Scientific Objectives

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; Dennis, Brian R.

1988-01-01

The purpose of the Max 1991 program is to gather coordinated sets of solar flare and active region data and to perform interpretive and theoretical research aimed at understanding flare energy storage and release, particle acceleration, flare energy transport, and the propagation of flare effects to Earth. The workshop was divided into four areas of concern: energy storage, energy release, particle acceleration, and energy transport.

Preface: SciDAC 2005

NASA Astrophysics Data System (ADS)

Mezzacappa, Anthony

2005-01-01

On 26-30 June 2005 at the Grand Hyatt on Union Square in San Francisco several hundred computational scientists from around the world came together for what can certainly be described as a celebration of computational science. Scientists from the SciDAC Program and scientists from other agencies and nations were joined by applied mathematicians and computer scientists to highlight the many successes in the past year where computation has led to scientific discovery in a variety of fields: lattice quantum chromodynamics, accelerator modeling, chemistry, biology, materials science, Earth and climate science, astrophysics, and combustion and fusion energy science. Also highlighted were the advances in numerical methods and computer science, and the multidisciplinary collaboration cutting across science, mathematics, and computer science that enabled these discoveries. The SciDAC Program was conceived and funded by the US Department of Energy Office of Science. It is the Office of Science's premier computational science program founded on what is arguably the perfect formula: the priority and focus is science and scientific discovery, with the understanding that the full arsenal of `enabling technologies' in applied mathematics and computer science must be brought to bear if we are to have any hope of attacking and ultimately solving today's computational Grand Challenge problems. The SciDAC Program has been in existence for four years, and many of the computational scientists funded by this program will tell you that the program has given them the hope of addressing their scientific problems in full realism for the very first time. Many of these scientists will also tell you that SciDAC has also fundamentally changed the way they do computational science. We begin this volume with one of DOE's great traditions, and core missions: energy research. As we will see, computation has been seminal to the critical advances that have been made in this arena. Of course, to understand our world, whether it is to understand its very nature or to understand it so as to control it for practical application, will require explorations on all of its scales. Computational science has been no less an important tool in this arena than it has been in the arena of energy research. From explorations of quantum chromodynamics, the fundamental theory that describes how quarks make up the protons and neutrons of which we are composed, to explorations of the complex biomolecules that are the building blocks of life, to explorations of some of the most violent phenomena in our universe and of the Universe itself, computation has provided not only significant insight, but often the only means by which we have been able to explore these complex, multicomponent systems and by which we have been able to achieve scientific discovery and understanding. While our ultimate target remains scientific discovery, it certainly can be said that at a fundamental level the world is mathematical. Equations ultimately govern the evolution of the systems of interest to us, be they physical, chemical, or biological systems. The development and choice of discretizations of these underlying equations is often a critical deciding factor in whether or not one is able to model such systems stably, faithfully, and practically, and in turn, the algorithms to solve the resultant discrete equations are the complementary, critical ingredient in the recipe to model the natural world. The use of parallel computing platforms, especially at the TeraScale, and the trend toward even larger numbers of processors, continue to present significant challenges in the development and implementation of these algorithms. Computational scientists often speak of their `workflows'. A workflow, as the name suggests, is the sum total of all complex and interlocking tasks, from simulation set up, execution, and I/O, to visualization and scientific discovery, through which the advancement in our understanding of the natural world is realized. For the computational scientist, enabling such workflows presents myriad, signiflcant challenges, and it is computer scientists that are called upon at such times to address these challenges. Simulations are currently generating data at the staggering rate of tens of TeraBytes per simulation, over the course of days. In the next few years, these data generation rates are expected to climb exponentially to hundreds of TeraBytes per simulation, performed over the course of months. The output, management, movement, analysis, and visualization of these data will be our key to unlocking the scientific discoveries buried within the data. And there is no hope of generating such data to begin with, or of scientific discovery, without stable computing platforms and a sufficiently high and sustained performance of scientific applications codes on them. Thus, scientific discovery in the realm of computational science at the TeraScale and beyond will occur at the intersection of science, applied mathematics, and computer science. The SciDAC Program was constructed to mirror this reality, and the pages that follow are a testament to the efficacy of such an approach. We would like to acknowledge the individuals on whose talents and efforts the success of SciDAC 2005 was based. Special thanks go to Betsy Riley for her work on the SciDAC 2005 Web site and meeting agenda, for lining up our corporate sponsors, for coordinating all media communications, and for her efforts in processing the proceedings contributions, to Sherry Hempfling for coordinating the overall SciDAC 2005 meeting planning, for handling a significant share of its associated communications, and for coordinating with the ORNL Conference Center and Grand Hyatt, to Angela Harris for producing many of the documents and records on which our meeting planning was based and for her efforts in coordinating with ORNL Graphics Services, to Angie Beach of the ORNL Conference Center for her efforts in procurement and setting up and executing the contracts with the hotel, and to John Bui and John Smith for their superb wireless networking and A/V set up and support. We are grateful for the relentless efforts of all of these individuals, their remarkable talents, and for the joy of working with them during this past year. They were the cornerstones of SciDAC 2005. Thanks also go to Kymba A'Hearn and Patty Boyd for on-site registration, Brittany Hagen for administrative support, Bruce Johnston for netcast support, Tim Jones for help with the proceedings and Web site, Sherry Lamb for housing and registration, Cindy Lathum for Web site design, Carolyn Peters for on-site registration, and Dami Rich for graphic design. And we would like to express our appreciation to the Oak Ridge National Laboratory, especially Jeff Nichols, the Argonne National Laboratory, the Lawrence Berkeley National Laboratory, and to our corporate sponsors, Cray, IBM, Intel, and SGI, for their support. We would like to extend special thanks also to our plenary speakers, technical speakers, poster presenters, and panelists for all of their efforts on behalf of SciDAC 2005 and for their remarkable achievements and contributions. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas and Margaret Smith of Institute of Physics Publishing, who worked tirelessly in order to provide us with this finished volume within two months, which is nothing short of miraculous. Finally, we wish to express our heartfelt thanks to Michael Strayer, SciDAC Director, whose vision it was to focus SciDAC 2005 on scientific discovery, around which all of the excitement we experienced revolved, and to our DOE SciDAC program managers, especially Fred Johnson, for their support, input, and help throughout.

Smart article: application of intelligent platforms in next generation biomedical publications.

PubMed

Mohammadi, Babak; Saeedi, Marjan; Haghpanah, Vahid

2017-01-01

Production of scientific data has been accelerated exponentially though ease of access to the required knowledge is still challenging. Hence, the emergence of new frameworks to allow more efficient storage of information would be beneficial. Attaining intelligent platforms enable the smart article to serve as a forum for exchanging idea among experts of academic disciplines for a rapid and efficient scientific discourse.

Summary Scientific Performance of EUCLID Detector Prototypes

NASA Technical Reports Server (NTRS)

Rauscher, Bernard J.

2011-01-01

NASA and the European Space Agency (ESA) plan to partner to build the EUCLID mission. EUCLID is a mission concept for studying the Dark Energy that is hypothesized to account for the accelerating cosmic expansion. For the past year, NASA has been building detector prototypes at Teledyne Imaging Sensors. This talk will summarize the measured scientific performance of these detector prototypes for astrophysical and cosmological applications.

Fermilab Today

Science.gov Websites

hundreds of feet below the Earth's surface, two laboratories are pushing basic scientific research to the miles through the Earth's crust from the Fermi National Accelerator Laboratory in Batavia, Illinois

A toolbox and a record for scientific model development

NASA Technical Reports Server (NTRS)

Ellman, Thomas

1994-01-01

Scientific computation can benefit from software tools that facilitate construction of computational models, control the application of models, and aid in revising models to handle new situations. Existing environments for scientific programming provide only limited means of handling these tasks. This paper describes a two pronged approach for handling these tasks: (1) designing a 'Model Development Toolbox' that includes a basic set of model constructing operations; and (2) designing a 'Model Development Record' that is automatically generated during model construction. The record is subsequently exploited by tools that control the application of scientific models and revise models to handle new situations. Our two pronged approach is motivated by our belief that the model development toolbox and record should be highly interdependent. In particular, a suitable model development record can be constructed only when models are developed using a well defined set of operations. We expect this research to facilitate rapid development of new scientific computational models, to help ensure appropriate use of such models and to facilitate sharing of such models among working computational scientists. We are testing this approach by extending SIGMA, and existing knowledge-based scientific software design tool.

The Petascale Data Storage Institute

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

Gibson, Garth; Long, Darrell; Honeyman, Peter

2013-07-01

Petascale computing infrastructures for scientific discovery make petascale demands on information storage capacity, performance, concurrency, reliability, availability, and manageability.The Petascale Data Storage Institute focuses on the data storage problems found in petascale scientific computing environments, with special attention to community issues such as interoperability, community buy-in, and shared tools.The Petascale Data Storage Institute is a collaboration between researchers at Carnegie Mellon University, National Energy Research Scientific Computing Center, Pacific Northwest National Laboratory, Oak Ridge National Laboratory, Sandia National Laboratory, Los Alamos National Laboratory, University of Michigan, and the University of California at Santa Cruz.

The need for scientific software engineering in the pharmaceutical industry

NASA Astrophysics Data System (ADS)

Luty, Brock; Rose, Peter W.

2017-03-01

Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

The need for scientific software engineering in the pharmaceutical industry.

PubMed

Luty, Brock; Rose, Peter W

2017-03-01

Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

GPU acceleration of Dock6's Amber scoring computation.

PubMed

Yang, Hailong; Zhou, Qiongqiong; Li, Bo; Wang, Yongjian; Luan, Zhongzhi; Qian, Depei; Li, Hanlu

2010-01-01

Dressing the problem of virtual screening is a long-term goal in the drug discovery field, which if properly solved, can significantly shorten new drugs' R&D cycle. The scoring functionality that evaluates the fitness of the docking result is one of the major challenges in virtual screening. In general, scoring functionality in docking requires a large amount of floating-point calculations, which usually takes several weeks or even months to be finished. This time-consuming procedure is unacceptable, especially when highly fatal and infectious virus arises such as SARS and H1N1, which forces the scoring task to be done in a limited time. This paper presents how to leverage the computational power of GPU to accelerate Dock6's (http://dock.compbio.ucsf.edu/DOCK_6/) Amber (J. Comput. Chem. 25: 1157-1174, 2004) scoring with NVIDIA CUDA (NVIDIA Corporation Technical Staff, Compute Unified Device Architecture - Programming Guide, NVIDIA Corporation, 2008) (Compute Unified Device Architecture) platform. We also discuss many factors that will greatly influence the performance after porting the Amber scoring to GPU, including thread management, data transfer, and divergence hidden. Our experiments show that the GPU-accelerated Amber scoring achieves a 6.5× speedup with respect to the original version running on AMD dual-core CPU for the same problem size. This acceleration makes the Amber scoring more competitive and efficient for large-scale virtual screening problems.

Application of Plasma Waveguides to High Energy Accelerators

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

Milchberg, Howard M

2013-03-30

The eventual success of laser-plasma based acceleration schemes for high-energy particle physics will require the focusing and stable guiding of short intense laser pulses in reproducible plasma channels. For this goal to be realized, many scientific issues need to be addressed. These issues include an understanding of the basic physics of, and an exploration of various schemes for, plasma channel formation. In addition, the coupling of intense laser pulses to these channels and the stable propagation of pulses in the channels require study. Finally, new theoretical and computational tools need to be developed to aid in the design and analysismore » of experiments and future accelerators. Here we propose a 3-year renewal of our combined theoretical and experimental program on the applications of plasma waveguides to high-energy accelerators. During the past grant period we have made a number of significant advances in the science of laser-plasma based acceleration. We pioneered the development of clustered gases as a new highly efficient medium for plasma channel formation. Our contributions here include theoretical and experimental studies of the physics of cluster ionization, heating, explosion, and channel formation. We have demonstrated for the first time the generation of and guiding in a corrugated plasma waveguide. The fine structure demonstrated in these guides is only possible with cluster jet heating by lasers. The corrugated guide is a slow wave structure operable at arbitrarily high laser intensities, allowing direct laser acceleration, a process we have explored in detail with simulations. The development of these guides opens the possibility of direct laser acceleration, a true miniature analogue of the SLAC RF-based accelerator. Our theoretical studies during this period have also contributed to the further development of the simulation codes, Wake and QuickPIC, which can be used for both laser driven and beam driven plasma based acceleration schemes. We will continue our development of advanced simulation tools by modifying the QuickPIC algorithm to allow for the simulation of plasma particle pick-up by the wake fields. We have also performed extensive simulations of plasma slow wave structures for efficient THz generation by guided laser beams or accelerated electron beams. We will pursue experimental studies of direct laser acceleration, and THz generation by two methods, ponderomotive-induced THz polarization, and THz radiation by laser accelerated electron beams. We also plan to study both conventional and corrugated plasma channels using our new 30 TW in our new lab facilities. We will investigate production of very long hydrogen plasma waveguides (5 cm). We will study guiding at increasing power levels through the onset of laser-induced cavitation (bubble regime) to assess the role played by the preformed channel. Experiments in direct acceleration will be performed, using laser plasma wakefields as the electron injector. Finally, we will use 2-colour ionization of gases as a high frequency THz source (<60 THz) in order for femtosecond measurements of low plasma densities in waveguides and beams.« less

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

DOE PAGES

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin; ...

2015-02-19

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

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

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

Bio-steps beyond Turing.

PubMed

Calude, Cristian S; Păun, Gheorghe

2004-11-01

Are there 'biologically computing agents' capable to compute Turing uncomputable functions? It is perhaps tempting to dismiss this question with a negative answer. Quite the opposite, for the first time in the literature on molecular computing we contend that the answer is not theoretically negative. Our results will be formulated in the language of membrane computing (P systems). Some mathematical results presented here are interesting in themselves. In contrast with most speed-up methods which are based on non-determinism, our results rest upon some universality results proved for deterministic P systems. These results will be used for building "accelerated P systems". In contrast with the case of Turing machines, acceleration is a part of the hardware (not a quality of the environment) and it is realised either by decreasing the size of "reactors" or by speeding-up the communication channels. Consequently, two acceleration postulates of biological inspiration are introduced; each of them poses specific questions to biology. Finally, in a more speculative part of the paper, we will deal with Turing non-computability activity of the brain and possible forms of (extraterrestrial) intelligence.

Acceleration of FDTD mode solver by high-performance computing techniques.

PubMed

Han, Lin; Xi, Yanping; Huang, Wei-Ping

2010-06-21

A two-dimensional (2D) compact finite-difference time-domain (FDTD) mode solver is developed based on wave equation formalism in combination with the matrix pencil method (MPM). The method is validated for calculation of both real guided and complex leaky modes of typical optical waveguides against the bench-mark finite-difference (FD) eigen mode solver. By taking advantage of the inherent parallel nature of the FDTD algorithm, the mode solver is implemented on graphics processing units (GPUs) using the compute unified device architecture (CUDA). It is demonstrated that the high-performance computing technique leads to significant acceleration of the FDTD mode solver with more than 30 times improvement in computational efficiency in comparison with the conventional FDTD mode solver running on CPU of a standard desktop computer. The computational efficiency of the accelerated FDTD method is in the same order of magnitude of the standard finite-difference eigen mode solver and yet require much less memory (e.g., less than 10%). Therefore, the new method may serve as an efficient, accurate and robust tool for mode calculation of optical waveguides even when the conventional eigen value mode solvers are no longer applicable due to memory limitation.

Angular Impact Mitigation System for Bicycle Helmets to Reduce Head Acceleration and Risk of Traumatic Brain Injury

PubMed Central

Hansen, Kirk; Dau, Nathan; Feist, Florian; Deck, Caroline; Willinger, Rémy; Madey, Steven M.; Bottlang, Michael

2013-01-01

Angular acceleration of the head is a known cause of traumatic brain injury (TBI), but contemporary bicycle helmets lack dedicated mechanisms to mitigate angular acceleration. A novel Angular Impact Mitigation (AIM) system for bicycle helmets has been developed that employs an elastically suspended aluminum honeycomb liner to absorb linear acceleration in normal impacts as well as angular acceleration in oblique impacts. This study tested bicycle helmets with and without AIM technology to comparatively assess impact mitigation. Normal impact tests were performed to measure linear head acceleration. Oblique impact tests were performed to measure angular head acceleration and neck loading. Furthermore, acceleration histories of oblique impacts were analyzed in a computational head model to predict the resulting risk of TBI in the form of concussion and diffuse axonal injury (DAI). Compared to standard helmets, AIM helmets resulted in a 14% reduction in peak linear acceleration (p < 0.001), a 34% reduction in peak angular acceleration (p < 0.001), and a 22% to 32% reduction in neck loading (p < 0.001). Computational results predicted that AIM helmets reduced the risk of concussion and DAI by 27% and 44%, respectively. In conclusion, these results demonstrated that AIM technology could effectively improve impact mitigation compared to a contemporary expanded polystyrene-based bicycle helmet, and may enhance prevention of bicycle-related TBI. Further research is required. PMID:23770518

Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

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

Sreepathi, Sarat; Kumar, Jitendra; Mills, Richard T.

A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like themore » Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.« less

Automated Production of Movies on a Cluster of Computers

NASA Technical Reports Server (NTRS)

Nail, Jasper; Le, Duong; Nail, William L.; Nail, William

2008-01-01

A method of accelerating and facilitating production of video and film motion-picture products, and software and generic designs of computer hardware to implement the method, are undergoing development. The method provides for automation of most of the tedious and repetitive tasks involved in editing and otherwise processing raw digitized imagery into final motion-picture products. The method was conceived to satisfy requirements, in industrial and scientific testing, for rapid processing of multiple streams of simultaneously captured raw video imagery into documentation in the form of edited video imagery and video derived data products for technical review and analysis. In the production of such video technical documentation, unlike in production of motion-picture products for entertainment, (1) it is often necessary to produce multiple video derived data products, (2) there are usually no second chances to repeat acquisition of raw imagery, (3) it is often desired to produce final products within minutes rather than hours, days, or months, and (4) consistency and quality, rather than aesthetics, are the primary criteria for judging the products. In the present method, the workflow has both serial and parallel aspects: processing can begin before all the raw imagery has been acquired, each video stream can be subjected to different stages of processing simultaneously on different computers that may be grouped into one or more cluster(s), and the final product may consist of multiple video streams. Results of processing on different computers are shared, so that workers can collaborate effectively.

Big Data, Deep Learning and Tianhe-2 at Sun Yat-Sen University, Guangzhou

NASA Astrophysics Data System (ADS)

Yuen, D. A.; Dzwinel, W.; Liu, J.; Zhang, K.

2014-12-01

In this decade the big data revolution has permeated in many fields, ranging from financial transactions, medical surveys and scientific endeavors, because of the big opportunities people see ahead. What to do with all this data remains an intriguing question. This is where computer scientists together with applied mathematicians have made some significant inroads in developing deep learning techniques for unraveling new relationships among the different variables by means of correlation analysis and data-assimilation methods. Deep-learning and big data taken together is a grand challenge task in High-performance computing which demand both ultrafast speed and large memory. The Tianhe-2 recently installed at Sun Yat-Sen University in Guangzhou is well positioned to take up this challenge because it is currently the world's fastest computer at 34 Petaflops. Each compute node of Tianhe-2 has two CPUs of Intel Xeon E5-2600 and three Xeon Phi accelerators. The Tianhe-2 has a very large fast memory RAM of 88 Gigabytes on each node. The system has a total memory of 1,375 Terabytes. All of these technical features will allow very high dimensional (more than 10) problem in deep learning to be explored carefully on the Tianhe-2. Problems in seismology which can be solved include three-dimensional seismic wave simulations of the whole Earth with a few km resolution and the recognition of new phases in seismic wave form from assemblage of large data sets.

Accelerated Reader. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2009

2009-01-01

"Accelerated Reader" is a computer-based reading management system designed to complement an existing classroom literacy program for grades pre-K-12. It is designed to increase the amount of time students spend reading independently. Students choose reading-level appropriate books or short stories for which Accelerated Reader tests are…

Computer generated hologram from point cloud using graphics processor.

PubMed

Chen, Rick H-Y; Wilkinson, Timothy D

2009-12-20

Computer generated holography is an extremely demanding and complex task when it comes to providing realistic reconstructions with full parallax, occlusion, and shadowing. We present an algorithm designed for data-parallel computing on modern graphics processing units to alleviate the computational burden. We apply Gaussian interpolation to create a continuous surface representation from discrete input object points. The algorithm maintains a potential occluder list for each individual hologram plane sample to keep the number of visibility tests to a minimum. We experimented with two approximations that simplify and accelerate occlusion computation. It is observed that letting several neighboring hologram plane samples share visibility information on object points leads to significantly faster computation without causing noticeable artifacts in the reconstructed images. Computing a reduced sample set via nonuniform sampling is also found to be an effective acceleration technique.

Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling (Final Report)

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

William J. Schroeder

2011-11-13

This report contains the comprehensive summary of the work performed on the SBIR Phase II, Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling at Kitware Inc. in collaboration with Stanford Linear Accelerator Center (SLAC). The goal of the work was to develop collaborative visualization tools for large-scale data as illustrated in the figure below. The solutions we proposed address the typical problems faced by geographicallyand organizationally-separated research and engineering teams, who produce large data (either through simulation or experimental measurement) and wish to work together to analyze and understand their data. Because the data is large, we expect that it cannotmore » be easily transported to each team member's work site, and that the visualization server must reside near the data. Further, we also expect that each work site has heterogeneous resources: some with large computing clients, tiled (or large) displays and high bandwidth; others sites as simple as a team member on a laptop computer. Our solution is based on the open-source, widely used ParaView large-data visualization application. We extended this tool to support multiple collaborative clients who may locally visualize data, and then periodically rejoin and synchronize with the group to discuss their findings. Options for managing session control, adding annotation, and defining the visualization pipeline, among others, were incorporated. We also developed and deployed a Web visualization framework based on ParaView that enables the Web browser to act as a participating client in a collaborative session. The ParaView Web Visualization framework leverages various Web technologies including WebGL, JavaScript, Java and Flash to enable interactive 3D visualization over the web using ParaView as the visualization server. We steered the development of this technology by teaming with the SLAC National Accelerator Laboratory. SLAC has a computationally-intensive problem important to the nations scientific progress as described shortly. Further, SLAC researchers routinely generate massive amounts of data, and frequently collaborate with other researchers located around the world. Thus SLAC is an ideal teammate through which to develop, test and deploy this technology. The nature of the datasets generated by simulations performed at SLAC presented unique visualization challenges especially when dealing with higher-order elements that were addressed during this Phase II. During this Phase II, we have developed a strong platform for collaborative visualization based on ParaView. We have developed and deployed a ParaView Web Visualization framework that can be used for effective collaboration over the Web. Collaborating and visualizing over the Web presents the community with unique opportunities for sharing and accessing visualization and HPC resources that hitherto with either inaccessible or difficult to use. The technology we developed in here will alleviate both these issues as it becomes widely deployed and adopted.« less

75 FR 65639 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-26

...: Computational Biology Special Emphasis Panel A. Date: October 29, 2010. Time: 2 p.m. to 3:30 p.m. Agenda: To.... Name of Committee: Center for Scientific Review Special Emphasis Panel; Member Conflict: Computational...

Quantum computational complexity, Einstein's equations and accelerated expansion of the Universe

NASA Astrophysics Data System (ADS)

Ge, Xian-Hui; Wang, Bin

2018-02-01

We study the relation between quantum computational complexity and general relativity. The quantum computational complexity is proposed to be quantified by the shortest length of geodesic quantum curves. We examine the complexity/volume duality in a geodesic causal ball in the framework of Fermi normal coordinates and derive the full non-linear Einstein equation. Using insights from the complexity/action duality, we argue that the accelerated expansion of the universe could be driven by the quantum complexity and free from coincidence and fine-tunning problems.

The Effects of Inquiry-Based Computer Simulation with Cooperative Learning on Scientific Thinking and Conceptual Understanding of Gas Laws

ERIC Educational Resources Information Center

Abdullah, Sopiah; Shariff, Adilah

2008-01-01

The purpose of the study was to investigate the effects of inquiry-based computer simulation with heterogeneous-ability cooperative learning (HACL) and inquiry-based computer simulation with friendship cooperative learning (FCL) on (a) scientific reasoning (SR) and (b) conceptual understanding (CU) among Form Four students in Malaysian Smart…

STREAM2016: Streaming Requirements, Experience, Applications and Middleware Workshop

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

Fox, Geoffrey; Jha, Shantenu; Ramakrishnan, Lavanya

The Department of Energy (DOE) Office of Science (SC) facilities including accelerators, light sources and neutron sources and sensors that study, the environment, and the atmosphere, are producing streaming data that needs to be analyzed for next-generation scientific discoveries. There has been an explosion of new research and technologies for stream analytics arising from the academic and private sectors. However, there has been no corresponding effort in either documenting the critical research opportunities or building a community that can create and foster productive collaborations. The two-part workshop series, STREAM: Streaming Requirements, Experience, Applications and Middleware Workshop (STREAM2015 and STREAM2016), weremore » conducted to bring the community together and identify gaps and future efforts needed by both NSF and DOE. This report describes the discussions, outcomes and conclusions from STREAM2016: Streaming Requirements, Experience, Applications and Middleware Workshop, the second of these workshops held on March 22-23, 2016 in Tysons, VA. STREAM2016 focused on the Department of Energy (DOE) applications, computational and experimental facilities, as well software systems. Thus, the role of “streaming and steering” as a critical mode of connecting the experimental and computing facilities was pervasive through the workshop. Given the overlap in interests and challenges with industry, the workshop had significant presence from several innovative companies and major contributors. The requirements that drive the proposed research directions, identified in this report, show an important opportunity for building competitive research and development program around streaming data. These findings and recommendations are consistent with vision outlined in NRC Frontiers of Data and National Strategic Computing Initiative (NCSI) [1, 2]. The discussions from the workshop are captured as topic areas covered in this report's sections. The report discusses four research directions driven by current and future application requirements reflecting the areas identified as important by STREAM2016. These include (i) Algorithms, (ii) Programming Models, Languages and Runtime Systems (iii) Human-in-the-loop and Steering in Scientific Workflow and (iv) Facilities.« less

Anderson Acceleration for Fixed-Point Iterations

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

Walker, Homer F.

The purpose of this grant was to support research on acceleration methods for fixed-point iterations, with applications to computational frameworks and simulation problems that are of interest to DOE.

Choosing order of operations to accelerate strip structure analysis in parameter range

NASA Astrophysics Data System (ADS)

Kuksenko, S. P.; Akhunov, R. R.; Gazizov, T. R.

2018-05-01

The paper considers the issue of using iteration methods in solving the sequence of linear algebraic systems obtained in quasistatic analysis of strip structures with the method of moments. Using the analysis of 4 strip structures, the authors have proved that additional acceleration (up to 2.21 times) of the iterative process can be obtained during the process of solving linear systems repeatedly by means of choosing a proper order of operations and a preconditioner. The obtained results can be used to accelerate the process of computer-aided design of various strip structures. The choice of the order of operations to accelerate the process is quite simple, universal and could be used not only for strip structure analysis but also for a wide range of computational problems.

GPU-accelerated phase-field simulation of dendritic solidification in a binary alloy

NASA Astrophysics Data System (ADS)

Yamanaka, Akinori; Aoki, Takayuki; Ogawa, Satoi; Takaki, Tomohiro

2011-03-01

The phase-field simulation for dendritic solidification of a binary alloy has been accelerated by using a graphic processing unit (GPU). To perform the phase-field simulation of the alloy solidification on GPU, a program code was developed with computer unified device architecture (CUDA). In this paper, the implementation technique of the phase-field model on GPU is presented. Also, we evaluated the acceleration performance of the three-dimensional solidification simulation by using a single NVIDIA TESLA C1060 GPU and the developed program code. The results showed that the GPU calculation for 5763 computational grids achieved the performance of 170 GFLOPS by utilizing the shared memory as a software-managed cache. Furthermore, it can be demonstrated that the computation with the GPU is 100 times faster than that with a single CPU core. From the obtained results, we confirmed the feasibility of realizing a real-time full three-dimensional phase-field simulation of microstructure evolution on a personal desktop computer.

Quantum supercharger library: hyper-parallelism of the Hartree-Fock method.

PubMed

Fernandes, Kyle D; Renison, C Alicia; Naidoo, Kevin J

2015-07-05

We present here a set of algorithms that completely rewrites the Hartree-Fock (HF) computations common to many legacy electronic structure packages (such as GAMESS-US, GAMESS-UK, and NWChem) into a massively parallel compute scheme that takes advantage of hardware accelerators such as Graphical Processing Units (GPUs). The HF compute algorithm is core to a library of routines that we name the Quantum Supercharger Library (QSL). We briefly evaluate the QSL's performance and report that it accelerates a HF 6-31G Self-Consistent Field (SCF) computation by up to 20 times for medium sized molecules (such as a buckyball) when compared with mature Central Processing Unit algorithms available in the legacy codes in regular use by researchers. It achieves this acceleration by massive parallelization of the one- and two-electron integrals and optimization of the SCF and Direct Inversion in the Iterative Subspace routines through the use of GPU linear algebra libraries. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

RIACS/USRA

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1993-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing, Advanced Methods for Scientific Computing, High Performance Networks and Technology, and Learning Systems. Parallel compiler techniques, adaptive numerical methods for flows in complicated geometries, and optimization were identified as important problems to investigate for ARC's involvement in the Computational Grand Challenges of the next decade.

GPUs benchmarking in subpixel image registration algorithm

NASA Astrophysics Data System (ADS)

Sanz-Sabater, Martin; Picazo-Bueno, Jose Angel; Micó, Vicente; Ferrerira, Carlos; Granero, Luis; Garcia, Javier

2015-05-01

Image registration techniques are used among different scientific fields, like medical imaging or optical metrology. The straightest way to calculate shifting between two images is using the cross correlation, taking the highest value of this correlation image. Shifting resolution is given in whole pixels which cannot be enough for certain applications. Better results can be achieved interpolating both images, as much as the desired resolution we want to get, and applying the same technique described before, but the memory needed by the system is significantly higher. To avoid memory consuming we are implementing a subpixel shifting method based on FFT. With the original images, subpixel shifting can be achieved multiplying its discrete Fourier transform by a linear phase with different slopes. This method is high time consuming method because checking a concrete shifting means new calculations. The algorithm, highly parallelizable, is very suitable for high performance computing systems. GPU (Graphics Processing Unit) accelerated computing became very popular more than ten years ago because they have hundreds of computational cores in a reasonable cheap card. In our case, we are going to register the shifting between two images, doing the first approach by FFT based correlation, and later doing the subpixel approach using the technique described before. We consider it as `brute force' method. So we will present a benchmark of the algorithm consisting on a first approach (pixel resolution) and then do subpixel resolution approaching, decreasing the shifting step in every loop achieving a high resolution in few steps. This program will be executed in three different computers. At the end, we will present the results of the computation, with different kind of CPUs and GPUs, checking the accuracy of the method, and the time consumed in each computer, discussing the advantages, disadvantages of the use of GPUs.

Open scientific communication urged

NASA Astrophysics Data System (ADS)

Richman, Barbara T.

In a report released last week the National Academy of Sciences' Panel on Scientific Communication and National Security concluded that the ‘limited and uncertain benefits’ of controls on the dissemination of scientific and technological research are ‘outweighed by the importance of scientific progress, which open communication accelerates, to the overall welfare of the nation.’ The 18-member panel, chaired by Dale R. Corson, president emeritus of Cornell University, was created last spring (Eos, April 20, 1982, p. 241) to examine the delicate balance between open dissemination of scientific and technical information and the U.S. government's desire to protect scientific and technological achievements from being translated into military advantages for our political adversaries.The panel dealt almost exclusively with the relationship between the United States and the Soviet Union but noted that there are ‘clear problems in scientific communication and national security involving Third World countries.’ Further study of this matter is necessary.

The emergence of spatial cyberinfrastructure.

PubMed

Wright, Dawn J; Wang, Shaowen

2011-04-05

Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge.

The emergence of spatial cyberinfrastructure

PubMed Central

Wright, Dawn J.; Wang, Shaowen

2011-01-01

Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge. PMID:21467227

Computer modeling of photodegradation

NASA Technical Reports Server (NTRS)

Guillet, J.

1986-01-01

A computer program to simulate the photodegradation of materials exposed to terrestrial weathering environments is being developed. Input parameters would include the solar spectrum, the daily levels and variations of temperature and relative humidity, and materials such as EVA. A brief description of the program, its operating principles, and how it works was initially described. After that, the presentation focuses on the recent work of simulating aging in a normal, terrestrial day-night cycle. This is significant, as almost all accelerated aging schemes maintain a constant light illumination without a dark cycle, and this may be a critical factor not included in acceleration aging schemes. For outdoor aging, the computer model is indicating that the night dark cycle has a dramatic influence on the chemistry of photothermal degradation, and hints that a dark cycle may be needed in an accelerated aging scheme.

Research | Computational Science | NREL

Science.gov Websites

Research Research NREL's computational science experts use advanced high-performance computing (HPC technologies, thereby accelerating the transformation of our nation's energy system. Enabling High-Impact Research NREL's computational science capabilities enable high-impact research. Some recent examples

Scientific program and abstracts

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

Gerich, C.

1983-01-01

The Fifth International Conference on High-Power Particle Beams is organized jointly by the Lawrence Livermore National Laboratory and Physics International Company. As in the previous conferences in this series, the program includes the following topics: high-power, electron- and ion-beam acceleration and transport; diode physics; high-power particle beam interaction with plasmas and dense targets; particle beam fusion (inertial confinement); collective ion acceleration; particle beam heating of magnetically confined plasmas; and generation of microwave/free-electron lasers.

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.

Tool Support for Software Lookup Table Optimization

DOE PAGES

Wilcox, Chris; Strout, Michelle Mills; Bieman, James M.

2011-01-01

A number of scientific applications are performance-limited by expressions that repeatedly call costly elementary functions. Lookup table (LUT) optimization accelerates the evaluation of such functions by reusing previously computed results. LUT methods can speed up applications that tolerate an approximation of function results, thereby achieving a high level of fuzzy reuse. One problem with LUT optimization is the difficulty of controlling the tradeoff between performance and accuracy. The current practice of manual LUT optimization adds programming effort by requiring extensive experimentation to make this tradeoff, and such hand tuning can obfuscate algorithms. In this paper we describe a methodology andmore » tool implementation to improve the application of software LUT optimization. Our Mesa tool implements source-to-source transformations for C or C++ code to automate the tedious and error-prone aspects of LUT generation such as domain profiling, error analysis, and code generation. We evaluate Mesa with five scientific applications. Our results show a performance improvement of 3.0× and 6.9× for two molecular biology algorithms, 1.4× for a molecular dynamics program, 2.1× to 2.8× for a neural network application, and 4.6× for a hydrology calculation. We find that Mesa enables LUT optimization with more control over accuracy and less effort than manual approaches.« less

Accelerating Science to Action: NGOs Catalyzing Scientific Research using Philanthropic/Corporate Funding

NASA Astrophysics Data System (ADS)

Hamburg, S.

2017-12-01

While government funding of scientific research has been the bedrock of scientific advances in the US, it is seldom quick or directly responsive to societal needs. If we are to effectively respond to the increasingly urgent needs for new science to address the environmental and social challenges faced by humanity and the environment we need to deploy new scientific models to augment government-centric approaches. The Environmental Defense Fund has developed an approach that accelerates the development and uptake of new science in pursuit of science-based policy to fill the gap while government research efforts are initiated. We utilized this approach in developing the data necessary to quantify methane emissions from the oil and gas supply chain. This effort was based on five key principles: studies led by an academic researchers; deployment of multiple methods whenever possible (e.g. top-down and bottom-up); all data made public (identity but not location masked when possible); external scientific review; results released in peer-reviewed scientific journals. The research to quantify methane emissions involved > 150 scientists from 40 institutions, resulting in 35 papers published over four years. In addition to the research community companies operating along the oil and gas value chain participated by providing access to sites/vehicles and funding for a portion of the academic research. The bulk of funding came from philanthropic sources. Overall the use of this alternative research/funding model allowed for the more rapid development of a robust body of policy-relevant knowledge that addressed an issue of high societal interest/value.

Evolution of the Virtualized HPC Infrastructure of Novosibirsk Scientific Center

NASA Astrophysics Data System (ADS)

Adakin, A.; Anisenkov, A.; Belov, S.; Chubarov, D.; Kalyuzhny, V.; Kaplin, V.; Korol, A.; Kuchin, N.; Lomakin, S.; Nikultsev, V.; Skovpen, K.; Sukharev, A.; Zaytsev, A.

2012-12-01

Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies, and Institute of Computational Mathematics and Mathematical Geophysics (ICM&MG). Since each institute has specific requirements on the architecture of computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for a particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM&MG), and a Grid Computing Facility of BINP. A dedicated optical network with the initial bandwidth of 10 Gb/s connecting these three facilities was built in order to make it possible to share the computing resources among the research communities, thus increasing the efficiency of operating the existing computing facilities and offering a common platform for building the computing infrastructure for future scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technology based on XEN and KVM platforms. This contribution gives a thorough review of the present status and future development prospects for the NSC virtualized computing infrastructure and the experience gained while using it for running production data analysis jobs related to HEP experiments being carried out at BINP, especially the KEDR detector experiment at the VEPP-4M electron-positron collider.

The High Energy Solar Physics mission (HESP): Scientific objectives and technical description

NASA Technical Reports Server (NTRS)

Crannell, Carol; Dennis, Brian; Davis, John; Emslie, Gordon; Haerendel, Gerhard; Hudson, High; Hurford, Gordon; Lin, Robert; Ling, James; Pick, Monique

1991-01-01

The High Energy Solar Physics mission offers the opportunity for major breakthroughs in the understanding of the fundamental energy release and particle acceleration processes at the core of the solar flare problem. The following subject areas are covered: the scientific objectives of HESP; what we can expect from the HESP observations; the high energy imaging spectrometer (HEISPEC); the HESP spacecraft; and budget and schedule.

Homage to Professor Meinhart H. Zenk: Crowd accelerated research and innovation.

PubMed

Heinz, Nanna; Møller, Birger Lindberg

2013-07-01

Professor Meinhart H. Zenk has had an enormous impact within the plant biochemistry area. Throughout his entire career he was able to identify and address key scientific issues within chemistry and plant secondary metabolism. Meinhart H. Zenk and his research associates have provided seminal scientific contributions within a multitude of research topics. A hallmark in Meinhart H. Zenk's research has been to rapidly introduce and apply new technologies and to initiate cross-disciplinary collaborations to provide groundbreaking new knowledge within research areas that at the time appeared highly complex and inaccessible to experimentation. He strived and managed to reach scientific excellence. In this way, he was an eminent key mentor within the plant biochemistry research community. Today, few single individuals possess so much knowledge. However, web-based social platforms enable fast and global distribution and sharing of information also including science related matters, unfortunately often prior to assessment of its correctness. Thus the demand of scientific mentoring that Meinhart H. Zenk offered the science community is as important as ever. In the honor of Meinhart H. Zenk, let us keep up that tradition and widen our engagement to encompass the new social media and benefit from the opportunities offered by crowd accelerated innovation. Copyright © 2012 Elsevier Ltd. All rights reserved.

An "Elective Replacement" Approach to Providing Extra Help in Math: The Talent Development Middle Schools' Computer- and Team-Assisted Mathematics Acceleration (CATAMA) Program.

ERIC Educational Resources Information Center

Mac Iver, Douglas J.; Balfanz, Robert; Plank, Stephan B.

1999-01-01

Two studies evaluated the Computer- and Team-Assisted Mathematics Acceleration course (CATAMA) in Talent Development Middle Schools. The first study compared growth in math achievement for 96 seventh-graders (48 of whom participated in CATAMA and 48 of whom did not); the second study gathered data from interviews with, and observations of, CATAMA…

Ion acceleration in a plasma focus

NASA Technical Reports Server (NTRS)

Gary, S. P.

1974-01-01

The electric and magnetic fields associated with anomalous diffusion to the axis of a linear plasma discharge are used to compute representative ion trajectories. Substantial axial acceleration of the ions is demonstrated.

Acceleration of Radiance for Lighting Simulation by Using Parallel Computing with OpenCL

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

Zuo, Wangda; McNeil, Andrew; Wetter, Michael

2011-09-06

We report on the acceleration of annual daylighting simulations for fenestration systems in the Radiance ray-tracing program. The algorithm was optimized to reduce both the redundant data input/output operations and the floating-point operations. To further accelerate the simulation speed, the calculation for matrix multiplications was implemented using parallel computing on a graphics processing unit. We used OpenCL, which is a cross-platform parallel programming language. Numerical experiments show that the combination of the above measures can speed up the annual daylighting simulations 101.7 times or 28.6 times when the sky vector has 146 or 2306 elements, respectively.

QALMA: A computational toolkit for the analysis of quality protocols for medical linear accelerators in radiation therapy

NASA Astrophysics Data System (ADS)

Rahman, Md Mushfiqur; Lei, Yu; Kalantzis, Georgios

2018-01-01

Quality Assurance (QA) for medical linear accelerator (linac) is one of the primary concerns in external beam radiation Therapy. Continued advancements in clinical accelerators and computer control technology make the QA procedures more complex and time consuming which often, adequate software accompanied with specific phantoms is required. To ameliorate that matter, we introduce QALMA (Quality Assurance for Linac with MATLAB), a MALAB toolkit which aims to simplify the quantitative analysis of QA for linac which includes Star-Shot analysis, Picket Fence test, Winston-Lutz test, Multileaf Collimator (MLC) log file analysis and verification of light & radiation field coincidence test.

Accelerator System Model (ASM) user manual with physics and engineering model documentation. ASM version 1.0

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

NONE

1993-07-01

The Accelerator System Model (ASM) is a computer program developed to model proton radiofrequency accelerators and to carry out system level trade studies. The ASM FORTRAN subroutines are incorporated into an intuitive graphical user interface which provides for the {open_quotes}construction{close_quotes} of the accelerator in a window on the computer screen. The interface is based on the Shell for Particle Accelerator Related Codes (SPARC) software technology written for the Macintosh operating system in the C programming language. This User Manual describes the operation and use of the ASM application within the SPARC interface. The Appendix provides a detailed description of themore » physics and engineering models used in ASM. ASM Version 1.0 is joint project of G. H. Gillespie Associates, Inc. and the Accelerator Technology (AT) Division of the Los Alamos National Laboratory. Neither the ASM Version 1.0 software nor this ASM Documentation may be reproduced without the expressed written consent of both the Los Alamos National Laboratory and G. H. Gillespie Associates, Inc.« less

Position Paper: Applying Machine Learning to Software Analysis to Achieve Trusted, Repeatable Scientific Computing

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

Prowell, Stacy J; Symons, Christopher T

2015-01-01

Producing trusted results from high-performance codes is essential for policy and has significant economic impact. We propose combining rigorous analytical methods with machine learning techniques to achieve the goal of repeatable, trustworthy scientific computing.

Embedded ensemble propagation for improving performance, portability, and scalability of uncertainty quantification on emerging computational architectures

DOE PAGES

Phipps, Eric T.; D'Elia, Marta; Edwards, Harold C.; ...

2017-04-18

In this study, quantifying simulation uncertainties is a critical component of rigorous predictive simulation. A key component of this is forward propagation of uncertainties in simulation input data to output quantities of interest. Typical approaches involve repeated sampling of the simulation over the uncertain input data, and can require numerous samples when accurately propagating uncertainties from large numbers of sources. Often simulation processes from sample to sample are similar and much of the data generated from each sample evaluation could be reused. We explore a new method for implementing sampling methods that simultaneously propagates groups of samples together in anmore » embedded fashion, which we call embedded ensemble propagation. We show how this approach takes advantage of properties of modern computer architectures to improve performance by enabling reuse between samples, reducing memory bandwidth requirements, improving memory access patterns, improving opportunities for fine-grained parallelization, and reducing communication costs. We describe a software technique for implementing embedded ensemble propagation based on the use of C++ templates and describe its integration with various scientific computing libraries within Trilinos. We demonstrate improved performance, portability and scalability for the approach applied to the simulation of partial differential equations on a variety of CPU, GPU, and accelerator architectures, including up to 131,072 cores on a Cray XK7 (Titan).« less

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond.

PubMed

Gama-Castro, Socorro; Salgado, Heladia; Santos-Zavaleta, Alberto; Ledezma-Tejeida, Daniela; Muñiz-Rascado, Luis; García-Sotelo, Jair Santiago; Alquicira-Hernández, Kevin; Martínez-Flores, Irma; Pannier, Lucia; Castro-Mondragón, Jaime Abraham; Medina-Rivera, Alejandra; Solano-Lira, Hilda; Bonavides-Martínez, César; Pérez-Rueda, Ernesto; Alquicira-Hernández, Shirley; Porrón-Sotelo, Liliana; López-Fuentes, Alejandra; Hernández-Koutoucheva, Anastasia; Del Moral-Chávez, Víctor; Rinaldi, Fabio; Collado-Vides, Julio

2016-01-04

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for 'neighborhood' genes to known operons and regulons, and computational developments. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Can beaches survive climate change?

USGS Publications Warehouse

Vitousek, Sean; Barnard, Patrick L.; Limber, Patrick W.

2017-01-01

Anthropogenic climate change is driving sea level rise, leading to numerous impacts on the coastal zone, such as increased coastal flooding, beach erosion, cliff failure, saltwater intrusion in aquifers, and groundwater inundation. Many beaches around the world are currently experiencing chronic erosion as a result of gradual, present-day rates of sea level rise (about 3 mm/year) and human-driven restrictions in sand supply (e.g., harbor dredging and river damming). Accelerated sea level rise threatens to worsen coastal erosion and challenge the very existence of natural beaches throughout the world. Understanding and predicting the rates of sea level rise and coastal erosion depends on integrating data on natural systems with computer simulations. Although many computer modeling approaches are available to simulate shoreline change, few are capable of making reliable long-term predictions needed for full adaption or to enhance resilience. Recent advancements have allowed convincing decadal to centennial-scale predictions of shoreline evolution. For example, along 500 km of the Southern California coast, a new model featuring data assimilation predicts that up to 67% of beaches may completely erode by 2100 without large-scale human interventions. In spite of recent advancements, coastal evolution models must continue to improve in their theoretical framework, quantification of accuracy and uncertainty, computational efficiency, predictive capability, and integration with observed data, in order to meet the scientific and engineering challenges produced by a changing climate.

Computational screening of organic polymer dielectrics for novel accelerator technologies

DOE PAGES

Pilania, Ghanshyam; Weis, Eric; Walker, Ethan M.; ...

2018-06-18

The use of infrared lasers to power accelerating dielectric structures is a developing area of research. Within this technology, the choice of the dielectric material forming the accelerating structures, such as the photonic band gap (PBG) structures, is dictated by a range of interrelated factors including their dielectric and optical properties, amenability to photo-polymerization, thermochemical stability and other target performance metrics of the particle accelerator. In this direction, electronic structure theory aided computational screening and design of dielectric materials can play a key role in identifying potential candidate materials with the targeted functionalities to guide experimental synthetic efforts. In anmore » attempt to systematically understand the role of chemistry in controlling the electronic structure and dielectric properties of organic polymeric materials, here we employ empirical screening and density functional theory (DFT) computations, as a part of our multi-step hierarchal screening strategy. Our DFT based analysis focused on the bandgap, dielectric permittivity, and frequency-dependent dielectric losses due to lattice absorption as key properties to down-select promising polymer motifs. In addition to the specific application of dielectric laser acceleration, the general methodology presented here is deemed to be valuable in the design of new insulators with an attractive combination of dielectric properties.« less

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

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

Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less

2011 Computation Directorate Annual Report

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

Crawford, D L

2012-04-11

From its founding in 1952 until today, Lawrence Livermore National Laboratory (LLNL) has made significant strategic investments to develop high performance computing (HPC) and its application to national security and basic science. Now, 60 years later, the Computation Directorate and its myriad resources and capabilities have become a key enabler for LLNL programs and an integral part of the effort to support our nation's nuclear deterrent and, more broadly, national security. In addition, the technological innovation HPC makes possible is seen as vital to the nation's economic vitality. LLNL, along with other national laboratories, is working to make supercomputing capabilitiesmore » and expertise available to industry to boost the nation's global competitiveness. LLNL is on the brink of an exciting milestone with the 2012 deployment of Sequoia, the National Nuclear Security Administration's (NNSA's) 20-petaFLOP/s resource that will apply uncertainty quantification to weapons science. Sequoia will bring LLNL's total computing power to more than 23 petaFLOP/s-all brought to bear on basic science and national security needs. The computing systems at LLNL provide game-changing capabilities. Sequoia and other next-generation platforms will enable predictive simulation in the coming decade and leverage industry trends, such as massively parallel and multicore processors, to run petascale applications. Efficient petascale computing necessitates refining accuracy in materials property data, improving models for known physical processes, identifying and then modeling for missing physics, quantifying uncertainty, and enhancing the performance of complex models and algorithms in macroscale simulation codes. Nearly 15 years ago, NNSA's Accelerated Strategic Computing Initiative (ASCI), now called the Advanced Simulation and Computing (ASC) Program, was the critical element needed to shift from test-based confidence to science-based confidence. Specifically, ASCI/ASC accelerated the development of simulation capabilities necessary to ensure confidence in the nuclear stockpile-far exceeding what might have been achieved in the absence of a focused initiative. While stockpile stewardship research pushed LLNL scientists to develop new computer codes, better simulation methods, and improved visualization technologies, this work also stimulated the exploration of HPC applications beyond the standard sponsor base. As LLNL advances to a petascale platform and pursues exascale computing (1,000 times faster than Sequoia), ASC will be paramount to achieving predictive simulation and uncertainty quantification. Predictive simulation and quantifying the uncertainty of numerical predictions where little-to-no data exists demands exascale computing and represents an expanding area of scientific research important not only to nuclear weapons, but to nuclear attribution, nuclear reactor design, and understanding global climate issues, among other fields. Aside from these lofty goals and challenges, computing at LLNL is anything but 'business as usual.' International competition in supercomputing is nothing new, but the HPC community is now operating in an expanded, more aggressive climate of global competitiveness. More countries understand how science and technology research and development are inextricably linked to economic prosperity, and they are aggressively pursuing ways to integrate HPC technologies into their native industrial and consumer products. In the interest of the nation's economic security and the science and technology that underpins it, LLNL is expanding its portfolio and forging new collaborations. We must ensure that HPC remains an asymmetric engine of innovation for the Laboratory and for the U.S. and, in doing so, protect our research and development dynamism and the prosperity it makes possible. One untapped area of opportunity LLNL is pursuing is to help U.S. industry understand how supercomputing can benefit their business. Industrial investment in HPC applications has historically been limited by the prohibitive cost of entry, the inaccessibility of software to run the powerful systems, and the years it takes to grow the expertise to develop codes and run them in an optimal way. LLNL is helping industry better compete in the global market place by providing access to some of the world's most powerful computing systems, the tools to run them, and the experts who are adept at using them. Our scientists are collaborating side by side with industrial partners to develop solutions to some of industry's toughest problems. The goal of the Livermore Valley Open Campus High Performance Computing Innovation Center is to allow American industry the opportunity to harness the power of supercomputing by leveraging the scientific and computational expertise at LLNL in order to gain a competitive advantage in the global economy.« less

A link between occupant and vehicle accelerations during common driving tasks.

PubMed

Mathias, Anne C; Shibata, Peggy A; Sprague, James K

2014-01-01

When evaluating occupant motions during driving tasks, it is desirable to have a well-established correlation between vehicle and occupant accelerations. Therefore, this study demonstrated a methodology to quantify accelerations experienced by the driver of a passenger vehicle and compare them to associated vehicle motions. Acceleration levels were measured at the seat and the driver’s head, cervical spine, and lumbar spine during six non-collision driving tasks. Tasks included mounting a 127 mm (5 in) -high curb, crossing railroad tracks, driving on a rough road, braking heavily from 13.4 m/s (30 mph), having a 89 mm (3.5 in)-diameter roller sequentially pass under two tires, and dropping one tire from a 171-mm (6.75 in) height. The driver experienced peak resultant accelerations of similar magnitudes across all trials. Peak body accelerations were less than 1.2 g, including 0.82 g lumbar acceleration during heavy braking and 0.88 g head acceleration during the curb mount. These preliminary measurements are comparable to or lower than accelerations experienced during non-driving activities such as sitting quickly. This study contributes to the scientific understanding of accelerations experienced by vehicle occupants and demonstrates the potential to relate vehicle and occupant accelerations during common driving activities that do not involve collisions.

Strategic Reading, Ontologies, and the Future of Scientific Publishing

NASA Astrophysics Data System (ADS)

Renear, Allen H.; Palmer, Carole L.

2009-08-01

The revolution in scientific publishing that has been promised since the 1980s is about to take place. Scientists have always read strategically, working with many articles simultaneously to search, filter, scan, link, annotate, and analyze fragments of content. An observed recent increase in strategic reading in the online environment will soon be further intensified by two current trends: (i) the widespread use of digital indexing, retrieval, and navigation resources and (ii) the emergence within many scientific disciplines of interoperable ontologies. Accelerated and enhanced by reading tools that take advantage of ontologies, reading practices will become even more rapid and indirect, transforming the ways in which scientists engage the literature and shaping the evolution of scientific publishing.

The role of the mechanical clock in medieval science.

PubMed

Álvarez, Víctor Pérez

2015-03-01

The invention and spread of the mechanical clock is a complex and multifaceted historical phenomenon. Some of these facets, such as its social impact, have been widely studied, but their scientific dimensions have often been dismissed. The mechanical clock was probably born as a scientific instrument for driving a model of the universe, and not only natural philosophers but also kings, nobles and other members of the social elites showed an interest in clocks as scientific instruments. Public clocks later spread a new way of telling time based on equal hours, laying the foundations for changes in time consciousness that would accelerate scientific thinking. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantum Testbeds Stakeholder Workshop (QTSW) Report meeting purpose and agenda.

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

Hebner, Gregory A.

Quantum computing (QC) is a promising early-stage technology with the potential to provide scientific computing capabilities far beyond what is possible with even an Exascale computer in specific problems of relevance to the Office of Science. These include (but are not limited to) materials modeling, molecular dynamics, and quantum chromodynamics. However, commercial QC systems are not yet available and the technical maturity of current QC hardware, software, algorithms, and systems integration is woefully incomplete. Thus, there is a significant opportunity for DOE to define the technology building blocks, and solve the system integration issues to enable a revolutionary tool. Oncemore » realized, QC will have world changing impact on economic competitiveness, the scientific enterprise, and citizen well-being. Prior to this workshop, DOE / Office of Advanced Scientific Computing Research (ASCR) hosted a workshop in 2015 to explore QC scientific applications. The goal of that workshop was to assess the viability of QC technologies to meet the computational requirements in support of DOE’s science and energy mission and to identify the potential impact of these technologies.« less

Klynac: Compact Linear Accelerator with Integrated Power Supply

NASA Astrophysics Data System (ADS)

Malyzhenkov, A. V.

Accelerators and accelerator-based light sources have a wide range of applications in science, engineering technology and medicine. Today the scientific community is working towards improving the quality of the accelerated beam and its parameters, while trying to develop technology for reducing accelerator size. This work describes a design of a compact linear accelerator (linac) prototype: resonant Klynac device, which is a combined linear accelerator and its power supply - klystron. The intended purpose of a Klynac device is to provide a compact and inexpensive alternative to a conventional 1 to 6 MeV accelerator, which typically requires a separate RF source, accelerator itself and all the associated hardware. Because the Klynac is a single structure, it has the potential to be much less sensitive to temperature variations than a system with separate klystron and linac. We start by introducing a simplified theoretical model for a Klynac device. We then demonstrate how a prototype is designed step-by-step using Particle-In-Cell simulation studies for mono-resonant and bi-resonant structures. Finally, we discuss design options from a stability point of view and required input power as well as behavior of competing modes for the actual built device.

Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

DOE PAGES

Haidar, Azzam; Jagode, Heike; Vaccaro, Phil; ...

2018-03-22

The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

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

Haidar, Azzam; Jagode, Heike; Vaccaro, Phil

The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

A Computing Environment to Support Repeatable Scientific Big Data Experimentation of World-Wide Scientific Literature

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

Schlicher, Bob G; Kulesz, James J; Abercrombie, Robert K

A principal tenant of the scientific method is that experiments must be repeatable and relies on ceteris paribus (i.e., all other things being equal). As a scientific community, involved in data sciences, we must investigate ways to establish an environment where experiments can be repeated. We can no longer allude to where the data comes from, we must add rigor to the data collection and management process from which our analysis is conducted. This paper describes a computing environment to support repeatable scientific big data experimentation of world-wide scientific literature, and recommends a system that is housed at the Oakmore » Ridge National Laboratory in order to provide value to investigators from government agencies, academic institutions, and industry entities. The described computing environment also adheres to the recently instituted digital data management plan mandated by multiple US government agencies, which involves all stages of the digital data life cycle including capture, analysis, sharing, and preservation. It particularly focuses on the sharing and preservation of digital research data. The details of this computing environment are explained within the context of cloud services by the three layer classification of Software as a Service , Platform as a Service , and Infrastructure as a Service .« less

GPU-accelerated computation of electron transfer.

PubMed

Höfinger, Siegfried; Acocella, Angela; Pop, Sergiu C; Narumi, Tetsu; Yasuoka, Kenji; Beu, Titus; Zerbetto, Francesco

2012-11-05

Electron transfer is a fundamental process that can be studied with the help of computer simulation. The underlying quantum mechanical description renders the problem a computationally intensive application. In this study, we probe the graphics processing unit (GPU) for suitability to this type of problem. Time-critical components are identified via profiling of an existing implementation and several different variants are tested involving the GPU at increasing levels of abstraction. A publicly available library supporting basic linear algebra operations on the GPU turns out to accelerate the computation approximately 50-fold with minor dependence on actual problem size. The performance gain does not compromise numerical accuracy and is of significant value for practical purposes. Copyright © 2012 Wiley Periodicals, Inc.

Physics through the 1990s: Nuclear physics

NASA Technical Reports Server (NTRS)

1986-01-01

The volume begins with a non-mathematical introduction to nuclear physics. A description of the major advances in the field follows, with chapters on nuclear structure and dynamics, fundamental forces in the nucleus, and nuclei under extreme conditions of temperature, density, and spin. Impacts of nuclear physics on astrophysics and the scientific and societal benefits of nuclear physics are then discussed. Another section deals with scientific frontiers, describing research into the realm of the quark-gluon plasma; the changing description of nuclear matter, specifically the use of the quark model; and the implications of the standard model and grand unified theories of elementary-particle physics; and finishes with recommendations and priorities for nuclear physics research facilities, instrumentation, accelerators, theory, education, and data bases. Appended are a list of national accelerator facilities, a list of reviewers, a bibliography, and a glossary.