USSR and Eastern Europe Scientific Abstracts, Cybernetics, Computers, and Automation Technology, Number 26

DTIC Science & Technology

1977-01-26

Sisteme Matematicheskogo Obespecheniya YeS EVM [ Applied Programs in the Software System for the Unified System of Computers], by A. Ye. Fateyev, A. I...computerized systems are most effective in large production complexes , in which the level of utilization of computers can be as high as 500,000...performance of these tasks could be furthered by the complex introduction of electronic computers in automated control systems. The creation of ASU

Atomic switch networks-nanoarchitectonic design of a complex system for natural computing.

PubMed

Demis, E C; Aguilera, R; Sillin, H O; Scharnhorst, K; Sandouk, E J; Aono, M; Stieg, A Z; Gimzewski, J K

2015-05-22

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Predicting Development of Mathematical Word Problem Solving Across the Intermediate Grades

PubMed Central

Tolar, Tammy D.; Fuchs, Lynn; Cirino, Paul T.; Fuchs, Douglas; Hamlett, Carol L.; Fletcher, Jack M.

2012-01-01

This study addressed predictors of the development of word problem solving (WPS) across the intermediate grades. At beginning of 3rd grade, 4 cohorts of students (N = 261) were measured on computation, language, nonverbal reasoning skills, and attentive behavior and were assessed 4 times from beginning of 3rd through end of 5th grade on 2 measures of WPS at low and high levels of complexity. Language skills were related to initial performance at both levels of complexity and did not predict growth at either level. Computational skills had an effect on initial performance in low- but not high-complexity problems and did not predict growth at either level of complexity. Attentive behavior did not predict initial performance but did predict growth in low-complexity, whereas it predicted initial performance but not growth for high-complexity problems. Nonverbal reasoning predicted initial performance and growth for low-complexity WPS, but only growth for high-complexity WPS. This evidence suggests that although mathematical structure is fixed, different cognitive resources may act as limiting factors in WPS development when the WPS context is varied. PMID:23325985

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

USGS Publications Warehouse

O'Donnell, Michael

2015-01-01

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

Complexity control algorithm based on adaptive mode selection for interframe coding in high efficiency video coding

NASA Astrophysics Data System (ADS)

Chen, Gang; Yang, Bing; Zhang, Xiaoyun; Gao, Zhiyong

2017-07-01

The latest high efficiency video coding (HEVC) standard significantly increases the encoding complexity for improving its coding efficiency. Due to the limited computational capability of handheld devices, complexity constrained video coding has drawn great attention in recent years. A complexity control algorithm based on adaptive mode selection is proposed for interframe coding in HEVC. Considering the direct proportionality between encoding time and computational complexity, the computational complexity is measured in terms of encoding time. First, complexity is mapped to a target in terms of prediction modes. Then, an adaptive mode selection algorithm is proposed for the mode decision process. Specifically, the optimal mode combination scheme that is chosen through offline statistics is developed at low complexity. If the complexity budget has not been used up, an adaptive mode sorting method is employed to further improve coding efficiency. The experimental results show that the proposed algorithm achieves a very large complexity control range (as low as 10%) for the HEVC encoder while maintaining good rate-distortion performance. For the lowdelayP condition, compared with the direct resource allocation method and the state-of-the-art method, an average gain of 0.63 and 0.17 dB in BDPSNR is observed for 18 sequences when the target complexity is around 40%.

Engineering and Computing Portal to Solve Environmental Problems

NASA Astrophysics Data System (ADS)

Gudov, A. M.; Zavozkin, S. Y.; Sotnikov, I. Y.

2018-01-01

This paper describes architecture and services of the Engineering and Computing Portal, which is considered to be a complex solution that provides access to high-performance computing resources, enables to carry out computational experiments, teach parallel technologies and solve computing tasks, including technogenic safety ones.

Parallel Computing:. Some Activities in High Energy Physics

NASA Astrophysics Data System (ADS)

Willers, Ian

This paper examines some activities in High Energy Physics that utilise parallel computing. The topic includes all computing from the proposed SIMD front end detectors, the farming applications, high-powered RISC processors and the large machines in the computer centers. We start by looking at the motivation behind using parallelism for general purpose computing. The developments around farming are then described from its simplest form to the more complex system in Fermilab. Finally, there is a list of some developments that are happening close to the experiments.

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

PubMed

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

Computer-Assisted Monitoring Of A Complex System

NASA Technical Reports Server (NTRS)

Beil, Bob J.; Mickelson, Eric M.; Sterritt, John M.; Costantino, Rob W.; Houvener, Bob C.; Super, Mike A.

1995-01-01

Propulsion System Advisor (PSA) computer-based system assists engineers and technicians in analyzing masses of sensory data indicative of operating conditions of space shuttle propulsion system during pre-launch and launch activities. Designed solely for monitoring; does not perform any control functions. Although PSA developed for highly specialized application, serves as prototype of noncontrolling, computer-based subsystems for monitoring other complex systems like electric-power-distribution networks and factories.

PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.

PubMed

Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar

2014-01-01

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

Efficient computation of the joint sample frequency spectra for multiple populations.

PubMed

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

Efficient computation of the joint sample frequency spectra for multiple populations

PubMed Central

Kamm, John A.; Terhorst, Jonathan; Song, Yun S.

2016-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity. PMID:28239248

Atomic switch networks—nanoarchitectonic design of a complex system for natural computing

NASA Astrophysics Data System (ADS)

Demis, E. C.; Aguilera, R.; Sillin, H. O.; Scharnhorst, K.; Sandouk, E. J.; Aono, M.; Stieg, A. Z.; Gimzewski, J. K.

2015-05-01

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing—a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

Design consideration in constructing high performance embedded Knowledge-Based Systems (KBS)

NASA Technical Reports Server (NTRS)

Dalton, Shelly D.; Daley, Philip C.

1988-01-01

As the hardware trends for artificial intelligence (AI) involve more and more complexity, the process of optimizing the computer system design for a particular problem will also increase in complexity. Space applications of knowledge based systems (KBS) will often require an ability to perform both numerically intensive vector computations and real time symbolic computations. Although parallel machines can theoretically achieve the speeds necessary for most of these problems, if the application itself is not highly parallel, the machine's power cannot be utilized. A scheme is presented which will provide the computer systems engineer with a tool for analyzing machines with various configurations of array, symbolic, scaler, and multiprocessors. High speed networks and interconnections make customized, distributed, intelligent systems feasible for the application of AI in space. The method presented can be used to optimize such AI system configurations and to make comparisons between existing computer systems. It is an open question whether or not, for a given mission requirement, a suitable computer system design can be constructed for any amount of money.

Fluid/Structure Interaction Studies of Aircraft Using High Fidelity Equations on Parallel Computers

NASA Technical Reports Server (NTRS)

Guruswamy, Guru; VanDalsem, William (Technical Monitor)

1994-01-01

Abstract Aeroelasticity which involves strong coupling of fluids, structures and controls is an important element in designing an aircraft. Computational aeroelasticity using low fidelity methods such as the linear aerodynamic flow equations coupled with the modal structural equations are well advanced. Though these low fidelity approaches are computationally less intensive, they are not adequate for the analysis of modern aircraft such as High Speed Civil Transport (HSCT) and Advanced Subsonic Transport (AST) which can experience complex flow/structure interactions. HSCT can experience vortex induced aeroelastic oscillations whereas AST can experience transonic buffet associated structural oscillations. Both aircraft may experience a dip in the flutter speed at the transonic regime. For accurate aeroelastic computations at these complex fluid/structure interaction situations, high fidelity equations such as the Navier-Stokes for fluids and the finite-elements for structures are needed. Computations using these high fidelity equations require large computational resources both in memory and speed. Current conventional super computers have reached their limitations both in memory and speed. As a result, parallel computers have evolved to overcome the limitations of conventional computers. This paper will address the transition that is taking place in computational aeroelasticity from conventional computers to parallel computers. The paper will address special techniques needed to take advantage of the architecture of new parallel computers. Results will be illustrated from computations made on iPSC/860 and IBM SP2 computer by using ENSAERO code that directly couples the Euler/Navier-Stokes flow equations with high resolution finite-element structural equations.

Comparison of computed tomography and complex motion tomography in the evaluation of cholesteatoma

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

Shaffer, K.A.

1984-08-01

High-resolution axial and coronal computed tomographic (CT) scans were compared with coronal and sagittal complex motion tomograms in patients with suspected middle ear cholesteatomas. Information on CT scans equaled or exceeded that on conventional complex motion tomograms in 16 of 17 patients, and in 11 it provided additional information. Soft-tissue resolution was superior with CT. In 14 patients who underwent surgery, CT provided information that was valuable to the surgeon. On the basis of this study, high-resolution CT is recommended as the preferred method for evaluating most patients with cholesteatomas of the temporal bone.

ASIC For Complex Fixed-Point Arithmetic

NASA Technical Reports Server (NTRS)

Petilli, Stephen G.; Grimm, Michael J.; Olson, Erlend M.

1995-01-01

Application-specific integrated circuit (ASIC) performs 24-bit, fixed-point arithmetic operations on arrays of complex-valued input data. High-performance, wide-band arithmetic logic unit (ALU) designed for use in computing fast Fourier transforms (FFTs) and for performing ditigal filtering functions. Other applications include general computations involved in analysis of spectra and digital signal processing.

Computational structure analysis of biomacromolecule complexes by interface geometry.

PubMed

Mahdavi, Sedigheh; Salehzadeh-Yazdi, Ali; Mohades, Ali; Masoudi-Nejad, Ali

2013-12-01

The ability to analyze and compare protein-nucleic acid and protein-protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein-nucleic acid and protein-protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diagram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA-protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ordinal optimization and its application to complex deterministic problems

NASA Astrophysics Data System (ADS)

Yang, Mike Shang-Yu

1998-10-01

We present in this thesis a new perspective to approach a general class of optimization problems characterized by large deterministic complexities. Many problems of real-world concerns today lack analyzable structures and almost always involve high level of difficulties and complexities in the evaluation process. Advances in computer technology allow us to build computer models to simulate the evaluation process through numerical means, but the burden of high complexities remains to tax the simulation with an exorbitant computing cost for each evaluation. Such a resource requirement makes local fine-tuning of a known design difficult under most circumstances, let alone global optimization. Kolmogorov equivalence of complexity and randomness in computation theory is introduced to resolve this difficulty by converting the complex deterministic model to a stochastic pseudo-model composed of a simple deterministic component and a white-noise like stochastic term. The resulting randomness is then dealt with by a noise-robust approach called Ordinal Optimization. Ordinal Optimization utilizes Goal Softening and Ordinal Comparison to achieve an efficient and quantifiable selection of designs in the initial search process. The approach is substantiated by a case study in the turbine blade manufacturing process. The problem involves the optimization of the manufacturing process of the integrally bladed rotor in the turbine engines of U.S. Air Force fighter jets. The intertwining interactions among the material, thermomechanical, and geometrical changes makes the current FEM approach prohibitively uneconomical in the optimization process. The generalized OO approach to complex deterministic problems is applied here with great success. Empirical results indicate a saving of nearly 95% in the computing cost.

Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics

NASA Astrophysics Data System (ADS)

Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey

2018-02-01

At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

Computational Aspects of Heat Transfer in Structures

NASA Technical Reports Server (NTRS)

Adelman, H. M. (Compiler)

1982-01-01

Techniques for the computation of heat transfer and associated phenomena in complex structures are examined with an emphasis on reentry flight vehicle structures. Analysis methods, computer programs, thermal analysis of large space structures and high speed vehicles, and the impact of computer systems are addressed.

Combinatorial computational chemistry approach for materials design: applications in deNOx catalysis, Fischer-Tropsch synthesis, lanthanoid complex, and lithium ion secondary battery.

PubMed

Koyama, Michihisa; Tsuboi, Hideyuki; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A; Miyamoto, Akira

2007-02-01

Computational chemistry can provide fundamental knowledge regarding various aspects of materials. While its impact in scientific research is greatly increasing, its contributions to industrially important issues are far from satisfactory. In order to realize industrial innovation by computational chemistry, a new concept "combinatorial computational chemistry" has been proposed by introducing the concept of combinatorial chemistry to computational chemistry. This combinatorial computational chemistry approach enables theoretical high-throughput screening for materials design. In this manuscript, we review the successful applications of combinatorial computational chemistry to deNO(x) catalysts, Fischer-Tropsch catalysts, lanthanoid complex catalysts, and cathodes of the lithium ion secondary battery.

High level language for measurement complex control based on the computer E-100I

NASA Technical Reports Server (NTRS)

Zubkov, B. V.

1980-01-01

A high level language was designed to control the process of conducting an experiment using the computer "Elektrinika-1001". Program examples are given to control the measuring and actuating devices. The procedure of including these programs in the suggested high level language is described.

Some Observations on the Current Status of Performing Finite Element Analyses

NASA Technical Reports Server (NTRS)

Raju, Ivatury S.; Knight, Norman F., Jr; Shivakumar, Kunigal N.

2015-01-01

Aerospace structures are complex high-performance structures. Advances in reliable and efficient computing and modeling tools are enabling analysts to consider complex configurations, build complex finite element models, and perform analysis rapidly. Many of the early career engineers of today are very proficient in the usage of modern computers, computing engines, complex software systems, and visualization tools. These young engineers are becoming increasingly efficient in building complex 3D models of complicated aerospace components. However, the current trends demonstrate blind acceptance of the results of the finite element analysis results. This paper is aimed at raising an awareness of this situation. Examples of the common encounters are presented. To overcome the current trends, some guidelines and suggestions for analysts, senior engineers, and educators are offered.

An Automated Approach to Very High Order Aeroacoustic Computations in Complex Geometries

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.; Goodrich, John W.

2000-01-01

Computational aeroacoustics requires efficient, high-resolution simulation tools. And for smooth problems, this is best accomplished with very high order in space and time methods on small stencils. But the complexity of highly accurate numerical methods can inhibit their practical application, especially in irregular geometries. This complexity is reduced by using a special form of Hermite divided-difference spatial interpolation on Cartesian grids, and a Cauchy-Kowalewslci recursion procedure for time advancement. In addition, a stencil constraint tree reduces the complexity of interpolating grid points that are located near wall boundaries. These procedures are used to automatically develop and implement very high order methods (>15) for solving the linearized Euler equations that can achieve less than one grid point per wavelength resolution away from boundaries by including spatial derivatives of the primitive variables at each grid point. The accuracy of stable surface treatments is currently limited to 11th order for grid aligned boundaries and to 2nd order for irregular boundaries.

Computationally efficient algorithm for high sampling-frequency operation of active noise control

NASA Astrophysics Data System (ADS)

Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati

2015-05-01

In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.

An electrostatic model for the determination of magnetic anisotropy in dysprosium complexes.

PubMed

Chilton, Nicholas F; Collison, David; McInnes, Eric J L; Winpenny, Richard E P; Soncini, Alessandro

2013-01-01

Understanding the anisotropic electronic structure of lanthanide complexes is important in areas as diverse as magnetic resonance imaging, luminescent cell labelling and quantum computing. Here we present an intuitive strategy based on a simple electrostatic method, capable of predicting the magnetic anisotropy of dysprosium(III) complexes, even in low symmetry. The strategy relies only on knowing the X-ray structure of the complex and the well-established observation that, in the absence of high symmetry, the ground state of dysprosium(III) is a doublet quantized along the anisotropy axis with an angular momentum quantum number mJ=±(15)/2. The magnetic anisotropy axis of 14 low-symmetry monometallic dysprosium(III) complexes computed via high-level ab initio calculations are very well reproduced by our electrostatic model. Furthermore, we show that the magnetic anisotropy is equally well predicted in a selection of low-symmetry polymetallic complexes.

A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization

PubMed Central

Sánchez-Rodríguez, David; Hernández-Morera, Pablo; Quinteiro, José Ma.; Alonso-González, Itziar

2015-01-01

Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have. PMID:26110413

Cognitive engineering models: A prerequisite to the design of human-computer interaction in complex dynamic systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1993-01-01

This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.

Visual saliency-based fast intracoding algorithm for high efficiency video coding

NASA Astrophysics Data System (ADS)

Zhou, Xin; Shi, Guangming; Zhou, Wei; Duan, Zhemin

2017-01-01

Intraprediction has been significantly improved in high efficiency video coding over H.264/AVC with quad-tree-based coding unit (CU) structure from size 64×64 to 8×8 and more prediction modes. However, these techniques cause a dramatic increase in computational complexity. An intracoding algorithm is proposed that consists of perceptual fast CU size decision algorithm and fast intraprediction mode decision algorithm. First, based on the visual saliency detection, an adaptive and fast CU size decision method is proposed to alleviate intraencoding complexity. Furthermore, a fast intraprediction mode decision algorithm with step halving rough mode decision method and early modes pruning algorithm is presented to selectively check the potential modes and effectively reduce the complexity of computation. Experimental results show that our proposed fast method reduces the computational complexity of the current HM to about 57% in encoding time with only 0.37% increases in BD rate. Meanwhile, the proposed fast algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.

Role of HPC in Advancing Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.

2004-01-01

On behalf of the High Performance Computing and Modernization Program (HPCMP) and NASA Advanced Supercomputing Division (NAS) a study is conducted to assess the role of supercomputers on computational aeroelasticity of aerospace vehicles. The study is mostly based on the responses to a web based questionnaire that was designed to capture the nuances of high performance computational aeroelasticity, particularly on parallel computers. A procedure is presented to assign a fidelity-complexity index to each application. Case studies based on major applications using HPCMP resources are presented.

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Queueing Network Models for Parallel Processing of Task Systems: an Operational Approach

NASA Technical Reports Server (NTRS)

Mak, Victor W. K.

1986-01-01

Computer performance modeling of possibly complex computations running on highly concurrent systems is considered. Earlier works in this area either dealt with a very simple program structure or resulted in methods with exponential complexity. An efficient procedure is developed to compute the performance measures for series-parallel-reducible task systems using queueing network models. The procedure is based on the concept of hierarchical decomposition and a new operational approach. Numerical results for three test cases are presented and compared to those of simulations.

Direct Comparison of a Tablet Computer and a Personal Digital Assistant for Point-of-Care Documentation in Eye Care

PubMed Central

Silvey, Garry M.; Macri, Jennifer M.; Lee, Paul P.; Lobach, David F.

2005-01-01

New mobile computing devices including personal digital assistants (PDAs) and tablet computers have emerged to facilitate data collection at the point of care. Unfortunately, little research has been reported regarding which device is optimal for a given care setting. In this study we created and compared functionally identical applications on a Palm operating system-based PDA and a Windows-based tablet computer for point-of-care documentation of clinical observations by eye care professionals when caring for patients with diabetes. Eye-care professionals compared the devices through focus group sessions and through validated usability surveys. We found that the application on the tablet computer was preferred over the PDA for documenting the complex data related to eye care. Our findings suggest that the selection of a mobile computing platform depends on the amount and complexity of the data to be entered; the tablet computer functions better for high volume, complex data entry, and the PDA, for low volume, simple data entry. PMID:16779128

The use of methods of structural optimization at the stage of designing high-rise buildings with steel construction

NASA Astrophysics Data System (ADS)

Vasilkin, Andrey

2018-03-01

The more designing solutions at the search stage for design for high-rise buildings can be synthesized by the engineer, the more likely that the final adopted version will be the most efficient and economical. However, in modern market conditions, taking into account the complexity and responsibility of high-rise buildings the designer does not have the necessary time to develop, analyze and compare any significant number of options. To solve this problem, it is expedient to use the high potential of computer-aided designing. To implement automated search for design solutions, it is proposed to develop the computing facilities, the application of which will significantly increase the productivity of the designer and reduce the complexity of designing. Methods of structural and parametric optimization have been adopted as the basis of the computing facilities. Their efficiency in the synthesis of design solutions is shown, also the schemes, that illustrate and explain the introduction of structural optimization in the traditional design of steel frames, are constructed. To solve the problem of synthesis and comparison of design solutions for steel frames, it is proposed to develop the computing facilities that significantly reduces the complexity of search designing and based on the use of methods of structural and parametric optimization.

Remote control system for high-perfomance computer simulation of crystal growth by the PFC method

NASA Astrophysics Data System (ADS)

Pavlyuk, Evgeny; Starodumov, Ilya; Osipov, Sergei

2017-04-01

Modeling of crystallization process by the phase field crystal method (PFC) - one of the important directions of modern computational materials science. In this paper, the practical side of the computer simulation of the crystallization process by the PFC method is investigated. To solve problems using this method, it is necessary to use high-performance computing clusters, data storage systems and other often expensive complex computer systems. Access to such resources is often limited, unstable and accompanied by various administrative problems. In addition, the variety of software and settings of different computing clusters sometimes does not allow researchers to use unified program code. There is a need to adapt the program code for each configuration of the computer complex. The practical experience of the authors has shown that the creation of a special control system for computing with the possibility of remote use can greatly simplify the implementation of simulations and increase the performance of scientific research. In current paper we show the principal idea of such a system and justify its efficiency.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

Massive parallelization of serial inference algorithms for a complex generalized linear model

PubMed Central

Suchard, Marc A.; Simpson, Shawn E.; Zorych, Ivan; Ryan, Patrick; Madigan, David

2014-01-01

Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. We focus on optimization and massive parallelization of cyclic coordinate descent approaches to fit a conditioned generalized linear model involving tens of millions of observations and thousands of predictors in a Bayesian context. We find orders-of-magnitude improvement in overall run-time. Coordinate descent approaches are ubiquitous in high-dimensional statistics and the algorithms we propose open up exciting new methodological possibilities with the potential to significantly improve drug safety. PMID:25328363

Diffraction Correlation to Reconstruct Highly Strained Particles

NASA Astrophysics Data System (ADS)

Brown, Douglas; Harder, Ross; Clark, Jesse; Kim, J. W.; Kiefer, Boris; Fullerton, Eric; Shpyrko, Oleg; Fohtung, Edwin

2015-03-01

Through the use of coherent x-ray diffraction a three-dimensional diffraction pattern of a highly strained nano-crystal can be recorded in reciprocal space by a detector. Only the intensities are recorded, resulting in a loss of the complex phase. The recorded diffraction pattern therefore requires computational processing to reconstruct the density and complex distribution of the diffracted nano-crystal. For highly strained crystals, standard methods using HIO and ER algorithms are no longer sufficient to reconstruct the diffraction pattern. Our solution is to correlate the symmetry in reciprocal space to generate an a priori shape constraint to guide the computational reconstruction of the diffraction pattern. This approach has improved the ability to accurately reconstruct highly strained nano-crystals.

Accurate complex scaling of three dimensional numerical potentials

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

Cerioni, Alessandro; Genovese, Luigi; Duchemin, Ivan

2013-05-28

The complex scaling method, which consists in continuing spatial coordinates into the complex plane, is a well-established method that allows to compute resonant eigenfunctions of the time-independent Schroedinger operator. Whenever it is desirable to apply the complex scaling to investigate resonances in physical systems defined on numerical discrete grids, the most direct approach relies on the application of a similarity transformation to the original, unscaled Hamiltonian. We show that such an approach can be conveniently implemented in the Daubechies wavelet basis set, featuring a very promising level of generality, high accuracy, and no need for artificial convergence parameters. Complex scalingmore » of three dimensional numerical potentials can be efficiently and accurately performed. By carrying out an illustrative resonant state computation in the case of a one-dimensional model potential, we then show that our wavelet-based approach may disclose new exciting opportunities in the field of computational non-Hermitian quantum mechanics.« less

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

PubMed

Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

PubMed Central

Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

Biclustering Protein Complex Interactions with a Biclique FindingAlgorithm

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

Ding, Chris; Zhang, Anne Ya; Holbrook, Stephen

2006-12-01

Biclustering has many applications in text mining, web clickstream mining, and bioinformatics. When data entries are binary, the tightest biclusters become bicliques. We propose a flexible and highly efficient algorithm to compute bicliques. We first generalize the Motzkin-Straus formalism for computing the maximal clique from L{sub 1} constraint to L{sub p} constraint, which enables us to provide a generalized Motzkin-Straus formalism for computing maximal-edge bicliques. By adjusting parameters, the algorithm can favor biclusters with more rows less columns, or vice verse, thus increasing the flexibility of the targeted biclusters. We then propose an algorithm to solve the generalized Motzkin-Straus optimizationmore » problem. The algorithm is provably convergent and has a computational complexity of O(|E|) where |E| is the number of edges. It relies on a matrix vector multiplication and runs efficiently on most current computer architectures. Using this algorithm, we bicluster the yeast protein complex interaction network. We find that biclustering protein complexes at the protein level does not clearly reflect the functional linkage among protein complexes in many cases, while biclustering at protein domain level can reveal many underlying linkages. We show several new biologically significant results.« less

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Computational complexities and storage requirements of some Riccati equation solvers

NASA Technical Reports Server (NTRS)

Utku, Senol; Garba, John A.; Ramesh, A. V.

1989-01-01

The linear optimal control problem of an nth-order time-invariant dynamic system with a quadratic performance functional is usually solved by the Hamilton-Jacobi approach. This leads to the solution of the differential matrix Riccati equation with a terminal condition. The bulk of the computation for the optimal control problem is related to the solution of this equation. There are various algorithms in the literature for solving the matrix Riccati equation. However, computational complexities and storage requirements as a function of numbers of state variables, control variables, and sensors are not available for all these algorithms. In this work, the computational complexities and storage requirements for some of these algorithms are given. These expressions show the immensity of the computational requirements of the algorithms in solving the Riccati equation for large-order systems such as the control of highly flexible space structures. The expressions are also needed to compute the speedup and efficiency of any implementation of these algorithms on concurrent machines.

Highly Selective Adsorption of Ethylene over Ethane in a MOF Featuring the Combination of Open Metal Site and -Complexation

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

Zhang, Yiming; Li, Baiyan; Wu, Zili

The introduction of the combination of open metal site (OMS) and -complexation into MOF has led to very high ethylene/ethane adsorption selectivity at 318K, as illustrated in the context of MIL-101-Cr-SO 3Ag. The interactions with ethylene from both OMS and -complexation in MIL-101-Cr-SO 3Ag have been investigated by in situ IR spectroscopic studies and computational calculations, which suggest -complexation contributes dominantly to the high ethylene/ethane adsorption selectivity.

Highly Selective Adsorption of Ethylene over Ethane in a MOF Featuring the Combination of Open Metal Site and -Complexation

DOE PAGES

Zhang, Yiming; Li, Baiyan; Wu, Zili; ...

2015-01-09

The introduction of the combination of open metal site (OMS) and -complexation into MOF has led to very high ethylene/ethane adsorption selectivity at 318K, as illustrated in the context of MIL-101-Cr-SO 3Ag. The interactions with ethylene from both OMS and -complexation in MIL-101-Cr-SO 3Ag have been investigated by in situ IR spectroscopic studies and computational calculations, which suggest -complexation contributes dominantly to the high ethylene/ethane adsorption selectivity.

Simulator validation results and proposed reporting format from flight testing a software model of a complex, high-performance airplane.

DOT National Transportation Integrated Search

2008-01-01

Computer simulations are often used in aviation studies. These simulation tools may require complex, high-fidelity aircraft models. Since many of the flight models used are third-party developed products, independent validation is desired prior to im...

Reconfigurable Computing for Computational Science: A New Focus in High Performance Computing

DTIC Science & Technology

2006-11-01

in the past decade. Researchers are regularly employing the power of large computing systems and parallel processing to tackle larger and more...complex problems in all of the physical sciences. For the past decade or so, most of this growth in computing power has been “free” with increased...the scientific computing community as a means to continued growth in computing capability. This paper offers a glimpse of the hardware and

Playable Serious Games for Studying and Programming Computational STEM and Informatics Applications of Distributed and Parallel Computer Architectures

ERIC Educational Resources Information Center

Amenyo, John-Thones

2012-01-01

Carefully engineered playable games can serve as vehicles for students and practitioners to learn and explore the programming of advanced computer architectures to execute applications, such as high performance computing (HPC) and complex, inter-networked, distributed systems. The article presents families of playable games that are grounded in…

Single-trial detection of visual evoked potentials by common spatial patterns and wavelet filtering for brain-computer interface.

PubMed

Tu, Yiheng; Huang, Gan; Hung, Yeung Sam; Hu, Li; Hu, Yong; Zhang, Zhiguo

2013-01-01

Event-related potentials (ERPs) are widely used in brain-computer interface (BCI) systems as input signals conveying a subject's intention. A fast and reliable single-trial ERP detection method can be used to develop a BCI system with both high speed and high accuracy. However, most of single-trial ERP detection methods are developed for offline EEG analysis and thus have a high computational complexity and need manual operations. Therefore, they are not applicable to practical BCI systems, which require a low-complexity and automatic ERP detection method. This work presents a joint spatial-time-frequency filter that combines common spatial patterns (CSP) and wavelet filtering (WF) for improving the signal-to-noise (SNR) of visual evoked potentials (VEP), which can lead to a single-trial ERP-based BCI.

Design considerations for computationally constrained two-way real-time video communication

NASA Astrophysics Data System (ADS)

Bivolarski, Lazar M.; Saunders, Steven E.; Ralston, John D.

2009-08-01

Today's video codecs have evolved primarily to meet the requirements of the motion picture and broadcast industries, where high-complexity studio encoding can be utilized to create highly-compressed master copies that are then broadcast one-way for playback using less-expensive, lower-complexity consumer devices for decoding and playback. Related standards activities have largely ignored the computational complexity and bandwidth constraints of wireless or Internet based real-time video communications using devices such as cell phones or webcams. Telecommunications industry efforts to develop and standardize video codecs for applications such as video telephony and video conferencing have not yielded image size, quality, and frame-rate performance that match today's consumer expectations and market requirements for Internet and mobile video services. This paper reviews the constraints and the corresponding video codec requirements imposed by real-time, 2-way mobile video applications. Several promising elements of a new mobile video codec architecture are identified, and more comprehensive computational complexity metrics and video quality metrics are proposed in order to support the design, testing, and standardization of these new mobile video codecs.

Fast algorithm for computing complex number-theoretic transforms

NASA Technical Reports Server (NTRS)

Reed, I. S.; Liu, K. Y.; Truong, T. K.

1977-01-01

A high-radix FFT algorithm for computing transforms over FFT, where q is a Mersenne prime, is developed to implement fast circular convolutions. This new algorithm requires substantially fewer multiplications than the conventional FFT.

Computing Systems | High-Performance Computing | NREL

Science.gov Websites

investigate, build, and test models of complex phenomena or entire integrated systems-that cannot be directly observed or manipulated in the lab, or would be too expensive or time consuming. Models and visualizations

Condor-COPASI: high-throughput computing for biochemical networks

PubMed Central

2012-01-01

Background Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise. Results We present Condor-COPASI, a server-based software tool that integrates COPASI, a biological pathway simulation tool, with Condor, a high-throughput computing environment. Condor-COPASI provides a web-based interface, which makes it extremely easy for a user to run a number of model simulation and analysis tasks in parallel. Tasks are transparently split into smaller parts, and submitted for execution on a Condor pool. Result output is presented to the user in a number of formats, including tables and interactive graphical displays. Conclusions Condor-COPASI can effectively use a Condor high-throughput computing environment to provide significant gains in performance for a number of model simulation and analysis tasks. Condor-COPASI is free, open source software, released under the Artistic License 2.0, and is suitable for use by any institution with access to a Condor pool. Source code is freely available for download at http://code.google.com/p/condor-copasi/, along with full instructions on deployment and usage. PMID:22834945

Does Cloud Computing in the Atmospheric Sciences Make Sense? A case study of hybrid cloud computing at NASA Langley Research Center

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.; Spangenberg, D.; Ayers, J. K.; Palikonda, R.; Vakhnin, A.; Dubois, R.; Murphy, P. R.

2014-12-01

The processing, storage and dissemination of satellite cloud and radiation products produced at NASA Langley Research Center are key activities for the Climate Science Branch. A constellation of systems operates in sync to accomplish these goals. Because of the complexity involved with operating such intricate systems, there are both high failure rates and high costs for hardware and system maintenance. Cloud computing has the potential to ameliorate cost and complexity issues. Over time, the cloud computing model has evolved and hybrid systems comprising off-site as well as on-site resources are now common. Towards our mission of providing the highest quality research products to the widest audience, we have explored the use of the Amazon Web Services (AWS) Cloud and Storage and present a case study of our results and efforts. This project builds upon NASA Langley Cloud and Radiation Group's experience with operating large and complex computing infrastructures in a reliable and cost effective manner to explore novel ways to leverage cloud computing resources in the atmospheric science environment. Our case study presents the project requirements and then examines the fit of AWS with the LaRC computing model. We also discuss the evaluation metrics, feasibility, and outcomes and close the case study with the lessons we learned that would apply to others interested in exploring the implementation of the AWS system in their own atmospheric science computing environments.

Design of convolutional tornado code

NASA Astrophysics Data System (ADS)

Zhou, Hui; Yang, Yao; Gao, Hongmin; Tan, Lu

2017-09-01

As a linear block code, the traditional tornado (tTN) code is inefficient in burst-erasure environment and its multi-level structure may lead to high encoding/decoding complexity. This paper presents a convolutional tornado (cTN) code which is able to improve the burst-erasure protection capability by applying the convolution property to the tTN code, and reduce computational complexity by abrogating the multi-level structure. The simulation results show that cTN code can provide a better packet loss protection performance with lower computation complexity than tTN code.

Hafnium-Based Contrast Agents for X-ray Computed Tomography.

PubMed

Berger, Markus; Bauser, Marcus; Frenzel, Thomas; Hilger, Christoph Stephan; Jost, Gregor; Lauria, Silvia; Morgenstern, Bernd; Neis, Christian; Pietsch, Hubertus; Sülzle, Detlev; Hegetschweiler, Kaspar

2017-05-15

Heavy-metal-based contrast agents (CAs) offer enhanced X-ray absorption for X-ray computed tomography (CT) compared to the currently used iodinated CAs. We report the discovery of new lanthanide and hafnium azainositol complexes and their optimization with respect to high water solubility and stability. Our efforts culminated in the synthesis of BAY-576, an uncharged hafnium complex with 3:2 stoichiometry and broken complex symmetry. The superior properties of this asymmetrically substituted hafnium CA were demonstrated by a CT angiography study in rabbits that revealed excellent signal contrast enhancement.

Costs and benefits of integrating information between the cerebral hemispheres: a computational perspective.

PubMed

Belger, A; Banich, M T

1998-07-01

Because interaction of the cerebral hemispheres has been found to aid task performance under demanding conditions, the present study examined how this effect is moderated by computational complexity, the degree of lateralization for a task, and individual differences in asymmetric hemispheric activation (AHA). Computational complexity was manipulated across tasks either by increasing the number of inputs to be processed or by increasing the number of steps to a decision. Comparison of within- and across-hemisphere trials indicated that the size of the between-hemisphere advantage increased as a function of task complexity, except for a highly lateralized rhyme decision task that can only be performed by the left hemisphere. Measures of individual differences in AHA revealed that when task demands and an individual's AHA both load on the same hemisphere, the ability to divide the processing between the hemispheres is limited. Thus, interhemispheric division of processing improves performance at higher levels of computational complexity only when the required operations can be divided between the hemispheres.

On the structure and spin states of Fe(III)-EDDHA complexes.

PubMed

Gómez-Gallego, Mar; Fernández, Israel; Pellico, Daniel; Gutiérrez, Angel; Sierra, Miguel A; Lucena, Juan J

2006-07-10

DFT methods are suitable for predicting both the geometries and spin states of EDDHA-Fe(III) complexes. Thus, extensive DFT computational studies have shown that the racemic-Fe(III) EDDHA complex is more stable than the meso isomer, regardless of the spin state of the central iron atom. A comparison of the energy values obtained for the complexes under study has also shown that high-spin (S = 5/2) complexes are more stable than low-spin (S = 1/2) ones. These computational results matched the experimental results of the magnetic susceptibility values of both isomers. In both cases, their behavior has been fitted as being due to isolated high-spin Fe(III) in a distorted octahedral environment. The study of the correlation diagram also confirms the high-spin iron in complex 2b. The geometry optimization of these complexes performed with the standard 3-21G* basis set for hydrogen, carbon, oxygen, and nitrogen and the Hay-Wadt small-core effective core potential (ECP) including a double-xi valence basis set for iron, followed by single-point energy refinement with the 6-31G* basis set, is suitable for predicting both the geometries and the spin-states of EDDHA-Fe(III) complexes. The presence of a high-spin iron in Fe(III)-EDDHA complexes could be the key to understanding their lack of reactivity in electron-transfer processes, either chemically or electrochemically induced, and their resistance to photodegradation.

Automated Approach to Very High-Order Aeroacoustic Computations. Revision

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.; Goodrich, John W.

2001-01-01

Computational aeroacoustics requires efficient, high-resolution simulation tools. For smooth problems, this is best accomplished with very high-order in space and time methods on small stencils. However, the complexity of highly accurate numerical methods can inhibit their practical application, especially in irregular geometries. This complexity is reduced by using a special form of Hermite divided-difference spatial interpolation on Cartesian grids, and a Cauchy-Kowalewski recursion procedure for time advancement. In addition, a stencil constraint tree reduces the complexity of interpolating grid points that am located near wall boundaries. These procedures are used to develop automatically and to implement very high-order methods (> 15) for solving the linearized Euler equations that can achieve less than one grid point per wavelength resolution away from boundaries by including spatial derivatives of the primitive variables at each grid point. The accuracy of stable surface treatments is currently limited to 11th order for grid aligned boundaries and to 2nd order for irregular boundaries.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

The computational challenges of Earth-system science.

PubMed

O'Neill, Alan; Steenman-Clark, Lois

2002-06-15

The Earth system--comprising atmosphere, ocean, land, cryosphere and biosphere--is an immensely complex system, involving processes and interactions on a wide range of space- and time-scales. To understand and predict the evolution of the Earth system is one of the greatest challenges of modern science, with success likely to bring enormous societal benefits. High-performance computing, along with the wealth of new observational data, is revolutionizing our ability to simulate the Earth system with computer models that link the different components of the system together. There are, however, considerable scientific and technical challenges to be overcome. This paper will consider four of them: complexity, spatial resolution, inherent uncertainty and time-scales. Meeting these challenges requires a significant increase in the power of high-performance computers. The benefits of being able to make reliable predictions about the evolution of the Earth system should, on their own, amply repay this investment.

CFD for hypersonic propulsion

NASA Technical Reports Server (NTRS)

Povinelli, Louis A.

1991-01-01

An overview is given of research activity on the application of computational fluid dynamics (CDF) for hypersonic propulsion systems. After the initial consideration of the highly integrated nature of air-breathing hypersonic engines and airframe, attention is directed toward computations carried out for the components of the engine. A generic inlet configuration is considered in order to demonstrate the highly three dimensional viscous flow behavior occurring within rectangular inlets. Reacting flow computations for simple jet injection as well as for more complex combustion chambers are then discussed in order to show the capability of viscous finite rate chemical reaction computer simulations. Finally, the nozzle flow fields are demonstrated, showing the existence of complex shear layers and shock structure in the exhaust plume. The general issues associated with code validation as well as the specific issue associated with the use of CFD for design are discussed. A prognosis for the success of CFD in the design of future propulsion systems is offered.

CFD for hypersonic propulsion

NASA Technical Reports Server (NTRS)

Povinelli, Louis A.

1990-01-01

An overview is given of research activity on the application of computational fluid dynamics (CDF) for hypersonic propulsion systems. After the initial consideration of the highly integrated nature of air-breathing hypersonic engines and airframe, attention is directed toward computations carried out for the components of the engine. A generic inlet configuration is considered in order to demonstrate the highly three dimensional viscous flow behavior occurring within rectangular inlets. Reacting flow computations for simple jet injection as well as for more complex combustion chambers are then discussed in order to show the capability of viscous finite rate chemical reaction computer simulations. Finally, the nozzle flow fields are demonstrated, showing the existence of complex shear layers and shock structure in the exhaust plume. The general issues associated with code validation as well as the specific issue associated with the use of CFD for design are discussed. A prognosis for the success of CFD in the design of future propulsion systems is offered.

Connectionist Models and Parallelism in High Level Vision.

DTIC Science & Technology

1985-01-01

GRANT NUMBER(s) Jerome A. Feldman N00014-82-K-0193 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENt. PROJECT, TASK Computer Science...Connectionist Models 2.1 Background and Overviev % Computer science is just beginning to look seriously at parallel computation : it may turn out that...the chair. The program includes intermediate level networks that compute more complex joints and ones that compute parallelograms in the image. These

Computational Characterization of Electromagnetic Field Propagation in Complex Structures

DTIC Science & Technology

1998-04-10

34Computational characterization of electromagnetic field propagation in complex structures", DAAH01-91-D-ROOS D.O. 59. Dr. Michael Scalora performed the...Development, and Engineering Center, Bldg. 7804, Room 242 Redstone Arsenal, Alabama 35898-5248 USA Dr. Michael Scalora Quantum Optics Group Tel:(205...scheduled to appear. They are: (1) M. Scalora , J.P. Dowling, A.S. Manka, CM. Bowden, and J.W. Haus, Pulse Propagation Near Highly Reflective

AstroGrid: Taverna in the Virtual Observatory .

NASA Astrophysics Data System (ADS)

Benson, K. M.; Walton, N. A.

This paper reports on the implementation of the Taverna workbench by AstroGrid, a tool for designing and executing workflows of tasks in the Virtual Observatory. The workflow approach helps astronomers perform complex task sequences with little technical effort. Visual approach to workflow construction streamlines highly complex analysis over public and private data and uses computational resources as minimal as a desktop computer. Some integration issues and future work are discussed in this article.

Task Assignment Heuristics for Distributed CFD Applications

NASA Technical Reports Server (NTRS)

Lopez-Benitez, N.; Djomehri, M. J.; Biswas, R.; Biegel, Bryan (Technical Monitor)

2001-01-01

CFD applications require high-performance computational platforms: 1. Complex physics and domain configuration demand strongly coupled solutions; 2. Applications are CPU and memory intensive; and 3. Huge resource requirements can only be satisfied by teraflop-scale machines or distributed computing.

High-efficiency photorealistic computer-generated holograms based on the backward ray-tracing technique

NASA Astrophysics Data System (ADS)

Wang, Yuan; Chen, Zhidong; Sang, Xinzhu; Li, Hui; Zhao, Linmin

2018-03-01

Holographic displays can provide the complete optical wave field of a three-dimensional (3D) scene, including the depth perception. However, it often takes a long computation time to produce traditional computer-generated holograms (CGHs) without more complex and photorealistic rendering. The backward ray-tracing technique is able to render photorealistic high-quality images, which noticeably reduce the computation time achieved from the high-degree parallelism. Here, a high-efficiency photorealistic computer-generated hologram method is presented based on the ray-tracing technique. Rays are parallelly launched and traced under different illuminations and circumstances. Experimental results demonstrate the effectiveness of the proposed method. Compared with the traditional point cloud CGH, the computation time is decreased to 24 s to reconstruct a 3D object of 100 ×100 rays with continuous depth change.

High performance network and channel-based storage

NASA Technical Reports Server (NTRS)

Katz, Randy H.

1991-01-01

In the traditional mainframe-centered view of a computer system, storage devices are coupled to the system through complex hardware subsystems called input/output (I/O) channels. With the dramatic shift towards workstation-based computing, and its associated client/server model of computation, storage facilities are now found attached to file servers and distributed throughout the network. We discuss the underlying technology trends that are leading to high performance network-based storage, namely advances in networks, storage devices, and I/O controller and server architectures. We review several commercial systems and research prototypes that are leading to a new approach to high performance computing based on network-attached storage.

Hardware-based Artificial Neural Networks for Size, Weight, and Power Constrained Platforms (Preprint)

DTIC Science & Technology

2012-11-01

few sensors/complex computations, and many sensors/simple computation. II. CHALLENGES WITH NANO-ENABLED NEUROMORPHIC CHIPS A wide variety of...scenarios. Neuromorphic processors, which are based on the highly parallelized computing architecture of the mammalian brain, show great promise in...in the brain. This fundamentally different approach, frequently referred to as neuromorphic computing, is thought to be better able to solve fuzzy

Hot spot computational identification: Application to the complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL-10

NASA Astrophysics Data System (ADS)

Moreira, I. S.; Fernandes, P. A.; Ramos, M. J.

The definition and comprehension of the hot spots in an interface is a subject of primary interest for a variety of fields, including structure-based drug design. Therefore, to achieve an alanine mutagenesis computational approach that is at the same time accurate and predictive, capable of reproducing the experimental mutagenesis values is a major challenge in the computational biochemistry field. Antibody/protein antigen complexes provide one of the greatest models to study protein-protein recognition process because they have three fundamentally features: specificity, high complementary association and a small epitope restricted to the diminutive complementary determining regions (CDR) region, while the remainder of the antibody is largely invariant. Thus, we apply a computational mutational methodological approach to the study of the antigen-antibody complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL-10. A critical evaluation that focuses essentially on the limitations and advantages between different computational methods for hot spot determination, as well as between experimental and computational methodological approaches, is presented.

Here and now: the intersection of computational science, quantum-mechanical simulations, and materials science

NASA Astrophysics Data System (ADS)

Marzari, Nicola

The last 30 years have seen the steady and exhilarating development of powerful quantum-simulation engines for extended systems, dedicated to the solution of the Kohn-Sham equations of density-functional theory, often augmented by density-functional perturbation theory, many-body perturbation theory, time-dependent density-functional theory, dynamical mean-field theory, and quantum Monte Carlo. Their implementation on massively parallel architectures, now leveraging also GPUs and accelerators, has started a massive effort in the prediction from first principles of many or of complex materials properties, leading the way to the exascale through the combination of HPC (high-performance computing) and HTC (high-throughput computing). Challenges and opportunities abound: complementing hardware and software investments and design; developing the materials' informatics infrastructure needed to encode knowledge into complex protocols and workflows of calculations; managing and curating data; resisting the complacency that we have already reached the predictive accuracy needed for materials design, or a robust level of verification of the different quantum engines. In this talk I will provide an overview of these challenges, with the ultimate prize being the computational understanding, prediction, and design of properties and performance for novel or complex materials and devices.

Combining high performance simulation, data acquisition, and graphics display computers

NASA Technical Reports Server (NTRS)

Hickman, Robert J.

1989-01-01

Issues involved in the continuing development of an advanced simulation complex are discussed. This approach provides the capability to perform the majority of tests on advanced systems, non-destructively. The controlled test environments can be replicated to examine the response of the systems under test to alternative treatments of the system control design, or test the function and qualification of specific hardware. Field tests verify that the elements simulated in the laboratories are sufficient. The digital computer is hosted by a Digital Equipment Corp. MicroVAX computer with an Aptec Computer Systems Model 24 I/O computer performing the communication function. An Applied Dynamics International AD100 performs the high speed simulation computing and an Evans and Sutherland PS350 performs on-line graphics display. A Scientific Computer Systems SCS40 acts as a high performance FORTRAN program processor to support the complex, by generating numerous large files from programs coded in FORTRAN that are required for the real time processing. Four programming languages are involved in the process, FORTRAN, ADSIM, ADRIO, and STAPLE. FORTRAN is employed on the MicroVAX host to initialize and terminate the simulation runs on the system. The generation of the data files on the SCS40 also is performed with FORTRAN programs. ADSIM and ADIRO are used to program the processing elements of the AD100 and its IOCP processor. STAPLE is used to program the Aptec DIP and DIA processors.

Structural studies of RNA-protein complexes: A hybrid approach involving hydrodynamics, scattering, and computational methods.

PubMed

Patel, Trushar R; Chojnowski, Grzegorz; Astha; Koul, Amit; McKenna, Sean A; Bujnicki, Janusz M

2017-04-15

The diverse functional cellular roles played by ribonucleic acids (RNA) have emphasized the need to develop rapid and accurate methodologies to elucidate the relationship between the structure and function of RNA. Structural biology tools such as X-ray crystallography and Nuclear Magnetic Resonance are highly useful methods to obtain atomic-level resolution models of macromolecules. However, both methods have sample, time, and technical limitations that prevent their application to a number of macromolecules of interest. An emerging alternative to high-resolution structural techniques is to employ a hybrid approach that combines low-resolution shape information about macromolecules and their complexes from experimental hydrodynamic (e.g. analytical ultracentrifugation) and solution scattering measurements (e.g., solution X-ray or neutron scattering), with computational modeling to obtain atomic-level models. While promising, scattering methods rely on aggregation-free, monodispersed preparations and therefore the careful development of a quality control pipeline is fundamental to an unbiased and reliable structural determination. This review article describes hydrodynamic techniques that are highly valuable for homogeneity studies, scattering techniques useful to study the low-resolution shape, and strategies for computational modeling to obtain high-resolution 3D structural models of RNAs, proteins, and RNA-protein complexes. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Temporally Adjusted Complex Ambiguity Function Mapping Algorithm for Geolocating Radio Frequency Signals

DTIC Science & Technology

2014-12-01

Introduction 1.1 Background In today’s world of high -tech warfare, we have developed the ability to deploy virtually any type of ordnance quickly and... ANSI Std. 239–18 i THIS PAGE INTENTIONALLY LEFT BLANK ii Approved for public release; distribution is unlimited TEMPORALLY ADJUSTED COMPLEX AMBIGUITY...this time due to time constraints and the high computational complexity involved in the current implementation of the Moss algorithm. Full maps, with

An exploratory investigation of various assessment instruments as correlates of complex visual monitoring performance.

DOT National Transportation Integrated Search

1980-10-01

The present study examined a variety of possible predictors of complex monitoring performance. The criterion task was designed to resemble that of a highly automated air traffic control radar system containing computer-generated alphanumeric displays...

ComplexQuant: high-throughput computational pipeline for the global quantitative analysis of endogenous soluble protein complexes using high resolution protein HPLC and precision label-free LC/MS/MS.

PubMed

Wan, Cuihong; Liu, Jian; Fong, Vincent; Lugowski, Andrew; Stoilova, Snejana; Bethune-Waddell, Dylan; Borgeson, Blake; Havugimana, Pierre C; Marcotte, Edward M; Emili, Andrew

2013-04-09

The experimental isolation and characterization of stable multi-protein complexes are essential to understanding the molecular systems biology of a cell. To this end, we have developed a high-throughput proteomic platform for the systematic identification of native protein complexes based on extensive fractionation of soluble protein extracts by multi-bed ion exchange high performance liquid chromatography (IEX-HPLC) combined with exhaustive label-free LC/MS/MS shotgun profiling. To support these studies, we have built a companion data analysis software pipeline, termed ComplexQuant. Proteins present in the hundreds of fractions typically collected per experiment are first identified by exhaustively interrogating MS/MS spectra using multiple database search engines within an integrative probabilistic framework, while accounting for possible post-translation modifications. Protein abundance is then measured across the fractions based on normalized total spectral counts and precursor ion intensities using a dedicated tool, PepQuant. This analysis allows co-complex membership to be inferred based on the similarity of extracted protein co-elution profiles. Each computational step has been optimized for processing large-scale biochemical fractionation datasets, and the reliability of the integrated pipeline has been benchmarked extensively. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

Autonomous control systems: applications to remote sensing and image processing

NASA Astrophysics Data System (ADS)

Jamshidi, Mohammad

2001-11-01

One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.

EMILiO: a fast algorithm for genome-scale strain design.

PubMed

Yang, Laurence; Cluett, William R; Mahadevan, Radhakrishnan

2011-05-01

Systems-level design of cell metabolism is becoming increasingly important for renewable production of fuels, chemicals, and drugs. Computational models are improving in the accuracy and scope of predictions, but are also growing in complexity. Consequently, efficient and scalable algorithms are increasingly important for strain design. Previous algorithms helped to consolidate the utility of computational modeling in this field. To meet intensifying demands for high-performance strains, both the number and variety of genetic manipulations involved in strain construction are increasing. Existing algorithms have experienced combinatorial increases in computational complexity when applied toward the design of such complex strains. Here, we present EMILiO, a new algorithm that increases the scope of strain design to include reactions with individually optimized fluxes. Unlike existing approaches that would experience an explosion in complexity to solve this problem, we efficiently generated numerous alternate strain designs producing succinate, l-glutamate and l-serine. This was enabled by successive linear programming, a technique new to the area of computational strain design. Copyright © 2011 Elsevier Inc. All rights reserved.

A new fast algorithm for computing a complex number: Theoretic transforms

NASA Technical Reports Server (NTRS)

Reed, I. S.; Liu, K. Y.; Truong, T. K.

1977-01-01

A high-radix fast Fourier transformation (FFT) algorithm for computing transforms over GF(sq q), where q is a Mersenne prime, is developed to implement fast circular convolutions. This new algorithm requires substantially fewer multiplications than the conventional FFT.

Computational structural mechanics methods research using an evolving framework

NASA Technical Reports Server (NTRS)

Knight, N. F., Jr.; Lotts, C. G.; Gillian, R. E.

1990-01-01

Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering☆

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

Enabling Large-Scale Biomedical Analysis in the Cloud

PubMed Central

Lin, Ying-Chih; Yu, Chin-Sheng; Lin, Yen-Jen

2013-01-01

Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable. PMID:24288665

The research of computer network security and protection strategy

NASA Astrophysics Data System (ADS)

He, Jian

2017-05-01

With the widespread popularity of computer network applications, its security is also received a high degree of attention. Factors affecting the safety of network is complex, for to do a good job of network security is a systematic work, has the high challenge. For safety and reliability problems of computer network system, this paper combined with practical work experience, from the threat of network security, security technology, network some Suggestions and measures for the system design principle, in order to make the masses of users in computer networks to enhance safety awareness and master certain network security technology.

Intricacies of modern supercomputing illustrated with recent advances in simulations of strongly correlated electron systems

NASA Astrophysics Data System (ADS)

Schulthess, Thomas C.

2013-03-01

The continued thousand-fold improvement in sustained application performance per decade on modern supercomputers keeps opening new opportunities for scientific simulations. But supercomputers have become very complex machines, built with thousands or tens of thousands of complex nodes consisting of multiple CPU cores or, most recently, a combination of CPU and GPU processors. Efficient simulations on such high-end computing systems require tailored algorithms that optimally map numerical methods to particular architectures. These intricacies will be illustrated with simulations of strongly correlated electron systems, where the development of quantum cluster methods, Monte Carlo techniques, as well as their optimal implementation by means of algorithms with improved data locality and high arithmetic density have gone hand in hand with evolving computer architectures. The present work would not have been possible without continued access to computing resources at the National Center for Computational Science of Oak Ridge National Laboratory, which is funded by the Facilities Division of the Office of Advanced Scientific Computing Research, and the Swiss National Supercomputing Center (CSCS) that is funded by ETH Zurich.

Editorial [Special issue on software defined networks and infrastructures, network function virtualisation, autonomous systems and network management

DOE PAGES

Biswas, Amitava; Liu, Chen; Monga, Inder; ...

2016-01-01

For last few years, there has been a tremendous growth in data traffic due to high adoption rate of mobile devices and cloud computing. Internet of things (IoT) will stimulate even further growth. This is increasing scale and complexity of telecom/internet service provider (SP) and enterprise data centre (DC) compute and network infrastructures. As a result, managing these large network-compute converged infrastructures is becoming complex and cumbersome. To cope up, network and DC operators are trying to automate network and system operations, administrations and management (OAM) functions. OAM includes all non-functional mechanisms which keep the network running.

GPU accelerated study of heat transfer and fluid flow by lattice Boltzmann method on CUDA

NASA Astrophysics Data System (ADS)

Ren, Qinlong

Lattice Boltzmann method (LBM) has been developed as a powerful numerical approach to simulate the complex fluid flow and heat transfer phenomena during the past two decades. As a mesoscale method based on the kinetic theory, LBM has several advantages compared with traditional numerical methods such as physical representation of microscopic interactions, dealing with complex geometries and highly parallel nature. Lattice Boltzmann method has been applied to solve various fluid behaviors and heat transfer process like conjugate heat transfer, magnetic and electric field, diffusion and mixing process, chemical reactions, multiphase flow, phase change process, non-isothermal flow in porous medium, microfluidics, fluid-structure interactions in biological system and so on. In addition, as a non-body-conformal grid method, the immersed boundary method (IBM) could be applied to handle the complex or moving geometries in the domain. The immersed boundary method could be coupled with lattice Boltzmann method to study the heat transfer and fluid flow problems. Heat transfer and fluid flow are solved on Euler nodes by LBM while the complex solid geometries are captured by Lagrangian nodes using immersed boundary method. Parallel computing has been a popular topic for many decades to accelerate the computational speed in engineering and scientific fields. Today, almost all the laptop and desktop have central processing units (CPUs) with multiple cores which could be used for parallel computing. However, the cost of CPUs with hundreds of cores is still high which limits its capability of high performance computing on personal computer. Graphic processing units (GPU) is originally used for the computer video cards have been emerged as the most powerful high-performance workstation in recent years. Unlike the CPUs, the cost of GPU with thousands of cores is cheap. For example, the GPU (GeForce GTX TITAN) which is used in the current work has 2688 cores and the price is only 1,000 US dollars. The release of NVIDIA's CUDA architecture which includes both hardware and programming environment in 2007 makes GPU computing attractive. Due to its highly parallel nature, lattice Boltzmann method is successfully ported into GPU with a performance benefit during the recent years. In the current work, LBM CUDA code is developed for different fluid flow and heat transfer problems. In this dissertation, lattice Boltzmann method and immersed boundary method are used to study natural convection in an enclosure with an array of conduting obstacles, double-diffusive convection in a vertical cavity with Soret and Dufour effects, PCM melting process in a latent heat thermal energy storage system with internal fins, mixed convection in a lid-driven cavity with a sinusoidal cylinder, and AC electrothermal pumping in microfluidic systems on a CUDA computational platform. It is demonstrated that LBM is an efficient method to simulate complex heat transfer problems using GPU on CUDA.

Geocomputation over Hybrid Computer Architecture and Systems: Prior Works and On-going Initiatives at UARK

NASA Astrophysics Data System (ADS)

Shi, X.

2015-12-01

As NSF indicated - "Theory and experimentation have for centuries been regarded as two fundamental pillars of science. It is now widely recognized that computational and data-enabled science forms a critical third pillar." Geocomputation is the third pillar of GIScience and geosciences. With the exponential growth of geodata, the challenge of scalable and high performance computing for big data analytics become urgent because many research activities are constrained by the inability of software or tool that even could not complete the computation process. Heterogeneous geodata integration and analytics obviously magnify the complexity and operational time frame. Many large-scale geospatial problems may be not processable at all if the computer system does not have sufficient memory or computational power. Emerging computer architectures, such as Intel's Many Integrated Core (MIC) Architecture and Graphics Processing Unit (GPU), and advanced computing technologies provide promising solutions to employ massive parallelism and hardware resources to achieve scalability and high performance for data intensive computing over large spatiotemporal and social media data. Exploring novel algorithms and deploying the solutions in massively parallel computing environment to achieve the capability for scalable data processing and analytics over large-scale, complex, and heterogeneous geodata with consistent quality and high-performance has been the central theme of our research team in the Department of Geosciences at the University of Arkansas (UARK). New multi-core architectures combined with application accelerators hold the promise to achieve scalability and high performance by exploiting task and data levels of parallelism that are not supported by the conventional computing systems. Such a parallel or distributed computing environment is particularly suitable for large-scale geocomputation over big data as proved by our prior works, while the potential of such advanced infrastructure remains unexplored in this domain. Within this presentation, our prior and on-going initiatives will be summarized to exemplify how we exploit multicore CPUs, GPUs, and MICs, and clusters of CPUs, GPUs and MICs, to accelerate geocomputation in different applications.

Effect of Computer-Delivered Testing on Achievement in a Mastery Learning Course of Study with Partial Scoring and Variable Pacing.

ERIC Educational Resources Information Center

Evans, Richard M.; Surkan, Alvin J.

The recent arrival of portable computer systems with high-level language interpreters now makes it practical to rapidly develop complex testing and scoring programs. These programs permit undergraduates access, at arbitrary times, to testing as an integral part of a mastery learning strategy. Effects of introducing the computer were studied by…

What Can You Learn from a Cell Phone? Almost Anything!

ERIC Educational Resources Information Center

Prensky, Marc

2005-01-01

Today's high-end cell phones have the computing power of a mid-1990s personal computer (PC)--while consuming only one one-hundredth of the energy. Even the simplest, voice-only phones have more complex and powerful chips than the 1969 on-board computer that landed a spaceship on the moon. In the United States, it is almost universally acknowledged…

Ways of achieving continuous service from computers

NASA Technical Reports Server (NTRS)

Quinn, M. J., Jr.

1974-01-01

This paper outlines the methods used in the real-time computer complex to keep computers operating. Methods include selectover, high-speed restart, and low-speed restart. The hardware and software needed to implement these methods is discussed as well as the system recovery facility, alternate device support, and timeout. In general, methods developed while supporting the Gemini, Apollo, and Skylab space missions are presented.

HyperForest: A high performance multi-processor architecture for real-time intelligent systems

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

Garcia, P. Jr.; Rebeil, J.P.; Pollard, H.

1997-04-01

Intelligent Systems are characterized by the intensive use of computer power. The computer revolution of the last few years is what has made possible the development of the first generation of Intelligent Systems. Software for second generation Intelligent Systems will be more complex and will require more powerful computing engines in order to meet real-time constraints imposed by new robots, sensors, and applications. A multiprocessor architecture was developed that merges the advantages of message-passing and shared-memory structures: expendability and real-time compliance. The HyperForest architecture will provide an expandable real-time computing platform for computationally intensive Intelligent Systems and open the doorsmore » for the application of these systems to more complex tasks in environmental restoration and cleanup projects, flexible manufacturing systems, and DOE`s own production and disassembly activities.« less

Parametric bicubic spline and CAD tools for complex targets shape modelling in physical optics radar cross section prediction

NASA Astrophysics Data System (ADS)

Delogu, A.; Furini, F.

1991-09-01

Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.

Fast parallel approach for 2-D DHT-based real-valued discrete Gabor transform.

PubMed

Tao, Liang; Kwan, Hon Keung

2009-12-01

Two-dimensional fast Gabor transform algorithms are useful for real-time applications due to the high computational complexity of the traditional 2-D complex-valued discrete Gabor transform (CDGT). This paper presents two block time-recursive algorithms for 2-D DHT-based real-valued discrete Gabor transform (RDGT) and its inverse transform and develops a fast parallel approach for the implementation of the two algorithms. The computational complexity of the proposed parallel approach is analyzed and compared with that of the existing 2-D CDGT algorithms. The results indicate that the proposed parallel approach is attractive for real time image processing.

High-Speed Systolic Array Testbed.

DTIC Science & Technology

1987-10-01

applications since the concept was introduced by H.T. Kung In 1978. This highly parallel architecture of nearet neighbor data communciation and...must be addressed. For instance, should bit-serial or bit parallei computation be utilized. Does the dynamic range of the candidate applications or...numericai stability of the algorithms used require computations In fixed point and Integer format or the architecturally more complex and slower floating

Computationally Efficient Power Allocation Algorithm in Multicarrier-Based Cognitive Radio Networks: OFDM and FBMC Systems

NASA Astrophysics Data System (ADS)

Shaat, Musbah; Bader, Faouzi

2010-12-01

Cognitive Radio (CR) systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC) can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM) for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs) constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

Numerical propulsion system simulation

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

TOSCA-based orchestration of complex clusters at the IaaS level

NASA Astrophysics Data System (ADS)

Caballer, M.; Donvito, G.; Moltó, G.; Rocha, R.; Velten, M.

2017-10-01

This paper describes the adoption and extension of the TOSCA standard by the INDIGO-DataCloud project for the definition and deployment of complex computing clusters together with the required support in both OpenStack and OpenNebula, carried out in close collaboration with industry partners such as IBM. Two examples of these clusters are described in this paper, the definition of an elastic computing cluster to support the Galaxy bioinformatics application where the nodes are dynamically added and removed from the cluster to adapt to the workload, and the definition of an scalable Apache Mesos cluster for the execution of batch jobs and support for long-running services. The coupling of TOSCA with Ansible Roles to perform automated installation has resulted in the definition of high-level, deterministic templates to provision complex computing clusters across different Cloud sites.

Computational Modeling of Liquid and Gaseous Control Valves

NASA Technical Reports Server (NTRS)

Daines, Russell; Ahuja, Vineet; Hosangadi, Ashvin; Shipman, Jeremy; Moore, Arden; Sulyma, Peter

2005-01-01

In this paper computational modeling efforts undertaken at NASA Stennis Space Center in support of rocket engine component testing are discussed. Such analyses include structurally complex cryogenic liquid valves and gas valves operating at high pressures and flow rates. Basic modeling and initial successes are documented, and other issues that make valve modeling at SSC somewhat unique are also addressed. These include transient behavior, valve stall, and the determination of flow patterns in LOX valves. Hexahedral structured grids are used for valves that can be simplifies through the use of axisymmetric approximation. Hybrid unstructured methodology is used for structurally complex valves that have disparate length scales and complex flow paths that include strong swirl, local recirculation zones/secondary flow effects. Hexahedral (structured), unstructured, and hybrid meshes are compared for accuracy and computational efficiency. Accuracy is determined using verification and validation techniques.

Efficient biprediction decision scheme for fast high efficiency video coding encoding

NASA Astrophysics Data System (ADS)

Park, Sang-hyo; Lee, Seung-ho; Jang, Euee S.; Jun, Dongsan; Kang, Jung-Won

2016-11-01

An efficient biprediction decision scheme of high efficiency video coding (HEVC) is proposed for fast-encoding applications. For low-delay video applications, bidirectional prediction can be used to increase compression performance efficiently with previous reference frames. However, at the same time, the computational complexity of the HEVC encoder is significantly increased due to the additional biprediction search. Although a some research has attempted to reduce this complexity, whether the prediction is strongly related to both motion complexity and prediction modes in a coding unit has not yet been investigated. A method that avoids most compression-inefficient search points is proposed so that the computational complexity of the motion estimation process can be dramatically decreased. To determine if biprediction is critical, the proposed method exploits the stochastic correlation of the context of prediction units (PUs): the direction of a PU and the accuracy of a motion vector. Through experimental results, the proposed method showed that the time complexity of biprediction can be reduced to 30% on average, outperforming existing methods in view of encoding time, number of function calls, and memory access.

Real-time, high frequency QRS electrocardiograph

NASA Technical Reports Server (NTRS)

Schlegel, Todd T. (Inventor); DePalma, Jude L. (Inventor); Moradi, Saeed (Inventor)

2006-01-01

Real time cardiac electrical data are received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed in real time in a useful form on a computer screen or monitor. The monitor displays the high frequency data from the QRS complex in units of microvolts, juxtaposed with a display of conventional ECG data in units of millivolts or microvolts. The high frequency data are analyzed for their root mean square (RMS) voltage values and the discrete RMS values and related parameters are displayed in real time. The high frequency data from the QRS complex are analyzed with imbedded algorithms to determine the presence or absence of reduced amplitude zones, referred to herein as RAZs. RAZs are displayed as go, no-go signals on the computer monitor. The RMS and related values of the high frequency components are displayed as time varying signals, and the presence or absence of RAZs may be similarly displayed over time.

Three VO2+ complexes of the pyridoxal-derived Schiff bases: Synthesis, experimental and theoretical characterizations, and catalytic activity in a cyclocondensation reaction

NASA Astrophysics Data System (ADS)

Jafari-Moghaddam, Faezeh; Beyramabadi, S. Ali; Khashi, Maryam; Morsali, Ali

2018-02-01

Three oxovanadium(IV) complexes of the pyridoxal Schiff bases have been newly synthesized and characterized. The used Schiff bases were N,N‧-dipyridoxyl(ethylenediamine), N,N‧-dipyridoxyl(1,3-propanediamine) and N,N‧-dipyridoxyl(1,2-benzenediamine). Also, the optimized geometry, assignment of the IR bands and the Natural Bond Orbital (NBO) analysis of the complexes have been computed using the density functional theory (DFT) methods. Dianionic form of the Schiff bases (L2-) acts as a tetradentate N2O2 ligand. The coordinating atoms of the Schiff base are the phenolate oxygens and imine nitrogens, which occupy four base positions of the square-pyramidal geometry of the complexes. The oxo ligand occupies the apical position of the [VO(L)] complexes. In the optimized geometry of the complexes, the coordinated Schiff bases have more planar structure than their free form. Due to the high-energy gaps, all of the complexes are predicted to be stable. Good agreement between the experimental values and the DFT-computed results supports suitability of the optimized geometries for the complexes. The investigated complexes show high catalytic activities in synthesis of the tetrahydrobenzo[b]pyrans through a three-component cyclocondensation reaction of dimedone, malononitrile and some aromatic aldehydes. The complexes catalyzed the reaction in solvent free conditions and the catalysts were found to be reusable.

Biologically inspired collision avoidance system for unmanned vehicles

NASA Astrophysics Data System (ADS)

Ortiz, Fernando E.; Graham, Brett; Spagnoli, Kyle; Kelmelis, Eric J.

2009-05-01

In this project, we collaborate with researchers in the neuroscience department at the University of Delaware to develop an Field Programmable Gate Array (FPGA)-based embedded computer, inspired by the brains of small vertebrates (fish). The mechanisms of object detection and avoidance in fish have been extensively studied by our Delaware collaborators. The midbrain optic tectum is a biological multimodal navigation controller capable of processing input from all senses that convey spatial information, including vision, audition, touch, and lateral-line (water current sensing in fish). Unfortunately, computational complexity makes these models too slow for use in real-time applications. These simulations are run offline on state-of-the-art desktop computers, presenting a gap between the application and the target platform: a low-power embedded device. EM Photonics has expertise in developing of high-performance computers based on commodity platforms such as graphic cards (GPUs) and FPGAs. FPGAs offer (1) high computational power, low power consumption and small footprint (in line with typical autonomous vehicle constraints), and (2) the ability to implement massively-parallel computational architectures, which can be leveraged to closely emulate biological systems. Combining UD's brain modeling algorithms and the power of FPGAs, this computer enables autonomous navigation in complex environments, and further types of onboard neural processing in future applications.

Role of optical computers in aeronautical control applications

NASA Technical Reports Server (NTRS)

Baumbick, R. J.

1981-01-01

The role that optical computers play in aircraft control is determined. The optical computer has the potential high speed capability required, especially for matrix/matrix operations. The optical computer also has the potential for handling nonlinear simulations in real time. They are also more compatible with fiber optic signal transmission. Optics also permit the use of passive sensors to measure process variables. No electrical energy need be supplied to the sensor. Complex interfacing between optical sensors and the optical computer is avoided if the optical sensor outputs can be directly processed by the optical computer.

Design applications for supercomputers

NASA Technical Reports Server (NTRS)

Studerus, C. J.

1987-01-01

The complexity of codes for solutions of real aerodynamic problems has progressed from simple two-dimensional models to three-dimensional inviscid and viscous models. As the algorithms used in the codes increased in accuracy, speed and robustness, the codes were steadily incorporated into standard design processes. The highly sophisticated codes, which provide solutions to the truly complex flows, require computers with large memory and high computational speed. The advent of high-speed supercomputers, such that the solutions of these complex flows become more practical, permits the introduction of the codes into the design system at an earlier stage. The results of several codes which either were already introduced into the design process or are rapidly in the process of becoming so, are presented. The codes fall into the area of turbomachinery aerodynamics and hypersonic propulsion. In the former category, results are presented for three-dimensional inviscid and viscous flows through nozzle and unducted fan bladerows. In the latter category, results are presented for two-dimensional inviscid and viscous flows for hypersonic vehicle forebodies and engine inlets.

Using an Adaptive Expertise Lens to Understand the Quality of Teachers' Classroom Implementation of Computer-Supported Complex Systems Curricula in High School Science

ERIC Educational Resources Information Center

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-01-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to…

Deepthi Vaidhynathan | NREL

Science.gov Websites

Complex Systems Simulation and Optimization Group on performance analysis and benchmarking latest . Research Interests High Performance Computing|Embedded System |Microprocessors & Microcontrollers

Low-complexity R-peak detection for ambulatory fetal monitoring.

PubMed

Rooijakkers, Michael J; Rabotti, Chiara; Oei, S Guid; Mischi, Massimo

2012-07-01

Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

Close to real life. [solving for transonic flow about lifting airfoils using supercomputers

NASA Technical Reports Server (NTRS)

Peterson, Victor L.; Bailey, F. Ron

1988-01-01

NASA's Numerical Aerodynamic Simulation (NAS) facility for CFD modeling of highly complex aerodynamic flows employs as its basic hardware two Cray-2s, an ETA-10 Model Q, an Amdahl 5880 mainframe computer that furnishes both support processing and access to 300 Gbytes of disk storage, several minicomputers and superminicomputers, and a Thinking Machines 16,000-device 'connection machine' processor. NAS, which was the first supercomputer facility to standardize operating-system and communication software on all processors, has done important Space Shuttle aerodynamics simulations and will be critical to the configurational refinement of the National Aerospace Plane and its intergrated powerplant, which will involve complex, high temperature reactive gasdynamic computations.

Using NCLab-karel to improve computational thinking skill of junior high school students

NASA Astrophysics Data System (ADS)

Kusnendar, J.; Prabawa, H. W.

2018-05-01

Increasingly human interaction with technology and the increasingly complex development of digital technology world make the theme of computer science education interesting to study. Previous studies on Computer Literacy and Competency reveal that Indonesian teachers in general have fairly high computational skill, but their skill utilization are limited to some applications. This engenders limited and minimum computer-related learning for the students. On the other hand, computer science education is considered unrelated to real-world solutions. This paper attempts to address the utilization of NCLab- Karel in shaping the computational thinking in students. This computational thinking is believed to be able to making learn students about technology. Implementation of Karel utilization provides information that Karel is able to increase student interest in studying computational material, especially algorithm. Observations made during the learning process also indicate the growth and development of computing mindset in students.

A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

PubMed Central

Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

2013-01-01

Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy, and robustness. PMID:24055554

VLSI implementation of a new LMS-based algorithm for noise removal in ECG signal

NASA Astrophysics Data System (ADS)

Satheeskumaran, S.; Sabrigiriraj, M.

2016-06-01

Least mean square (LMS)-based adaptive filters are widely deployed for removing artefacts in electrocardiogram (ECG) due to less number of computations. But they posses high mean square error (MSE) under noisy environment. The transform domain variable step-size LMS algorithm reduces the MSE at the cost of computational complexity. In this paper, a variable step-size delayed LMS adaptive filter is used to remove the artefacts from the ECG signal for improved feature extraction. The dedicated digital Signal processors provide fast processing, but they are not flexible. By using field programmable gate arrays, the pipelined architectures can be used to enhance the system performance. The pipelined architecture can enhance the operation efficiency of the adaptive filter and save the power consumption. This technique provides high signal-to-noise ratio and low MSE with reduced computational complexity; hence, it is a useful method for monitoring patients with heart-related problem.

Remote sensing image ship target detection method based on visual attention model

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

A programmable computational image sensor for high-speed vision

NASA Astrophysics Data System (ADS)

Yang, Jie; Shi, Cong; Long, Xitian; Wu, Nanjian

2013-08-01

In this paper we present a programmable computational image sensor for high-speed vision. This computational image sensor contains four main blocks: an image pixel array, a massively parallel processing element (PE) array, a row processor (RP) array and a RISC core. The pixel-parallel PE is responsible for transferring, storing and processing image raw data in a SIMD fashion with its own programming language. The RPs are one dimensional array of simplified RISC cores, it can carry out complex arithmetic and logic operations. The PE array and RP array can finish great amount of computation with few instruction cycles and therefore satisfy the low- and middle-level high-speed image processing requirement. The RISC core controls the whole system operation and finishes some high-level image processing algorithms. We utilize a simplified AHB bus as the system bus to connect our major components. Programming language and corresponding tool chain for this computational image sensor are also developed.

Computational efficient unsupervised coastline detection from single-polarization 1-look SAR images of complex coastal environments

NASA Astrophysics Data System (ADS)

Garzelli, Andrea; Zoppetti, Claudia; Pinelli, Gianpaolo

2017-10-01

Coastline detection in synthetic aperture radar (SAR) images is crucial in many application fields, from coastal erosion monitoring to navigation, from damage assessment to security planning for port facilities. The backscattering difference between land and sea is not always documented in SAR imagery, due to the severe speckle noise, especially in 1-look data with high spatial resolution, high sea state, or complex coastal environments. This paper presents an unsupervised, computationally efficient solution to extract the coastline acquired by only one single-polarization 1-look SAR image. Extensive tests on Spotlight COSMO-SkyMed images of complex coastal environments and objective assessment demonstrate the validity of the proposed procedure which is compared to state-of-the-art methods through visual results and with an objective evaluation of the distance between the detected and the true coastline provided by regional authorities.

A performance comparison of scalar, vector, and concurrent vector computers including supercomputers for modeling transport of reactive contaminants in groundwater

NASA Astrophysics Data System (ADS)

Tripathi, Vijay S.; Yeh, G. T.

1993-06-01

Sophisticated and highly computation-intensive models of transport of reactive contaminants in groundwater have been developed in recent years. Application of such models to real-world contaminant transport problems, e.g., simulation of groundwater transport of 10-15 chemically reactive elements (e.g., toxic metals) and relevant complexes and minerals in two and three dimensions over a distance of several hundred meters, requires high-performance computers including supercomputers. Although not widely recognized as such, the computational complexity and demand of these models compare with well-known computation-intensive applications including weather forecasting and quantum chemical calculations. A survey of the performance of a variety of available hardware, as measured by the run times for a reactive transport model HYDROGEOCHEM, showed that while supercomputers provide the fastest execution times for such problems, relatively low-cost reduced instruction set computer (RISC) based scalar computers provide the best performance-to-price ratio. Because supercomputers like the Cray X-MP are inherently multiuser resources, often the RISC computers also provide much better turnaround times. Furthermore, RISC-based workstations provide the best platforms for "visualization" of groundwater flow and contaminant plumes. The most notable result, however, is that current workstations costing less than $10,000 provide performance within a factor of 5 of a Cray X-MP.

Complex optimization for big computational and experimental neutron datasets

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

Bao, Feng; Oak Ridge National Lab.; Archibald, Richard

Here, we present a framework to use high performance computing to determine accurate solutions to the inverse optimization problem of big experimental data against computational models. We demonstrate how image processing, mathematical regularization, and hierarchical modeling can be used to solve complex optimization problems on big data. We also demonstrate how both model and data information can be used to further increase solution accuracy of optimization by providing confidence regions for the processing and regularization algorithms. Finally, we use the framework in conjunction with the software package SIMPHONIES to analyze results from neutron scattering experiments on silicon single crystals, andmore » refine first principles calculations to better describe the experimental data.« less

Complex optimization for big computational and experimental neutron datasets

DOE PAGES

Bao, Feng; Oak Ridge National Lab.; Archibald, Richard; ...

2016-11-07

Here, we present a framework to use high performance computing to determine accurate solutions to the inverse optimization problem of big experimental data against computational models. We demonstrate how image processing, mathematical regularization, and hierarchical modeling can be used to solve complex optimization problems on big data. We also demonstrate how both model and data information can be used to further increase solution accuracy of optimization by providing confidence regions for the processing and regularization algorithms. Finally, we use the framework in conjunction with the software package SIMPHONIES to analyze results from neutron scattering experiments on silicon single crystals, andmore » refine first principles calculations to better describe the experimental data.« less

Computational reacting gas dynamics

NASA Technical Reports Server (NTRS)

Lam, S. H.

1993-01-01

In the study of high speed flows at high altitudes, such as that encountered by re-entry spacecrafts, the interaction of chemical reactions and other non-equilibrium processes in the flow field with the gas dynamics is crucial. Generally speaking, problems of this level of complexity must resort to numerical methods for solutions, using sophisticated computational fluid dynamics (CFD) codes. The difficulties introduced by reacting gas dynamics can be classified into three distinct headings: (1) the usually inadequate knowledge of the reaction rate coefficients in the non-equilibrium reaction system; (2) the vastly larger number of unknowns involved in the computation and the expected stiffness of the equations; and (3) the interpretation of the detailed reacting CFD numerical results. The research performed accepts the premise that reacting flows of practical interest in the future will in general be too complex or 'untractable' for traditional analytical developments. The power of modern computers must be exploited. However, instead of focusing solely on the construction of numerical solutions of full-model equations, attention is also directed to the 'derivation' of the simplified model from the given full-model. In other words, the present research aims to utilize computations to do tasks which have traditionally been done by skilled theoreticians: to reduce an originally complex full-model system into an approximate but otherwise equivalent simplified model system. The tacit assumption is that once the appropriate simplified model is derived, the interpretation of the detailed numerical reacting CFD numerical results will become much easier. The approach of the research is called computational singular perturbation (CSP).

[AERA. Dream machines and computing practices at the Mathematical Center].

PubMed

Alberts, Gerard; De Beer, Huub T

2008-01-01

Dream machines may be just as effective as the ones materialised. Their symbolic thrust can be quite powerful. The Amsterdam 'Mathematisch Centrum' (Mathematical Center), founded February 11, 1946, created a Computing Department in an effort to realise its goal of serving society. When Aad van Wijngaarden was appointed as head of the Computing Department, however, he claimed space for scientific research and computer construction, next to computing as a service. Still, the computing service following the five stage style of Hartree's numerical analysis remained a dominant characteristic of the work of the Computing Department. The high level of ambition held by Aad van Wijngaarden lead to ever renewed projections of big automatic computers, symbolised by the never-built AERA. Even a machine that was actually constructed, the ARRA which followed A.D. Booth's design of the ARC, never made it into real operation. It did serve Van Wijngaarden to bluff his way into the computer age by midsummer 1952. Not until January 1954 did the computing department have a working stored program computer, which for reasons of policy went under the same name: ARRA. After just one other machine, the ARMAC, had been produced, a separate company, Electrologica, was set up for the manufacture of computers, which produced the rather successful X1 computer. The combination of ambition and absence of a working machine lead to a high level of work on programming, way beyond the usual ideas of libraries of subroutines. Edsger W. Dijkstra in particular led the way to an emphasis on the duties of the programmer within the pattern of numerical analysis. Programs generating programs, known elsewhere as autocoding systems, were at the 'Mathematisch Centrum' called 'superprograms'. Practical examples were usually called a 'complex', in Dutch, where in English one might say 'system'. Historically, this is where software begins. Dekker's matrix complex, Dijkstra's interrupt system, Dijkstra and Zonneveld's ALGOL compiler--which for housekeeping contained 'the complex'--were actual examples of such super programs. In 1960 this compiler gave the Mathematical Center a leading edge in the early development of software.

Lumbo-Pelvic-Hip Complex Pain in a Competitive Basketball Player

PubMed Central

Reiman, Michael P.; Cox, Kara D.; Jones, Kay S.; Byrd, J. W.

2011-01-01

Establishing the cause of lumbo-pelvic-hip complex pain is a challenge for many clinicians. This case report describes the mechanism of injury, diagnostic process, surgical management, and rehabilitation of a female high school basketball athlete who sustained an injury when falling on her right side. Diagnostics included clinical examination, radiography of the spine and hip joint, magnetic resonance imaging arthrogram, 3-dimensional computed tomography scan, and computed tomography of the hip joint. A systematic multidisciplinary clinical approach resulted in the patient’s return to previous functional levels. PMID:23015993

Multiscale high-order/low-order (HOLO) algorithms and applications

NASA Astrophysics Data System (ADS)

Chacón, L.; Chen, G.; Knoll, D. A.; Newman, C.; Park, H.; Taitano, W.; Willert, J. A.; Womeldorff, G.

2017-02-01

We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

A nodal discontinuous Galerkin approach to 3-D viscoelastic wave propagation in complex geological media

NASA Astrophysics Data System (ADS)

Lambrecht, L.; Lamert, A.; Friederich, W.; Möller, T.; Boxberg, M. S.

2018-03-01

A nodal discontinuous Galerkin (NDG) approach is developed and implemented for the computation of viscoelastic wavefields in complex geological media. The NDG approach combines unstructured tetrahedral meshes with an element-wise, high-order spatial interpolation of the wavefield based on Lagrange polynomials. Numerical fluxes are computed from an exact solution of the heterogeneous Riemann problem. Our implementation offers capabilities for modelling viscoelastic wave propagation in 1-D, 2-D and 3-D settings of very different spatial scale with little logistical overhead. It allows the import of external tetrahedral meshes provided by independent meshing software and can be run in a parallel computing environment. Computation of adjoint wavefields and an interface for the computation of waveform sensitivity kernels are offered. The method is validated in 2-D and 3-D by comparison to analytical solutions and results from a spectral element method. The capabilities of the NDG method are demonstrated through a 3-D example case taken from tunnel seismics which considers high-frequency elastic wave propagation around a curved underground tunnel cutting through inclined and faulted sedimentary strata. The NDG method was coded into the open-source software package NEXD and is available from GitHub.

ClimateSpark: An in-memory distributed computing framework for big climate data analytics

NASA Astrophysics Data System (ADS)

Hu, Fei; Yang, Chaowei; Schnase, John L.; Duffy, Daniel Q.; Xu, Mengchao; Bowen, Michael K.; Lee, Tsengdar; Song, Weiwei

2018-06-01

The unprecedented growth of climate data creates new opportunities for climate studies, and yet big climate data pose a grand challenge to climatologists to efficiently manage and analyze big data. The complexity of climate data content and analytical algorithms increases the difficulty of implementing algorithms on high performance computing systems. This paper proposes an in-memory, distributed computing framework, ClimateSpark, to facilitate complex big data analytics and time-consuming computational tasks. Chunking data structure improves parallel I/O efficiency, while a spatiotemporal index is built for the chunks to avoid unnecessary data reading and preprocessing. An integrated, multi-dimensional, array-based data model (ClimateRDD) and ETL operations are developed to address big climate data variety by integrating the processing components of the climate data lifecycle. ClimateSpark utilizes Spark SQL and Apache Zeppelin to develop a web portal to facilitate the interaction among climatologists, climate data, analytic operations and computing resources (e.g., using SQL query and Scala/Python notebook). Experimental results show that ClimateSpark conducts different spatiotemporal data queries/analytics with high efficiency and data locality. ClimateSpark is easily adaptable to other big multiple-dimensional, array-based datasets in various geoscience domains.

40-Gb/s PAM4 with low-complexity equalizers for next-generation PON systems

NASA Astrophysics Data System (ADS)

Tang, Xizi; Zhou, Ji; Guo, Mengqi; Qi, Jia; Hu, Fan; Qiao, Yaojun; Lu, Yueming

2018-01-01

In this paper, we demonstrate 40-Gb/s four-level pulse amplitude modulation (PAM4) transmission with 10 GHz devices and low-complexity equalizers for next-generation passive optical network (PON) systems. Simple feed-forward equalizer (FFE) and decision feedback equalizer (DFE) enable 20 km fiber transmission while high-complexity Volterra algorithm in combination with FFE and DFE can extend the transmission distance to 40 km. A simplified Volterra algorithm is proposed for reducing computational complexity. Simulation results show that the simplified Volterra algorithm reduces up to ∼75% computational complexity at a relatively low cost of only 0.4 dB power budget. At a forward error correction (FEC) threshold of 10-3 , we achieve 31.2 dB and 30.8 dB power budget over 40 km fiber transmission using traditional FFE-DFE-Volterra and our simplified FFE-DFE-Volterra, respectively.

The High-Performance Computing and Communications program, the national information infrastructure and health care.

PubMed Central

Lindberg, D A; Humphreys, B L

1995-01-01

The High-Performance Computing and Communications (HPCC) program is a multiagency federal effort to advance the state of computing and communications and to provide the technologic platform on which the National Information Infrastructure (NII) can be built. The HPCC program supports the development of high-speed computers, high-speed telecommunications, related software and algorithms, education and training, and information infrastructure technology and applications. The vision of the NII is to extend access to high-performance computing and communications to virtually every U.S. citizen so that the technology can be used to improve the civil infrastructure, lifelong learning, energy management, health care, etc. Development of the NII will require resolution of complex economic and social issues, including information privacy. Health-related applications supported under the HPCC program and NII initiatives include connection of health care institutions to the Internet; enhanced access to gene sequence data; the "Visible Human" Project; and test-bed projects in telemedicine, electronic patient records, shared informatics tool development, and image systems. PMID:7614116

DEMONSTRATION BULLETIN: HIGH VOLTAGE ELECTRON BEAM TECHNOLOGY - HIGH VOLTAGE ENVIRONMENTAL APPLICATIONS, INC.

EPA Science Inventory

The high energy electron beam irradiation technology is a low temperature method for destroying complex mixtures of hazardous organic chemicals in solutions containing solids. The system consists of a computer-automated, portable electron beam accelerator and a delivery system. T...

Artificial Intelligence Applications to High-Technology Training.

ERIC Educational Resources Information Center

Dede, Christopher

1987-01-01

Discusses the use of artificial intelligence to improve occupational instruction in complex subjects with high performance goals, such as those required for high-technology jobs. Highlights include intelligent computer assisted instruction, examples in space technology training, intelligent simulation environments, and the need for adult training…

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.

Programming Pluralism: Using Learning Analytics to Detect Patterns in the Learning of Computer Programming

ERIC Educational Resources Information Center

Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne

2014-01-01

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…

Computer-Aided Engineering Tools | Water Power | NREL

Science.gov Websites

energy converters that will provide a full range of simulation capabilities for single devices and arrays simulation of water power technologies on high-performance computers enables the study of complex systems and experimentation. Such simulation is critical to accelerate progress in energy programs within the U.S. Department

Fractal Simulations of African Design in Pre-College Computing Education

ERIC Educational Resources Information Center

Eglash, Ron; Krishnamoorthy, Mukkai; Sanchez, Jason; Woodbridge, Andrew

2011-01-01

This article describes the use of fractal simulations of African design in a high school computing class. Fractal patterns--repetitions of shape at multiple scales--are a common feature in many aspects of African design. In African architecture we often see circular houses grouped in circular complexes, or rectangular houses in rectangular…

Investigating the Effectiveness of Computer Simulations for Chemistry Learning

ERIC Educational Resources Information Center

Plass, Jan L.; Milne, Catherine; Homer, Bruce D.; Schwartz, Ruth N.; Hayward, Elizabeth O.; Jordan, Trace; Verkuilen, Jay; Ng, Florrie; Wang, Yan; Barrientos, Juan

2012-01-01

Are well-designed computer simulations an effective tool to support student understanding of complex concepts in chemistry when integrated into high school science classrooms? We investigated scaling up the use of a sequence of simulations of kinetic molecular theory and associated topics of diffusion, gas laws, and phase change, which we designed…

Multimodal Learning Analytics and Education Data Mining: Using Computational Technologies to Measure Complex Learning Tasks

ERIC Educational Resources Information Center

Blikstein, Paulo; Worsley, Marcelo

2016-01-01

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

Use of Multiple GPUs to Speedup the Execution of a Three-Dimensional Computational Model of the Innate Immune System

NASA Astrophysics Data System (ADS)

Xavier, M. P.; do Nascimento, T. M.; dos Santos, R. W.; Lobosco, M.

2014-03-01

The development of computational systems that mimics the physiological response of organs or even the entire body is a complex task. One of the issues that makes this task extremely complex is the huge computational resources needed to execute the simulations. For this reason, the use of parallel computing is mandatory. In this work, we focus on the simulation of temporal and spatial behaviour of some human innate immune system cells and molecules in a small three-dimensional section of a tissue. To perform this simulation, we use multiple Graphics Processing Units (GPUs) in a shared-memory environment. Despite of high initialization and communication costs imposed by the use of GPUs, the techniques used to implement the HIS simulator have shown to be very effective to achieve this purpose.

"Attention on the flight deck": what ambulatory care providers can learn from pilots about complex coordinated actions.

PubMed

Frankel, Richard M; Saleem, Jason J

2013-12-01

Technical and interpersonal challenges of using electronic health records (EHRs) in ambulatory care persist. We use cockpit communication as an example of highly coordinated complex activity during flight and compare it with providers' communication when computers are used in the exam room. Maximum variation sampling was used to identify two videotapes from a parent study of primary care physicians' exam room computer demonstrating the greatest variation. We then produced and analyzed visualizations of the time providers spent looking at the computer and looking at the patient. Unlike the cockpit which is engineered to optimize joint attention on complex coordinated activities, we found polar extremes in the use of joint focus of attention to manage the medical encounter. We conclude that there is a great deal of room for improving the balance of interpersonal and technical attention that occurs in routine ambulatory visits in which computers are present in the exam room. Using well-known aviation practices can help primary care providers become more aware of the opportunities and challenges for enhancing the physician patient relationship in an era of exam room computing. Published by Elsevier Ireland Ltd.

Streamwise Vorticity Generation in Laminar and Turbulent Jets

NASA Technical Reports Server (NTRS)

Demuren, Aodeji O.; Wilson, Robert V.

1999-01-01

Complex streamwise vorticity fields are observed in the evolution of non-circular jets. Generation mechanisms are investigated via Reynolds-averaged (RANS), large-eddy (LES) and direct numerical (DNS) simulations of laminar and turbulent rectangular jets. Complex vortex interactions are found in DNS of laminar jets, but axis-switching is observed only when a single instability mode is present in the incoming mixing layer. With several modes present, the structures are not coherent and no axis-switching occurs, RANS computations also produce no axis-switching. On the other hand, LES of high Reynolds number turbulent jets produce axis-switching even for cases with several instability modes in the mixing layer. Analysis of the source terms of the mean streamwise vorticity equation through post-processing of the instantaneous results shows that, complex interactions of gradients of the normal and shear Reynolds stresses are responsible for the generation of streamwise vorticity which leads to axis-switching. RANS computations confirm these results. k - epsilon turbulence model computations fail to reproduce the phenomenon, whereas algebraic Reynolds stress model (ASM) computations, in which the secondary normal and shear stresses are computed explicitly, succeeded in reproducing the phenomenon accurately.

Oligomerization of G protein-coupled receptors: computational methods.

PubMed

Selent, J; Kaczor, A A

2011-01-01

Recent research has unveiled the complexity of mechanisms involved in G protein-coupled receptor (GPCR) functioning in which receptor dimerization/oligomerization may play an important role. Although the first high-resolution X-ray structure for a likely functional chemokine receptor dimer has been deposited in the Protein Data Bank, the interactions and mechanisms of dimer formation are not yet fully understood. In this respect, computational methods play a key role for predicting accurate GPCR complexes. This review outlines computational approaches focusing on sequence- and structure-based methodologies as well as discusses their advantages and limitations. Sequence-based approaches that search for possible protein-protein interfaces in GPCR complexes have been applied with success in several studies, but did not yield always consistent results. Structure-based methodologies are a potent complement to sequence-based approaches. For instance, protein-protein docking is a valuable method especially when guided by experimental constraints. Some disadvantages like limited receptor flexibility and non-consideration of the membrane environment have to be taken into account. Molecular dynamics simulation can overcome these drawbacks giving a detailed description of conformational changes in a native-like membrane. Successful prediction of GPCR complexes using computational approaches combined with experimental efforts may help to understand the role of dimeric/oligomeric GPCR complexes for fine-tuning receptor signaling. Moreover, since such GPCR complexes have attracted interest as potential drug target for diverse diseases, unveiling molecular determinants of dimerization/oligomerization can provide important implications for drug discovery.

Patient-Specific Computational Modeling of Human Phonation

NASA Astrophysics Data System (ADS)

Xue, Qian; Zheng, Xudong; University of Maine Team

2013-11-01

Phonation is a common biological process resulted from the complex nonlinear coupling between glottal aerodynamics and vocal fold vibrations. In the past, the simplified symmetric straight geometric models were commonly employed for experimental and computational studies. The shape of larynx lumen and vocal folds are highly three-dimensional indeed and the complex realistic geometry produces profound impacts on both glottal flow and vocal fold vibrations. To elucidate the effect of geometric complexity on voice production and improve the fundamental understanding of human phonation, a full flow-structure interaction simulation is carried out on a patient-specific larynx model. To the best of our knowledge, this is the first patient-specific flow-structure interaction study of human phonation. The simulation results are well compared to the established human data. The effects of realistic geometry on glottal flow and vocal fold dynamics are investigated. It is found that both glottal flow and vocal fold dynamics present a high level of difference from the previous simplified model. This study also paved the important step toward the development of computer model for voice disease diagnosis and surgical planning. The project described was supported by Grant Number ROlDC007125 from the National Institute on Deafness and Other Communication Disorders (NIDCD).

User's guide for ENSAERO: A multidisciplinary program for fluid/structural/control interaction studies of aircraft (release 1)

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.

1994-01-01

Strong interactions can occur between the flow about an aerospace vehicle and its structural components resulting in several important aeroelastic phenomena. These aeroelastic phenomena can significantly influence the performance of the vehicle. At present, closed-form solutions are available for aeroelastic computations when flows are in either the linear subsonic or supersonic range. However, for aeroelasticity involving complex nonlinear flows with shock waves, vortices, flow separations, and aerodynamic heating, computational methods are still under development. These complex aeroelastic interactions can be dangerous and limit the performance of aircraft. Examples of these detrimental effects are aircraft with highly swept wings experiencing vortex-induced aeroelastic oscillations, transonic regime at which the flutter speed is low, aerothermoelastic loads that play a critical role in the design of high-speed vehicles, and flow separations that often lead to buffeting with undesirable structural oscillations. The simulation of these complex aeroelastic phenomena requires an integrated analysis of fluids and structures. This report presents a summary of the development, applications, and procedures to use the multidisciplinary computer code ENSAERO. This code is based on the Euler/Navier-Stokes flow equations and modal/finite-element structural equations.

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations.

PubMed

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei; Jiang, Yu

2017-12-01

The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1-2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. © The Authors 2017. Published by Oxford University Press.

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations

PubMed Central

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei

2017-01-01

Abstract Background The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Results Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1–2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. Conclusions The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. PMID:29220491

Applications of complex systems theory in nursing education, research, and practice.

PubMed

Clancy, Thomas R; Effken, Judith A; Pesut, Daniel

2008-01-01

The clinical and administrative processes in today's healthcare environment are becoming increasingly complex. Multiple providers, new technology, competition, and the growing ubiquity of information all contribute to the notion of health care as a complex system. A complex system (CS) is characterized by a highly connected network of entities (e.g., physical objects, people or groups of people) from which higher order behavior emerges. Research in the transdisciplinary field of CS has focused on the use of computational modeling and simulation as a methodology for analyzing CS behavior. The creation of virtual worlds through computer simulation allows researchers to analyze multiple variables simultaneously and begin to understand behaviors that are common regardless of the discipline. The application of CS principles, mediated through computer simulation, informs nursing practice of the benefits and drawbacks of new procedures, protocols and practices before having to actually implement them. The inclusion of new computational tools and their applications in nursing education is also gaining attention. For example, education in CSs and applied computational applications has been endorsed by The Institute of Medicine, the American Organization of Nurse Executives and the American Association of Colleges of Nursing as essential training of nurse leaders. The purpose of this article is to review current research literature regarding CS science within the context of expert practice and implications for the education of nurse leadership roles. The article focuses on 3 broad areas: CS defined, literature review and exemplars from CS research and applications of CS theory in nursing leadership education. The article also highlights the key role nursing informaticists play in integrating emerging computational tools in the analysis of complex nursing systems.

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

Grid-converged solution and analysis of the unsteady viscous flow in a two-dimensional shock tube

NASA Astrophysics Data System (ADS)

Zhou, Guangzhao; Xu, Kun; Liu, Feng

2018-01-01

The flow in a shock tube is extremely complex with dynamic multi-scale structures of sharp fronts, flow separation, and vortices due to the interaction of the shock wave, the contact surface, and the boundary layer over the side wall of the tube. Prediction and understanding of the complex fluid dynamics are of theoretical and practical importance. It is also an extremely challenging problem for numerical simulation, especially at relatively high Reynolds numbers. Daru and Tenaud ["Evaluation of TVD high resolution schemes for unsteady viscous shocked flows," Comput. Fluids 30, 89-113 (2001)] proposed a two-dimensional model problem as a numerical test case for high-resolution schemes to simulate the flow field in a square closed shock tube. Though many researchers attempted this problem using a variety of computational methods, there is not yet an agreed-upon grid-converged solution of the problem at the Reynolds number of 1000. This paper presents a rigorous grid-convergence study and the resulting grid-converged solutions for this problem by using a newly developed, efficient, and high-order gas-kinetic scheme. Critical data extracted from the converged solutions are documented as benchmark data. The complex fluid dynamics of the flow at Re = 1000 are discussed and analyzed in detail. Major phenomena revealed by the numerical computations include the downward concentration of the fluid through the curved shock, the formation of the vortices, the mechanism of the shock wave bifurcation, the structure of the jet along the bottom wall, and the Kelvin-Helmholtz instability near the contact surface. Presentation and analysis of those flow processes provide important physical insight into the complex flow physics occurring in a shock tube.

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Neural simulations on multi-core architectures.

PubMed

Eichner, Hubert; Klug, Tobias; Borst, Alexander

2009-01-01

Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations. At the same time, a rather radical change in personal computer technology emerges with the establishment of multi-cores: high-density, explicitly parallel processor architectures for both high performance as well as standard desktop computers. This work introduces strategies for the parallelization of biophysically realistic neural simulations based on the compartmental modeling technique and results of such an implementation, with a strong focus on multi-core architectures and automation, i.e. user-transparent load balancing.

Neural Simulations on Multi-Core Architectures

PubMed Central

Eichner, Hubert; Klug, Tobias; Borst, Alexander

2009-01-01

Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations. At the same time, a rather radical change in personal computer technology emerges with the establishment of multi-cores: high-density, explicitly parallel processor architectures for both high performance as well as standard desktop computers. This work introduces strategies for the parallelization of biophysically realistic neural simulations based on the compartmental modeling technique and results of such an implementation, with a strong focus on multi-core architectures and automation, i.e. user-transparent load balancing. PMID:19636393

A visual programming environment for the Navier-Stokes computer

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl; Crockett, Thomas W.; Middleton, David

1988-01-01

The Navier-Stokes computer is a high-performance, reconfigurable, pipelined machine designed to solve large computational fluid dynamics problems. Due to the complexity of the architecture, development of effective, high-level language compilers for the system appears to be a very difficult task. Consequently, a visual programming methodology has been developed which allows users to program the system at an architectural level by constructing diagrams of the pipeline configuration. These schematic program representations can then be checked for validity and automatically translated into machine code. The visual environment is illustrated by using a prototype graphical editor to program an example problem.

Petascale self-consistent electromagnetic computations using scalable and accurate algorithms for complex structures

NASA Astrophysics Data System (ADS)

Cary, John R.; Abell, D.; Amundson, J.; Bruhwiler, D. L.; Busby, R.; Carlsson, J. A.; Dimitrov, D. A.; Kashdan, E.; Messmer, P.; Nieter, C.; Smithe, D. N.; Spentzouris, P.; Stoltz, P.; Trines, R. M.; Wang, H.; Werner, G. R.

2006-09-01

As the size and cost of particle accelerators escalate, high-performance computing plays an increasingly important role; optimization through accurate, detailed computermodeling increases performance and reduces costs. But consequently, computer simulations face enormous challenges. Early approximation methods, such as expansions in distance from the design orbit, were unable to supply detailed accurate results, such as in the computation of wake fields in complex cavities. Since the advent of message-passing supercomputers with thousands of processors, earlier approximations are no longer necessary, and it is now possible to compute wake fields, the effects of dampers, and self-consistent dynamics in cavities accurately. In this environment, the focus has shifted towards the development and implementation of algorithms that scale to large numbers of processors. So-called charge-conserving algorithms evolve the electromagnetic fields without the need for any global solves (which are difficult to scale up to many processors). Using cut-cell (or embedded) boundaries, these algorithms can simulate the fields in complex accelerator cavities with curved walls. New implicit algorithms, which are stable for any time-step, conserve charge as well, allowing faster simulation of structures with details small compared to the characteristic wavelength. These algorithmic and computational advances have been implemented in the VORPAL7 Framework, a flexible, object-oriented, massively parallel computational application that allows run-time assembly of algorithms and objects, thus composing an application on the fly.

Offdiagonal complexity: A computationally quick complexity measure for graphs and networks

NASA Astrophysics Data System (ADS)

Claussen, Jens Christian

2007-02-01

A vast variety of biological, social, and economical networks shows topologies drastically differing from random graphs; yet the quantitative characterization remains unsatisfactory from a conceptual point of view. Motivated from the discussion of small scale-free networks, a biased link distribution entropy is defined, which takes an extremum for a power-law distribution. This approach is extended to the node-node link cross-distribution, whose nondiagonal elements characterize the graph structure beyond link distribution, cluster coefficient and average path length. From here a simple (and computationally cheap) complexity measure can be defined. This offdiagonal complexity (OdC) is proposed as a novel measure to characterize the complexity of an undirected graph, or network. While both for regular lattices and fully connected networks OdC is zero, it takes a moderately low value for a random graph and shows high values for apparently complex structures as scale-free networks and hierarchical trees. The OdC approach is applied to the Helicobacter pylori protein interaction network and randomly rewired surrogates.

A 3D puzzle approach to building protein-DNA structures.

PubMed

Hinton, Deborah M

2017-03-15

Despite recent advances in structural analysis, it is still challenging to obtain a high-resolution structure for a complex of RNA polymerase, transcriptional factors, and DNA. However, using biochemical constraints, 3D printed models of available structures, and computer modeling, one can build biologically relevant models of such supramolecular complexes.

Application of advanced grid generation techniques for flow field computations about complex configurations

NASA Technical Reports Server (NTRS)

Kathong, Monchai; Tiwari, Surendra N.

1988-01-01

In the computation of flowfields about complex configurations, it is very difficult to construct a boundary-fitted coordinate system. An alternative approach is to use several grids at once, each of which is generated independently. This procedure is called the multiple grids or zonal grids approach; its applications are investigated. The method conservative providing conservation of fluxes at grid interfaces. The Euler equations are solved numerically on such grids for various configurations. The numerical scheme used is the finite-volume technique with a three-stage Runge-Kutta time integration. The code is vectorized and programmed to run on the CDC VPS-32 computer. Steady state solutions of the Euler equations are presented and discussed. The solutions include: low speed flow over a sphere, high speed flow over a slender body, supersonic flow through a duct, and supersonic internal/external flow interaction for an aircraft configuration at various angles of attack. The results demonstrate that the multiple grids approach along with the conservative interfacing is capable of computing the flows about the complex configurations where the use of a single grid system is not possible.

Scattering and Absorption Properties of Polydisperse Wavelength-sized Particles Covered with Much Smaller Grains

NASA Technical Reports Server (NTRS)

Dlugach, Jana M.; Mishchenko, Michael I.; Mackowski, Daniel W.

2012-01-01

Using the results of direct, numerically exact computer solutions of the Maxwell equations, we analyze scattering and absorption characteristics of polydisperse compound particles in the form of wavelength-sized spheres covered with a large number of much smaller spherical grains.The results pertain to the complex refractive indices1.55 + i0.0003,1.55 + i0.3, and 3 + i0.1. We show that the optical effects of dusting wavelength-sized hosts by microscopic grains can vary depending on the number and size of the grains as well as on the complex refractive index. Our computations also demonstrate the high efficiency of the new superposition T-matrix code developed for use on distributed memory computer clusters.

Information processing using a single dynamical node as complex system

PubMed Central

Appeltant, L.; Soriano, M.C.; Van der Sande, G.; Danckaert, J.; Massar, S.; Dambre, J.; Schrauwen, B.; Mirasso, C.R.; Fischer, I.

2011-01-01

Novel methods for information processing are highly desired in our information-driven society. Inspired by the brain's ability to process information, the recently introduced paradigm known as 'reservoir computing' shows that complex networks can efficiently perform computation. Here we introduce a novel architecture that reduces the usually required large number of elements to a single nonlinear node with delayed feedback. Through an electronic implementation, we experimentally and numerically demonstrate excellent performance in a speech recognition benchmark. Complementary numerical studies also show excellent performance for a time series prediction benchmark. These results prove that delay-dynamical systems, even in their simplest manifestation, can perform efficient information processing. This finding paves the way to feasible and resource-efficient technological implementations of reservoir computing. PMID:21915110

Routine Discovery of Complex Genetic Models using Genetic Algorithms

PubMed Central

Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.

2010-01-01

Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983

Distributed Computation of the knn Graph for Large High-Dimensional Point Sets

PubMed Central

Plaku, Erion; Kavraki, Lydia E.

2009-01-01

High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) graphs. The knn graph of a data set is obtained by connecting each point to its k closest points. As the research in the above-mentioned fields progressively addresses problems of unprecedented complexity, the demand for computing knn graphs based on arbitrary distance metrics and large high-dimensional data sets increases, exceeding resources available to a single machine. In this work we efficiently distribute the computation of knn graphs for clusters of processors with message passing. Extensions to our distributed framework include the computation of graphs based on other proximity queries, such as approximate knn or range queries. Our experiments show nearly linear speedup with over one hundred processors and indicate that similar speedup can be obtained with several hundred processors. PMID:19847318

Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling.

PubMed

Perdikaris, P; Raissi, M; Damianou, A; Lawrence, N D; Karniadakis, G E

2017-02-01

Multi-fidelity modelling enables accurate inference of quantities of interest by synergistically combining realizations of low-cost/low-fidelity models with a small set of high-fidelity observations. This is particularly effective when the low- and high-fidelity models exhibit strong correlations, and can lead to significant computational gains over approaches that solely rely on high-fidelity models. However, in many cases of practical interest, low-fidelity models can only be well correlated to their high-fidelity counterparts for a specific range of input parameters, and potentially return wrong trends and erroneous predictions if probed outside of their validity regime. Here we put forth a probabilistic framework based on Gaussian process regression and nonlinear autoregressive schemes that is capable of learning complex nonlinear and space-dependent cross-correlations between models of variable fidelity, and can effectively safeguard against low-fidelity models that provide wrong trends. This introduces a new class of multi-fidelity information fusion algorithms that provide a fundamental extension to the existing linear autoregressive methodologies, while still maintaining the same algorithmic complexity and overall computational cost. The performance of the proposed methods is tested in several benchmark problems involving both synthetic and real multi-fidelity datasets from computational fluid dynamics simulations.

An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

PubMed

Kundu, Kousik; Backofen, Rolf

2017-01-01

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

iMarNet: an ocean biogeochemistry model inter-comparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-07-01

Ocean biogeochemistry (OBGC) models span a wide range of complexities from highly simplified, nutrient-restoring schemes, through nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, through to models that represent a broader trophic structure by grouping organisms as plankton functional types (PFT) based on their biogeochemical role (Dynamic Green Ocean Models; DGOM) and ecosystem models which group organisms by ecological function and trait. OBGC models are now integral components of Earth System Models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here, we present an inter-comparison of six OBGC models that were candidates for implementation within the next UK Earth System Model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the Nucleus for the European Modelling of the Ocean (NEMO) ocean general circulation model (GCM), and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform or underperform all other models across all metrics. Nonetheless, the simpler models that are easier to tune are broadly closer to observations across a number of fields, and thus offer a high-efficiency option for ESMs that prioritise high resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low resolution climate dynamics and high complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-12-01

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

The FuturICT education accelerator

NASA Astrophysics Data System (ADS)

Johnson, J.; Buckingham Shum, S.; Willis, A.; Bishop, S.; Zamenopoulos, T.; Swithenby, S.; MacKay, R.; Merali, Y.; Lorincz, A.; Costea, C.; Bourgine, P.; Louçã, J.; Kapenieks, A.; Kelley, P.; Caird, S.; Bromley, J.; Deakin Crick, R.; Goldspink, C.; Collet, P.; Carbone, A.; Helbing, D.

2012-11-01

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year `man-on-the-moon' project is proposed in which FuturICT's unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a `wind tunnel' for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT.

Is Model-Based Development a Favorable Approach for Complex and Safety-Critical Computer Systems on Commercial Aircraft?

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

A system is safety-critical if its failure can endanger human life or cause significant damage to property or the environment. State-of-the-art computer systems on commercial aircraft are highly complex, software-intensive, functionally integrated, and network-centric systems of systems. Ensuring that such systems are safe and comply with existing safety regulations is costly and time-consuming as the level of rigor in the development process, especially the validation and verification activities, is determined by considerations of system complexity and safety criticality. A significant degree of care and deep insight into the operational principles of these systems is required to ensure adequate coverage of all design implications relevant to system safety. Model-based development methodologies, methods, tools, and techniques facilitate collaboration and enable the use of common design artifacts among groups dealing with different aspects of the development of a system. This paper examines the application of model-based development to complex and safety-critical aircraft computer systems. Benefits and detriments are identified and an overall assessment of the approach is given.

Real-time, high frequency QRS electrocardiograph with reduced amplitude zone detection

NASA Technical Reports Server (NTRS)

Schlegel, Todd T. (Inventor); DePalma, Jude L. (Inventor); Moradi, Saeed (Inventor)

2009-01-01

Real time cardiac electrical data are received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed in real time in a useful form on a computer screen or monitor. The monitor displays the high frequency data from the QRS complex in units of microvolts, juxtaposed with a display of conventional ECG data in units of millivolts or microvolts. The high frequency data are analyzed for their root mean square (RMS) voltage values and the discrete RMS values and related parameters are displayed in real time. The high frequency data from the QRS complex are analyzed with imbedded algorithms to determine the presence or absence of reduced amplitude zones, referred to herein as ''RAZs''. RAZs are displayed as ''go, no-go'' signals on the computer monitor. The RMS and related values of the high frequency components are displayed as time varying signals, and the presence or absence of RAZs may be similarly displayed over time.

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

PubMed

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-02-20

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

Air Force Laboratory’s 2005 Technology Milestones

DTIC Science & Technology

2006-01-01

Computational materials science methods can benefit the design and property prediction of complex real-world materials. With these models , scientists and...Warfighter Page Air High - Frequency Acoustic System...800) 203-6451 High - Frequency Acoustic System Payoff Scientists created the High - Frequency Acoustic Suppression Technology (HiFAST) airflow control

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

Chacón, L., E-mail: chacon@lanl.gov; Chen, G.; Knoll, D.A.

We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLOmore » approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Numerical Simulation of Pollutants' Transport and Fate in AN Unsteady Flow in Lower Bear River, Box Elder County, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2013-12-01

This study presents numerical application and statistical development of Stream Water Quality Modeling (SWQM) as a tool to investigate, manage, and research the transport and fate of water pollutants in Lower Bear River, Box elder County, Utah. The concerned segment under study is the Bear River starting from Cutler Dam to its confluence with the Malad River (Subbasin HUC 16010204). Water quality problems arise primarily from high phosphorus and total suspended sediment concentrations that were caused by five permitted point source discharges and complex network of canals and ducts of varying sizes and carrying capacities that transport water (for farming and agriculture uses) from Bear River and then back to it. Utah Department of Environmental Quality (DEQ) has designated the entire reach of the Bear River between Cutler Reservoir and Great Salt Lake as impaired. Stream water quality modeling (SWQM) requires specification of an appropriate model structure and process formulation according to nature of study area and purpose of investigation. The current model is i) one dimensional (1D), ii) numerical, iii) unsteady, iv) mechanistic, v) dynamic, and vi) spatial (distributed). The basic principle during the study is using mass balance equations and numerical methods (Fickian advection-dispersion approach) for solving the related partial differential equations. Model error decreases and sensitivity increases as a model becomes more complex, as such: i) uncertainty (in parameters, data input and model structure), and ii) model complexity, will be under investigation. Watershed data (water quality parameters together with stream flow, seasonal variations, surrounding landscape, stream temperature, and points/nonpoint sources) were obtained majorly using the HydroDesktop which is a free and open source GIS enabled desktop application to find, download, visualize, and analyze time series of water and climate data registered with the CUAHSI Hydrologic Information System. Processing, assessment of validity, and distribution of time-series data was explored using the GNU R language (statistical computing and graphics environment). Physical, chemical, and biological processes equations were written in FORTRAN codes (High Performance Fortran) in order to compute and solve their hyperbolic and parabolic complexities. Post analysis of results conducted using GNU R language. High performance computing (HPC) will be introduced to expedite solving complex computational processes using parallel programming. It is expected that the model will assess nonpoint sources and specific point sources data to understand pollutants' causes, transfer, dispersion, and concentration in different locations of Bear River. Investigation the impact of reduction/removal in non-point nutrient loading to Bear River water quality management could be addressed. Keywords: computer modeling; numerical solutions; sensitivity analysis; uncertainty analysis; ecosystem processes; high Performance computing; water quality.

Field programmable gate array-assigned complex-valued computation and its limits

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

Bernard-Schwarz, Maria, E-mail: maria.bernardschwarz@ni.com; Institute of Applied Physics, TU Wien, Wiedner Hauptstrasse 8, 1040 Wien; Zwick, Wolfgang

We discuss how leveraging Field Programmable Gate Array (FPGA) technology as part of a high performance computing platform reduces latency to meet the demanding real time constraints of a quantum optics simulation. Implementations of complex-valued operations using fixed point numeric on a Virtex-5 FPGA compare favorably to more conventional solutions on a central processing unit. Our investigation explores the performance of multiple fixed point options along with a traditional 64 bits floating point version. With this information, the lowest execution times can be estimated. Relative error is examined to ensure simulation accuracy is maintained.

Scalable quantum computation scheme based on quantum-actuated nuclear-spin decoherence-free qubits

NASA Astrophysics Data System (ADS)

Dong, Lihong; Rong, Xing; Geng, Jianpei; Shi, Fazhan; Li, Zhaokai; Duan, Changkui; Du, Jiangfeng

2017-11-01

We propose a novel theoretical scheme of quantum computation. Nuclear spin pairs are utilized to encode decoherence-free (DF) qubits. A nitrogen-vacancy center serves as a quantum actuator to initialize, readout, and quantum control the DF qubits. The realization of CNOT gates between two DF qubits are also presented. Numerical simulations show high fidelities of all these processes. Additionally, we discuss the potential of scalability. Our scheme reduces the challenge of classical interfaces from controlling and observing complex quantum systems down to a simple quantum actuator. It also provides a novel way to handle complex quantum systems.

Comparing Computer-Supported Dynamic Modeling and "Paper & Pencil" Concept Mapping Technique in Students' Collaborative Activity

ERIC Educational Resources Information Center

Komis, Vassilis; Ergazaki, Marida; Zogza, Vassiliki

2007-01-01

This study aims at highlighting the collaborative activity of two high school students (age 14) in the cases of modeling the complex biological process of plant growth with two different tools: the "paper & pencil" concept mapping technique and the computer-supported educational environment "ModelsCreator". Students' shared activity in both cases…

Self-Directed Student Research through Analysis of Microarray Datasets: A Computer-Based Functional Genomics Practical Class for Masters-Level Students

ERIC Educational Resources Information Center

Grenville-Briggs, Laura J.; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate…

High Performance Parallel Computational Nanotechnology

NASA Technical Reports Server (NTRS)

Saini, Subhash; Craw, James M. (Technical Monitor)

1995-01-01

At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to control mini robotic manipulators for positional control; scalable numerical algorithms for reliability, verifications and testability. There appears no fundamental obstacle to simulating molecular compilers and molecular computers on high performance parallel computers, just as the Boeing 777 was simulated on a computer before manufacturing it.

High performance transcription factor-DNA docking with GPU computing

PubMed Central

2012-01-01

Background Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. Methods In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems. Results The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design. Conclusions We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem. PMID:22759575

Controlling Light Transmission Through Highly Scattering Media Using Semi-Definite Programming as a Phase Retrieval Computation Method.

PubMed

N'Gom, Moussa; Lien, Miao-Bin; Estakhri, Nooshin M; Norris, Theodore B; Michielssen, Eric; Nadakuditi, Raj Rao

2017-05-31

Complex Semi-Definite Programming (SDP) is introduced as a novel approach to phase retrieval enabled control of monochromatic light transmission through highly scattering media. In a simple optical setup, a spatial light modulator is used to generate a random sequence of phase-modulated wavefronts, and the resulting intensity speckle patterns in the transmitted light are acquired on a camera. The SDP algorithm allows computation of the complex transmission matrix of the system from this sequence of intensity-only measurements, without need for a reference beam. Once the transmission matrix is determined, optimal wavefronts are computed that focus the incident beam to any position or sequence of positions on the far side of the scattering medium, without the need for any subsequent measurements or wavefront shaping iterations. The number of measurements required and the degree of enhancement of the intensity at focus is determined by the number of pixels controlled by the spatial light modulator.

Development of Moire machine vision

NASA Technical Reports Server (NTRS)

Harding, Kevin G.

1987-01-01

Three dimensional perception is essential to the development of versatile robotics systems in order to handle complex manufacturing tasks in future factories and in providing high accuracy measurements needed in flexible manufacturing and quality control. A program is described which will develop the potential of Moire techniques to provide this capability in vision systems and automated measurements, and demonstrate artificial intelligence (AI) techniques to take advantage of the strengths of Moire sensing. Moire techniques provide a means of optically manipulating the complex visual data in a three dimensional scene into a form which can be easily and quickly analyzed by computers. This type of optical data manipulation provides high productivity through integrated automation, producing a high quality product while reducing computer and mechanical manipulation requirements and thereby the cost and time of production. This nondestructive evaluation is developed to be able to make full field range measurement and three dimensional scene analysis.

Openwebglobe 2: Visualization of Complex 3D-GEODATA in the (mobile) Webbrowser

NASA Astrophysics Data System (ADS)

Christen, M.

2016-06-01

Providing worldwide high resolution data for virtual globes consists of compute and storage intense tasks for processing data. Furthermore, rendering complex 3D-Geodata, such as 3D-City models with an extremely high polygon count and a vast amount of textures at interactive framerates is still a very challenging task, especially on mobile devices. This paper presents an approach for processing, caching and serving massive geospatial data in a cloud-based environment for large scale, out-of-core, highly scalable 3D scene rendering on a web based virtual globe. Cloud computing is used for processing large amounts of geospatial data and also for providing 2D and 3D map data to a large amount of (mobile) web clients. In this paper the approach for processing, rendering and caching very large datasets in the currently developed virtual globe "OpenWebGlobe 2" is shown, which displays 3D-Geodata on nearly every device.

Development of Moire machine vision

NASA Astrophysics Data System (ADS)

Harding, Kevin G.

1987-10-01

Three dimensional perception is essential to the development of versatile robotics systems in order to handle complex manufacturing tasks in future factories and in providing high accuracy measurements needed in flexible manufacturing and quality control. A program is described which will develop the potential of Moire techniques to provide this capability in vision systems and automated measurements, and demonstrate artificial intelligence (AI) techniques to take advantage of the strengths of Moire sensing. Moire techniques provide a means of optically manipulating the complex visual data in a three dimensional scene into a form which can be easily and quickly analyzed by computers. This type of optical data manipulation provides high productivity through integrated automation, producing a high quality product while reducing computer and mechanical manipulation requirements and thereby the cost and time of production. This nondestructive evaluation is developed to be able to make full field range measurement and three dimensional scene analysis.

The Evolution of Biological Complexity in Digital Organisms

NASA Astrophysics Data System (ADS)

Ofria, Charles

2013-03-01

When Darwin first proposed his theory of evolution by natural selection, he realized that it had a problem explaining the origins of traits of ``extreme perfection and complication'' such as the vertebrate eye. Critics of Darwin's theory have latched onto this perceived flaw as a proof that Darwinian evolution is impossible. In anticipation of this issue, Darwin described the perfect data needed to understand this process, but lamented that such data are ``scarcely ever possible'' to obtain. In this talk, I will discuss research where we use populations of digital organisms (self-replicating and evolving computer programs) to elucidate the genetic and evolutionary processes by which new, highly-complex traits arise, drawing inspiration directly from Darwin's wistful thinking and hypotheses. During the process of evolution in these fully-transparent computational environments we can measure the incorporation of new information into the genome, a process akin to a natural Maxwell's Demon, and identify the original source of any such information. We show that, as Darwin predicted, much of the information used to encode a complex trait was already in the genome as part of simpler evolved traits, and that many routes must be possible for a new complex trait to have a high probability of successfully evolving. In even more extreme examples of the evolution of complexity, we are now using these same principles to examine the evolutionary dynamics the drive major transitions in evolution; that is transitions to higher-levels of organization, which are some of the most complex evolutionary events to occur in nature. Finally, I will explore some of the implications of this research to other aspects of evolutionary biology and as well as ways that these evolutionary principles can be applied toward solving computational and engineering problems.

Common data buffer system. [communication with computational equipment utilized in spacecraft operations

NASA Technical Reports Server (NTRS)

Byrne, F. (Inventor)

1981-01-01

A high speed common data buffer system is described for providing an interface and communications medium between a plurality of computers utilized in a distributed computer complex forming part of a checkout, command and control system for space vehicles and associated ground support equipment. The system includes the capability for temporarily storing data to be transferred between computers, for transferring a plurality of interrupts between computers, for monitoring and recording these transfers, and for correcting errors incurred in these transfers. Validity checks are made on each transfer and appropriate error notification is given to the computer associated with that transfer.

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

2015-03-01

We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

Physical Realization of a Supervised Learning System Built with Organic Memristive Synapses

NASA Astrophysics Data System (ADS)

Lin, Yu-Pu; Bennett, Christopher H.; Cabaret, Théo; Vodenicarevic, Damir; Chabi, Djaafar; Querlioz, Damien; Jousselme, Bruno; Derycke, Vincent; Klein, Jacques-Olivier

2016-09-01

Multiple modern applications of electronics call for inexpensive chips that can perform complex operations on natural data with limited energy. A vision for accomplishing this is implementing hardware neural networks, which fuse computation and memory, with low cost organic electronics. A challenge, however, is the implementation of synapses (analog memories) composed of such materials. In this work, we introduce robust, fastly programmable, nonvolatile organic memristive nanodevices based on electrografted redox complexes that implement synapses thanks to a wide range of accessible intermediate conductivity states. We demonstrate experimentally an elementary neural network, capable of learning functions, which combines four pairs of organic memristors as synapses and conventional electronics as neurons. Our architecture is highly resilient to issues caused by imperfect devices. It tolerates inter-device variability and an adaptable learning rule offers immunity against asymmetries in device switching. Highly compliant with conventional fabrication processes, the system can be extended to larger computing systems capable of complex cognitive tasks, as demonstrated in complementary simulations.

Physical Realization of a Supervised Learning System Built with Organic Memristive Synapses.

PubMed

Lin, Yu-Pu; Bennett, Christopher H; Cabaret, Théo; Vodenicarevic, Damir; Chabi, Djaafar; Querlioz, Damien; Jousselme, Bruno; Derycke, Vincent; Klein, Jacques-Olivier

2016-09-07

Multiple modern applications of electronics call for inexpensive chips that can perform complex operations on natural data with limited energy. A vision for accomplishing this is implementing hardware neural networks, which fuse computation and memory, with low cost organic electronics. A challenge, however, is the implementation of synapses (analog memories) composed of such materials. In this work, we introduce robust, fastly programmable, nonvolatile organic memristive nanodevices based on electrografted redox complexes that implement synapses thanks to a wide range of accessible intermediate conductivity states. We demonstrate experimentally an elementary neural network, capable of learning functions, which combines four pairs of organic memristors as synapses and conventional electronics as neurons. Our architecture is highly resilient to issues caused by imperfect devices. It tolerates inter-device variability and an adaptable learning rule offers immunity against asymmetries in device switching. Highly compliant with conventional fabrication processes, the system can be extended to larger computing systems capable of complex cognitive tasks, as demonstrated in complementary simulations.

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Wave processes in the human cardiovascular system: The measuring complex, computing models, and diagnostic analysis

NASA Astrophysics Data System (ADS)

Ganiev, R. F.; Reviznikov, D. L.; Rogoza, A. N.; Slastushenskiy, Yu. V.; Ukrainskiy, L. E.

2017-03-01

A description of a complex approach to investigation of nonlinear wave processes in the human cardiovascular system based on a combination of high-precision methods of measuring a pulse wave, mathematical methods of processing the empirical data, and methods of direct numerical modeling of hemodynamic processes in an arterial tree is given.

Web Exclusive--Is the Sky the Limit to Educational Improvement?

ERIC Educational Resources Information Center

Schleicher, Andreas

2012-01-01

Today, education systems need to enable people to become lifelong learners, to manage complex ways of thinking and complex ways of working that computers can't take over easily. The task for educators and policy makers is to ensure that countries rise to this challenge. High performing education systems like Finland's and Singapore's tend to…

Multiscale high-order/low-order (HOLO) algorithms and applications

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

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan

Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Multiscale high-order/low-order (HOLO) algorithms and applications

DOE PAGES

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan; ...

2016-11-11

Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking.

PubMed

Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun

2016-12-01

Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.

Electronic Structure of Transition Metal Clusters, Actinide Complexes and Their Reactivities

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

Krishnan Balasubramanian

2009-07-18

This is a continuing DOE-BES funded project on transition metal and actinide containing species, aimed at the electronic structure and spectroscopy of transition metal and actinide containing species. While a long term connection of these species is to catalysis and environmental management of high-level nuclear wastes, the immediate relevance is directly to other DOE-BES funded experimental projects at DOE-National labs and universities. There are a number of ongoing gas-phase spectroscopic studies of these species at various places, and our computational work has been inspired by these experimental studies and we have also inspired other experimental and theoretical studies. Thus ourmore » studies have varied from spectroscopy of diatomic transition metal carbides to large complexes containing transition metals, and actinide complexes that are critical to the environment. In addition, we are continuing to make code enhancements and modernization of ALCHEMY II set of codes and its interface with relativistic configuration interaction (RCI). At present these codes can carry out multi-reference computations that included up to 60 million configurations and multiple states from each such CI expansion. ALCHEMY II codes have been modernized and converted to a variety of platforms such as Windows XP, and Linux. We have revamped the symbolic CI code to automate the MRSDCI technique so that the references are automatically chosen with a given cutoff from the CASSCF and thus we are doing accurate MRSDCI computations with 10,000 or larger reference space of configurations. The RCI code can also handle a large number of reference configurations, which include up to 10,000 reference configurations. Another major progress is in routinely including larger basis sets up to 5g functions in thee computations. Of course higher angular momenta functions can also be handled using Gaussian and other codes with other methods such as DFT, MP2, CCSD(T), etc. We have also calibrated our RECP methods with all-electron Douglas-Kroll relativistic methods. We have the capabilities for computing full CI extrapolations including spin-orbit effects and several one-electron properties and electron density maps including spin-orbit effects. We are continuously collaborating with several experimental groups around the country and at National Labs to carry out computational studies on the DOE-BES funded projects. The past work in the last 3 years was primarily motivated and driven by the concurrent or recent experimental studies on these systems. We were thus significantly benefited by coordinating our computational efforts with experimental studies. The interaction between theory and experiment has resulted in some unique and exciting opportunities. For example, for the very first time ever, the upper spin-orbit component of a heavy trimer such as Au{sub 3} was experimentally observed as a result of our accurate computational study on the upper electronic states of gold trimer. Likewise for the first time AuH{sub 2} could be observed and interpreted clearly due to our computed potential energy surfaces that revealed the existence of a large barrier to convert the isolated AuH{sub 2} back to Au and H{sub 2}. We have also worked on yet to be observed systems and have made predictions for future experiments. We have computed the spectroscopic and thermodynamic properties of transition metal carbides transition metal clusters and compared our electronic states to the anion photodetachment spectra of Lai Sheng Wang. Prof Mike Morse and coworkers(funded also by DOE-BES) and Prof Stimle and coworkers(also funded by DOE-BES) are working on the spectroscopic properties of transition metal carbides and nitrides. Our predictions on the excited states of transition metal clusters such as Hf{sub 3}, Nb{sub 2}{sup +} etc., have been confirmed experimentally by Prof. Lombardi and coworkers using resonance Raman spectroscopy. We have also been studying larger complexes critical to the environmental management of high-level nuclear wastes. In collaboration with experimental colleague Prof Hieno Nitsche (Berkeley) and Dr. Pat Allen (Livermore, EXAFS) we have studied the uranyl complexes with silicates and carbonates. It should be stressed that although our computed ionization potential of uranium oxide was in conflict with the existing experimental data at the time, a subsequent gas-phase experimental work by Prof Mike Haven and coworkers published as communication in JACS confirmed our computed result to within 0.1 eV. This provides considerable confidence that the computed results in large basis sets with highly-correlated wave functions have excellent accuracies and they have the capabilities to predict the excited states also with great accuracy. Computations of actinide complexes (Uranyl and plutonyl complexes) are critical to management of high-level nuclear wastes.« less

Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi

1989-01-01

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.

Applications of Phase-Based Motion Processing

NASA Technical Reports Server (NTRS)

Branch, Nicholas A.; Stewart, Eric C.

2018-01-01

Image pyramids provide useful information in determining structural response at low cost using commercially available cameras. The current effort applies previous work on the complex steerable pyramid to analyze and identify imperceptible linear motions in video. Instead of implicitly computing motion spectra through phase analysis of the complex steerable pyramid and magnifying the associated motions, instead present a visual technique and the necessary software to display the phase changes of high frequency signals within video. The present technique quickly identifies regions of largest motion within a video with a single phase visualization and without the artifacts of motion magnification, but requires use of the computationally intensive Fourier transform. While Riesz pyramids present an alternative to the computationally intensive complex steerable pyramid for motion magnification, the Riesz formulation contains significant noise, and motion magnification still presents large amounts of data that cannot be quickly assessed by the human eye. Thus, user-friendly software is presented for quickly identifying structural response through optical flow and phase visualization in both Python and MATLAB.

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

Modeling of a Sequential Two-Stage Combustor

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Liu, N.-S.; Gallagher, J. R.; Ryder, R. C.; Brankovic, A.; Hendricks, J. A.

2005-01-01

A sequential two-stage, natural gas fueled power generation combustion system is modeled to examine the fundamental aerodynamic and combustion characteristics of the system. The modeling methodology includes CAD-based geometry definition, and combustion computational fluid dynamics analysis. Graphical analysis is used to examine the complex vortical patterns in each component, identifying sources of pressure loss. The simulations demonstrate the importance of including the rotating high-pressure turbine blades in the computation, as this results in direct computation of combustion within the first turbine stage, and accurate simulation of the flow in the second combustion stage. The direct computation of hot-streaks through the rotating high-pressure turbine stage leads to improved understanding of the aerodynamic relationships between the primary and secondary combustors and the turbomachinery.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

PubMed

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data

PubMed Central

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H.

2013-01-01

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the “big data” challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce. PMID:24501719

Java Performance for Scientific Applications on LLNL Computer Systems

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

Kapfer, C; Wissink, A

2002-05-10

Languages in use for high performance computing at the laboratory--Fortran (f77 and f90), C, and C++--have many years of development behind them and are generally considered the fastest available. However, Fortran and C do not readily extend to object-oriented programming models, limiting their capability for very complex simulation software. C++ facilitates object-oriented programming but is a very complex and error-prone language. Java offers a number of capabilities that these other languages do not. For instance it implements cleaner (i.e., easier to use and less prone to errors) object-oriented models than C++. It also offers networking and security as part ofmore » the language standard, and cross-platform executables that make it architecture neutral, to name a few. These features have made Java very popular for industrial computing applications. The aim of this paper is to explain the trade-offs in using Java for large-scale scientific applications at LLNL. Despite its advantages, the computational science community has been reluctant to write large-scale computationally intensive applications in Java due to concerns over its poor performance. However, considerable progress has been made over the last several years. The Java Grande Forum [1] has been promoting the use of Java for large-scale computing. Members have introduced efficient array libraries, developed fast just-in-time (JIT) compilers, and built links to existing packages used in high performance parallel computing.« less

Variable-Complexity Multidisciplinary Optimization on Parallel Computers

NASA Technical Reports Server (NTRS)

Grossman, Bernard; Mason, William H.; Watson, Layne T.; Haftka, Raphael T.

1998-01-01

This report covers work conducted under grant NAG1-1562 for the NASA High Performance Computing and Communications Program (HPCCP) from December 7, 1993, to December 31, 1997. The objective of the research was to develop new multidisciplinary design optimization (MDO) techniques which exploit parallel computing to reduce the computational burden of aircraft MDO. The design of the High-Speed Civil Transport (HSCT) air-craft was selected as a test case to demonstrate the utility of our MDO methods. The three major tasks of this research grant included: development of parallel multipoint approximation methods for the aerodynamic design of the HSCT, use of parallel multipoint approximation methods for structural optimization of the HSCT, mathematical and algorithmic development including support in the integration of parallel computation for items (1) and (2). These tasks have been accomplished with the development of a response surface methodology that incorporates multi-fidelity models. For the aerodynamic design we were able to optimize with up to 20 design variables using hundreds of expensive Euler analyses together with thousands of inexpensive linear theory simulations. We have thereby demonstrated the application of CFD to a large aerodynamic design problem. For the predicting structural weight we were able to combine hundreds of structural optimizations of refined finite element models with thousands of optimizations based on coarse models. Computations have been carried out on the Intel Paragon with up to 128 nodes. The parallel computation allowed us to perform combined aerodynamic-structural optimization using state of the art models of a complex aircraft configurations.

Computational high-resolution optical imaging of the living human retina

NASA Astrophysics Data System (ADS)

Shemonski, Nathan D.; South, Fredrick A.; Liu, Yuan-Zhi; Adie, Steven G.; Scott Carney, P.; Boppart, Stephen A.

2015-07-01

High-resolution in vivo imaging is of great importance for the fields of biology and medicine. The introduction of hardware-based adaptive optics (HAO) has pushed the limits of optical imaging, enabling high-resolution near diffraction-limited imaging of previously unresolvable structures. In ophthalmology, when combined with optical coherence tomography, HAO has enabled a detailed three-dimensional visualization of photoreceptor distributions and individual nerve fibre bundles in the living human retina. However, the introduction of HAO hardware and supporting software adds considerable complexity and cost to an imaging system, limiting the number of researchers and medical professionals who could benefit from the technology. Here we demonstrate a fully automated computational approach that enables high-resolution in vivo ophthalmic imaging without the need for HAO. The results demonstrate that computational methods in coherent microscopy are applicable in highly dynamic living systems.

Ab Initio Reactive Computer Aided Molecular Design

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

Martínez, Todd J.

Few would dispute that theoretical chemistry tools can now provide keen insights into chemical phenomena. Yet the holy grail of efficient and reliable prediction of complex reactivity has remained elusive. Fortunately, recent advances in electronic structure theory based on the concepts of both element- and rank-sparsity, coupled with the emergence of new highly parallel computer architectures, have led to a significant increase in the time and length scales which can be simulated using first principles molecular dynamics. This then opens the possibility of new discovery-based approaches to chemical reactivity, such as the recently proposed ab initio nanoreactor. Here, we arguemore » that due to these and other recent advances, the holy grail of computational discovery for complex chemical reactivity is rapidly coming within our reach.« less

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.

Ab Initio Reactive Computer Aided Molecular Design

DOE PAGES

Martínez, Todd J.

2017-03-21

Few would dispute that theoretical chemistry tools can now provide keen insights into chemical phenomena. Yet the holy grail of efficient and reliable prediction of complex reactivity has remained elusive. Fortunately, recent advances in electronic structure theory based on the concepts of both element- and rank-sparsity, coupled with the emergence of new highly parallel computer architectures, have led to a significant increase in the time and length scales which can be simulated using first principles molecular dynamics. This then opens the possibility of new discovery-based approaches to chemical reactivity, such as the recently proposed ab initio nanoreactor. Here, we arguemore » that due to these and other recent advances, the holy grail of computational discovery for complex chemical reactivity is rapidly coming within our reach.« less

Reducing Communication in Algebraic Multigrid Using Additive Variants

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

Vassilevski, Panayot S.; Yang, Ulrike Meier

Algebraic multigrid (AMG) has proven to be an effective scalable solver on many high performance computers. However, its increasing communication complexity on coarser levels has shown to seriously impact its performance on computers with high communication cost. Moreover, additive AMG variants provide not only increased parallelism as well as decreased numbers of messages per cycle but also generally exhibit slower convergence. Here we present various new additive variants with convergence rates that are significantly improved compared to the classical additive algebraic multigrid method and investigate their potential for decreased communication, and improved communication-computation overlap, features that are essential for goodmore » performance on future exascale architectures.« less

Reducing Communication in Algebraic Multigrid Using Additive Variants

DOE PAGES

Vassilevski, Panayot S.; Yang, Ulrike Meier

2014-02-12

Algebraic multigrid (AMG) has proven to be an effective scalable solver on many high performance computers. However, its increasing communication complexity on coarser levels has shown to seriously impact its performance on computers with high communication cost. Moreover, additive AMG variants provide not only increased parallelism as well as decreased numbers of messages per cycle but also generally exhibit slower convergence. Here we present various new additive variants with convergence rates that are significantly improved compared to the classical additive algebraic multigrid method and investigate their potential for decreased communication, and improved communication-computation overlap, features that are essential for goodmore » performance on future exascale architectures.« less

Optical interconnection networks for high-performance computing systems

NASA Astrophysics Data System (ADS)

Biberman, Aleksandr; Bergman, Keren

2012-04-01

Enabled by silicon photonic technology, optical interconnection networks have the potential to be a key disruptive technology in computing and communication industries. The enduring pursuit of performance gains in computing, combined with stringent power constraints, has fostered the ever-growing computational parallelism associated with chip multiprocessors, memory systems, high-performance computing systems and data centers. Sustaining these parallelism growths introduces unique challenges for on- and off-chip communications, shifting the focus toward novel and fundamentally different communication approaches. Chip-scale photonic interconnection networks, enabled by high-performance silicon photonic devices, offer unprecedented bandwidth scalability with reduced power consumption. We demonstrate that the silicon photonic platforms have already produced all the high-performance photonic devices required to realize these types of networks. Through extensive empirical characterization in much of our work, we demonstrate such feasibility of waveguides, modulators, switches and photodetectors. We also demonstrate systems that simultaneously combine many functionalities to achieve more complex building blocks. We propose novel silicon photonic devices, subsystems, network topologies and architectures to enable unprecedented performance of these photonic interconnection networks. Furthermore, the advantages of photonic interconnection networks extend far beyond the chip, offering advanced communication environments for memory systems, high-performance computing systems, and data centers.

LXtoo: an integrated live Linux distribution for the bioinformatics community

PubMed Central

2012-01-01

Background Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Findings Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. Conclusions LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo. PMID:22813356

LXtoo: an integrated live Linux distribution for the bioinformatics community.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Meng, Xiao-Hua; He, Qing-Yu

2012-07-19

Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo.

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

PubMed

Baichoo, Shakuntala; Ouzounis, Christos A

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. Copyright © 2017 Elsevier B.V. All rights reserved.

Complexity Bounds for Quantum Computation

DTIC Science & Technology

2007-06-22

Programs Trustees of Boston University Boston, MA 02215 - Complexity Bounds for Quantum Computation REPORT DOCUMENTATION PAGE 18. SECURITY CLASSIFICATION...Complexity Bounds for Quantum Comp[utation Report Title ABSTRACT This project focused on upper and lower bounds for quantum computability using constant...classical computation models, particularly emphasizing new examples of where quantum circuits are more powerful than their classical counterparts. A second

Distributed Computing Architecture for Image-Based Wavefront Sensing and 2 D FFTs

NASA Technical Reports Server (NTRS)

Smith, Jeffrey S.; Dean, Bruce H.; Haghani, Shadan

2006-01-01

Image-based wavefront sensing (WFS) provides significant advantages over interferometric-based wavefi-ont sensors such as optical design simplicity and stability. However, the image-based approach is computational intensive, and therefore, specialized high-performance computing architectures are required in applications utilizing the image-based approach. The development and testing of these high-performance computing architectures are essential to such missions as James Webb Space Telescope (JWST), Terrestial Planet Finder-Coronagraph (TPF-C and CorSpec), and Spherical Primary Optical Telescope (SPOT). The development of these specialized computing architectures require numerous two-dimensional Fourier Transforms, which necessitate an all-to-all communication when applied on a distributed computational architecture. Several solutions for distributed computing are presented with an emphasis on a 64 Node cluster of DSPs, multiple DSP FPGAs, and an application of low-diameter graph theory. Timing results and performance analysis will be presented. The solutions offered could be applied to other all-to-all communication and scientifically computationally complex problems.

Solid-state NMR imaging system

DOEpatents

Gopalsami, Nachappa; Dieckman, Stephen L.; Ellingson, William A.

1992-01-01

An apparatus for use with a solid-state NMR spectrometer includes a special imaging probe with linear, high-field strength gradient fields and high-power broadband RF coils using a back projection method for data acquisition and image reconstruction, and a real-time pulse programmer adaptable for use by a conventional computer for complex high speed pulse sequences.

What Does Quality Programming Mean for High Achieving Students?

ERIC Educational Resources Information Center

Samudzi, Cleo

2008-01-01

The Missouri Academy of Science, Mathematics and Computing (Missouri Academy) is a two-year accelerated, early-entrance-to-college, residential school that matches the level, complexity and pace of the curriculum with the readiness and motivation of high achieving high school students. The school is a part of Northwest Missouri State University…

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

Metagram Software - A New Perspective on the Art of Computation.

DTIC Science & Technology

1981-10-01

numober) Computer Programming Information and Analysis Metagramming Philosophy Intelligence Information Systefs Abstraction & Metasystems Metagranmming...control would also serve well in the analysis of military and political intelligence, and in other areas where highly abstract methods of thought serve...needed in intelligence because several levels of abstraction are involved in a political or military system, because analysis entails a complex interplay

EIAGRID: In-field optimization of seismic data acquisition by real-time subsurface imaging using a remote GRID computing environment.

NASA Astrophysics Data System (ADS)

Heilmann, B. Z.; Vallenilla Ferrara, A. M.

2009-04-01

The constant growth of contaminated sites, the unsustainable use of natural resources, and, last but not least, the hydrological risk related to extreme meteorological events and increased climate variability are major environmental issues of today. Finding solutions for these complex problems requires an integrated cross-disciplinary approach, providing a unified basis for environmental science and engineering. In computer science, grid computing is emerging worldwide as a formidable tool allowing distributed computation and data management with administratively-distant resources. Utilizing these modern High Performance Computing (HPC) technologies, the GRIDA3 project bundles several applications from different fields of geoscience aiming to support decision making for reasonable and responsible land use and resource management. In this abstract we present a geophysical application called EIAGRID that uses grid computing facilities to perform real-time subsurface imaging by on-the-fly processing of seismic field data and fast optimization of the processing workflow. Even though, seismic reflection profiling has a broad application range spanning from shallow targets in a few meters depth to targets in a depth of several kilometers, it is primarily used by the hydrocarbon industry and hardly for environmental purposes. The complexity of data acquisition and processing poses severe problems for environmental and geotechnical engineering: Professional seismic processing software is expensive to buy and demands large experience from the user. In-field processing equipment needed for real-time data Quality Control (QC) and immediate optimization of the acquisition parameters is often not available for this kind of studies. As a result, the data quality will be suboptimal. In the worst case, a crucial parameter such as receiver spacing, maximum offset, or recording time turns out later to be inappropriate and the complete acquisition campaign has to be repeated. The EIAGRID portal provides an innovative solution to this problem combining state-of-the-art data processing methods and modern remote grid computing technology. In field-processing equipment is substituted by remote access to high performance grid computing facilities. The latter can be ubiquitously controlled by a user-friendly web-browser interface accessed from the field by any mobile computer using wireless data transmission technology such as UMTS (Universal Mobile Telecommunications System) or HSUPA/HSDPA (High-Speed Uplink/Downlink Packet Access). The complexity of data-manipulation and processing and thus also the time demanding user interaction is minimized by a data-driven, and highly automated velocity analysis and imaging approach based on the Common-Reflection-Surface (CRS) stack. Furthermore, the huge computing power provided by the grid deployment allows parallel testing of alternative processing sequences and parameter settings, a feature which considerably reduces the turn-around times. A shared data storage using georeferencing tools and data grid technology is under current development. It will allow to publish already accomplished projects, making results, processing workflows and parameter settings available in a transparent and reproducible way. Creating a unified database shared by all users will facilitate complex studies and enable the use of data-crossing techniques to incorporate results of other environmental applications hosted on the GRIDA3 portal.

Using the Eclipse Parallel Tools Platform to Assist Earth Science Model Development and Optimization on High Performance Computers

NASA Astrophysics Data System (ADS)

Alameda, J. C.

2011-12-01

Development and optimization of computational science models, particularly on high performance computers, and with the advent of ubiquitous multicore processor systems, practically on every system, has been accomplished with basic software tools, typically, command-line based compilers, debuggers, performance tools that have not changed substantially from the days of serial and early vector computers. However, model complexity, including the complexity added by modern message passing libraries such as MPI, and the need for hybrid code models (such as openMP and MPI) to be able to take full advantage of high performance computers with an increasing core count per shared memory node, has made development and optimization of such codes an increasingly arduous task. Additional architectural developments, such as many-core processors, only complicate the situation further. In this paper, we describe how our NSF-funded project, "SI2-SSI: A Productive and Accessible Development Workbench for HPC Applications Using the Eclipse Parallel Tools Platform" (WHPC) seeks to improve the Eclipse Parallel Tools Platform, an environment designed to support scientific code development targeted at a diverse set of high performance computing systems. Our WHPC project to improve Eclipse PTP takes an application-centric view to improve PTP. We are using a set of scientific applications, each with a variety of challenges, and using PTP to drive further improvements to both the scientific application, as well as to understand shortcomings in Eclipse PTP from an application developer perspective, to drive our list of improvements we seek to make. We are also partnering with performance tool providers, to drive higher quality performance tool integration. We have partnered with the Cactus group at Louisiana State University to improve Eclipse's ability to work with computational frameworks and extremely complex build systems, as well as to develop educational materials to incorporate into computational science and engineering codes. Finally, we are partnering with the lead PTP developers at IBM, to ensure we are as effective as possible within the Eclipse community development. We are also conducting training and outreach to our user community, including conference BOF sessions, monthly user calls, and an annual user meeting, so that we can best inform the improvements we make to Eclipse PTP. With these activities we endeavor to encourage use of modern software engineering practices, as enabled through the Eclipse IDE, with computational science and engineering applications. These practices include proper use of source code repositories, tracking and rectifying issues, measuring and monitoring code performance changes against both optimizations as well as ever-changing software stacks and configurations on HPC systems, as well as ultimately encouraging development and maintenance of testing suites -- things that have become commonplace in many software endeavors, but have lagged in the development of science applications. We view that the challenge with the increased complexity of both HPC systems and science applications demands the use of better software engineering methods, preferably enabled by modern tools such as Eclipse PTP, to help the computational science community thrive as we evolve the HPC landscape.

Rational Design of Highly Potent and Slow-Binding Cytochrome bc1 Inhibitor as Fungicide by Computational Substitution Optimization

PubMed Central

Hao, Ge-Fei; Yang, Sheng-Gang; Huang, Wei; Wang, Le; Shen, Yan-Qing; Tu, Wen-Long; Li, Hui; Huang, Li-Shar; Wu, Jia-Wei; Berry, Edward A.; Yang, Guang-Fu

2015-01-01

Hit to lead (H2L) optimization is a key step for drug and agrochemical discovery. A critical challenge for H2L optimization is the low efficiency due to the lack of predictive method with high accuracy. We described a new computational method called Computational Substitution Optimization (CSO) that has allowed us to rapidly identify compounds with cytochrome bc1 complex inhibitory activity in the nanomolar and subnanomolar range. The comprehensively optimized candidate has proved to be a slow binding inhibitor of bc1 complex, ~73-fold more potent (Ki = 4.1 nM) than the best commercial fungicide azoxystrobin (AZ; Ki = 297.6 nM) and shows excellent in vivo fungicidal activity against downy mildew and powdery mildew disease. The excellent correlation between experimental and calculated binding free-energy shifts together with further crystallographic analysis confirmed the prediction accuracy of CSO method. To the best of our knowledge, CSO is a new computational approach to substitution-scanning mutagenesis of ligand and could be used as a general strategy of H2L optimisation in drug and agrochemical design.

Quantum simulations with noisy quantum computers

NASA Astrophysics Data System (ADS)

Gambetta, Jay

Quantum computing is a new computational paradigm that is expected to lie beyond the standard model of computation. This implies a quantum computer can solve problems that can't be solved by a conventional computer with tractable overhead. To fully harness this power we need a universal fault-tolerant quantum computer. However the overhead in building such a machine is high and a full solution appears to be many years away. Nevertheless, we believe that we can build machines in the near term that cannot be emulated by a conventional computer. It is then interesting to ask what these can be used for. In this talk we will present our advances in simulating complex quantum systems with noisy quantum computers. We will show experimental implementations of this on some small quantum computers.

Rapid solution of large-scale systems of equations

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1994-01-01

The analysis and design of complex aerospace structures requires the rapid solution of large systems of linear and nonlinear equations, eigenvalue extraction for buckling, vibration and flutter modes, structural optimization and design sensitivity calculation. Computers with multiple processors and vector capabilities can offer substantial computational advantages over traditional scalar computer for these analyses. These computers fall into two categories: shared memory computers and distributed memory computers. This presentation covers general-purpose, highly efficient algorithms for generation/assembly or element matrices, solution of systems of linear and nonlinear equations, eigenvalue and design sensitivity analysis and optimization. All algorithms are coded in FORTRAN for shared memory computers and many are adapted to distributed memory computers. The capability and numerical performance of these algorithms will be addressed.

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

PubMed Central

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-01-01

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequency-domain and achieves computational complexity reduction. PMID:28230763

Self-similar slip distributions on irregular shaped faults

NASA Astrophysics Data System (ADS)

Herrero, A.; Murphy, S.

2018-06-01

We propose a strategy to place a self-similar slip distribution on a complex fault surface that is represented by an unstructured mesh. This is possible by applying a strategy based on the composite source model where a hierarchical set of asperities, each with its own slip function which is dependent on the distance from the asperity centre. Central to this technique is the efficient, accurate computation of distance between two points on the fault surface. This is known as the geodetic distance problem. We propose a method to compute the distance across complex non-planar surfaces based on a corollary of the Huygens' principle. The difference between this method compared to others sample-based algorithms which precede it is the use of a curved front at a local level to calculate the distance. This technique produces a highly accurate computation of the distance as the curvature of the front is linked to the distance from the source. Our local scheme is based on a sequence of two trilaterations, producing a robust algorithm which is highly precise. We test the strategy on a planar surface in order to assess its ability to keep the self-similarity properties of a slip distribution. We also present a synthetic self-similar slip distribution on a real slab topography for a M8.5 event. This method for computing distance may be extended to the estimation of first arrival times in both complex 3D surfaces or 3D volumes.

TUMOR HAPLOTYPE ASSEMBLY ALGORITHMS FOR CANCER GENOMICS

PubMed Central

AGUIAR, DEREK; WONG, WENDY S.W.; ISTRAIL, SORIN

2014-01-01

The growing availability of inexpensive high-throughput sequence data is enabling researchers to sequence tumor populations within a single individual at high coverage. But, cancer genome sequence evolution and mutational phenomena like driver mutations and gene fusions are difficult to investigate without first reconstructing tumor haplotype sequences. Haplotype assembly of single individual tumor populations is an exceedingly difficult task complicated by tumor haplotype heterogeneity, tumor or normal cell sequence contamination, polyploidy, and complex patterns of variation. While computational and experimental haplotype phasing of diploid genomes has seen much progress in recent years, haplotype assembly in cancer genomes remains uncharted territory. In this work, we describe HapCompass-Tumor a computational modeling and algorithmic framework for haplotype assembly of copy number variable cancer genomes containing haplotypes at different frequencies and complex variation. We extend our polyploid haplotype assembly model and present novel algorithms for (1) complex variations, including copy number changes, as varying numbers of disjoint paths in an associated graph, (2) variable haplotype frequencies and contamination, and (3) computation of tumor haplotypes using simple cycles of the compass graph which constrain the space of haplotype assembly solutions. The model and algorithm are implemented in the software package HapCompass-Tumor which is available for download from http://www.brown.edu/Research/Istrail_Lab/. PMID:24297529

Evaluation of a micro-scale wind model's performance over realistic building clusters using wind tunnel experiments

NASA Astrophysics Data System (ADS)

Zhang, Ning; Du, Yunsong; Miao, Shiguang; Fang, Xiaoyi

2016-08-01

The simulation performance over complex building clusters of a wind simulation model (Wind Information Field Fast Analysis model, WIFFA) in a micro-scale air pollutant dispersion model system (Urban Microscale Air Pollution dispersion Simulation model, UMAPS) is evaluated using various wind tunnel experimental data including the CEDVAL (Compilation of Experimental Data for Validation of Micro-Scale Dispersion Models) wind tunnel experiment data and the NJU-FZ experiment data (Nanjing University-Fang Zhuang neighborhood wind tunnel experiment data). The results show that the wind model can reproduce the vortexes triggered by urban buildings well, and the flow patterns in urban street canyons and building clusters can also be represented. Due to the complex shapes of buildings and their distributions, the simulation deviations/discrepancies from the measurements are usually caused by the simplification of the building shapes and the determination of the key zone sizes. The computational efficiencies of different cases are also discussed in this paper. The model has a high computational efficiency compared to traditional numerical models that solve the Navier-Stokes equations, and can produce very high-resolution (1-5 m) wind fields of a complex neighborhood scale urban building canopy (~ 1 km ×1 km) in less than 3 min when run on a personal computer.

Classified one-step high-radix signed-digit arithmetic units

NASA Astrophysics Data System (ADS)

Cherri, Abdallah K.

1998-08-01

High-radix number systems enable higher information storage density, less complexity, fewer system components, and fewer cascaded gates and operations. A simple one-step fully parallel high-radix signed-digit arithmetic is proposed for parallel optical computing based on new joint spatial encodings. This reduces hardware requirements and improves throughput by reducing the space-bandwidth produce needed. The high-radix signed-digit arithmetic operations are based on classifying the neighboring input digit pairs into various groups to reduce the computation rules. A new joint spatial encoding technique is developed to present both the operands and the computation rules. This technique increases the spatial bandwidth product of the spatial light modulators of the system. An optical implementation of the proposed high-radix signed-digit arithmetic operations is also presented. It is shown that our one-step trinary signed-digit and quaternary signed-digit arithmetic units are much simpler and better than all previously reported high-radix signed-digit techniques.

Characterization of known protein complexes using k-connectivity and other topological measures

PubMed Central

Gallagher, Suzanne R; Goldberg, Debra S

2015-01-01

Many protein complexes are densely packed, so proteins within complexes often interact with several other proteins in the complex. Steric constraints prevent most proteins from simultaneously binding more than a handful of other proteins, regardless of the number of proteins in the complex. Because of this, as complex size increases, several measures of the complex decrease within protein-protein interaction networks. However, k-connectivity, the number of vertices or edges that need to be removed in order to disconnect a graph, may be consistently high for protein complexes. The property of k-connectivity has been little used previously in the investigation of protein-protein interactions. To understand the discriminative power of k-connectivity and other topological measures for identifying unknown protein complexes, we characterized these properties in known Saccharomyces cerevisiae protein complexes in networks generated both from highly accurate X-ray crystallography experiments which give an accurate model of each complex, and also as the complexes appear in high-throughput yeast 2-hybrid studies in which new complexes may be discovered. We also computed these properties for appropriate random subgraphs.We found that clustering coefficient, mutual clustering coefficient, and k-connectivity are better indicators of known protein complexes than edge density, degree, or betweenness. This suggests new directions for future protein complex-finding algorithms. PMID:26913183

Influence of the chelator structures on the stability of Re and Tc tricarbonyl complexes with iminodiacetic acid tridentate ligands: a computational study.

PubMed

Hernández-Valdés, Daniel; Rodríguez-Riera, Zalua; Díaz-García, Alicia; Benoist, Eric; Jáuregui-Haza, Ulises

2016-08-01

The development of novel radiopharmaceuticals for nuclear medicine based on M(CO)3 (M = Tc, Re) complexes has attracted great attention. The versatility of this core and the easy production of the fac-[M(CO)3(H2O)3](+) precursor could explain this interest. The main characteristics of these tricarbonyl complexes are the high substitution stability of the three CO ligands and the corresponding lability of the coordinated water molecules, yielding, via easy exchange of a variety of bi- and tridentate ligands, complexes xof very high kinetic stability. Here, a computational study of different tricarbonyl complexes of Re(I) and Tc(I) was performed using density functional theory. The solvent effect was simulated using the polarizable continuum model. These structures were used as a starting point to investigate the relative stabilities of tricarbonyl complexes with various tridentate ligands. These complexes included an iminodiacetic acid unit for tridentate coordination to the fac-[M(CO)3](+) moiety (M = Re, Tc), an aromatic ring system bearing a functional group (-NO2, -NH2, and -Cl) as a linking site model, and a tethering moiety (a methylene, ethylene, propylene butylene, or pentylene bridge) between the linking and coordinating sites. The optimized complexes showed geometries comparable to those inferred from X-ray data. In general, the Re complexes were more stable than the corresponding Tc complexes. Furthermore, using NH2 as the functional group, a medium length carbon chain, and ortho substitution increased complex stability. All of the bonds involving the metal center presented a closed shell interaction with dative or covalent character, and the strength of these bonds decreased in the sequence Tc-CO > Tc-O > Tc-N.

Guest Editorial High Performance Computing (HPC) Applications for a More Resilient and Efficient Power Grid

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

Huang, Zhenyu Henry; Tate, Zeb; Abhyankar, Shrirang

The power grid has been evolving over the last 120 years, but it is seeing more changes in this decade and next than it has seen over the past century. In particular, the widespread deployment of intermittent renewable generation, smart loads and devices, hierarchical and distributed control technologies, phasor measurement units, energy storage, and widespread usage of electric vehicles will require fundamental changes in methods and tools for the operation and planning of the power grid. The resulting new dynamic and stochastic behaviors will demand the inclusion of more complexity in modeling the power grid. Solving such complex models inmore » the traditional computing environment will be a major challenge. Along with the increasing complexity of power system models, the increasing complexity of smart grid data further adds to the prevailing challenges. In this environment, the myriad of smart sensors and meters in the power grid increase by multiple orders of magnitude, so do the volume and speed of the data. The information infrastructure will need to drastically change to support the exchange of enormous amounts of data as smart grid applications will need the capability to collect, assimilate, analyze and process the data, to meet real-time grid functions. High performance computing (HPC) holds the promise to enhance these functions, but it is a great resource that has not been fully explored and adopted for the power grid domain.« less

Human systems dynamics: Toward a computational model

NASA Astrophysics Data System (ADS)

Eoyang, Glenda H.

2012-09-01

A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

High-Performance Algorithms and Complex Fluids | Computational Science |

Science.gov Websites

only possible by combining experimental data with simulation. Capabilities Capabilities include: Block -laden, non-Newtonian, as well as traditional internal and external flows. Contact Ray Grout Group

Recent advances in QM/MM free energy calculations using reference potentials.

PubMed

Duarte, Fernanda; Amrein, Beat A; Blaha-Nelson, David; Kamerlin, Shina C L

2015-05-01

Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.

Large-scale structural analysis: The structural analyst, the CSM Testbed and the NAS System

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Mccleary, Susan L.; Macy, Steven C.; Aminpour, Mohammad A.

1989-01-01

The Computational Structural Mechanics (CSM) activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM testbed methods development environment is presented and some numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

An Object-Oriented Approach to Writing Computational Electromagnetics Codes

NASA Technical Reports Server (NTRS)

Zimmerman, Martin; Mallasch, Paul G.

1996-01-01

Presently, most computer software development in the Computational Electromagnetics (CEM) community employs the structured programming paradigm, particularly using the Fortran language. Other segments of the software community began switching to an Object-Oriented Programming (OOP) paradigm in recent years to help ease design and development of highly complex codes. This paper examines design of a time-domain numerical analysis CEM code using the OOP paradigm, comparing OOP code and structured programming code in terms of software maintenance, portability, flexibility, and speed.

A Unified Framework for Simulating Markovian Models of Highly Dependable Systems

DTIC Science & Technology

1989-07-01

ependability I’valuiation of Complex lault- lolerant Computing Systems. Ptreedings of the 1-.et-enth Sv~npmiun on Falult- lolerant Comnputing. Portland, Maine...New York. [12] (icis;t, R.M. and ’I’rivedi, K.S. (1983). I!Itra-Il gh Reliability Prediction for Fault-’ lolerant Computer Systems. IEE.-E Trw.%,.cions... 1998 ). Surv’ey of Software Tools for [valuating Reli- ability. A vailability, and Serviceabilitv. ACA1 Computing S urveyjs 20. 4, 227-269). [32] Meyer

Comparative phyloinformatics of virus genes at micro and macro levels in a distributed computing environment.

PubMed

Singh, Dadabhai T; Trehan, Rahul; Schmidt, Bertil; Bretschneider, Timo

2008-01-01

Preparedness for a possible global pandemic caused by viruses such as the highly pathogenic influenza A subtype H5N1 has become a global priority. In particular, it is critical to monitor the appearance of any new emerging subtypes. Comparative phyloinformatics can be used to monitor, analyze, and possibly predict the evolution of viruses. However, in order to utilize the full functionality of available analysis packages for large-scale phyloinformatics studies, a team of computer scientists, biostatisticians and virologists is needed--a requirement which cannot be fulfilled in many cases. Furthermore, the time complexities of many algorithms involved leads to prohibitive runtimes on sequential computer platforms. This has so far hindered the use of comparative phyloinformatics as a commonly applied tool in this area. In this paper the graphical-oriented workflow design system called Quascade and its efficient usage for comparative phyloinformatics are presented. In particular, we focus on how this task can be effectively performed in a distributed computing environment. As a proof of concept, the designed workflows are used for the phylogenetic analysis of neuraminidase of H5N1 isolates (micro level) and influenza viruses (macro level). The results of this paper are hence twofold. Firstly, this paper demonstrates the usefulness of a graphical user interface system to design and execute complex distributed workflows for large-scale phyloinformatics studies of virus genes. Secondly, the analysis of neuraminidase on different levels of complexity provides valuable insights of this virus's tendency for geographical based clustering in the phylogenetic tree and also shows the importance of glycan sites in its molecular evolution. The current study demonstrates the efficiency and utility of workflow systems providing a biologist friendly approach to complex biological dataset analysis using high performance computing. In particular, the utility of the platform Quascade for deploying distributed and parallelized versions of a variety of computationally intensive phylogenetic algorithms has been shown. Secondly, the analysis of the utilized H5N1 neuraminidase datasets at macro and micro levels has clearly indicated a pattern of spatial clustering of the H5N1 viral isolates based on geographical distribution rather than temporal or host range based clustering.

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

NASA Astrophysics Data System (ADS)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

Graphics Flutter Analysis Methods, an interactive computing system at Lockheed-California Company

NASA Technical Reports Server (NTRS)

Radovcich, N. A.

1975-01-01

An interactive computer graphics system, Graphics Flutter Analysis Methods (GFAM), was developed to complement FAMAS, a matrix-oriented batch computing system, and other computer programs in performing complex numerical calculations using a fully integrated data management system. GFAM has many of the matrix operation capabilities found in FAMAS, but on a smaller scale, and is utilized when the analysis requires a high degree of interaction between the engineer and computer, and schedule constraints exclude the use of batch entry programs. Applications of GFAM to a variety of preliminary design, development design, and project modification programs suggest that interactive flutter analysis using matrix representations is a feasible and cost effective computing tool.

Plasmonic computing of spatial differentiation

NASA Astrophysics Data System (ADS)

Zhu, Tengfeng; Zhou, Yihan; Lou, Yijie; Ye, Hui; Qiu, Min; Ruan, Zhichao; Fan, Shanhui

2017-05-01

Optical analog computing offers high-throughput low-power-consumption operation for specialized computational tasks. Traditionally, optical analog computing in the spatial domain uses a bulky system of lenses and filters. Recent developments in metamaterials enable the miniaturization of such computing elements down to a subwavelength scale. However, the required metamaterial consists of a complex array of meta-atoms, and direct demonstration of image processing is challenging. Here, we show that the interference effects associated with surface plasmon excitations at a single metal-dielectric interface can perform spatial differentiation. And we experimentally demonstrate edge detection of an image without any Fourier lens. This work points to a simple yet powerful mechanism for optical analog computing at the nanoscale.

Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

NASA Astrophysics Data System (ADS)

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-05-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

Photofragmentation of Gas-Phase Lanthanide Cyclopentadienyl Complexes: Experimental and Time-Dependent Excited-State Molecular Dynamics

PubMed Central

2015-01-01

Unimolecular gas-phase laser-photodissociation reaction mechanisms of open-shell lanthanide cyclopentadienyl complexes, Ln(Cp)3 and Ln(TMCp)3, are analyzed from experimental and computational perspectives. The most probable pathways for the photoreactions are inferred from photoionization time-of-flight mass spectrometry (PI-TOF-MS), which provides the sequence of reaction intermediates and the distribution of final products. Time-dependent excited-state molecular dynamics (TDESMD) calculations provide insight into the electronic mechanisms for the individual steps of the laser-driven photoreactions for Ln(Cp)3. Computational analysis correctly predicts several key reaction products as well as the observed branching between two reaction pathways: (1) ligand ejection and (2) ligand cracking. Simulations support our previous assertion that both reaction pathways are initiated via a ligand-to-metal charge-transfer (LMCT) process. For the more complex chemistry of the tetramethylcyclopentadienyl complexes Ln(TMCp)3, TMESMD is less tractable, but computational geometry optimization reveals the structures of intermediates deduced from PI-TOF-MS, including several classic “tuck-in” structures and products of Cp ring expansion. The results have important implications for metal–organic catalysis and laser-assisted metal–organic chemical vapor deposition (LCVD) of insulators with high dielectric constants. PMID:24910492

Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Wong, Jay Ming

2014-01-01

Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

[The P300-based brain-computer interface: presentation of the complex "flash + movement" stimuli].

PubMed

Ganin, I P; Kaplan, A Ia

2014-01-01

The P300 based brain-computer interface requires the detection of P300 wave of brain event-related potentials. Most of its users learn the BCI control in several minutes and after the short classifier training they can type a text on the computer screen or assemble an image of separate fragments in simple BCI-based video games. Nevertheless, insufficient attractiveness for users and conservative stimuli organization in this BCI may restrict its integration into real information processes control. At the same time initial movement of object (motion-onset stimuli) may be an independent factor that induces P300 wave. In current work we checked the hypothesis that complex "flash + movement" stimuli together with drastic and compact stimuli organization on the computer screen may be much more attractive for user while operating in P300 BCI. In 20 subjects research we showed the effectiveness of our interface. Both accuracy and P300 amplitude were higher for flashing stimuli and complex "flash + movement" stimuli compared to motion-onset stimuli. N200 amplitude was maximal for flashing stimuli, while for "flash + movement" stimuli and motion-onset stimuli it was only a half of it. Similar BCI with complex stimuli may be embedded into compact control systems requiring high level of user attention under impact of negative external effects obstructing the BCI control.

Computational Materials Science | Materials Science | NREL

Science.gov Websites

of water splitting and fuel cells Nanoparticles for thermal storage New Materials for High-Capacity Theoretical Methodologies for Studying Complex Materials Contact Stephan Lany Staff Scientist Dr. Lany is a

Computer mediated decision making : phase 2

DOT National Transportation Integrated Search

1999-02-01

The presentation of highly technical information during the public phases of complex design projects is often complicated by the participants' inability to understand the terminology and interpret the materials provided. The research was undertaken a...

Two-photon quantum walk in a multimode fiber

PubMed Central

Defienne, Hugo; Barbieri, Marco; Walmsley, Ian A.; Smith, Brian J.; Gigan, Sylvain

2016-01-01

Multiphoton propagation in connected structures—a quantum walk—offers the potential of simulating complex physical systems and provides a route to universal quantum computation. Increasing the complexity of quantum photonic networks where the walk occurs is essential for many applications. We implement a quantum walk of indistinguishable photon pairs in a multimode fiber supporting 380 modes. Using wavefront shaping, we control the propagation of the two-photon state through the fiber in which all modes are coupled. Excitation of arbitrary output modes of the system is realized by controlling classical and quantum interferences. This report demonstrates a highly multimode platform for multiphoton interference experiments and provides a powerful method to program a general high-dimensional multiport optical circuit. This work paves the way for the next generation of photonic devices for quantum simulation, computing, and communication. PMID:27152325

An Analysis of Performance Enhancement Techniques for Overset Grid Applications

NASA Technical Reports Server (NTRS)

Djomehri, J. J.; Biswas, R.; Potsdam, M.; Strawn, R. C.; Biegel, Bryan (Technical Monitor)

2002-01-01

The overset grid methodology has significantly reduced time-to-solution of high-fidelity computational fluid dynamics (CFD) simulations about complex aerospace configurations. The solution process resolves the geometrical complexity of the problem domain by using separately generated but overlapping structured discretization grids that periodically exchange information through interpolation. However, high performance computations of such large-scale realistic applications must be handled efficiently on state-of-the-art parallel supercomputers. This paper analyzes the effects of various performance enhancement techniques on the parallel efficiency of an overset grid Navier-Stokes CFD application running on an SGI Origin2000 machine. Specifically, the role of asynchronous communication, grid splitting, and grid grouping strategies are presented and discussed. Results indicate that performance depends critically on the level of latency hiding and the quality of load balancing across the processors.

Letter regarding 'Comparison between low-cost marker-less and high-end marker-based motion capture systems for the computer-aided assessment of working ergonomics' by Patrizi et al. and research reproducibility.

PubMed

2017-04-01

The reporting of research in a manner that allows reproduction in subsequent investigations is important for scientific progress. Several details of the recent study by Patrizi et al., 'Comparison between low-cost marker-less and high-end marker-based motion capture systems for the computer-aided assessment of working ergonomics', are absent from the published manuscript and make reproduction of findings impossible. As new and complex technologies with great promise for ergonomics develop, new but surmountable challenges for reporting investigations using these technologies in a reproducible manner arise. Practitioner Summary: As with traditional methods, scientific reporting of new and complex ergonomics technologies should be performed in a manner that allows reproduction in subsequent investigations and supports scientific advancement.

Fast Numerical Simulation of Focused Ultrasound Treatments During Respiratory Motion With Discontinuous Motion Boundaries.

PubMed

Schwenke, Michael; Georgii, Joachim; Preusser, Tobias

2017-07-01

Focused ultrasound (FUS) is rapidly gaining clinical acceptance for several target tissues in the human body. Yet, treating liver targets is not clinically applied due to a high complexity of the procedure (noninvasiveness, target motion, complex anatomy, blood cooling effects, shielding by ribs, and limited image-based monitoring). To reduce the complexity, numerical FUS simulations can be utilized for both treatment planning and execution. These use-cases demand highly accurate and computationally efficient simulations. We propose a numerical method for the simulation of abdominal FUS treatments during respiratory motion of the organs and target. Especially, a novel approach is proposed to simulate the heating during motion by solving Pennes' bioheat equation in a computational reference space, i.e., the equation is mathematically transformed to the reference. The approach allows for motion discontinuities, e.g., the sliding of the liver along the abdominal wall. Implementing the solver completely on the graphics processing unit and combining it with an atlas-based ultrasound simulation approach yields a simulation performance faster than real time (less than 50-s computing time for 100 s of treatment time) on a modern off-the-shelf laptop. The simulation method is incorporated into a treatment planning demonstration application that allows to simulate real patient cases including respiratory motion. The high performance of the presented simulation method opens the door to clinical applications. The methods bear the potential to enable the application of FUS for moving organs.

High Performance Computing of Meshless Time Domain Method on Multi-GPU Cluster

NASA Astrophysics Data System (ADS)

Ikuno, Soichiro; Nakata, Susumu; Hirokawa, Yuta; Itoh, Taku

2015-01-01

High performance computing of Meshless Time Domain Method (MTDM) on multi-GPU using the supercomputer HA-PACS (Highly Accelerated Parallel Advanced system for Computational Sciences) at University of Tsukuba is investigated. Generally, the finite difference time domain (FDTD) method is adopted for the numerical simulation of the electromagnetic wave propagation phenomena. However, the numerical domain must be divided into rectangle meshes, and it is difficult to adopt the problem in a complexed domain to the method. On the other hand, MTDM can be easily adept to the problem because MTDM does not requires meshes. In the present study, we implement MTDM on multi-GPU cluster to speedup the method, and numerically investigate the performance of the method on multi-GPU cluster. To reduce the computation time, the communication time between the decomposed domain is hided below the perfect matched layer (PML) calculation procedure. The results of computation show that speedup of MTDM on 128 GPUs is 173 times faster than that of single CPU calculation.

Aerodynamic analysis for aircraft with nacelles, pylons, and winglets at transonic speeds

NASA Technical Reports Server (NTRS)

Boppe, Charles W.

1987-01-01

A computational method has been developed to provide an analysis for complex realistic aircraft configurations at transonic speeds. Wing-fuselage configurations with various combinations of pods, pylons, nacelles, and winglets can be analyzed along with simpler shapes such as airfoils, isolated wings, and isolated bodies. The flexibility required for the treatment of such diverse geometries is obtained by using a multiple nested grid approach in the finite-difference relaxation scheme. Aircraft components (and their grid systems) can be added or removed as required. As a result, the computational method can be used in the same manner as a wind tunnel to study high-speed aerodynamic interference effects. The multiple grid approach also provides high boundary point density/cost ratio. High resolution pressure distributions can be obtained. Computed results are correlated with wind tunnel and flight data using four different transport configurations. Experimental/computational component interference effects are included for cases where data are available. The computer code used for these comparisons is described in the appendices.

Computational Process Modeling for Additive Manufacturing (OSU)

NASA Technical Reports Server (NTRS)

Bagg, Stacey; Zhang, Wei

2015-01-01

Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

High accuracy mantle convection simulation through modern numerical methods - II: realistic models and problems

NASA Astrophysics Data System (ADS)

Heister, Timo; Dannberg, Juliane; Gassmöller, Rene; Bangerth, Wolfgang

2017-08-01

Computations have helped elucidate the dynamics of Earth's mantle for several decades already. The numerical methods that underlie these simulations have greatly evolved within this time span, and today include dynamically changing and adaptively refined meshes, sophisticated and efficient solvers, and parallelization to large clusters of computers. At the same time, many of the methods - discussed in detail in a previous paper in this series - were developed and tested primarily using model problems that lack many of the complexities that are common to the realistic models our community wants to solve today. With several years of experience solving complex and realistic models, we here revisit some of the algorithm designs of the earlier paper and discuss the incorporation of more complex physics. In particular, we re-consider time stepping and mesh refinement algorithms, evaluate approaches to incorporate compressibility, and discuss dealing with strongly varying material coefficients, latent heat, and how to track chemical compositions and heterogeneities. Taken together and implemented in a high-performance, massively parallel code, the techniques discussed in this paper then allow for high resolution, 3-D, compressible, global mantle convection simulations with phase transitions, strongly temperature dependent viscosity and realistic material properties based on mineral physics data.

Computer-Aided Design/Computer-Assisted Manufacture Monolithic Restorations for Severely Worn Dentition: A Case History Report.

PubMed

Abou-Ayash, Samir; Boldt, Johannes; Vuck, Alexander

Full-arch rehabilitation of patients with severe tooth wear due to parafunctional behavior is a challenge for dentists and dental technicians, especially when a highly esthetic outcome is desired. A variety of different treatment options and prosthetic materials are available for such a clinical undertaking. The ongoing progress of computer-aided design/computer-assisted manufacture technologies in combination with all-ceramic materials provides a predictable workflow for these complex cases. This case history report describes a comprehensive, step-by-step treatment protocol leading to an optimally predictable treatment outcome for an esthetically compromised patient.

The Need for Optical Means as an Alternative for Electronic Computing

NASA Technical Reports Server (NTRS)

Adbeldayem, Hossin; Frazier, Donald; Witherow, William; Paley, Steve; Penn, Benjamin; Bank, Curtis; Whitaker, Ann F. (Technical Monitor)

2001-01-01

An increasing demand for faster computers is rapidly growing to encounter the fast growing rate of Internet, space communication, and robotic industry. Unfortunately, the Very Large Scale Integration technology is approaching its fundamental limits beyond which the device will be unreliable. Optical interconnections and optical integrated circuits are strongly believed to provide the way out of the extreme limitations imposed on the growth of speed and complexity of nowadays computations by conventional electronics. This paper demonstrates two ultra-fast, all-optical logic gates and a high-density storage medium, which are essential components in building the future optical computer.

Turbulence modeling of free shear layers for high-performance aircraft

NASA Technical Reports Server (NTRS)

Sondak, Douglas L.

1993-01-01

The High Performance Aircraft (HPA) Grand Challenge of the High Performance Computing and Communications (HPCC) program involves the computation of the flow over a high performance aircraft. A variety of free shear layers, including mixing layers over cavities, impinging jets, blown flaps, and exhaust plumes, may be encountered in such flowfields. Since these free shear layers are usually turbulent, appropriate turbulence models must be utilized in computations in order to accurately simulate these flow features. The HPCC program is relying heavily on parallel computers. A Navier-Stokes solver (POVERFLOW) utilizing the Baldwin-Lomax algebraic turbulence model was developed and tested on a 128-node Intel iPSC/860. Algebraic turbulence models run very fast, and give good results for many flowfields. For complex flowfields such as those mentioned above, however, they are often inadequate. It was therefore deemed that a two-equation turbulence model will be required for the HPA computations. The k-epsilon two-equation turbulence model was implemented on the Intel iPSC/860. Both the Chien low-Reynolds-number model and a generalized wall-function formulation were included.

Computational Lipidomics and Lipid Bioinformatics: Filling In the Blanks.

PubMed

Pauling, Josch; Klipp, Edda

2016-12-22

Lipids are highly diverse metabolites of pronounced importance in health and disease. While metabolomics is a broad field under the omics umbrella that may also relate to lipids, lipidomics is an emerging field which specializes in the identification, quantification and functional interpretation of complex lipidomes. Today, it is possible to identify and distinguish lipids in a high-resolution, high-throughput manner and simultaneously with a lot of structural detail. However, doing so may produce thousands of mass spectra in a single experiment which has created a high demand for specialized computational support to analyze these spectral libraries. The computational biology and bioinformatics community has so far established methodology in genomics, transcriptomics and proteomics but there are many (combinatorial) challenges when it comes to structural diversity of lipids and their identification, quantification and interpretation. This review gives an overview and outlook on lipidomics research and illustrates ongoing computational and bioinformatics efforts. These efforts are important and necessary steps to advance the lipidomics field alongside analytic, biochemistry, biomedical and biology communities and to close the gap in available computational methodology between lipidomics and other omics sub-branches.

Computational methods in metabolic engineering for strain design.

PubMed

Long, Matthew R; Ong, Wai Kit; Reed, Jennifer L

2015-08-01

Metabolic engineering uses genetic approaches to control microbial metabolism to produce desired compounds. Computational tools can identify new biological routes to chemicals and the changes needed in host metabolism to improve chemical production. Recent computational efforts have focused on exploring what compounds can be made biologically using native, heterologous, and/or enzymes with broad specificity. Additionally, computational methods have been developed to suggest different types of genetic modifications (e.g. gene deletion/addition or up/down regulation), as well as suggest strategies meeting different criteria (e.g. high yield, high productivity, or substrate co-utilization). Strategies to improve the runtime performances have also been developed, which allow for more complex metabolic engineering strategies to be identified. Future incorporation of kinetic considerations will further improve strain design algorithms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computational Aerodynamic Modeling of Small Quadcopter Vehicles

NASA Technical Reports Server (NTRS)

Yoon, Seokkwan; Ventura Diaz, Patricia; Boyd, D. Douglas; Chan, William M.; Theodore, Colin R.

2017-01-01

High-fidelity computational simulations have been performed which focus on rotor-fuselage and rotor-rotor aerodynamic interactions of small quad-rotor vehicle systems. The three-dimensional unsteady Navier-Stokes equations are solved on overset grids using high-order accurate schemes, dual-time stepping, low Mach number preconditioning, and hybrid turbulence modeling. Computational results for isolated rotors are shown to compare well with available experimental data. Computational results in hover reveal the differences between a conventional configuration where the rotors are mounted above the fuselage and an unconventional configuration where the rotors are mounted below the fuselage. Complex flow physics in forward flight is investigated. The goal of this work is to demonstrate that understanding of interactional aerodynamics can be an important factor in design decisions regarding rotor and fuselage placement for next-generation multi-rotor drones.

CFD Analysis and Design Optimization Using Parallel Computers

NASA Technical Reports Server (NTRS)

Martinelli, Luigi; Alonso, Juan Jose; Jameson, Antony; Reuther, James

1997-01-01

A versatile and efficient multi-block method is presented for the simulation of both steady and unsteady flow, as well as aerodynamic design optimization of complete aircraft configurations. The compressible Euler and Reynolds Averaged Navier-Stokes (RANS) equations are discretized using a high resolution scheme on body-fitted structured meshes. An efficient multigrid implicit scheme is implemented for time-accurate flow calculations. Optimum aerodynamic shape design is achieved at very low cost using an adjoint formulation. The method is implemented on parallel computing systems using the MPI message passing interface standard to ensure portability. The results demonstrate that, by combining highly efficient algorithms with parallel computing, it is possible to perform detailed steady and unsteady analysis as well as automatic design for complex configurations using the present generation of parallel computers.

From the desktop to the grid: scalable bioinformatics via workflow conversion.

PubMed

de la Garza, Luis; Veit, Johannes; Szolek, Andras; Röttig, Marc; Aiche, Stephan; Gesing, Sandra; Reinert, Knut; Kohlbacher, Oliver

2016-03-12

Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks. There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free -an aspect that could potentially drive away members of the scientific community. We have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: the Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources. Our work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results.

Spatial aliasing for efficient direction-of-arrival estimation based on steering vector reconstruction

NASA Astrophysics Data System (ADS)

Yan, Feng-Gang; Cao, Bin; Rong, Jia-Jia; Shen, Yi; Jin, Ming

2016-12-01

A new technique is proposed to reduce the computational complexity of the multiple signal classification (MUSIC) algorithm for direction-of-arrival (DOA) estimate using a uniform linear array (ULA). The steering vector of the ULA is reconstructed as the Kronecker product of two other steering vectors, and a new cost function with spatial aliasing at hand is derived. Thanks to the estimation ambiguity of this spatial aliasing, mirror angles mathematically relating to the true DOAs are generated, based on which the full spectral search involved in the MUSIC algorithm is highly compressed into a limited angular sector accordingly. Further complexity analysis and performance studies are conducted by computer simulations, which demonstrate that the proposed estimator requires an extremely reduced computational burden while it shows a similar accuracy to the standard MUSIC.

A comprehensive pipeline for multi-resolution modeling of the mitral valve: Validation, computational efficiency, and predictive capability.

PubMed

Drach, Andrew; Khalighi, Amir H; Sacks, Michael S

2018-02-01

Multiple studies have demonstrated that the pathological geometries unique to each patient can affect the durability of mitral valve (MV) repairs. While computational modeling of the MV is a promising approach to improve the surgical outcomes, the complex MV geometry precludes use of simplified models. Moreover, the lack of complete in vivo geometric information presents significant challenges in the development of patient-specific computational models. There is thus a need to determine the level of detail necessary for predictive MV models. To address this issue, we have developed a novel pipeline for building attribute-rich computational models of MV with varying fidelity directly from the in vitro imaging data. The approach combines high-resolution geometric information from loaded and unloaded states to achieve a high level of anatomic detail, followed by mapping and parametric embedding of tissue attributes to build a high-resolution, attribute-rich computational models. Subsequent lower resolution models were then developed and evaluated by comparing the displacements and surface strains to those extracted from the imaging data. We then identified the critical levels of fidelity for building predictive MV models in the dilated and repaired states. We demonstrated that a model with a feature size of about 5 mm and mesh size of about 1 mm was sufficient to predict the overall MV shape, stress, and strain distributions with high accuracy. However, we also noted that more detailed models were found to be needed to simulate microstructural events. We conclude that the developed pipeline enables sufficiently complex models for biomechanical simulations of MV in normal, dilated, repaired states. Copyright © 2017 John Wiley & Sons, Ltd.

Ultra-Scale Computing for Emergency Evacuation

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

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

2010-01-01

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

Data Processing Aspects of MEDLARS

PubMed Central

Austin, Charles J.

1964-01-01

The speed and volume requirements of MEDLARS necessitate the use of high-speed data processing equipment, including paper-tape typewriters, a digital computer, and a special device for producing photo-composed output. Input to the system is of three types: variable source data, including citations from the literature and search requests; changes to such master files as the medical subject headings list and the journal record file; and operating instructions such as computer programs and procedures for machine operators. MEDLARS builds two major stores of data on magnetic tape. The Processed Citation File includes bibliographic citations in expanded form for high-quality printing at periodic intervals. The Compressed Citation File is a coded, time-sequential citation store which is used for high-speed searching against demand request input. Major design considerations include converting variable-length, alphanumeric data to mechanical form quickly and accurately; serial searching by the computer within a reasonable period of time; high-speed printing that must be of graphic quality; and efficient maintenance of various complex computer files. PMID:14119287

DATA PROCESSING ASPECTS OF MEDLARS.

PubMed

AUSTIN, C J

1964-01-01

The speed and volume requirements of MEDLARS necessitate the use of high-speed data processing equipment, including paper-tape typewriters, a digital computer, and a special device for producing photo-composed output. Input to the system is of three types: variable source data, including citations from the literature and search requests; changes to such master files as the medical subject headings list and the journal record file; and operating instructions such as computer programs and procedures for machine operators. MEDLARS builds two major stores of data on magnetic tape. The Processed Citation File includes bibliographic citations in expanded form for high-quality printing at periodic intervals. The Compressed Citation File is a coded, time-sequential citation store which is used for high-speed searching against demand request input. Major design considerations include converting variable-length, alphanumeric data to mechanical form quickly and accurately; serial searching by the computer within a reasonable period of time; high-speed printing that must be of graphic quality; and efficient maintenance of various complex computer files.

Security and Cloud Outsourcing Framework for Economic Dispatch

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

Sarker, Mushfiqur R.; Wang, Jianhui; Li, Zuyi

The computational complexity and problem sizes of power grid applications have increased significantly with the advent of renewable resources and smart grid technologies. The current paradigm of solving these issues consist of inhouse high performance computing infrastructures, which have drawbacks of high capital expenditures, maintenance, and limited scalability. Cloud computing is an ideal alternative due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. A major challenge, however, remains in that the highly confidential grid data is susceptible for potential cyberattacks when outsourced to the cloud. In this work, a security and cloud outsourcing framework is developed for themore » Economic Dispatch (ED) linear programming application. As a result, the security framework transforms the ED linear program into a confidentiality-preserving linear program, that masks both the data and problem structure, thus enabling secure outsourcing to the cloud. Results show that for large grid test cases the performance gain and costs outperforms the in-house infrastructure.« less

Security and Cloud Outsourcing Framework for Economic Dispatch

DOE PAGES

Sarker, Mushfiqur R.; Wang, Jianhui; Li, Zuyi; ...

2017-04-24

The computational complexity and problem sizes of power grid applications have increased significantly with the advent of renewable resources and smart grid technologies. The current paradigm of solving these issues consist of inhouse high performance computing infrastructures, which have drawbacks of high capital expenditures, maintenance, and limited scalability. Cloud computing is an ideal alternative due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. A major challenge, however, remains in that the highly confidential grid data is susceptible for potential cyberattacks when outsourced to the cloud. In this work, a security and cloud outsourcing framework is developed for themore » Economic Dispatch (ED) linear programming application. As a result, the security framework transforms the ED linear program into a confidentiality-preserving linear program, that masks both the data and problem structure, thus enabling secure outsourcing to the cloud. Results show that for large grid test cases the performance gain and costs outperforms the in-house infrastructure.« less

Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems.

PubMed

Choi, Hyungsuk; Choi, Woohyuk; Quan, Tran Minh; Hildebrand, David G C; Pfister, Hanspeter; Jeong, Won-Ki

2014-12-01

As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and GPU accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing GPU clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi's Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

PubMed

Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

PubMed Central

Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622

Moving alcohol prevention research forward-Part I: introducing a complex systems paradigm.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

The drinking environment is a complex system consisting of a number of heterogeneous, evolving and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. A complex systems paradigm, grounded in socio-ecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models can further increase stakeholder buy-in, understanding and policymaking. A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions. © 2017 Society for the Study of Addiction.

Computational Modeling and Treatment Identification in the Myelodysplastic Syndromes.

PubMed

Drusbosky, Leylah M; Cogle, Christopher R

2017-10-01

This review discusses the need for computational modeling in myelodysplastic syndromes (MDS) and early test results. As our evolving understanding of MDS reveals a molecularly complicated disease, the need for sophisticated computer analytics is required to keep track of the number and complex interplay among the molecular abnormalities. Computational modeling and digital drug simulations using whole exome sequencing data input have produced early results showing high accuracy in predicting treatment response to standard of care drugs. Furthermore, the computational MDS models serve as clinically relevant MDS cell lines for pre-clinical assays of investigational agents. MDS is an ideal disease for computational modeling and digital drug simulations. Current research is focused on establishing the prediction value of computational modeling. Future research will test the clinical advantage of computer-informed therapy in MDS.

UTDallas Offline Computing System for B Physics with the Babar Experiment at SLAC

NASA Astrophysics Data System (ADS)

Benninger, Tracy L.

1998-10-01

The University of Texas at Dallas High Energy Physics group is building a high performance, large storage computing system for B physics research with the BaBar experiment (``factory'') at the Stanford Linear Accelerator Center. The goal of this system is to analyze one terabyte of complex Event Store data from BaBar in one to two days. The foundation of the computing system is a Sun E6000 Enterprise multiprocessor system, with additions of a Sun StorEdge L1800 Tape Library, a Sun Workstation for processing batch jobs, staging disks and interface cards. The design considerations, current status, projects underway, and possible upgrade paths will be discussed.

High frame-rate computational ghost imaging system using an optical fiber phased array and a low-pixel APD array.

PubMed

Liu, Chunbo; Chen, Jingqiu; Liu, Jiaxin; Han, Xiang'e

2018-04-16

To obtain a high imaging frame rate, a computational ghost imaging system scheme is proposed based on optical fiber phased array (OFPA). Through high-speed electro-optic modulators, the randomly modulated OFPA can provide much faster speckle projection, which can be precomputed according to the geometry of the fiber array and the known phases for modulation. Receiving the signal light with a low-pixel APD array can effectively decrease the requirement on sampling quantity and computation complexity owing to the reduced data dimensionality while avoiding the image aliasing due to the spatial periodicity of the speckles. The results of analysis and simulation show that the frame rate of the proposed imaging system can be significantly improved compared with traditional systems.

2013 R&D 100 Award: ‘Miniapps’ Bolster High Performance Computing

ScienceCinema

Belak, Jim; Richards, David

2018-06-12

Two Livermore computer scientists served on a Sandia National Laboratories-led team that developed Mantevo Suite 1.0, the first integrated suite of small software programs, also called "miniapps," to be made available to the high performance computing (HPC) community. These miniapps facilitate the development of new HPC systems and the applications that run on them. Miniapps (miniature applications) serve as stripped down surrogates for complex, full-scale applications that can require a great deal of time and effort to port to a new HPC system because they often consist of hundreds of thousands of lines of code. The miniapps are a prototype that contains some or all of the essentials of the real application but with many fewer lines of code, making the miniapp more versatile for experimentation. This allows researchers to more rapidly explore options and optimize system design, greatly improving the chances the full-scale application will perform successfully. These miniapps have become essential tools for exploring complex design spaces because they can reliably predict the performance of full applications.

A high temperature fatigue life prediction computer code based on the total strain version of StrainRange Partitioning (SRP)

NASA Technical Reports Server (NTRS)

Mcgaw, Michael A.; Saltsman, James F.

1993-01-01

A recently developed high-temperature fatigue life prediction computer code is presented and an example of its usage given. The code discussed is based on the Total Strain version of Strainrange Partitioning (TS-SRP). Included in this code are procedures for characterizing the creep-fatigue durability behavior of an alloy according to TS-SRP guidelines and predicting cyclic life for complex cycle types for both isothermal and thermomechanical conditions. A reasonably extensive materials properties database is included with the code.

Real-time data reduction capabilities at the Langley 7 by 10 foot high speed tunnel

NASA Technical Reports Server (NTRS)

Fox, C. H., Jr.

1980-01-01

The 7 by 10 foot high speed tunnel performs a wide range of tests employing a variety of model installation methods. To support the reduction of static data from this facility, a generalized wind tunnel data reduction program had been developed for use on the Langley central computer complex. The capabilities of a version of this generalized program adapted for real time use on a dedicated on-site computer are discussed. The input specifications, instructions for the console operator, and full descriptions of the algorithms are included.

Research on image complexity evaluation method based on color information

NASA Astrophysics Data System (ADS)

Wang, Hao; Duan, Jin; Han, Xue-hui; Xiao, Bo

2017-11-01

In order to evaluate the complexity of a color image more effectively and find the connection between image complexity and image information, this paper presents a method to compute the complexity of image based on color information.Under the complexity ,the theoretical analysis first divides the complexity from the subjective level, divides into three levels: low complexity, medium complexity and high complexity, and then carries on the image feature extraction, finally establishes the function between the complexity value and the color characteristic model. The experimental results show that this kind of evaluation method can objectively reconstruct the complexity of the image from the image feature research. The experimental results obtained by the method of this paper are in good agreement with the results of human visual perception complexity,Color image complexity has a certain reference value.

Finite Dimensional Approximations for Continuum Multiscale Problems

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

Berlyand, Leonid

2017-01-24

The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed researchmore » was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.« less

High-order hydrodynamic algorithms for exascale computing

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

Morgan, Nathaniel Ray

Hydrodynamic algorithms are at the core of many laboratory missions ranging from simulating ICF implosions to climate modeling. The hydrodynamic algorithms commonly employed at the laboratory and in industry (1) typically lack requisite accuracy for complex multi- material vortical flows and (2) are not well suited for exascale computing due to poor data locality and poor FLOP/memory ratios. Exascale computing requires advances in both computer science and numerical algorithms. We propose to research the second requirement and create a new high-order hydrodynamic algorithm that has superior accuracy, excellent data locality, and excellent FLOP/memory ratios. This proposal will impact a broadmore » range of research areas including numerical theory, discrete mathematics, vorticity evolution, gas dynamics, interface instability evolution, turbulent flows, fluid dynamics and shock driven flows. If successful, the proposed research has the potential to radically transform simulation capabilities and help position the laboratory for computing at the exascale.« less

Intrinsic dimensionality predicts the saliency of natural dynamic scenes.

PubMed

Vig, Eleonora; Dorr, Michael; Martinetz, Thomas; Barth, Erhardt

2012-06-01

Since visual attention-based computer vision applications have gained popularity, ever more complex, biologically inspired models seem to be needed to predict salient locations (or interest points) in naturalistic scenes. In this paper, we explore how far one can go in predicting eye movements by using only basic signal processing, such as image representations derived from efficient coding principles, and machine learning. To this end, we gradually increase the complexity of a model from simple single-scale saliency maps computed on grayscale videos to spatiotemporal multiscale and multispectral representations. Using a large collection of eye movements on high-resolution videos, supervised learning techniques fine-tune the free parameters whose addition is inevitable with increasing complexity. The proposed model, although very simple, demonstrates significant improvement in predicting salient locations in naturalistic videos over four selected baseline models and two distinct data labeling scenarios.

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

Complexity Optimization and High-Throughput Low-Latency Hardware Implementation of a Multi-Electrode Spike-Sorting Algorithm

PubMed Central

Dragas, Jelena; Jäckel, David; Hierlemann, Andreas; Franke, Felix

2017-01-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction. PMID:25415989

Complexity optimization and high-throughput low-latency hardware implementation of a multi-electrode spike-sorting algorithm.

PubMed

Dragas, Jelena; Jackel, David; Hierlemann, Andreas; Franke, Felix

2015-03-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.

Thermodynamic cost of computation, algorithmic complexity and the information metric

NASA Technical Reports Server (NTRS)

Zurek, W. H.

1989-01-01

Algorithmic complexity is discussed as a computational counterpart to the second law of thermodynamics. It is shown that algorithmic complexity, which is a measure of randomness, sets limits on the thermodynamic cost of computations and casts a new light on the limitations of Maxwell's demon. Algorithmic complexity can also be used to define distance between binary strings.

Neural Network Training by Integration of Adjoint Systems of Equations Forward in Time

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad (Inventor); Barhen, Jacob (Inventor)

1999-01-01

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically. it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved. but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. Tbc trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Neural network training by integration of adjoint systems of equations forward in time

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad (Inventor); Barhen, Jacob (Inventor)

1992-01-01

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically, it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved, but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. The trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Vector spherical quasi-Gaussian vortex beams

NASA Astrophysics Data System (ADS)

Mitri, F. G.

2014-02-01

Model equations for describing and efficiently computing the radiation profiles of tightly spherically focused higher-order electromagnetic beams of vortex nature are derived stemming from a vectorial analysis with the complex-source-point method. This solution, termed as a high-order quasi-Gaussian (qG) vortex beam, exactly satisfies the vector Helmholtz and Maxwell's equations. It is characterized by a nonzero integer degree and order (n,m), respectively, an arbitrary waist w0, a diffraction convergence length known as the Rayleigh range zR, and an azimuthal phase dependency in the form of a complex exponential corresponding to a vortex beam. An attractive feature of the high-order solution is the rigorous description of strongly focused (or strongly divergent) vortex wave fields without the need of either the higher-order corrections or the numerically intensive methods. Closed-form expressions and computational results illustrate the analysis and some properties of the high-order qG vortex beams based on the axial and transverse polarization schemes of the vector potentials with emphasis on the beam waist.

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

NASA Astrophysics Data System (ADS)

Mosby, Matthew; Matouš, Karel

2015-12-01

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

Urban Typologies: Towards an ORNL Urban Information System (UrbIS)

NASA Astrophysics Data System (ADS)

KC, B.; King, A. W.; Sorokine, A.; Crow, M. C.; Devarakonda, R.; Hilbert, N. L.; Karthik, R.; Patlolla, D.; Surendran Nair, S.

2016-12-01

Urban environments differ in a large number of key attributes; these include infrastructure, morphology, demography, and economic and social variables, among others. These attributes determine many urban properties such as energy and water consumption, greenhouse gas emissions, air quality, public health, sustainability, and vulnerability and resilience to climate change. Characterization of urban environments by a single property such as population size does not sufficiently capture this complexity. In addressing this multivariate complexity one typically faces such problems as disparate and scattered data, challenges of big data management, spatial searching, insufficient computational capacity for data-driven analysis and modelling, and the lack of tools to quickly visualize the data and compare the analytical results across different cities and regions. We have begun the development of an Urban Information System (UrbIS) to address these issues, one that embraces the multivariate "big data" of urban areas and their environments across the United States utilizing the Big Data as a Service (BDaaS) concept. With technological roots in High-performance Computing (HPC), BDaaS is based on the idea of outsourcing computations to different computing paradigms, scalable to super-computers. UrbIS aims to incorporate federated metadata search, integrated modeling and analysis, and geovisualization into a single seamless workflow. The system includes web-based 2D/3D visualization with an iGlobe interface, fast cloud-based and server-side data processing and analysis, and a metadata search engine based on the Mercury data search system developed at Oak Ridge National Laboratory (ORNL). Results of analyses will be made available through web services. We are implementing UrbIS in ORNL's Compute and Data Environment for Science (CADES) and are leveraging ORNL experience in complex data and geospatial projects. The development of UrbIS is being guided by an investigation of urban heat islands (UHI) using high-dimensional clustering and statistics to define urban typologies (types of cities) in an investigation of how UHI vary with urban type across the United States.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

PubMed

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.

High-resolution method for evolving complex interface networks

NASA Astrophysics Data System (ADS)

Pan, Shucheng; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-04-01

In this paper we describe a high-resolution transport formulation of the regional level-set approach for an improved prediction of the evolution of complex interface networks. The novelty of this method is twofold: (i) construction of local level sets and reconstruction of a global level set, (ii) local transport of the interface network by employing high-order spatial discretization schemes for improved representation of complex topologies. Various numerical test cases of multi-region flow problems, including triple-point advection, single vortex flow, mean curvature flow, normal driven flow, dry foam dynamics and shock-bubble interaction show that the method is accurate and suitable for a wide range of complex interface-network evolutions. Its overall computational cost is comparable to the Semi-Lagrangian regional level-set method while the prediction accuracy is significantly improved. The approach thus offers a viable alternative to previous interface-network level-set method.

THC-MP: High performance numerical simulation of reactive transport and multiphase flow in porous media

NASA Astrophysics Data System (ADS)

Wei, Xiaohui; Li, Weishan; Tian, Hailong; Li, Hongliang; Xu, Haixiao; Xu, Tianfu

2015-07-01

The numerical simulation of multiphase flow and reactive transport in the porous media on complex subsurface problem is a computationally intensive application. To meet the increasingly computational requirements, this paper presents a parallel computing method and architecture. Derived from TOUGHREACT that is a well-established code for simulating subsurface multi-phase flow and reactive transport problems, we developed a high performance computing THC-MP based on massive parallel computer, which extends greatly on the computational capability for the original code. The domain decomposition method was applied to the coupled numerical computing procedure in the THC-MP. We designed the distributed data structure, implemented the data initialization and exchange between the computing nodes and the core solving module using the hybrid parallel iterative and direct solver. Numerical accuracy of the THC-MP was verified through a CO2 injection-induced reactive transport problem by comparing the results obtained from the parallel computing and sequential computing (original code). Execution efficiency and code scalability were examined through field scale carbon sequestration applications on the multicore cluster. The results demonstrate successfully the enhanced performance using the THC-MP on parallel computing facilities.

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

NASA Astrophysics Data System (ADS)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

Creation of parallel algorithms for the solution of problems of gas dynamics on multi-core computers and GPU

NASA Astrophysics Data System (ADS)

Rybakin, B.; Bogatencov, P.; Secrieru, G.; Iliuha, N.

2013-10-01

The paper deals with a parallel algorithm for calculations on multiprocessor computers and GPU accelerators. The calculations of shock waves interaction with low-density bubble results and the problem of the gas flow with the forces of gravity are presented. This algorithm combines a possibility to capture a high resolution of shock waves, the second-order accuracy for TVD schemes, and a possibility to observe a low-level diffusion of the advection scheme. Many complex problems of continuum mechanics are numerically solved on structured or unstructured grids. To improve the accuracy of the calculations is necessary to choose a sufficiently small grid (with a small cell size). This leads to the drawback of a substantial increase of computation time. Therefore, for the calculations of complex problems it is reasonable to use the method of Adaptive Mesh Refinement. That is, the grid refinement is performed only in the areas of interest of the structure, where, e.g., the shock waves are generated, or a complex geometry or other such features exist. Thus, the computing time is greatly reduced. In addition, the execution of the application on the resulting sequence of nested, decreasing nets can be parallelized. Proposed algorithm is based on the AMR method. Utilization of AMR method can significantly improve the resolution of the difference grid in areas of high interest, and from other side to accelerate the processes of the multi-dimensional problems calculating. Parallel algorithms of the analyzed difference models realized for the purpose of calculations on graphic processors using the CUDA technology [1].

Computer-Aided Molecular Design of Bis-phosphine Oxide Lanthanide Extractants

DOE PAGES

McCann, Billy W.; Silva, Nuwan De; Windus, Theresa L.; ...

2016-02-17

Computer-aided molecular design and high-throughput screening of viable host architectures can significantly reduce the efforts in the design of novel ligands for efficient extraction of rare earth elements. This paper presents a computational approach to the deliberate design of bis-phosphine oxide host architectures that are structurally organized for complexation of trivalent lanthanides. Molecule building software, HostDesigner, was interfaced with molecular mechanics software, PCModel, providing a tool for generating and screening millions of potential R 2(O)P-link-P(O)R 2 ligand geometries. The molecular mechanics ranking of ligand structures is consistent with both the solution-phase free energies of complexation obtained with density functional theorymore » and the performance of known bis-phosphine oxide extractants. For the case where link is -CH 2-, evaluation of the ligand geometry provides the first characterization of a steric origin for the ‘anomalous aryl strengthening’ effect. The design approach has identified a number of novel bis-phosphine oxide ligands that are better organized for lanthanide complexation than previously studied examples.« less

Feature extraction using first and second derivative extrema (FSDE) for real-time and hardware-efficient spike sorting.

PubMed

Paraskevopoulou, Sivylla E; Barsakcioglu, Deren Y; Saberi, Mohammed R; Eftekhar, Amir; Constandinou, Timothy G

2013-04-30

Next generation neural interfaces aspire to achieve real-time multi-channel systems by integrating spike sorting on chip to overcome limitations in communication channel capacity. The feasibility of this approach relies on developing highly efficient algorithms for feature extraction and clustering with the potential of low-power hardware implementation. We are proposing a feature extraction method, not requiring any calibration, based on first and second derivative features of the spike waveform. The accuracy and computational complexity of the proposed method are quantified and compared against commonly used feature extraction methods, through simulation across four datasets (with different single units) at multiple noise levels (ranging from 5 to 20% of the signal amplitude). The average classification error is shown to be below 7% with a computational complexity of 2N-3, where N is the number of sample points of each spike. Overall, this method presents a good trade-off between accuracy and computational complexity and is thus particularly well-suited for hardware-efficient implementation. Copyright © 2013 Elsevier B.V. All rights reserved.

Programming languages and compiler design for realistic quantum hardware.

PubMed

Chong, Frederic T; Franklin, Diana; Martonosi, Margaret

2017-09-13

Quantum computing sits at an important inflection point. For years, high-level algorithms for quantum computers have shown considerable promise, and recent advances in quantum device fabrication offer hope of utility. A gap still exists, however, between the hardware size and reliability requirements of quantum computing algorithms and the physical machines foreseen within the next ten years. To bridge this gap, quantum computers require appropriate software to translate and optimize applications (toolflows) and abstraction layers. Given the stringent resource constraints in quantum computing, information passed between layers of software and implementations will differ markedly from in classical computing. Quantum toolflows must expose more physical details between layers, so the challenge is to find abstractions that expose key details while hiding enough complexity.

Programming languages and compiler design for realistic quantum hardware

NASA Astrophysics Data System (ADS)

Chong, Frederic T.; Franklin, Diana; Martonosi, Margaret

2017-09-01

Quantum computing sits at an important inflection point. For years, high-level algorithms for quantum computers have shown considerable promise, and recent advances in quantum device fabrication offer hope of utility. A gap still exists, however, between the hardware size and reliability requirements of quantum computing algorithms and the physical machines foreseen within the next ten years. To bridge this gap, quantum computers require appropriate software to translate and optimize applications (toolflows) and abstraction layers. Given the stringent resource constraints in quantum computing, information passed between layers of software and implementations will differ markedly from in classical computing. Quantum toolflows must expose more physical details between layers, so the challenge is to find abstractions that expose key details while hiding enough complexity.

Rapid indirect trajectory optimization on highly parallel computing architectures

NASA Astrophysics Data System (ADS)

Antony, Thomas

Trajectory optimization is a field which can benefit greatly from the advantages offered by parallel computing. The current state-of-the-art in trajectory optimization focuses on the use of direct optimization methods, such as the pseudo-spectral method. These methods are favored due to their ease of implementation and large convergence regions while indirect methods have largely been ignored in the literature in the past decade except for specific applications in astrodynamics. It has been shown that the shortcomings conventionally associated with indirect methods can be overcome by the use of a continuation method in which complex trajectory solutions are obtained by solving a sequence of progressively difficult optimization problems. High performance computing hardware is trending towards more parallel architectures as opposed to powerful single-core processors. Graphics Processing Units (GPU), which were originally developed for 3D graphics rendering have gained popularity in the past decade as high-performance, programmable parallel processors. The Compute Unified Device Architecture (CUDA) framework, a parallel computing architecture and programming model developed by NVIDIA, is one of the most widely used platforms in GPU computing. GPUs have been applied to a wide range of fields that require the solution of complex, computationally demanding problems. A GPU-accelerated indirect trajectory optimization methodology which uses the multiple shooting method and continuation is developed using the CUDA platform. The various algorithmic optimizations used to exploit the parallelism inherent in the indirect shooting method are described. The resulting rapid optimal control framework enables the construction of high quality optimal trajectories that satisfy problem-specific constraints and fully satisfy the necessary conditions of optimality. The benefits of the framework are highlighted by construction of maximum terminal velocity trajectories for a hypothetical long range weapon system. The techniques used to construct an initial guess from an analytic near-ballistic trajectory and the methods used to formulate the necessary conditions of optimality in a manner that is transparent to the designer are discussed. Various hypothetical mission scenarios that enforce different combinations of initial, terminal, interior point and path constraints demonstrate the rapid construction of complex trajectories without requiring any a-priori insight into the structure of the solutions. Trajectory problems of this kind were previously considered impractical to solve using indirect methods. The performance of the GPU-accelerated solver is found to be 2x--4x faster than MATLAB's bvp4c, even while running on GPU hardware that is five years behind the state-of-the-art.

Amoeba-inspired nanoarchitectonic computing: solving intractable computational problems using nanoscale photoexcitation transfer dynamics.

PubMed

Aono, Masashi; Naruse, Makoto; Kim, Song-Ju; Wakabayashi, Masamitsu; Hori, Hirokazu; Ohtsu, Motoichi; Hara, Masahiko

2013-06-18

Biologically inspired computing devices and architectures are expected to overcome the limitations of conventional technologies in terms of solving computationally demanding problems, adapting to complex environments, reducing energy consumption, and so on. We previously demonstrated that a primitive single-celled amoeba (a plasmodial slime mold), which exhibits complex spatiotemporal oscillatory dynamics and sophisticated computing capabilities, can be used to search for a solution to a very hard combinatorial optimization problem. We successfully extracted the essential spatiotemporal dynamics by which the amoeba solves the problem. This amoeba-inspired computing paradigm can be implemented by various physical systems that exhibit suitable spatiotemporal dynamics resembling the amoeba's problem-solving process. In this Article, we demonstrate that photoexcitation transfer phenomena in certain quantum nanostructures mediated by optical near-field interactions generate the amoebalike spatiotemporal dynamics and can be used to solve the satisfiability problem (SAT), which is the problem of judging whether a given logical proposition (a Boolean formula) is self-consistent. SAT is related to diverse application problems in artificial intelligence, information security, and bioinformatics and is a crucially important nondeterministic polynomial time (NP)-complete problem, which is believed to become intractable for conventional digital computers when the problem size increases. We show that our amoeba-inspired computing paradigm dramatically outperforms a conventional stochastic search method. These results indicate the potential for developing highly versatile nanoarchitectonic computers that realize powerful solution searching with low energy consumption.

Students' explanations in complex learning of disciplinary programming

NASA Astrophysics Data System (ADS)

Vieira, Camilo

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, engineers do not know how to exploit CSE affordances. This dissertation intends to introduce computational tools and methods contextualized within the Materials Science and Engineering curriculum. Considering that learning how to program is a complex task, the dissertation explores effective pedagogical practices that can support student disciplinary and computational learning. Two case studies will be evaluated to identify the characteristics of effective worked examples in the context of CSE. Specifically, this dissertation explores students explanations of these worked examples in two engineering courses with different levels of transparency: a programming course in materials science and engineering glass box and a thermodynamics course involving computational representations black box. Results from this study suggest that students benefit in different ways from writing in-code comments. These benefits include but are not limited to: connecting xv individual lines of code to the overall problem, getting familiar with the syntax, learning effective algorithm design strategies, and connecting computation with their discipline. Students in the glass box context generate higher quality explanations than students in the black box context. These explanations are related to students prior experiences. Specifically, students with low ability to do programming engage in a more thorough explanation process than students with high ability. This dissertation concludes proposing an adaptation to the instructional principles of worked-examples for the context of CSE education.

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.

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed Central

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system’s behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics. PMID:29163041

TomoMiner and TomoMinerCloud: A software platform for large-scale subtomogram structural analysis

PubMed Central

Frazier, Zachary; Xu, Min; Alber, Frank

2017-01-01

SUMMARY Cryo-electron tomography (cryoET) captures the 3D electron density distribution of macromolecular complexes in close to native state. With the rapid advance of cryoET acquisition technologies, it is possible to generate large numbers (>100,000) of subtomograms, each containing a macromolecular complex. Often, these subtomograms represent a heterogeneous sample due to variations in structure and composition of a complex in situ form or because particles are a mixture of different complexes. In this case subtomograms must be classified. However, classification of large numbers of subtomograms is a time-intensive task and often a limiting bottleneck. This paper introduces an open source software platform, TomoMiner, for large-scale subtomogram classification, template matching, subtomogram averaging, and alignment. Its scalable and robust parallel processing allows efficient classification of tens to hundreds of thousands of subtomograms. Additionally, TomoMiner provides a pre-configured TomoMinerCloud computing service permitting users without sufficient computing resources instant access to TomoMiners high-performance features. PMID:28552576

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system's behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics.

Advanced complex trait analysis.

PubMed

Gray, A; Stewart, I; Tenesa, A

2012-12-01

The Genome-wide Complex Trait Analysis (GCTA) software package can quantify the contribution of genetic variation to phenotypic variation for complex traits. However, as those datasets of interest continue to increase in size, GCTA becomes increasingly computationally prohibitive. We present an adapted version, Advanced Complex Trait Analysis (ACTA), demonstrating dramatically improved performance. We restructure the genetic relationship matrix (GRM) estimation phase of the code and introduce the highly optimized parallel Basic Linear Algebra Subprograms (BLAS) library combined with manual parallelization and optimization. We introduce the Linear Algebra PACKage (LAPACK) library into the restricted maximum likelihood (REML) analysis stage. For a test case with 8999 individuals and 279,435 single nucleotide polymorphisms (SNPs), we reduce the total runtime, using a compute node with two multi-core Intel Nehalem CPUs, from ∼17 h to ∼11 min. The source code is fully available under the GNU Public License, along with Linux binaries. For more information see http://www.epcc.ed.ac.uk/software-products/acta. a.gray@ed.ac.uk Supplementary data are available at Bioinformatics online.

Fitting Multimeric Protein Complexes into Electron Microscopy Maps Using 3D Zernike Descriptors

PubMed Central

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2012-01-01

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root mean square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases. PMID:22417139

Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors.

PubMed

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2012-06-14

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.

An Exploration of Cognitive Agility as Quantified by Attention Allocation in a Complex Environment

DTIC Science & Technology

2017-03-01

quantified by eye-tracking data collected while subjects played a military-relevant cognitive agility computer game (Make Goal), to determine whether...subjects played a military-relevant cognitive agility computer game (Make Goal), to determine whether certain patterns are associated with effective...Group and Control Group on Eye Tracking and Game Performance .....................36 3. Comparison between High and Low Performers on Eye tracking and

Research on Electrically Driven Single Photon Emitter by Diamond for Quantum Cryptography

DTIC Science & Technology

2015-03-24

by diamond for quantum cryptography 5a. CONTRACT NUMBER FA2386-14-1-4037 5b. GRANT NUMBE R Grant 14IOA093_144037 5c. PROGRAM ELEMENT...emerged as a highly competitive platform for applications in quantum cryptography , quantum computing, spintronics, and sensing or metrology...15. SUBJECT TERMS Diamond LED, Nitrogen Vacancy Complex, Quantum Computing, Quantum Cryptography , Single Spin Single Photon 16. SECURITY

Compression of hyper-spectral images using an accelerated nonnegative tensor decomposition

NASA Astrophysics Data System (ADS)

Li, Jin; Liu, Zilong

2017-12-01

Nonnegative tensor Tucker decomposition (NTD) in a transform domain (e.g., 2D-DWT, etc) has been used in the compression of hyper-spectral images because it can remove redundancies between spectrum bands and also exploit spatial correlations of each band. However, the use of a NTD has a very high computational cost. In this paper, we propose a low complexity NTD-based compression method of hyper-spectral images. This method is based on a pair-wise multilevel grouping approach for the NTD to overcome its high computational cost. The proposed method has a low complexity under a slight decrease of the coding performance compared to conventional NTD. We experimentally confirm this method, which indicates that this method has the less processing time and keeps a better coding performance than the case that the NTD is not used. The proposed approach has a potential application in the loss compression of hyper-spectral or multi-spectral images

Recent advances in QM/MM free energy calculations using reference potentials☆

PubMed Central

Duarte, Fernanda; Amrein, Beat A.; Blaha-Nelson, David; Kamerlin, Shina C.L.

2015-01-01

Background Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Scope of review Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. Major conclusions The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. General significance As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. PMID:25038480

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay; Lyzenga, Greg; Granat, Robert; Fox, Geoffrey; Pierce, Marlon; Rundle, John; McLeod, Dennis; Grant, Lisa; Tullis, Terry

2004-01-01

In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

The Mathematical Modeling and Computer Simulation of Electrochemical Micromachining Using Ultrashort Pulses

NASA Astrophysics Data System (ADS)

Kozak, J.; Gulbinowicz, D.; Gulbinowicz, Z.

2009-05-01

The need for complex and accurate three dimensional (3-D) microcomponents is increasing rapidly for many industrial and consumer products. Electrochemical machining process (ECM) has the potential of generating desired crack-free and stress-free surfaces of microcomponents. This paper reports a study of pulse electrochemical micromachining (PECMM) using ultrashort (nanoseconds) pulses for generating complex 3-D microstructures of high accuracy. A mathematical model of the microshaping process with taking into consideration unsteady phenomena in electrical double layer has been developed. The software for computer simulation of PECM has been developed and the effects of machining parameters on anodic localization and final shape of machined surface are presented.

Three-dimensional scene encryption and display based on computer-generated holograms.

PubMed

Kong, Dezhao; Cao, Liangcai; Jin, Guofan; Javidi, Bahram

2016-10-10

An optical encryption and display method for a three-dimensional (3D) scene is proposed based on computer-generated holograms (CGHs) using a single phase-only spatial light modulator. The 3D scene is encoded as one complex Fourier CGH. The Fourier CGH is then decomposed into two phase-only CGHs with random distributions by the vector stochastic decomposition algorithm. Two CGHs are interleaved as one final phase-only CGH for optical encryption and reconstruction. The proposed method can support high-level nonlinear optical 3D scene security and complex amplitude modulation of the optical field. The exclusive phase key offers strong resistances of decryption attacks. Experimental results demonstrate the validity of the novel method.

Extreme-scale Algorithms and Solver Resilience

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

Dongarra, Jack

A widening gap exists between the peak performance of high-performance computers and the performance achieved by complex applications running on these platforms. Over the next decade, extreme-scale systems will present major new challenges to algorithm development that could amplify this mismatch in such a way that it prevents the productive use of future DOE Leadership computers due to the following; Extreme levels of parallelism due to multicore processors; An increase in system fault rates requiring algorithms to be resilient beyond just checkpoint/restart; Complex memory hierarchies and costly data movement in both energy and performance; Heterogeneous system architectures (mixing CPUs, GPUs,more » etc.); and Conflicting goals of performance, resilience, and power requirements.« less

BridgeRank: A novel fast centrality measure based on local structure of the network

NASA Astrophysics Data System (ADS)

Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh

2018-04-01

Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.

Computational complexity of the landscape II-Cosmological considerations

NASA Astrophysics Data System (ADS)

Denef, Frederik; Douglas, Michael R.; Greene, Brian; Zukowski, Claire

2018-05-01

We propose a new approach for multiverse analysis based on computational complexity, which leads to a new family of "computational" measure factors. By defining a cosmology as a space-time containing a vacuum with specified properties (for example small cosmological constant) together with rules for how time evolution will produce the vacuum, we can associate global time in a multiverse with clock time on a supercomputer which simulates it. We argue for a principle of "limited computational complexity" governing early universe dynamics as simulated by this supercomputer, which translates to a global measure for regulating the infinities of eternal inflation. The rules for time evolution can be thought of as a search algorithm, whose details should be constrained by a stronger principle of "minimal computational complexity". Unlike previously studied global measures, ours avoids standard equilibrium considerations and the well-known problems of Boltzmann Brains and the youngness paradox. We also give various definitions of the computational complexity of a cosmology, and argue that there are only a few natural complexity classes.

High surface area silicon materials: fundamentals and new technology.

PubMed

Buriak, Jillian M

2006-01-15

Crystalline silicon forms the basis of just about all computing technologies on the planet, in the form of microelectronics. An enormous amount of research infrastructure and knowledge has been developed over the past half-century to construct complex functional microelectronic structures in silicon. As a result, it is highly probable that silicon will remain central to computing and related technologies as a platform for integration of, for instance, molecular electronics, sensing elements and micro- and nanoelectromechanical systems. Porous nanocrystalline silicon is a fascinating variant of the same single crystal silicon wafers used to make computer chips. Its synthesis, a straightforward electrochemical, chemical or photochemical etch, is compatible with existing silicon-based fabrication techniques. Porous silicon literally adds an entirely new dimension to the realm of silicon-based technologies as it has a complex, three-dimensional architecture made up of silicon nanoparticles, nanowires, and channel structures. The intrinsic material is photoluminescent at room temperature in the visible region due to quantum confinement effects, and thus provides an optical element to electronic applications. Our group has been developing new organic surface reactions on porous and nanocrystalline silicon to tailor it for a myriad of applications, including molecular electronics and sensing. Integration of organic and biological molecules with porous silicon is critical to harness the properties of this material. The construction and use of complex, hierarchical molecular synthetic strategies on porous silicon will be described.

Combined UMC- DFT prediction of electron-hole coupling in unit cells of pentacene crystals.

PubMed

Leal, Luciano Almeida; de Souza Júnior, Rafael Timóteo; de Almeida Fonseca, Antonio Luciano; Ribeiro Junior, Luiz Antonio; Blawid, Stefan; da Silva Filho, Demetrio Antonio; da Cunha, Wiliam Ferreira

2017-05-01

Pentacene is an organic semiconductor that draws special attention from the scientific community due to the high mobility of its charge carriers. As electron-hole interactions are important aspects in the regard of such property, a computationally inexpensive method to predict the coupling between these quasi-particles is highly desired. In this work, we propose a hybrid methodology of combining Uncoupled Monte Carlo Simulations (UMC) and Density functional Theory (DFT) methodologies to obtain a good compromise between computational feasibility and accuracy. As a first step in considering a Pentacene crystal, we describe its unit cell: the Pentacene Dimer. Because many conformations can be encountered for the dimer and considering the complexity of the system, we make use of UMC in order to find the most probable structures and relative orientations for the Pentacene-Pentacene complex. Following, we carry out electronic structure calculations in the scope of DFT with the goal of describing the electron-hole coupling on the most probable configurations obtained by UMC. The comparison of our results with previously reported data on the literature suggests that the methodology is well suited for describing transfer integrals of organic semiconductors. The observed accuracy together with the smaller computational cost required by our approach allows us to conclude that such methodology might be an important tool towards the description of systems with higher complexity.

An Initial Multi-Domain Modeling of an Actively Cooled Structure

NASA Technical Reports Server (NTRS)

Steinthorsson, Erlendur

1997-01-01

A methodology for the simulation of turbine cooling flows is being developed. The methodology seeks to combine numerical techniques that optimize both accuracy and computational efficiency. Key components of the methodology include the use of multiblock grid systems for modeling complex geometries, and multigrid convergence acceleration for enhancing computational efficiency in highly resolved fluid flow simulations. The use of the methodology has been demonstrated in several turbo machinery flow and heat transfer studies. Ongoing and future work involves implementing additional turbulence models, improving computational efficiency, adding AMR.

Numerical computation of linear instability of detonations

NASA Astrophysics Data System (ADS)

Kabanov, Dmitry; Kasimov, Aslan

2017-11-01

We propose a method to study linear stability of detonations by direct numerical computation. The linearized governing equations together with the shock-evolution equation are solved in the shock-attached frame using a high-resolution numerical algorithm. The computed results are processed by the Dynamic Mode Decomposition technique to generate dispersion relations. The method is applied to the reactive Euler equations with simple-depletion chemistry as well as more complex multistep chemistry. The results are compared with those known from normal-mode analysis. We acknowledge financial support from King Abdullah University of Science and Technology.

Computing the universe: how large-scale simulations illuminate galaxies and dark energy

NASA Astrophysics Data System (ADS)

O'Shea, Brian

2015-04-01

High-performance and large-scale computing is absolutely to understanding astronomical objects such as stars, galaxies, and the cosmic web. This is because these are structures that operate on physical, temporal, and energy scales that cannot be reasonably approximated in the laboratory, and whose complexity and nonlinearity often defies analytic modeling. In this talk, I show how the growth of computing platforms over time has facilitated our understanding of astrophysical and cosmological phenomena, focusing primarily on galaxies and large-scale structure in the Universe.

Special issue of Computers and Fluids in honor of Cecil E. (Chuck) Leith

DOE PAGES

Zhou, Ye; Herring, Jackson

2017-05-12

Here, this special issue of Computers and Fluids is dedicated to Cecil E. (Chuck) Leith in honor of his research contributions, leadership in the areas of statistical fluid mechanics, computational fluid dynamics, and climate theory. Leith's contribution to these fields emerged from his interest in solving complex fluid flow problems--even those at high Mach numbers--in an era well before large scale supercomputing became the dominant mode of inquiry into these fields. Yet the issues raised and solved by his research effort are still of vital interest today.

CSM Testbed Development and Large-Scale Structural Applications

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Gillian, R. E.; Mccleary, Susan L.; Lotts, C. G.; Poole, E. L.; Overman, A. L.; Macy, S. C.

1989-01-01

A research activity called Computational Structural Mechanics (CSM) conducted at the NASA Langley Research Center is described. This activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM Testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM Testbed methods development environment is presented and some new numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

Special issue of Computers and Fluids in honor of Cecil E. (Chuck) Leith

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

Zhou, Ye; Herring, Jackson

Here, this special issue of Computers and Fluids is dedicated to Cecil E. (Chuck) Leith in honor of his research contributions, leadership in the areas of statistical fluid mechanics, computational fluid dynamics, and climate theory. Leith's contribution to these fields emerged from his interest in solving complex fluid flow problems--even those at high Mach numbers--in an era well before large scale supercomputing became the dominant mode of inquiry into these fields. Yet the issues raised and solved by his research effort are still of vital interest today.

The Application of COMSOL Multiphysics Package on the Modelling of Complex 3-D Lithospheric Electrical Resistivity Structures - A Case Study from the Proterozoic Orogenic belt within the North China Craton

NASA Astrophysics Data System (ADS)

Guo, L.; Yin, Y.; Deng, M.; Guo, L.; Yan, J.

2017-12-01

At present, most magnetotelluric (MT) forward modelling and inversion codes are based on finite difference method. But its structured mesh gridding cannot be well adapted for the conditions with arbitrary topography or complex tectonic structures. By contrast, the finite element method is more accurate in calculating complex and irregular 3-D region and has lower requirement of function smoothness. However, the complexity of mesh gridding and limitation of computer capacity has been affecting its application. COMSOL Multiphysics is a cross-platform finite element analysis, solver and multiphysics full-coupling simulation software. It achieves highly accurate numerical simulations with high computational performance and outstanding multi-field bi-directional coupling analysis capability. In addition, its AC/DC and RF module can be used to easily calculate the electromagnetic responses of complex geological structures. Using the adaptive unstructured grid, the calculation is much faster. In order to improve the discretization technique of computing area, we use the combination of Matlab and COMSOL Multiphysics to establish a general procedure for calculating the MT responses for arbitrary resistivity models. The calculated responses include the surface electric and magnetic field components, impedance components, magnetic transfer functions and phase tensors. Then, the reliability of this procedure is certificated by 1-D, 2-D and 3-D and anisotropic forward modeling tests. Finally, we establish the 3-D lithospheric resistivity model for the Proterozoic Wutai-Hengshan Mts. within the North China Craton by fitting the real MT data collected there. The reliability of the model is also verified by induced vectors and phase tensors. Our model shows more details and better resolution, compared with the previously published 3-D model based on the finite difference method. In conclusion, COMSOL Multiphysics package is suitable for modeling the 3-D lithospheric resistivity structures under complex tectonic deformation backgrounds, which could be a good complement to the existing finite-difference inversion algorithms.

Integrating CFD, CAA, and Experiments Towards Benchmark Datasets for Airframe Noise Problems

NASA Technical Reports Server (NTRS)

Choudhari, Meelan M.; Yamamoto, Kazuomi

2012-01-01

Airframe noise corresponds to the acoustic radiation due to turbulent flow in the vicinity of airframe components such as high-lift devices and landing gears. The combination of geometric complexity, high Reynolds number turbulence, multiple regions of separation, and a strong coupling with adjacent physical components makes the problem of airframe noise highly challenging. Since 2010, the American Institute of Aeronautics and Astronautics has organized an ongoing series of workshops devoted to Benchmark Problems for Airframe Noise Computations (BANC). The BANC workshops are aimed at enabling a systematic progress in the understanding and high-fidelity predictions of airframe noise via collaborative investigations that integrate state of the art computational fluid dynamics, computational aeroacoustics, and in depth, holistic, and multifacility measurements targeting a selected set of canonical yet realistic configurations. This paper provides a brief summary of the BANC effort, including its technical objectives, strategy, and selective outcomes thus far.

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

NASA Astrophysics Data System (ADS)

Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

2017-12-01

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

High Performance Computing for Modeling Wind Farms and Their Impact

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

PubMed Central

Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930

Optical Computers and Space Technology

NASA Technical Reports Server (NTRS)

Abdeldayem, Hossin A.; Frazier, Donald O.; Penn, Benjamin; Paley, Mark S.; Witherow, William K.; Banks, Curtis; Hicks, Rosilen; Shields, Angela

1995-01-01

The rapidly increasing demand for greater speed and efficiency on the information superhighway requires significant improvements over conventional electronic logic circuits. Optical interconnections and optical integrated circuits are strong candidates to provide the way out of the extreme limitations imposed on the growth of speed and complexity of nowadays computations by the conventional electronic logic circuits. The new optical technology has increased the demand for high quality optical materials. NASA's recent involvement in processing optical materials in space has demonstrated that a new and unique class of high quality optical materials are processible in a microgravity environment. Microgravity processing can induce improved orders in these materials and could have a significant impact on the development of optical computers. We will discuss NASA's role in processing these materials and report on some of the associated nonlinear optical properties which are quite useful for optical computers technology.

Undecidability and Irreducibility Conditions for Open-Ended Evolution and Emergence.

PubMed

Hernández-Orozco, Santiago; Hernández-Quiroz, Francisco; Zenil, Hector

2018-01-01

Is undecidability a requirement for open-ended evolution (OEE)? Using methods derived from algorithmic complexity theory, we propose robust computational definitions of open-ended evolution and the adaptability of computable dynamical systems. Within this framework, we show that decidability imposes absolute limits on the stable growth of complexity in computable dynamical systems. Conversely, systems that exhibit (strong) open-ended evolution must be undecidable, establishing undecidability as a requirement for such systems. Complexity is assessed in terms of three measures: sophistication, coarse sophistication, and busy beaver logical depth. These three complexity measures assign low complexity values to random (incompressible) objects. As time grows, the stated complexity measures allow for the existence of complex states during the evolution of a computable dynamical system. We show, however, that finding these states involves undecidable computations. We conjecture that for similar complexity measures that assign low complexity values, decidability imposes comparable limits on the stable growth of complexity, and that such behavior is necessary for nontrivial evolutionary systems. We show that the undecidability of adapted states imposes novel and unpredictable behavior on the individuals or populations being modeled. Such behavior is irreducible. Finally, we offer an example of a system, first proposed by Chaitin, that exhibits strong OEE.

77 FR 50726 - Software Requirement Specifications for Digital Computer Software and Complex Electronics Used in...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-22

... Computer Software and Complex Electronics Used in Safety Systems of Nuclear Power Plants AGENCY: Nuclear...-1209, ``Software Requirement Specifications for Digital Computer Software and Complex Electronics used... Electronics Engineers (ANSI/IEEE) Standard 830-1998, ``IEEE Recommended Practice for Software Requirements...

Identification and addressing reduction-related misconceptions

NASA Astrophysics Data System (ADS)

Gal-Ezer, Judith; Trakhtenbrot, Mark

2016-07-01

Reduction is one of the key techniques used for problem-solving in computer science. In particular, in the theory of computation and complexity (TCC), mapping and polynomial reductions are used for analysis of decidability and computational complexity of problems, including the core concept of NP-completeness. Reduction is a highly abstract technique that involves revealing close non-trivial connections between problems that often seem to have nothing in common. As a result, proper understanding and application of reduction is a serious challenge for students and a source of numerous misconceptions. The main contribution of this paper is detection of such misconceptions, analysis of their roots, and proposing a way to address them in an undergraduate TCC course. Our observations suggest that the main source of the misconceptions is the false intuitive rule "the bigger is a set/problem, the harder it is to solve". Accordingly, we developed a series of exercises for proactive prevention of these misconceptions.

A space-efficient quantum computer simulator suitable for high-speed FPGA implementation

NASA Astrophysics Data System (ADS)

Frank, Michael P.; Oniciuc, Liviu; Meyer-Baese, Uwe H.; Chiorescu, Irinel

2009-05-01

Conventional vector-based simulators for quantum computers are quite limited in the size of the quantum circuits they can handle, due to the worst-case exponential growth of even sparse representations of the full quantum state vector as a function of the number of quantum operations applied. However, this exponential-space requirement can be avoided by using general space-time tradeoffs long known to complexity theorists, which can be appropriately optimized for this particular problem in a way that also illustrates some interesting reformulations of quantum mechanics. In this paper, we describe the design and empirical space/time complexity measurements of a working software prototype of a quantum computer simulator that avoids excessive space requirements. Due to its space-efficiency, this design is well-suited to embedding in single-chip environments, permitting especially fast execution that avoids access latencies to main memory. We plan to prototype our design on a standard FPGA development board.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

Modeling synthetic lethality

PubMed Central

Le Meur, Nolwenn; Gentleman, Robert

2008-01-01

Background Synthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units. Results In Saccharomyces cerevisiae, we identified multi-protein complexes and pairs of multi-protein complexes that share an unusually high number of synthetic genetic interactions. As previously predicted, we found that synthetic lethality can arise from subunits of an essential multi-protein complex or between pairs of multi-protein complexes. Finally, using multi-protein complexes allowed us to take into account the pleiotropic nature of the gene products. Conclusions Modeling synthetic lethality using current estimates of the yeast interactome is an efficient approach to disentangle some of the complex molecular interactions that drive a cell. Our model in conjunction with applied statistical methods and computational methods provides new tools to better characterize synthetic genetic interactions. PMID:18789146

Squid - a simple bioinformatics grid.

PubMed

Carvalho, Paulo C; Glória, Rafael V; de Miranda, Antonio B; Degrave, Wim M

2005-08-03

BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled "Squid" that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers. Most distributed computing / grid solutions have complex installation procedures requiring a computer specialist, or have limitations regarding operating systems. Squid is a multi-platform, open-source program designed to "keep things simple" while offering high-end computing power for large scale applications. Squid also has an efficient fault tolerance and crash recovery system against data loss, being able to re-route jobs upon node failure and recover even if the master machine fails. Our results show that a Squid application, working with N nodes and proper network resources, can process BLAST queries almost N times faster than if working with only one computer. Squid offers high-end computing, even for the non-specialist, and is freely available at the project web site. Its open-source and binary Windows distributions contain detailed instructions and a "plug-n-play" instalation containing a pre-configured example.

Access to computer-based leisure for individuals with profound disabilities.

PubMed

Bache, Jane; Derwent, Gary

2008-01-01

Advances in computer technology and the Internet have meant that more and more occupations can be made available to disabled individuals, including occupations generally considered to be leisure. However, computers and the Internet also provide barriers to access for these individuals. This article discusses some of these barriers, solutions to them and highlights the complexities involved in the provision of a computer-based assistive technology solution for access to leisure for a profoundly disabled young lady. It also points out the need for the input of a highly skilled, multi-disciplinary team in the assessment for and provision of such a system.

BlueSNP: R package for highly scalable genome-wide association studies using Hadoop clusters.

PubMed

Huang, Hailiang; Tata, Sandeep; Prill, Robert J

2013-01-01

Computational workloads for genome-wide association studies (GWAS) are growing in scale and complexity outpacing the capabilities of single-threaded software designed for personal computers. The BlueSNP R package implements GWAS statistical tests in the R programming language and executes the calculations across computer clusters configured with Apache Hadoop, a de facto standard framework for distributed data processing using the MapReduce formalism. BlueSNP makes computationally intensive analyses, such as estimating empirical p-values via data permutation, and searching for expression quantitative trait loci over thousands of genes, feasible for large genotype-phenotype datasets. http://github.com/ibm-bioinformatics/bluesnp

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 value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation

NASA Astrophysics Data System (ADS)

Salman Shahid, Syed; Bikson, Marom; Salman, Humaira; Wen, Peng; Ahfock, Tony

2014-06-01

Objectives. Computational methods are increasingly used to optimize transcranial direct current stimulation (tDCS) dose strategies and yet complexities of existing approaches limit their clinical access. Since predictive modelling indicates the relevance of subject/pathology based data and hence the need for subject specific modelling, the incremental clinical value of increasingly complex modelling methods must be balanced against the computational and clinical time and costs. For example, the incorporation of multiple tissue layers and measured diffusion tensor (DTI) based conductivity estimates increase model precision but at the cost of clinical and computational resources. Costs related to such complexities aggregate when considering individual optimization and the myriad of potential montages. Here, rather than considering if additional details change current-flow prediction, we consider when added complexities influence clinical decisions. Approach. Towards developing quantitative and qualitative metrics of value/cost associated with computational model complexity, we considered field distributions generated by two 4 × 1 high-definition montages (m1 = 4 × 1 HD montage with anode at C3 and m2 = 4 × 1 HD montage with anode at C1) and a single conventional (m3 = C3-Fp2) tDCS electrode montage. We evaluated statistical methods, including residual error (RE) and relative difference measure (RDM), to consider the clinical impact and utility of increased complexities, namely the influence of skull, muscle and brain anisotropic conductivities in a volume conductor model. Main results. Anisotropy modulated current-flow in a montage and region dependent manner. However, significant statistical changes, produced within montage by anisotropy, did not change qualitative peak and topographic comparisons across montages. Thus for the examples analysed, clinical decision on which dose to select would not be altered by the omission of anisotropic brain conductivity. Significance. Results illustrate the need to rationally balance the role of model complexity, such as anisotropy in detailed current flow analysis versus value in clinical dose design. However, when extending our analysis to include axonal polarization, the results provide presumably clinically meaningful information. Hence the importance of model complexity may be more relevant with cellular level predictions of neuromodulation.

Classifying High-noise EEG in Complex Environments for Brain-computer Interaction Technologies

DTIC Science & Technology

2012-02-01

differentiation in the brain signal that our classification approach seeks to identify despite the noise in the recorded EEG signal and the complexity of...performed two offline classifications , one using BCILab (1), the other using LibSVM (2). Distinct classifiers were trained for each individual in...order to improve individual classifier performance (3). The highest classification performance results were obtained using individual frequency bands

Simulation tools for scattering corrections in spectrally resolved x-ray computed tomography using McXtrace

NASA Astrophysics Data System (ADS)

Busi, Matteo; Olsen, Ulrik L.; Knudsen, Erik B.; Frisvad, Jeppe R.; Kehres, Jan; Dreier, Erik S.; Khalil, Mohamad; Haldrup, Kristoffer

2018-03-01

Spectral computed tomography is an emerging imaging method that involves using recently developed energy discriminating photon-counting detectors (PCDs). This technique enables measurements at isolated high-energy ranges, in which the dominating undergoing interaction between the x-ray and the sample is the incoherent scattering. The scattered radiation causes a loss of contrast in the results, and its correction has proven to be a complex problem, due to its dependence on energy, material composition, and geometry. Monte Carlo simulations can utilize a physical model to estimate the scattering contribution to the signal, at the cost of high computational time. We present a fast Monte Carlo simulation tool, based on McXtrace, to predict the energy resolved radiation being scattered and absorbed by objects of complex shapes. We validate the tool through measurements using a CdTe single PCD (Multix ME-100) and use it for scattering correction in a simulation of a spectral CT. We found the correction to account for up to 7% relative amplification in the reconstructed linear attenuation. It is a useful tool for x-ray CT to obtain a more accurate material discrimination, especially in the high-energy range, where the incoherent scattering interactions become prevailing (>50 keV).

Sky-blue emitting bridged diiridium complexes: beneficial effects of intramolecular π-π stacking.

PubMed

Congrave, Daniel G; Hsu, Yu-Ting; Batsanov, Andrei S; Beeby, Andrew; Bryce, Martin R

2018-02-06

The potential of intramolecular π-π interactions to influence the photophysical properties of diiridium complexes is an unexplored topic, and provides the motivation for the present study. A series of diarylhydrazide-bridged diiridium complexes functionalised with phenylpyridine (ppy)-based cyclometalating ligands is reported. It is shown by NMR studies in solution and single crystal X-ray analysis that intramolecular π-π interactions between the bridging and cyclometalating ligands rigidify the complexes leading to high luminescence quantum efficiencies in solution and in doped films. Fluorine substituents on the phenyl rings of the bridge promote the intramolecular π-π interactions. Notably, these non-covalent interactions are harnessed in the rational design and synthesis of the first examples of highly emissive sky-blue diiridium complexes featuring conjugated bridging ligands, for which they play a vital role in the structural and photophysical properties. Experimental results are supported by computational studies.

Community Detection in Complex Networks via Clique Conductance.

PubMed

Lu, Zhenqi; Wahlström, Johan; Nehorai, Arye

2018-04-13

Network science plays a central role in understanding and modeling complex systems in many areas including physics, sociology, biology, computer science, economics, politics, and neuroscience. One of the most important features of networks is community structure, i.e., clustering of nodes that are locally densely interconnected. Communities reveal the hierarchical organization of nodes, and detecting communities is of great importance in the study of complex systems. Most existing community-detection methods consider low-order connection patterns at the level of individual links. But high-order connection patterns, at the level of small subnetworks, are generally not considered. In this paper, we develop a novel community-detection method based on cliques, i.e., local complete subnetworks. The proposed method overcomes the deficiencies of previous similar community-detection methods by considering the mathematical properties of cliques. We apply the proposed method to computer-generated graphs and real-world network datasets. When applied to networks with known community structure, the proposed method detects the structure with high fidelity and sensitivity. When applied to networks with no a priori information regarding community structure, the proposed method yields insightful results revealing the organization of these complex networks. We also show that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.

Spectrally formulated user-defined element in conventional finite element environment for wave motion analysis in 2-D composite structures

NASA Astrophysics Data System (ADS)

Khalili, Ashkan; Jha, Ratneshwar; Samaratunga, Dulip

2016-11-01

Wave propagation analysis in 2-D composite structures is performed efficiently and accurately through the formulation of a User-Defined Element (UEL) based on the wavelet spectral finite element (WSFE) method. The WSFE method is based on the first-order shear deformation theory which yields accurate results for wave motion at high frequencies. The 2-D WSFE model is highly efficient computationally and provides a direct relationship between system input and output in the frequency domain. The UEL is formulated and implemented in Abaqus (commercial finite element software) for wave propagation analysis in 2-D composite structures with complexities. Frequency domain formulation of WSFE leads to complex valued parameters, which are decoupled into real and imaginary parts and presented to Abaqus as real values. The final solution is obtained by forming a complex value using the real number solutions given by Abaqus. Five numerical examples are presented in this article, namely undamaged plate, impacted plate, plate with ply drop, folded plate and plate with stiffener. Wave motions predicted by the developed UEL correlate very well with Abaqus simulations. The results also show that the UEL largely retains computational efficiency of the WSFE method and extends its ability to model complex features.

Mechanistic Basis for High Stereoselectivity and Broad Substrate Scope in the (salen)Co(III)-Catalyzed Hydrolytic Kinetic Resolution

PubMed Central

Ford, David D.; Nielsen, Lars P. C.; Zuend, Stephan J.; Jacobsen, Eric N.

2013-01-01

In the (salen)Co(III)-catalyzed hydrolytic kinetic resolution (HKR) of terminal epoxides, the rate- and stereoselectivity-determining epoxide ring-opening step occurs by a cooperative bimetallic mechanism with one Co(III) complex acting as a Lewis acid and another serving to deliver the hydroxide nucleophile. In this paper, we analyze the basis for the extraordinarily high stereoselectivity and broad substrate scope observed in the HKR. We demonstrate that the stereochemistry of each of the two (salen)Co(III) complexes in the rate-determining transition structure is important for productive catalysis: a measurable rate of hydrolysis occurs only if the absolute stereochemistry of each of these (salen)Co(III) complexes is the same. Experimental and computational studies provide strong evidence that stereochemical communication in the HKR is mediated by the stepped conformation of the salen ligand, and not the shape of the chiral diamine backbone of the ligand. A detailed computational analysis reveals that the epoxide binds the Lewis acidic Co(III) complex in a well-defined geometry imposed by stereoelectronic, rather than steric effects. This insight serves as the basis of a complete stereochemical and transition structure model that sheds light on the reasons for the broad substrate generality of the HKR. PMID:24041239

Mechanistic basis for high stereoselectivity and broad substrate scope in the (salen)Co(III)-catalyzed hydrolytic kinetic resolution.

PubMed

Ford, David D; Nielsen, Lars P C; Zuend, Stephan J; Musgrave, Charles B; Jacobsen, Eric N

2013-10-16

In the (salen)Co(III)-catalyzed hydrolytic kinetic resolution (HKR) of terminal epoxides, the rate- and stereoselectivity-determining epoxide ring-opening step occurs by a cooperative bimetallic mechanism with one Co(III) complex acting as a Lewis acid and another serving to deliver the hydroxide nucleophile. In this paper, we analyze the basis for the extraordinarily high stereoselectivity and broad substrate scope observed in the HKR. We demonstrate that the stereochemistry of each of the two (salen)Co(III) complexes in the rate-determining transition structure is important for productive catalysis: a measurable rate of hydrolysis occurs only if the absolute stereochemistry of each of these (salen)Co(III) complexes is the same. Experimental and computational studies provide strong evidence that stereochemical communication in the HKR is mediated by the stepped conformation of the salen ligand, and not the shape of the chiral diamine backbone of the ligand. A detailed computational analysis reveals that the epoxide binds the Lewis acidic Co(III) complex in a well-defined geometry imposed by stereoelectronic rather than steric effects. This insight serves as the basis of a complete stereochemical and transition structure model that sheds light on the reasons for the broad substrate generality of the HKR.

Experimental studies of applications of time-reversal acoustics to noncoherent underwater communications.

PubMed

Heinemann, M; Larraza, A; Smith, K B

2003-06-01

The most difficult problem in shallow underwater acoustic communications is considered to be the time-varying multipath propagation because it impacts negatively on data rates. At high data rates the intersymbol interference requires adaptive algorithms on the receiver side that lead to computationally intensive and complex signal processing. A novel technique called time-reversal acoustics (TRA) can environmentally adapt the acoustic propagation effects of a complex medium in order to focus energy at a particular target range and depth. Using TRA, the multipath structure is reduced because all the propagation paths add coherently at the intended target location. This property of time-reversal acoustics suggests a potential application in the field of noncoherent acoustic communications. This work presents results of a tank scale experiment using an algorithm for rapid transmission of binary data in a complex underwater environment with the TRA approach. A simple 15-symbol code provides an example of the simplicity and feasibility of the approach. Covert coding due to the inherent scrambling induced by the environment at points other than the intended receiver is also investigated. The experiments described suggest a high potential in data rate for the time-reversal approach in underwater acoustic communications while keeping the computational complexity low.

Cloud Computing for Complex Performance Codes.

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

Appel, Gordon John; Hadgu, Teklu; Klein, Brandon Thorin

This report describes the use of cloud computing services for running complex public domain performance assessment problems. The work consisted of two phases: Phase 1 was to demonstrate complex codes, on several differently configured servers, could run and compute trivial small scale problems in a commercial cloud infrastructure. Phase 2 focused on proving non-trivial large scale problems could be computed in the commercial cloud environment. The cloud computing effort was successfully applied using codes of interest to the geohydrology and nuclear waste disposal modeling community.

Advanced laser modeling with BLAZE multiphysics

NASA Astrophysics Data System (ADS)

Palla, Andrew D.; Carroll, David L.; Gray, Michael I.; Suzuki, Lui

2017-01-01

The BLAZE Multiphysics™ software simulation suite was specifically developed to model highly complex multiphysical systems in a computationally efficient and highly scalable manner. These capabilities are of particular use when applied to the complexities associated with high energy laser systems that combine subsonic/transonic/supersonic fluid dynamics, chemically reacting flows, laser electronics, heat transfer, optical physics, and in some cases plasma discharges. In this paper we present detailed cw and pulsed gas laser calculations using the BLAZE model with comparisons to data. Simulations of DPAL, XPAL, ElectricOIL (EOIL), and the optically pumped rare gas laser were found to be in good agreement with experimental data.

Description and operational status of the National Transonic Facility computer complex

NASA Technical Reports Server (NTRS)

Boyles, G. B., Jr.

1986-01-01

This paper describes the National Transonic Facility (NTF) computer complex and its support of tunnel operations. The capabilities of the research data acquisition and reduction are discussed along with the types of data that can be acquired and presented. Pretest, test, and posttest capabilities are also outlined along with a discussion of the computer complex to monitor the tunnel control processes and provide the tunnel operators with information needed to control the tunnel. Planned enhancements to the computer complex for support of future testing are presented.

Attitudes and gender differences of high school seniors within one-to-one computing environments in South Dakota

NASA Astrophysics Data System (ADS)

Nelson, Mathew

In today's age of exponential change and technological advancement, awareness of any gender gap in technology and computer science-related fields is crucial, but further research must be done in an effort to better understand the complex interacting factors contributing to the gender gap. This study utilized a survey to investigate specific gender differences relating to computing self-efficacy, computer usage, and environmental factors of exposure, personal interests, and parental influence that impact gender differences of high school students within a one-to-one computing environment in South Dakota. The population who completed the One-to-One High School Computing Survey for this study consisted of South Dakota high school seniors who had been involved in a one-to-one computing environment for two or more years. The data from the survey were analyzed using descriptive and inferential statistics for the determined variables. From the review of literature and data analysis several conclusions were drawn from the findings. Among them are that overall, there was very little difference in perceived computing self-efficacy and computing anxiety between male and female students within the one-to-one computing initiative. The study supported the current research that males and females utilized computers similarly, but males spent more time using their computers to play online games. Early exposure to computers, or the age at which the student was first exposed to a computer, and the number of computers present in the home (computer ownership) impacted computing self-efficacy. The results also indicated parental encouragement to work with computers also contributed positively to both male and female students' computing self-efficacy. Finally the study also found that both mothers and fathers encouraged their male children more than their female children to work with computing and pursue careers in computing science fields.

Desktop supercomputer: what can it do?

NASA Astrophysics Data System (ADS)

Bogdanov, A.; Degtyarev, A.; Korkhov, V.

2017-12-01

The paper addresses the issues of solving complex problems that require using supercomputers or multiprocessor clusters available for most researchers nowadays. Efficient distribution of high performance computing resources according to actual application needs has been a major research topic since high-performance computing (HPC) technologies became widely introduced. At the same time, comfortable and transparent access to these resources was a key user requirement. In this paper we discuss approaches to build a virtual private supercomputer available at user's desktop: a virtual computing environment tailored specifically for a target user with a particular target application. We describe and evaluate possibilities to create the virtual supercomputer based on light-weight virtualization technologies, and analyze the efficiency of our approach compared to traditional methods of HPC resource management.

Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers

NASA Technical Reports Server (NTRS)

Reuther, James; Jameson, Antony; Alonso, Juan Jose; Rimlinger, Mark J.; Saunders, David

1997-01-01

An aerodynamic shape optimization method that treats the design of complex aircraft configurations subject to high fidelity computational fluid dynamics (CFD), geometric constraints and multiple design points is described. The design process will be greatly accelerated through the use of both control theory and distributed memory computer architectures. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on a higher order CFD method. In order to facilitate the integration of these high fidelity CFD approaches into future multi-disciplinary optimization (NW) applications, new methods must be developed which are capable of simultaneously addressing complex geometries, multiple objective functions, and geometric design constraints. In our earlier studies, we coupled the adjoint based design formulations with unconstrained optimization algorithms and showed that the approach was effective for the aerodynamic design of airfoils, wings, wing-bodies, and complex aircraft configurations. In many of the results presented in these earlier works, geometric constraints were satisfied either by a projection into feasible space or by posing the design space parameterization such that it automatically satisfied constraints. Furthermore, with the exception of reference 9 where the second author initially explored the use of multipoint design in conjunction with adjoint formulations, our earlier works have focused on single point design efforts. Here we demonstrate that the same methodology may be extended to treat complete configuration designs subject to multiple design points and geometric constraints. Examples are presented for both transonic and supersonic configurations ranging from wing alone designs to complex configuration designs involving wing, fuselage, nacelles and pylons.

Spectral-Element Seismic Wave Propagation Codes for both Forward Modeling in Complex Media and Adjoint Tomography

NASA Astrophysics Data System (ADS)

Smith, J. A.; Peter, D. B.; Tromp, J.; Komatitsch, D.; Lefebvre, M. P.

2015-12-01

We present both SPECFEM3D_Cartesian and SPECFEM3D_GLOBE open-source codes, representing high-performance numerical wave solvers simulating seismic wave propagation for local-, regional-, and global-scale application. These codes are suitable for both forward propagation in complex media and tomographic imaging. Both solvers compute highly accurate seismic wave fields using the continuous Galerkin spectral-element method on unstructured meshes. Lateral variations in compressional- and shear-wave speeds, density, as well as 3D attenuation Q models, topography and fluid-solid coupling are all readily included in both codes. For global simulations, effects due to rotation, ellipticity, the oceans, 3D crustal models, and self-gravitation are additionally included. Both packages provide forward and adjoint functionality suitable for adjoint tomography on high-performance computing architectures. We highlight the most recent release of the global version which includes improved performance, simultaneous MPI runs, OpenCL and CUDA support via an automatic source-to-source transformation library (BOAST), parallel I/O readers and writers for databases using ADIOS and seismograms using the recently developed Adaptable Seismic Data Format (ASDF) with built-in provenance. This makes our spectral-element solvers current state-of-the-art, open-source community codes for high-performance seismic wave propagation on arbitrarily complex 3D models. Together with these solvers, we provide full-waveform inversion tools to image the Earth's interior at unprecedented resolution.

A Two-Stage Reconstruction Processor for Human Detection in Compressive Sensing CMOS Radar.

PubMed

Tsao, Kuei-Chi; Lee, Ling; Chu, Ta-Shun; Huang, Yuan-Hao

2018-04-05

Complementary metal-oxide-semiconductor (CMOS) radar has recently gained much research attraction because small and low-power CMOS devices are very suitable for deploying sensing nodes in a low-power wireless sensing system. This study focuses on the signal processing of a wireless CMOS impulse radar system that can detect humans and objects in the home-care internet-of-things sensing system. The challenges of low-power CMOS radar systems are the weakness of human signals and the high computational complexity of the target detection algorithm. The compressive sensing-based detection algorithm can relax the computational costs by avoiding the utilization of matched filters and reducing the analog-to-digital converter bandwidth requirement. The orthogonal matching pursuit (OMP) is one of the popular signal reconstruction algorithms for compressive sensing radar; however, the complexity is still very high because the high resolution of human respiration leads to high-dimension signal reconstruction. Thus, this paper proposes a two-stage reconstruction algorithm for compressive sensing radar. The proposed algorithm not only has lower complexity than the OMP algorithm by 75% but also achieves better positioning performance than the OMP algorithm especially in noisy environments. This study also designed and implemented the algorithm by using Vertex-7 FPGA chip (Xilinx, San Jose, CA, USA). The proposed reconstruction processor can support the 256 × 13 real-time radar image display with a throughput of 28.2 frames per second.

Computer image generation: Reconfigurability as a strategy in high fidelity space applications

NASA Technical Reports Server (NTRS)

Bartholomew, Michael J.

1989-01-01

The demand for realistic, high fidelity, computer image generation systems to support space simulation is well established. However, as the number and diversity of space applications increase, the complexity and cost of computer image generation systems also increase. One strategy used to harmonize cost with varied requirements is establishment of a reconfigurable image generation system that can be adapted rapidly and easily to meet new and changing requirements. The reconfigurability strategy through the life cycle of system conception, specification, design, implementation, operation, and support for high fidelity computer image generation systems are discussed. The discussion is limited to those issues directly associated with reconfigurability and adaptability of a specialized scene generation system in a multi-faceted space applications environment. Examples and insights gained through the recent development and installation of the Improved Multi-function Scene Generation System at Johnson Space Center, Systems Engineering Simulator are reviewed and compared with current simulator industry practices. The results are clear; the strategy of reconfigurability applied to space simulation requirements provides a viable path to supporting diverse applications with an adaptable computer image generation system.

Computational modeling in melanoma for novel drug discovery.

PubMed

Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

2016-06-01

There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.

Bayesian linkage and segregation analysis: factoring the problem.

PubMed

Matthysse, S

2000-01-01

Complex segregation analysis and linkage methods are mathematical techniques for the genetic dissection of complex diseases. They are used to delineate complex modes of familial transmission and to localize putative disease susceptibility loci to specific chromosomal locations. The computational problem of Bayesian linkage and segregation analysis is one of integration in high-dimensional spaces. In this paper, three available techniques for Bayesian linkage and segregation analysis are discussed: Markov Chain Monte Carlo (MCMC), importance sampling, and exact calculation. The contribution of each to the overall integration will be explicitly discussed.

How genome complexity can explain the difficulty of aligning reads to genomes.

PubMed

Phan, Vinhthuy; Gao, Shanshan; Tran, Quang; Vo, Nam S

2015-01-01

Although it is frequently observed that aligning short reads to genomes becomes harder if they contain complex repeat patterns, there has not been much effort to quantify the relationship between complexity of genomes and difficulty of short-read alignment. Existing measures of sequence complexity seem unsuitable for the understanding and quantification of this relationship. We investigated several measures of complexity and found that length-sensitive measures of complexity had the highest correlation to accuracy of alignment. In particular, the rate of distinct substrings of length k, where k is similar to the read length, correlated very highly to alignment performance in terms of precision and recall. We showed how to compute this measure efficiently in linear time, making it useful in practice to estimate quickly the difficulty of alignment for new genomes without having to align reads to them first. We showed how the length-sensitive measures could provide additional information for choosing aligners that would align consistently accurately on new genomes. We formally established a connection between genome complexity and the accuracy of short-read aligners. The relationship between genome complexity and alignment accuracy provides additional useful information for selecting suitable aligners for new genomes. Further, this work suggests that the complexity of genomes sometimes should be thought of in terms of specific computational problems, such as the alignment of short reads to genomes.

The change in critical technologies for computational physics

NASA Technical Reports Server (NTRS)

Watson, Val

1990-01-01

It is noted that the types of technology required for computational physics are changing as the field matures. Emphasis has shifted from computer technology to algorithm technology and, finally, to visual analysis technology as areas of critical research for this field. High-performance graphical workstations tied to a supercommunicator with high-speed communications along with the development of especially tailored visualization software has enabled analysis of highly complex fluid-dynamics simulations. Particular reference is made here to the development of visual analysis tools at NASA's Numerical Aerodynamics Simulation Facility. The next technology which this field requires is one that would eliminate visual clutter by extracting key features of simulations of physics and technology in order to create displays that clearly portray these key features. Research in the tuning of visual displays to human cognitive abilities is proposed. The immediate transfer of technology to all levels of computers, specifically the inclusion of visualization primitives in basic software developments for all work stations and PCs, is recommended.

Scout: high-performance heterogeneous computing made simple

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

Jablin, James; Mc Cormick, Patrick; Herlihy, Maurice

2011-01-26

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focusmore » on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.« less

New technologies in radiation therapy: ensuring patient safety, radiation safety and regulatory issues in radiation oncology.

PubMed

Amols, Howard I

2008-11-01

New technologies such as intensity modulated and image guided radiation therapy, computer controlled linear accelerators, record and verify systems, electronic charts, and digital imaging have revolutionized radiation therapy over the past 10-15 y. Quality assurance (QA) as historically practiced and as recommended in reports such as American Association of Physicists in Medicine Task Groups 40 and 53 needs to be updated to address the increasing complexity and computerization of radiotherapy equipment, and the increased quantity of data defining a treatment plan and treatment delivery. While new technology has reduced the probability of many types of medical events, seeing new types of errors caused by improper use of new technology, communication failures between computers, corrupted or erroneous computer data files, and "software bugs" are now being seen. The increased use of computed tomography, magnetic resonance, and positron emission tomography imaging has become routine for many types of radiotherapy treatment planning, and QA for imaging modalities is beyond the expertise of most radiotherapy physicists. Errors in radiotherapy rarely result solely from hardware failures. More commonly they are a combination of computer and human errors. The increased use of radiosurgery, hypofractionation, more complex intensity modulated treatment plans, image guided radiation therapy, and increasing financial pressures to treat more patients in less time will continue to fuel this reliance on high technology and complex computer software. Clinical practitioners and regulatory agencies are beginning to realize that QA for new technologies is a major challenge and poses dangers different in nature than what are historically familiar.

Analysis of high-order SNP barcodes in mitochondrial D-loop for chronic dialysis susceptibility.

PubMed

Yang, Cheng-Hong; Lin, Yu-Da; Chuang, Li-Yeh; Chang, Hsueh-Wei

2016-10-01

Positively identifying disease-associated single nucleotide polymorphism (SNP) markers in genome-wide studies entails the complex association analysis of a huge number of SNPs. Such large numbers of SNP barcode (SNP/genotype combinations) continue to pose serious computational challenges, especially for high-dimensional data. We propose a novel exploiting SNP barcode method based on differential evolution, termed IDE (improved differential evolution). IDE uses a "top combination strategy" to improve the ability of differential evolution to explore high-order SNP barcodes in high-dimensional data. We simulate disease data and use real chronic dialysis data to test four global optimization algorithms. In 48 simulated disease models, we show that IDE outperforms existing global optimization algorithms in terms of exploring ability and power to detect the specific SNP/genotype combinations with a maximum difference between cases and controls. In real data, we show that IDE can be used to evaluate the relative effects of each individual SNP on disease susceptibility. IDE generated significant SNP barcode with less computational complexity than the other algorithms, making IDE ideally suited for analysis of high-order SNP barcodes. Copyright © 2016 Elsevier Inc. All rights reserved.

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

NASA Technical Reports Server (NTRS)

Leser, Patrick E.; Hochhalter, Jacob D.; Newman, John A.; Leser, William P.; Warner, James E.; Wawrzynek, Paul A.; Yuan, Fuh-Gwo

2015-01-01

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

STARS: An Integrated, Multidisciplinary, Finite-Element, Structural, Fluids, Aeroelastic, and Aeroservoelastic Analysis Computer Program

NASA Technical Reports Server (NTRS)

Gupta, K. K.

1997-01-01

A multidisciplinary, finite element-based, highly graphics-oriented, linear and nonlinear analysis capability that includes such disciplines as structures, heat transfer, linear aerodynamics, computational fluid dynamics, and controls engineering has been achieved by integrating several new modules in the original STARS (STructural Analysis RoutineS) computer program. Each individual analysis module is general-purpose in nature and is effectively integrated to yield aeroelastic and aeroservoelastic solutions of complex engineering problems. Examples of advanced NASA Dryden Flight Research Center projects analyzed by the code in recent years include the X-29A, F-18 High Alpha Research Vehicle/Thrust Vectoring Control System, B-52/Pegasus Generic Hypersonics, National AeroSpace Plane (NASP), SR-71/Hypersonic Launch Vehicle, and High Speed Civil Transport (HSCT) projects. Extensive graphics capabilities exist for convenient model development and postprocessing of analysis results. The program is written in modular form in standard FORTRAN language to run on a variety of computers, such as the IBM RISC/6000, SGI, DEC, Cray, and personal computer; associated graphics codes use OpenGL and IBM/graPHIGS language for color depiction. This program is available from COSMIC, the NASA agency for distribution of computer programs.

Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking

ERIC Educational Resources Information Center

Berland, Matthew; Wilensky, Uri

2015-01-01

Both complex systems methods (such as agent-based modeling) and computational methods (such as programming) provide powerful ways for students to understand new phenomena. To understand how to effectively teach complex systems and computational content to younger students, we conducted a study in four urban middle school classrooms comparing…

A First Approach to Filament Dynamics

ERIC Educational Resources Information Center

Silva, P. E. S.; de Abreu, F. Vistulo; Simoes, R.; Dias, R. G.

2010-01-01

Modelling elastic filament dynamics is a topic of high interest due to the wide range of applications. However, it has reached a high level of complexity in the literature, making it unaccessible to a beginner. In this paper we explain the main steps involved in the computational modelling of the dynamics of an elastic filament. We first derive…

Solid rocket booster internal flow analysis by highly accurate adaptive computational methods

NASA Technical Reports Server (NTRS)

Huang, C. Y.; Tworzydlo, W.; Oden, J. T.; Bass, J. M.; Cullen, C.; Vadaketh, S.

1991-01-01

The primary objective of this project was to develop an adaptive finite element flow solver for simulating internal flows in the solid rocket booster. Described here is a unique flow simulator code for analyzing highly complex flow phenomena in the solid rocket booster. New methodologies and features incorporated into this analysis tool are described.

Phosphorescent cyclometalated complexes for efficient blue organic light-emitting diodes

PubMed Central

Suzuri, Yoshiyuki; Oshiyama, Tomohiro; Ito, Hiroto; Hiyama, Kunihisa; Kita, Hiroshi

2014-01-01

Phosphorescent emitters are extremely important for efficient organic light-emitting diodes (OLEDs), which attract significant attention. Phosphorescent emitters, which have a high phosphorescence quantum yield at room temperature, typically contain a heavy metal such as iridium and have been reported to emit blue, green and red light. In particular, the blue cyclometalated complexes with high efficiency and high stability are being developed. In this review, we focus on blue cyclometalated complexes. Recent progress of computational analysis necessary to design a cyclometalated complex is introduced. The prediction of the radiative transition is indispensable to get an emissive cyclometalated complex. We summarize four methods to control phosphorescence peak of the cyclometalated complex: (i) substituent effect on ligands, (ii) effects of ancillary ligands on heteroleptic complexes, (iii) design of the ligand skeleton, and (iv) selection of the central metal. It is considered that novel ligand skeletons would be important to achieve both a high efficiency and long lifetime in the blue OLEDs. Moreover, the combination of an emitter and a host is important as well as the emitter itself. According to the dependences on the combination of an emitter and a host, the control of exciton density of the triplet is necessary to achieve both a high efficiency and a long lifetime, because the annihilations of the triplet state cause exciton quenching and material deterioration. PMID:27877712

Phosphorescent cyclometalated complexes for efficient blue organic light-emitting diodes

NASA Astrophysics Data System (ADS)

Suzuri, Yoshiyuki; Oshiyama, Tomohiro; Ito, Hiroto; Hiyama, Kunihisa; Kita, Hiroshi

2014-10-01

Phosphorescent emitters are extremely important for efficient organic light-emitting diodes (OLEDs), which attract significant attention. Phosphorescent emitters, which have a high phosphorescence quantum yield at room temperature, typically contain a heavy metal such as iridium and have been reported to emit blue, green and red light. In particular, the blue cyclometalated complexes with high efficiency and high stability are being developed. In this review, we focus on blue cyclometalated complexes. Recent progress of computational analysis necessary to design a cyclometalated complex is introduced. The prediction of the radiative transition is indispensable to get an emissive cyclometalated complex. We summarize four methods to control phosphorescence peak of the cyclometalated complex: (i) substituent effect on ligands, (ii) effects of ancillary ligands on heteroleptic complexes, (iii) design of the ligand skeleton, and (iv) selection of the central metal. It is considered that novel ligand skeletons would be important to achieve both a high efficiency and long lifetime in the blue OLEDs. Moreover, the combination of an emitter and a host is important as well as the emitter itself. According to the dependences on the combination of an emitter and a host, the control of exciton density of the triplet is necessary to achieve both a high efficiency and a long lifetime, because the annihilations of the triplet state cause exciton quenching and material deterioration.

A resource management architecture based on complex network theory in cloud computing federation

NASA Astrophysics Data System (ADS)

Zhang, Zehua; Zhang, Xuejie

2011-10-01

Cloud Computing Federation is a main trend of Cloud Computing. Resource Management has significant effect on the design, realization, and efficiency of Cloud Computing Federation. Cloud Computing Federation has the typical characteristic of the Complex System, therefore, we propose a resource management architecture based on complex network theory for Cloud Computing Federation (abbreviated as RMABC) in this paper, with the detailed design of the resource discovery and resource announcement mechanisms. Compare with the existing resource management mechanisms in distributed computing systems, a Task Manager in RMABC can use the historical information and current state data get from other Task Managers for the evolution of the complex network which is composed of Task Managers, thus has the advantages in resource discovery speed, fault tolerance and adaptive ability. The result of the model experiment confirmed the advantage of RMABC in resource discovery performance.

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

PubMed Central

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L.; Rufo, Elena

2013-01-01

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation. PMID:23609804

Computational burden resulting from image recognition of high resolution radar sensors.

PubMed

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L; Rufo, Elena

2013-04-22

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.

URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.

Computer aided reliability, availability, and safety modeling for fault-tolerant computer systems with commentary on the HARP program

NASA Technical Reports Server (NTRS)

Shooman, Martin L.

1991-01-01

Many of the most challenging reliability problems of our present decade involve complex distributed systems such as interconnected telephone switching computers, air traffic control centers, aircraft and space vehicles, and local area and wide area computer networks. In addition to the challenge of complexity, modern fault-tolerant computer systems require very high levels of reliability, e.g., avionic computers with MTTF goals of one billion hours. Most analysts find that it is too difficult to model such complex systems without computer aided design programs. In response to this need, NASA has developed a suite of computer aided reliability modeling programs beginning with CARE 3 and including a group of new programs such as: HARP, HARP-PC, Reliability Analysts Workbench (Combination of model solvers SURE, STEM, PAWS, and common front-end model ASSIST), and the Fault Tree Compiler. The HARP program is studied and how well the user can model systems using this program is investigated. One of the important objectives will be to study how user friendly this program is, e.g., how easy it is to model the system, provide the input information, and interpret the results. The experiences of the author and his graduate students who used HARP in two graduate courses are described. Some brief comparisons were made with the ARIES program which the students also used. Theoretical studies of the modeling techniques used in HARP are also included. Of course no answer can be any more accurate than the fidelity of the model, thus an Appendix is included which discusses modeling accuracy. A broad viewpoint is taken and all problems which occurred in the use of HARP are discussed. Such problems include: computer system problems, installation manual problems, user manual problems, program inconsistencies, program limitations, confusing notation, long run times, accuracy problems, etc.

Discontinuous Galerkin Methods and High-Speed Turbulent Flows

NASA Astrophysics Data System (ADS)

Atak, Muhammed; Larsson, Johan; Munz, Claus-Dieter

2014-11-01

Discontinuous Galerkin methods gain increasing importance within the CFD community as they combine arbitrary high order of accuracy in complex geometries with parallel efficiency. Particularly the discontinuous Galerkin spectral element method (DGSEM) is a promising candidate for both the direct numerical simulation (DNS) and large eddy simulation (LES) of turbulent flows due to its excellent scaling attributes. In this talk, we present a DNS of a compressible turbulent boundary layer along a flat plate at a free-stream Mach number of M = 2.67 and assess the computational efficiency of the DGSEM at performing high-fidelity simulations of both transitional and turbulent boundary layers. We compare the accuracy of the results as well as the computational performance to results using a high order finite difference method.

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

PubMed

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

MaRIE theory, modeling and computation roadmap executive summary

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

Lookman, Turab

The confluence of MaRIE (Matter-Radiation Interactions in Extreme) and extreme (exascale) computing timelines offers a unique opportunity in co-designing the elements of materials discovery, with theory and high performance computing, itself co-designed by constrained optimization of hardware and software, and experiments. MaRIE's theory, modeling, and computation (TMC) roadmap efforts have paralleled 'MaRIE First Experiments' science activities in the areas of materials dynamics, irradiated materials and complex functional materials in extreme conditions. The documents that follow this executive summary describe in detail for each of these areas the current state of the art, the gaps that exist and the road mapmore » to MaRIE and beyond. Here we integrate the various elements to articulate an overarching theme related to the role and consequences of heterogeneities which manifest as competing states in a complex energy landscape. MaRIE experiments will locate, measure and follow the dynamical evolution of these heterogeneities. Our TMC vision spans the various pillar science and highlights the key theoretical and experimental challenges. We also present a theory, modeling and computation roadmap of the path to and beyond MaRIE in each of the science areas.« less

Tackling some of the most intricate geophysical challenges via high-performance computing

NASA Astrophysics Data System (ADS)

Khosronejad, A.

2016-12-01

Recently, world has been witnessing significant enhancements in computing power of supercomputers. Computer clusters in conjunction with the advanced mathematical algorithms has set the stage for developing and applying powerful numerical tools to tackle some of the most intricate geophysical challenges that today`s engineers face. One such challenge is to understand how turbulent flows, in real-world settings, interact with (a) rigid and/or mobile complex bed bathymetry of waterways and sea-beds in the coastal areas; (b) objects with complex geometry that are fully or partially immersed; and (c) free-surface of waterways and water surface waves in the coastal area. This understanding is especially important because the turbulent flows in real-world environments are often bounded by geometrically complex boundaries, which dynamically deform and give rise to multi-scale and multi-physics transport phenomena, and characterized by multi-lateral interactions among various phases (e.g. air/water/sediment phases). Herein, I present some of the multi-scale and multi-physics geophysical fluid mechanics processes that I have attempted to study using an in-house high-performance computational model, the so-called VFS-Geophysics. More specifically, I will present the simulation results of turbulence/sediment/solute/turbine interactions in real-world settings. Parts of the simulations I present are performed to gain scientific insights into the processes such as sand wave formation (A. Khosronejad, and F. Sotiropoulos, (2014), Numerical simulation of sand waves in a turbulent open channel flow, Journal of Fluid Mechanics, 753:150-216), while others are carried out to predict the effects of climate change and large flood events on societal infrastructures ( A. Khosronejad, et al., (2016), Large eddy simulation of turbulence and solute transport in a forested headwater stream, Journal of Geophysical Research:, doi: 10.1002/2014JF003423).

Combustion and Magnetohydrodynamic Processes in Advanced Pulse Detonation Rocket Engines

DTIC Science & Technology

2012-10-01

use of high-order numerical methods can also be a powerful tool in the analysis of such complex flows, but we need to understand the interaction of...computational physics, 43(2):357372, 1981. [47] B. Einfeldt. On godunov-type methods for gas dynamics . SIAM Journal on Numerical Analysis , pages 294...dimensional effects with complex reaction kinetics, the simple one-dimensional detonation structure provides a rich spectrum of dynamical features which are

Efficient Symbolic Task Planning for Multiple Mobile Robots

DTIC Science & Technology

2016-12-13

Efficient Symbolic Task Planning for Multiple Mobile Robots Yuqian Jiang December 13, 2016 Abstract Symbolic task planning enables a robot to make...high-level deci- sions toward a complex goal by computing a sequence of actions with minimum expected costs. This thesis builds on a single- robot ...time complexity of optimal planning for multiple mobile robots . In this thesis we first investigate the performance of the state-of-the-art solvers of

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Development and application of computational aerothermodynamics flowfield computer codes

NASA Technical Reports Server (NTRS)

Venkatapathy, Ethiraj

1994-01-01

Research was performed in the area of computational modeling and application of hypersonic, high-enthalpy, thermo-chemical nonequilibrium flow (Aerothermodynamics) problems. A number of computational fluid dynamic (CFD) codes were developed and applied to simulate high altitude rocket-plume, the Aeroassist Flight Experiment (AFE), hypersonic base flow for planetary probes, the single expansion ramp model (SERN) connected with the National Aerospace Plane, hypersonic drag devices, hypersonic ramp flows, ballistic range models, shock tunnel facility nozzles, transient and steady flows in the shock tunnel facility, arc-jet flows, thermochemical nonequilibrium flows around simple and complex bodies, axisymmetric ionized flows of interest to re-entry, unsteady shock induced combustion phenomena, high enthalpy pulsed facility simulations, and unsteady shock boundary layer interactions in shock tunnels. Computational modeling involved developing appropriate numerical schemes for the flows on interest and developing, applying, and validating appropriate thermochemical processes. As part of improving the accuracy of the numerical predictions, adaptive grid algorithms were explored, and a user-friendly, self-adaptive code (SAGE) was developed. Aerothermodynamic flows of interest included energy transfer due to strong radiation, and a significant level of effort was spent in developing computational codes for calculating radiation and radiation modeling. In addition, computational tools were developed and applied to predict the radiative heat flux and spectra that reach the model surface.

Data Provenance Hybridization Supporting Extreme-Scale Scientific WorkflowApplications

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

Elsethagen, Todd O.; Stephan, Eric G.; Raju, Bibi

As high performance computing (HPC) infrastructures continue to grow in capability and complexity, so do the applications that they serve. HPC and distributed-area computing (DAC) (e.g. grid and cloud) users are looking increasingly toward workflow solutions to orchestrate their complex application coupling, pre- and post-processing needs To gain insight and a more quantitative understanding of a workflow’s performance our method includes not only the capture of traditional provenance information, but also the capture and integration of system environment metrics helping to give context and explanation for a workflow’s execution. In this paper, we describe IPPD’s provenance management solution (ProvEn) andmore » its hybrid data store combining both of these data provenance perspectives.« less

A decision-theoretic approach to the display of information for time-critical decisions: The Vista project

NASA Technical Reports Server (NTRS)

Horvitz, Eric; Ruokangas, Corinne; Srinivas, Sampath; Barry, Matthew

1993-01-01

We describe a collaborative research and development effort between the Palo Alto Laboratory of the Rockwell Science Center, Rockwell Space Operations Company, and the Propulsion Systems Section of NASA JSC to design computational tools that can manage the complexity of information displayed to human operators in high-stakes, time-critical decision contexts. We shall review an application from NASA Mission Control and describe how we integrated a probabilistic diagnostic model and a time-dependent utility model, with techniques for managing the complexity of computer displays. Then, we shall describe the behavior of VPROP, a system constructed to demonstrate promising display-management techniques. Finally, we shall describe our current research directions on the Vista 2 follow-on project.

A consensus algorithm for approximate string matching and its application to QRS complex detection

NASA Astrophysics Data System (ADS)

Alba, Alfonso; Mendez, Martin O.; Rubio-Rincon, Miguel E.; Arce-Santana, Edgar R.

2016-08-01

In this paper, a novel algorithm for approximate string matching (ASM) is proposed. The novelty resides in the fact that, unlike most other methods, the proposed algorithm is not based on the Hamming or Levenshtein distances, but instead computes a score for each symbol in the search text based on a consensus measure. Those symbols with sufficiently high scores will likely correspond to approximate instances of the pattern string. To demonstrate the usefulness of the proposed method, it has been applied to the detection of QRS complexes in electrocardiographic signals with competitive results when compared against the classic Pan-Tompkins (PT) algorithm. The proposed method outperformed PT in 72% of the test cases, with no extra computational cost.

In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report

DOE PAGES

Bethel, EW; Bauer, A; Abbasi, H; ...

2016-06-10

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i.e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed /visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU’s and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitionersmore » using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.« less

An immersed boundary method for modeling a dirty geometry data

NASA Astrophysics Data System (ADS)

Onishi, Keiji; Tsubokura, Makoto

2017-11-01

We present a robust, fast, and low preparation cost immersed boundary method (IBM) for simulating an incompressible high Re flow around highly complex geometries. The method is achieved by the dispersion of the momentum by the axial linear projection and the approximate domain assumption satisfying the mass conservation around the wall including cells. This methodology has been verified against an analytical theory and wind tunnel experiment data. Next, we simulate the problem of flow around a rotating object and demonstrate the ability of this methodology to the moving geometry problem. This methodology provides the possibility as a method for obtaining a quick solution at a next large scale supercomputer. This research was supported by MEXT as ``Priority Issue on Post-K computer'' (Development of innovative design and production processes) and used computational resources of the K computer provided by the RIKEN Advanced Institute for Computational Science.

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

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

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

2005-01-01

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

High Performance GPU-Based Fourier Volume Rendering.

PubMed

Abdellah, Marwan; Eldeib, Ayman; Sharawi, Amr

2015-01-01

Fourier volume rendering (FVR) is a significant visualization technique that has been used widely in digital radiography. As a result of its (N (2)log⁡N) time complexity, it provides a faster alternative to spatial domain volume rendering algorithms that are (N (3)) computationally complex. Relying on the Fourier projection-slice theorem, this technique operates on the spectral representation of a 3D volume instead of processing its spatial representation to generate attenuation-only projections that look like X-ray radiographs. Due to the rapid evolution of its underlying architecture, the graphics processing unit (GPU) became an attractive competent platform that can deliver giant computational raw power compared to the central processing unit (CPU) on a per-dollar-basis. The introduction of the compute unified device architecture (CUDA) technology enables embarrassingly-parallel algorithms to run efficiently on CUDA-capable GPU architectures. In this work, a high performance GPU-accelerated implementation of the FVR pipeline on CUDA-enabled GPUs is presented. This proposed implementation can achieve a speed-up of 117x compared to a single-threaded hybrid implementation that uses the CPU and GPU together by taking advantage of executing the rendering pipeline entirely on recent GPU architectures.

Transonic Navier-Stokes wing solutions using a zonal approach. Part 2: High angle-of-attack simulation

NASA Technical Reports Server (NTRS)

Chaderjian, N. M.

1986-01-01

A computer code is under development whereby the thin-layer Reynolds-averaged Navier-Stokes equations are to be applied to realistic fighter-aircraft configurations. This transonic Navier-Stokes code (TNS) utilizes a zonal approach in order to treat complex geometries and satisfy in-core computer memory constraints. The zonal approach has been applied to isolated wing geometries in order to facilitate code development. Part 1 of this paper addresses the TNS finite-difference algorithm, zonal methodology, and code validation with experimental data. Part 2 of this paper addresses some numerical issues such as code robustness, efficiency, and accuracy at high angles of attack. Special free-stream-preserving metrics proved an effective way to treat H-mesh singularities over a large range of severe flow conditions, including strong leading-edge flow gradients, massive shock-induced separation, and stall. Furthermore, lift and drag coefficients have been computed for a wing up through CLmax. Numerical oil flow patterns and particle trajectories are presented both for subcritical and transonic flow. These flow simulations are rich with complex separated flow physics and demonstrate the efficiency and robustness of the zonal approach.

A micro-hydrology computation ordering algorithm

NASA Astrophysics Data System (ADS)

Croley, Thomas E.

1980-11-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented "node" definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing microhydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies.

A CU-Level Rate and Distortion Estimation Scheme for RDO of Hardware-Friendly HEVC Encoders Using Low-Complexity Integer DCTs.

PubMed

Lee, Bumshik; Kim, Munchurl

2016-08-01

In this paper, a low complexity coding unit (CU)-level rate and distortion estimation scheme is proposed for High Efficiency Video Coding (HEVC) hardware-friendly implementation where a Walsh-Hadamard transform (WHT)-based low-complexity integer discrete cosine transform (DCT) is employed for distortion estimation. Since HEVC adopts quadtree structures of coding blocks with hierarchical coding depths, it becomes more difficult to estimate accurate rate and distortion values without actually performing transform, quantization, inverse transform, de-quantization, and entropy coding. Furthermore, DCT for rate-distortion optimization (RDO) is computationally high, because it requires a number of multiplication and addition operations for various transform block sizes of 4-, 8-, 16-, and 32-orders and requires recursive computations to decide the optimal depths of CU or transform unit. Therefore, full RDO-based encoding is highly complex, especially for low-power implementation of HEVC encoders. In this paper, a rate and distortion estimation scheme is proposed in CU levels based on a low-complexity integer DCT that can be computed in terms of WHT whose coefficients are produced in prediction stages. For rate and distortion estimation in CU levels, two orthogonal matrices of 4×4 and 8×8 , which are applied to WHT that are newly designed in a butterfly structure only with addition and shift operations. By applying the integer DCT based on the WHT and newly designed transforms in each CU block, the texture rate can precisely be estimated after quantization using the number of non-zero quantized coefficients and the distortion can also be precisely estimated in transform domain without de-quantization and inverse transform required. In addition, a non-texture rate estimation is proposed by using a pseudoentropy code to obtain accurate total rate estimates. The proposed rate and the distortion estimation scheme can effectively be used for HW-friendly implementation of HEVC encoders with 9.8% loss over HEVC full RDO, which much less than 20.3% and 30.2% loss of a conventional approach and Hadamard-only scheme, respectively.

CCOMP: An efficient algorithm for complex roots computation of determinantal equations

NASA Astrophysics Data System (ADS)

Zouros, Grigorios P.

2018-01-01

In this paper a free Python algorithm, entitled CCOMP (Complex roots COMPutation), is developed for the efficient computation of complex roots of determinantal equations inside a prescribed complex domain. The key to the method presented is the efficient determination of the candidate points inside the domain which, in their close neighborhood, a complex root may lie. Once these points are detected, the algorithm proceeds to a two-dimensional minimization problem with respect to the minimum modulus eigenvalue of the system matrix. In the core of CCOMP exist three sub-algorithms whose tasks are the efficient estimation of the minimum modulus eigenvalues of the system matrix inside the prescribed domain, the efficient computation of candidate points which guarantee the existence of minima, and finally, the computation of minima via bound constrained minimization algorithms. Theoretical results and heuristics support the development and the performance of the algorithm, which is discussed in detail. CCOMP supports general complex matrices, and its efficiency, applicability and validity is demonstrated to a variety of microwave applications.

Computational analysis of forebody tangential slot blowing

NASA Technical Reports Server (NTRS)

Gee, Ken; Agosta-Greenman, Roxana M.; Rizk, Yehia M.; Schiff, Lewis B.; Cummings, Russell M.

1994-01-01

An overview of the computational effort to analyze forebody tangential slot blowing is presented. Tangential slot blowing generates side force and yawing moment which may be used to control an aircraft flying at high-angle-of-attack. Two different geometries are used in the analysis: (1) The High Alpha Research Vehicle; and (2) a generic chined forebody. Computations using the isolated F/A-18 forebody are obtained at full-scale wind tunnel test conditions for direct comparison with available experimental data. The effects of over- and under-blowing on force and moment production are analyzed. Time-accurate solutions using the isolated forebody are obtained to study the force onset timelag of tangential slot blowing. Computations using the generic chined forebody are obtained at experimental wind tunnel conditions, and the results compared with available experimental data. This computational analysis compliments the experimental results and provides a detailed understanding of the effects of tangential slot blowing on the flow field about simple and complex geometries.

Sensitivity Analysis of Multidisciplinary Rotorcraft Simulations

NASA Technical Reports Server (NTRS)

Wang, Li; Diskin, Boris; Biedron, Robert T.; Nielsen, Eric J.; Bauchau, Olivier A.

2017-01-01

A multidisciplinary sensitivity analysis of rotorcraft simulations involving tightly coupled high-fidelity computational fluid dynamics and comprehensive analysis solvers is presented and evaluated. An unstructured sensitivity-enabled Navier-Stokes solver, FUN3D, and a nonlinear flexible multibody dynamics solver, DYMORE, are coupled to predict the aerodynamic loads and structural responses of helicopter rotor blades. A discretely-consistent adjoint-based sensitivity analysis available in FUN3D provides sensitivities arising from unsteady turbulent flows and unstructured dynamic overset meshes, while a complex-variable approach is used to compute DYMORE structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Numerical results verify accuracy of the FUN3D/DYMORE system by conducting simulations for a benchmark rotorcraft test model and comparing solutions with established analyses and experimental data. Complex-variable implementation of sensitivity analysis of DYMORE and the coupled FUN3D/DYMORE system is verified by comparing with real-valued analysis and sensitivities. Correctness of adjoint formulations for FUN3D/DYMORE interfaces is verified by comparing adjoint-based and complex-variable sensitivities. Finally, sensitivities of the lift and drag functions obtained by complex-variable FUN3D/DYMORE simulations are compared with sensitivities computed by the multidisciplinary sensitivity analysis, which couples adjoint-based flow and grid sensitivities of FUN3D and FUN3D/DYMORE interfaces with complex-variable sensitivities of DYMORE structural responses.

DockTrina: docking triangular protein trimers.

PubMed

Popov, Petr; Ritchie, David W; Grudinin, Sergei

2014-01-01

In spite of the abundance of oligomeric proteins within a cell, the structural characterization of protein-protein interactions is still a challenging task. In particular, many of these interactions involve heteromeric complexes, which are relatively difficult to determine experimentally. Hence there is growing interest in using computational techniques to model such complexes. However, assembling large heteromeric complexes computationally is a highly combinatorial problem. Nonetheless the problem can be simplified greatly by considering interactions between protein trimers. After dimers and monomers, triangular trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) are the most frequently observed quaternary structural motifs according to the three-dimensional (3D) complex database. This article presents DockTrina, a novel protein docking method for modeling the 3D structures of nonsymmetrical triangular trimers. The method takes as input pair-wise contact predictions from a rigid body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation test. Finally, it ranks the predictions using a scoring function which combines triples of pair-wise contact terms and a geometric clash penalty term. The overall approach takes less than 2 min per complex on a modern desktop computer. The method is tested and validated using a benchmark set of 220 bound and seven unbound protein trimer structures. DockTrina will be made available at http://nano-d.inrialpes.fr/software/docktrina. Copyright © 2013 Wiley Periodicals, Inc.

Extension of optical lithography by mask-litho integration with computational lithography

NASA Astrophysics Data System (ADS)

Takigawa, T.; Gronlund, K.; Wiley, J.

2010-05-01

Wafer lithography process windows can be enlarged by using source mask co-optimization (SMO). Recently, SMO including freeform wafer scanner illumination sources has been developed. Freeform sources are generated by a programmable illumination system using a micro-mirror array or by custom Diffractive Optical Elements (DOE). The combination of freeform sources and complex masks generated by SMO show increased wafer lithography process window and reduced MEEF. Full-chip mask optimization using source optimized by SMO can generate complex masks with small variable feature size sub-resolution assist features (SRAF). These complex masks create challenges for accurate mask pattern writing and low false-defect inspection. The accuracy of the small variable-sized mask SRAF patterns is degraded by short range mask process proximity effects. To address the accuracy needed for these complex masks, we developed a highly accurate mask process correction (MPC) capability. It is also difficult to achieve low false-defect inspections of complex masks with conventional mask defect inspection systems. A printability check system, Mask Lithography Manufacturability Check (M-LMC), is developed and integrated with 199-nm high NA inspection system, NPI. M-LMC successfully identifies printable defects from all of the masses of raw defect images collected during the inspection of a complex mask. Long range mask CD uniformity errors are compensated by scanner dose control. A mask CD uniformity error map obtained by mask metrology system is used as input data to the scanner. Using this method, wafer CD uniformity is improved. As reviewed above, mask-litho integration technology with computational lithography is becoming increasingly important.

A Systematic Approach for Obtaining Performance on Matrix-Like Operations

NASA Astrophysics Data System (ADS)

Veras, Richard Michael

Scientific Computation provides a critical role in the scientific process because it allows us ask complex queries and test predictions that would otherwise be unfeasible to perform experimentally. Because of its power, Scientific Computing has helped drive advances in many fields ranging from Engineering and Physics to Biology and Sociology to Economics and Drug Development and even to Machine Learning and Artificial Intelligence. Common among these domains is the desire for timely computational results, thus a considerable amount of human expert effort is spent towards obtaining performance for these scientific codes. However, this is no easy task because each of these domains present their own unique set of challenges to software developers, such as domain specific operations, structurally complex data and ever-growing datasets. Compounding these problems are the myriads of constantly changing, complex and unique hardware platforms that an expert must target. Unfortunately, an expert is typically forced to reproduce their effort across multiple problem domains and hardware platforms. In this thesis, we demonstrate the automatic generation of expert level high-performance scientific codes for Dense Linear Algebra (DLA), Structured Mesh (Stencil), Sparse Linear Algebra and Graph Analytic. In particular, this thesis seeks to address the issue of obtaining performance on many complex platforms for a certain class of matrix-like operations that span across many scientific, engineering and social fields. We do this by automating a method used for obtaining high performance in DLA and extending it to structured, sparse and scale-free domains. We argue that it is through the use of the underlying structure found in the data from these domains that enables this process. Thus, obtaining performance for most operations does not occur in isolation of the data being operated on, but instead depends significantly on the structure of the data.

Automated Design of Complex Dynamic Systems

PubMed Central

Hermans, Michiel; Schrauwen, Benjamin; Bienstman, Peter; Dambre, Joni

2014-01-01

Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems. PMID:24497969

Bilayer avalanche spin-diode logic

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

Friedman, Joseph S., E-mail: joseph.friedman@u-psud.fr; Querlioz, Damien; Fadel, Eric R.

2015-11-15

A novel spintronic computing paradigm is proposed and analyzed in which InSb p-n bilayer avalanche spin-diodes are cascaded to efficiently perform complex logic operations. This spin-diode logic family uses control wires to generate magnetic fields that modulate the resistance of the spin-diodes, and currents through these devices control the resistance of cascaded devices. Electromagnetic simulations are performed to demonstrate the cascading mechanism, and guidelines are provided for the development of this innovative computing technology. This cascading scheme permits compact logic circuits with switching speeds determined by electromagnetic wave propagation rather than electron motion, enabling high-performance spintronic computing.

Parameters that affect parallel processing for computational electromagnetic simulation codes on high performance computing clusters

NASA Astrophysics Data System (ADS)

Moon, Hongsik

What is the impact of multicore and associated advanced technologies on computational software for science? Most researchers and students have multicore laptops or desktops for their research and they need computing power to run computational software packages. Computing power was initially derived from Central Processing Unit (CPU) clock speed. That changed when increases in clock speed became constrained by power requirements. Chip manufacturers turned to multicore CPU architectures and associated technological advancements to create the CPUs for the future. Most software applications benefited by the increased computing power the same way that increases in clock speed helped applications run faster. However, for Computational ElectroMagnetics (CEM) software developers, this change was not an obvious benefit - it appeared to be a detriment. Developers were challenged to find a way to correctly utilize the advancements in hardware so that their codes could benefit. The solution was parallelization and this dissertation details the investigation to address these challenges. Prior to multicore CPUs, advanced computer technologies were compared with the performance using benchmark software and the metric was FLoting-point Operations Per Seconds (FLOPS) which indicates system performance for scientific applications that make heavy use of floating-point calculations. Is FLOPS an effective metric for parallelized CEM simulation tools on new multicore system? Parallel CEM software needs to be benchmarked not only by FLOPS but also by the performance of other parameters related to type and utilization of the hardware, such as CPU, Random Access Memory (RAM), hard disk, network, etc. The codes need to be optimized for more than just FLOPs and new parameters must be included in benchmarking. In this dissertation, the parallel CEM software named High Order Basis Based Integral Equation Solver (HOBBIES) is introduced. This code was developed to address the needs of the changing computer hardware platforms in order to provide fast, accurate and efficient solutions to large, complex electromagnetic problems. The research in this dissertation proves that the performance of parallel code is intimately related to the configuration of the computer hardware and can be maximized for different hardware platforms. To benchmark and optimize the performance of parallel CEM software, a variety of large, complex projects are created and executed on a variety of computer platforms. The computer platforms used in this research are detailed in this dissertation. The projects run as benchmarks are also described in detail and results are presented. The parameters that affect parallel CEM software on High Performance Computing Clusters (HPCC) are investigated. This research demonstrates methods to maximize the performance of parallel CEM software code.

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

NASA Technical Reports Server (NTRS)

Aguilo, Miguel A.; Warner, James E.

2017-01-01

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

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

PubMed Central

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

2007-01-01

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

Poly-Omic Prediction of Complex Traits: OmicKriging

PubMed Central

Wheeler, Heather E.; Aquino-Michaels, Keston; Gamazon, Eric R.; Trubetskoy, Vassily V.; Dolan, M. Eileen; Huang, R. Stephanie; Cox, Nancy J.; Im, Hae Kyung

2014-01-01

High-confidence prediction of complex traits such as disease risk or drug response is an ultimate goal of personalized medicine. Although genome-wide association studies have discovered thousands of well-replicated polymorphisms associated with a broad spectrum of complex traits, the combined predictive power of these associations for any given trait is generally too low to be of clinical relevance. We propose a novel systems approach to complex trait prediction, which leverages and integrates similarity in genetic, transcriptomic, or other omics-level data. We translate the omic similarity into phenotypic similarity using a method called Kriging, commonly used in geostatistics and machine learning. Our method called OmicKriging emphasizes the use of a wide variety of systems-level data, such as those increasingly made available by comprehensive surveys of the genome, transcriptome, and epigenome, for complex trait prediction. Furthermore, our OmicKriging framework allows easy integration of prior information on the function of subsets of omics-level data from heterogeneous sources without the sometimes heavy computational burden of Bayesian approaches. Using seven disease datasets from the Wellcome Trust Case Control Consortium (WTCCC), we show that OmicKriging allows simple integration of sparse and highly polygenic components yielding comparable performance at a fraction of the computing time of a recently published Bayesian sparse linear mixed model method. Using a cellular growth phenotype, we show that integrating mRNA and microRNA expression data substantially increases performance over either dataset alone. Using clinical statin response, we show improved prediction over existing methods. PMID:24799323

Phased Array Imaging of Complex-Geometry Composite Components.

PubMed

Brath, Alex J; Simonetti, Francesco

2017-10-01

Progress in computational fluid dynamics and the availability of new composite materials are driving major advances in the design of aerospace engine components which now have highly complex geometries optimized to maximize system performance. However, shape complexity poses significant challenges to traditional nondestructive evaluation methods whose sensitivity and selectivity rapidly decrease as surface curvature increases. In addition, new aerospace materials typically exhibit an intricate microstructure that further complicates the inspection. In this context, an attractive solution is offered by combining ultrasonic phased array (PA) technology with immersion testing. Here, the water column formed between the complex surface of the component and the flat face of a linear or matrix array probe ensures ideal acoustic coupling between the array and the component as the probe is continuously scanned to form a volumetric rendering of the part. While the immersion configuration is desirable for practical testing, the interpretation of the measured ultrasonic signals for image formation is complicated by reflection and refraction effects that occur at the water-component interface. To account for refraction, the geometry of the interface must first be reconstructed from the reflected signals and subsequently used to compute suitable delay laws to focus inside the component. These calculations are based on ray theory and can be computationally intensive. Moreover, strong reflections from the interface can lead to a thick dead zone beneath the surface of the component which limits sensitivity to shallow subsurface defects. This paper presents a general approach that combines advanced computing for rapid ray tracing in anisotropic media with a 256-channel parallel array architecture. The full-volume inspection of complex-shape components is enabled through the combination of both reflected and transmitted signals through the part using a pair of arrays held in a yoke configuration. Experimental results are provided for specimens of increasing complexity relevant to aerospace applications such as fan blades. It is shown that PA technology can provide a robust solution to detect a variety of defects including porosity and waviness in composite parts.

Computer-based learning in neuroanatomy: A longitudinal study of learning, transfer, and retention

NASA Astrophysics Data System (ADS)

Chariker, Julia H.

A longitudinal experiment was conducted to explore computer-based learning of neuroanatomy. Using a realistic 3D graphical model of neuroanatomy, and sections derived from the model, exploratory graphical tools were integrated into interactive computer programs so as to allow adaptive exploration. 72 participants learned either sectional anatomy alone or learned whole anatomy followed by sectional anatomy. Sectional anatomy was explored either in perceptually continuous animation or discretely, as in the use of an anatomical atlas. Learning was measured longitudinally to a high performance criterion. After learning, transfer to biomedical images and long-term retention was tested. Learning whole anatomy prior to learning sectional anatomy led to a more efficient learning experience. Learners demonstrated high levels of transfer from whole anatomy to sectional anatomy and from sectional anatomy to complex biomedical images. All learning groups demonstrated high levels of retention at 2--3 weeks.

Scalable software-defined optical networking with high-performance routing and wavelength assignment algorithms.

PubMed

Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin

2015-10-19

The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study.

Computational challenges, tools and resources for analyzing co- and post-transcriptional events in high throughput

PubMed Central

Bahrami-Samani, Emad; Vo, Dat T.; de Araujo, Patricia Rosa; Vogel, Christine; Smith, Andrew D.; Penalva, Luiz O. F.; Uren, Philip J.

2014-01-01

Co- and post-transcriptional regulation of gene expression is complex and multi-faceted, spanning the complete RNA lifecycle from genesis to decay. High-throughput profiling of the constituent events and processes is achieved through a range of technologies that continue to expand and evolve. Fully leveraging the resulting data is non-trivial, and requires the use of computational methods and tools carefully crafted for specific data sources and often intended to probe particular biological processes. Drawing upon databases of information pre-compiled by other researchers can further elevate analyses. Within this review, we describe the major co- and post-transcriptional events in the RNA lifecycle that are amenable to high-throughput profiling. We place specific emphasis on the analysis of the resulting data, in particular the computational tools and resources available, as well as looking towards future challenges that remain to be addressed. PMID:25515586

Nektar++: An open-source spectral/ hp element framework

NASA Astrophysics Data System (ADS)

Cantwell, C. D.; Moxey, D.; Comerford, A.; Bolis, A.; Rocco, G.; Mengaldo, G.; De Grazia, D.; Yakovlev, S.; Lombard, J.-E.; Ekelschot, D.; Jordi, B.; Xu, H.; Mohamied, Y.; Eskilsson, C.; Nelson, B.; Vos, P.; Biotto, C.; Kirby, R. M.; Sherwin, S. J.

2015-07-01

Nektar++ is an open-source software framework designed to support the development of high-performance scalable solvers for partial differential equations using the spectral/ hp element method. High-order methods are gaining prominence in several engineering and biomedical applications due to their improved accuracy over low-order techniques at reduced computational cost for a given number of degrees of freedom. However, their proliferation is often limited by their complexity, which makes these methods challenging to implement and use. Nektar++ is an initiative to overcome this limitation by encapsulating the mathematical complexities of the underlying method within an efficient C++ framework, making the techniques more accessible to the broader scientific and industrial communities. The software supports a variety of discretisation techniques and implementation strategies, supporting methods research as well as application-focused computation, and the multi-layered structure of the framework allows the user to embrace as much or as little of the complexity as they need. The libraries capture the mathematical constructs of spectral/ hp element methods, while the associated collection of pre-written PDE solvers provides out-of-the-box application-level functionality and a template for users who wish to develop solutions for addressing questions in their own scientific domains.

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

PubMed

Guo, Xuan; Meng, Yu; Yu, Ning; Pan, Yi

2014-04-10

Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS.

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

PubMed Central

2014-01-01

Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS. PMID:24717145

Pen-based computers: Computers without keys

NASA Technical Reports Server (NTRS)

Conklin, Cheryl L.

1994-01-01

The National Space Transportation System (NSTS) is comprised of many diverse and highly complex systems incorporating the latest technologies. Data collection associated with ground processing of the various Space Shuttle system elements is extremely challenging due to the many separate processing locations where data is generated. This presents a significant problem when the timely collection, transfer, collation, and storage of data is required. This paper describes how new technology, referred to as Pen-Based computers, is being used to transform the data collection process at Kennedy Space Center (KSC). Pen-Based computers have streamlined procedures, increased data accuracy, and now provide more complete information than previous methods. The end results is the elimination of Shuttle processing delays associated with data deficiencies.

Information Power Grid Posters

NASA Technical Reports Server (NTRS)

Vaziri, Arsi

2003-01-01

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

A software methodology for compiling quantum programs

NASA Astrophysics Data System (ADS)

Häner, Thomas; Steiger, Damian S.; Svore, Krysta; Troyer, Matthias

2018-04-01

Quantum computers promise to transform our notions of computation by offering a completely new paradigm. To achieve scalable quantum computation, optimizing compilers and a corresponding software design flow will be essential. We present a software architecture for compiling quantum programs from a high-level language program to hardware-specific instructions. We describe the necessary layers of abstraction and their differences and similarities to classical layers of a computer-aided design flow. For each layer of the stack, we discuss the underlying methods for compilation and optimization. Our software methodology facilitates more rapid innovation among quantum algorithm designers, quantum hardware engineers, and experimentalists. It enables scalable compilation of complex quantum algorithms and can be targeted to any specific quantum hardware implementation.

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

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

Estep, Donald

2015-11-30

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

Free Energy Minimization Calculation of Complex Chemical Equilibria. Reduction of Silicon Dioxide with Carbon at High Temperature.

ERIC Educational Resources Information Center

Wai, C. M.; Hutchinson, S. G.

1989-01-01

Discusses the calculation of free energy in reactions between silicon dioxide and carbon. Describes several computer programs for calculating the free energy minimization and their uses in chemistry classrooms. Lists 16 references. (YP)

High Performance Computing and Cutting-Edge Analysis Can Open New

Science.gov Websites

Realms March 1, 2018 Two people looking at a 3D interactive graphical data the Visualization Center in capabilities to visualize complex, 3D images of the wakes from multiple wind turbines so that we can better

Electron-Atom Ionization Calculations using Propagating Exterior Complex Scaling

NASA Astrophysics Data System (ADS)

Bartlett, Philip

2007-10-01

The exterior complex scaling method (Science 286 (1999) 2474), pioneered by Rescigno, McCurdy and coworkers, provided highly accurate ab initio solutions for electron-hydrogen collisions by directly solving the time-independent Schr"odinger equation in coordinate space. An extension of this method, propagating exterior complex scaling (PECS), was developed by Bartlett and Stelbovics (J. Phys. B 37 (2004) L69, J. Phys. B 39 (2006) R379) and has been demonstrated to provide computationally efficient and accurate calculations of ionization and scattering cross sections over a large range of energies below, above and near the ionization threshold. An overview of the PECS method for three-body collisions and the computational advantages of its propagation and iterative coupling techniques will be presented along with results of: (1) near-threshold ionization of electron-hydrogen collisions and the Wannier threshold laws, (2) scattering cross section resonances below the ionization threshold, and (3) total and differential cross sections for electron collisions with excited targets and hydrogenic ions from low through to high energies. Recently, the PECS method has been extended to solve four-body collisions using time-independent methods in coordinate space and has initially been applied to the s-wave model for electron-helium collisions. A description of the extensions made to the PECS method to facilitate these significantly more computationally demanding calculations will be given, and results will be presented for elastic, single-excitation, double-excitation, single-ionization and double-ionization collisions.

Force and Stress along Simulated Dissociation Pathways of Cucurbituril-Guest Systems.

PubMed

Velez-Vega, Camilo; Gilson, Michael K

2012-03-13

The field of host-guest chemistry provides computationally tractable yet informative model systems for biomolecular recognition. We applied molecular dynamics simulations to study the forces and mechanical stresses associated with forced dissociation of aqueous cucurbituril-guest complexes with high binding affinities. First, the unbinding transitions were modeled with constant velocity pulling (steered dynamics) and a soft spring constant, to model atomic force microscopy (AFM) experiments. The computed length-force profiles yield rupture forces in good agreement with available measurements. We also used steered dynamics with high spring constants to generate paths characterized by a tight control over the specified pulling distance; these paths were then equilibrated via umbrella sampling simulations and used to compute time-averaged mechanical stresses along the dissociation pathways. The stress calculations proved to be informative regarding the key interactions determining the length-force profiles and rupture forces. In particular, the unbinding transition of one complex is found to be a stepwise process, which is initially dominated by electrostatic interactions between the guest's ammoniums and the host's carbonyl groups, and subsequently limited by the extraction of the guest's bulky bicyclooctane moiety; the latter step requires some bond stretching at the cucurbituril's extraction portal. Conversely, the dissociation of a second complex with a more slender guest is mainly driven by successive electrostatic interactions between the different guest's ammoniums and the host's carbonyl groups. The calculations also provide information on the origins of thermodynamic irreversibilities in these forced dissociation processes.

Research of aerohydrodynamic and aeroelastic processes on PNRPU HPC system

NASA Astrophysics Data System (ADS)

Modorskii, V. Ya.; Shevelev, N. A.

2016-10-01

Research of aerohydrodynamic and aeroelastic processes with the High Performance Computing Complex in PNIPU is actively conducted within the university priority development direction "Aviation engine and gas turbine technology". Work is carried out in two areas: development and use of domestic software and use of well-known foreign licensed applied software packets. In addition, the third direction associated with the verification of computational experiments - physical modeling, with unique proprietary experimental installations is being developed.

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

DOE PAGES

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

2016-04-20

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

Petascale computation performance of lightweight multiscale cardiac models using hybrid programming models.

PubMed

Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

2011-01-01

Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.

Automated validation of a computer operating system

NASA Technical Reports Server (NTRS)

Dervage, M. M.; Milberg, B. A.

1970-01-01

Programs apply selected input/output loads to complex computer operating system and measure performance of that system under such loads. Technique lends itself to checkout of computer software designed to monitor automated complex industrial systems.

An assessment and application of turbulence models for hypersonic flows

NASA Technical Reports Server (NTRS)

Coakley, T. J.; Viegas, J. R.; Huang, P. G.; Rubesin, M. W.

1990-01-01

The current approach to the Accurate Computation of Complex high-speed flows is to solve the Reynolds averaged Navier-Stokes equations using finite difference methods. An integral part of this approach consists of development and applications of mathematical turbulence models which are necessary in predicting the aerothermodynamic loads on the vehicle and the performance of the propulsion plant. Computations of several high speed turbulent flows using various turbulence models are described and the models are evaluated by comparing computations with the results of experimental measurements. The cases investigated include flows over insulated and cooled flat plates with Mach numbers ranging from 2 to 8 and wall temperature ratios ranging from 0.2 to 1.0. The turbulence models investigated include zero-equation, two-equation, and Reynolds-stress transport models.

High-resolution 3D laser imaging based on tunable fiber array link

NASA Astrophysics Data System (ADS)

Zhao, Sisi; Ruan, Ningjuan; Yang, Song

2017-10-01

Airborne photoelectric reconnaissance system with the bore sight down to the ground is an important battlefield situational awareness system, which can be used for reconnaissance and surveillance of complex ground scene. Airborne 3D imaging Lidar system is recognized as the most potential candidates for target detection under the complex background, and is progressing in the directions of high resolution, long distance detection, high sensitivity, low power consumption, high reliability, eye safe and multi-functional. However, the traditional 3D laser imaging system has the disadvantages of lower imaging resolutions because of the small size of the existing detector, and large volume. This paper proposes a high resolution laser 3D imaging technology based on the tunable optical fiber array link. The echo signal is modulated by a tunable optical fiber array link and then transmitted to the focal plane detector. The detector converts the optical signal into electrical signals which is given to the computer. Then, the computer accomplishes the signal calculation and image restoration based on modulation information, and then reconstructs the target image. This paper establishes the mathematical model of tunable optical fiber array signal receiving link, and proposes the simulation and analysis of the affect factors on high density multidimensional point cloud reconstruction.

Technical Development and Application of Soft Computing in Agricultural and Biological Engineering

USDA-ARS?s Scientific Manuscript database

Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

Development of Soft Computing and Applications in Agricultural and Biological Engineering

USDA-ARS?s Scientific Manuscript database

Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

Evaluation of a Multicore-Optimized Implementation for Tomographic Reconstruction

PubMed Central

Agulleiro, Jose-Ignacio; Fernández, José Jesús

2012-01-01

Tomography allows elucidation of the three-dimensional structure of an object from a set of projection images. In life sciences, electron microscope tomography is providing invaluable information about the cell structure at a resolution of a few nanometres. Here, large images are required to combine wide fields of view with high resolution requirements. The computational complexity of the algorithms along with the large image size then turns tomographic reconstruction into a computationally demanding problem. Traditionally, high-performance computing techniques have been applied to cope with such demands on supercomputers, distributed systems and computer clusters. In the last few years, the trend has turned towards graphics processing units (GPUs). Here we present a detailed description and a thorough evaluation of an alternative approach that relies on exploitation of the power available in modern multicore computers. The combination of single-core code optimization, vector processing, multithreading and efficient disk I/O operations succeeds in providing fast tomographic reconstructions on standard computers. The approach turns out to be competitive with the fastest GPU-based solutions thus far. PMID:23139768

Studying an Eulerian Computer Model on Different High-performance Computer Platforms and Some Applications

NASA Astrophysics Data System (ADS)

Georgiev, K.; Zlatev, Z.

2010-11-01

The Danish Eulerian Model (DEM) is an Eulerian model for studying the transport of air pollutants on large scale. Originally, the model was developed at the National Environmental Research Institute of Denmark. The model computational domain covers Europe and some neighbour parts belong to the Atlantic Ocean, Asia and Africa. If DEM model is to be applied by using fine grids, then its discretization leads to a huge computational problem. This implies that such a model as DEM must be run only on high-performance computer architectures. The implementation and tuning of such a complex large-scale model on each different computer is a non-trivial task. Here, some comparison results of running of this model on different kind of vector (CRAY C92A, Fujitsu, etc.), parallel computers with distributed memory (IBM SP, CRAY T3E, Beowulf clusters, Macintosh G4 clusters, etc.), parallel computers with shared memory (SGI Origin, SUN, etc.) and parallel computers with two levels of parallelism (IBM SMP, IBM BlueGene/P, clusters of multiprocessor nodes, etc.) will be presented. The main idea in the parallel version of DEM is domain partitioning approach. Discussions according to the effective use of the cache and hierarchical memories of the modern computers as well as the performance, speed-ups and efficiency achieved will be done. The parallel code of DEM, created by using MPI standard library, appears to be highly portable and shows good efficiency and scalability on different kind of vector and parallel computers. Some important applications of the computer model output are presented in short.

Complex matrix multiplication operations with data pre-conditioning in a high performance computing architecture

DOEpatents

Eichenberger, Alexandre E; Gschwind, Michael K; Gunnels, John A

2014-02-11

Mechanisms for performing a complex matrix multiplication operation are provided. A vector load operation is performed to load a first vector operand of the complex matrix multiplication operation to a first target vector register. The first vector operand comprises a real and imaginary part of a first complex vector value. A complex load and splat operation is performed to load a second complex vector value of a second vector operand and replicate the second complex vector value within a second target vector register. The second complex vector value has a real and imaginary part. A cross multiply add operation is performed on elements of the first target vector register and elements of the second target vector register to generate a partial product of the complex matrix multiplication operation. The partial product is accumulated with other partial products and a resulting accumulated partial product is stored in a result vector register.

EEG complexity as a biomarker for autism spectrum disorder risk

PubMed Central

2011-01-01

Background Complex neurodevelopmental disorders may be characterized by subtle brain function signatures early in life before behavioral symptoms are apparent. Such endophenotypes may be measurable biomarkers for later cognitive impairments. The nonlinear complexity of electroencephalography (EEG) signals is believed to contain information about the architecture of the neural networks in the brain on many scales. Early detection of abnormalities in EEG signals may be an early biomarker for developmental cognitive disorders. The goal of this paper is to demonstrate that the modified multiscale entropy (mMSE) computed on the basis of resting state EEG data can be used as a biomarker of normal brain development and distinguish typically developing children from a group of infants at high risk for autism spectrum disorder (ASD), defined on the basis of an older sibling with ASD. Methods Using mMSE as a feature vector, a multiclass support vector machine algorithm was used to classify typically developing and high-risk groups. Classification was computed separately within each age group from 6 to 24 months. Results Multiscale entropy appears to go through a different developmental trajectory in infants at high risk for autism (HRA) than it does in typically developing controls. Differences appear to be greatest at ages 9 to 12 months. Using several machine learning algorithms with mMSE as a feature vector, infants were classified with over 80% accuracy into control and HRA groups at age 9 months. Classification accuracy for boys was close to 100% at age 9 months and remains high (70% to 90%) at ages 12 and 18 months. For girls, classification accuracy was highest at age 6 months, but declines thereafter. Conclusions This proof-of-principle study suggests that mMSE computed from resting state EEG signals may be a useful biomarker for early detection of risk for ASD and abnormalities in cognitive development in infants. To our knowledge, this is the first demonstration of an information theoretic analysis of EEG data for biomarkers in infants at risk for a complex neurodevelopmental disorder. PMID:21342500

Amination with Pd-NHC complexes: rate and computational studies involving substituted aniline substrates.

PubMed

Hoi, Ka Hou; Çalimsiz, Selçuk; Froese, Robert D J; Hopkinson, Alan C; Organ, Michael G

2012-01-02

The amination of aryl chlorides with various aniline derivatives using the N-heterocyclic carbene-based Pd complexes Pd-PEPPSI-IPr and Pd-PEPPSI-IPent (PEPPSI=pyridine, enhanced precatalyst, preparation, stabilization, and initiation; IPr=diisopropylphenylimidazolium derivative; IPent= diisopentylphenylimidazolium derivative) has been studied. Rate studies have shown a reliance on the aryl chloride to be electron poor, although oxidative addition is not rate limiting. Anilines couple best when they are electron rich, which would seem to discount deprotonation of the intermediate metal ammonium complex as being rate limiting in favour of reductive elimination. In previous studies with secondary amines using PEPPSI complexes, deprotonation was proposed to be the slow step in the cycle. These experimental findings relating to mechanism were corroborated by computation. Pd-PEPPSI-IPr and the more hindered Pd-PEPPSI-IPent catalysts were used to couple deactivated aryl chlorides with electron poor anilines; while the IPr catalysis was sluggish, the IPent catalyst performed extremely well, again showing the high reactivity of this broadly useful catalyst. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Peregrine Transition from CentOS6 to CentOS7 | High-Performance Computing |

Science.gov Websites

). Users should consider them primarily as examples, which they can copy and modify for their own use with HPC environments. This can permit one-step access to pre-existing complex software stacks, or /projects. This is not a highly suggested mechanism, but might serve for one-time needs. In the unlikely

X-ray-binary spectra in the lamp post model

NASA Astrophysics Data System (ADS)

Vincent, F. H.; Różańska, A.; Zdziarski, A. A.; Madej, J.

2016-05-01

Context. The high-energy radiation from black-hole binaries may be due to the reprocessing of a lamp located on the black hole rotation axis and emitting X-rays. The observed spectrum is made of three major components: the direct spectrum traveling from the lamp directly to the observer; the thermal bump at the equilibrium temperature of the accretion disk heated by the lamp; and the reflected spectrum essentially made of the Compton hump and the iron-line complex. Aims: We aim to accurately compute the complete reprocessed spectrum (thermal bump + reflected) of black-hole binaries over the entire X-ray band. We also determine the strength of the direct component. Our choice of parameters is adapted to a source showing an important thermal component. We are particularly interested in investigating the possibility to use the iron-line complex as a probe to constrain the black hole spin. Methods: We computed in full general relativity the illumination of a thin accretion disk by a fixed X-ray lamp along the rotation axis. We used the ATM21 radiative transfer code to compute the local, energy-dependent spectrum emitted along the disk as a function of radius, emission angle and black hole spin. We then ray traced this local spectrum to determine the final reprocessed spectrum as received by a distant observer. We consider two extreme values of the black hole spin (a = 0 and a = 0.98) and discuss the dependence of the local and ray-traced spectra on the emission angle and black hole spin. Results: We show the importance of the angle dependence of the total disk specific intensity spectrum emitted by the illuminated atmosphere when the thermal disk emission is fully taken into account. The disk flux, together with the X-ray flux from the lamp, determines the temperature and ionization structure of the atmosphere. High black hole spin implies high temperature in the inner disk regions, therefore, the emitted thermal disk spectrum fully covers the iron-line complex. As a result, instead of fluorescent iron emission line, we locally observe absorption lines produced in the hot disk atmosphere. Absorption lines are narrow and disappear after ray tracing the local spectrum. Conclusions: Our results mainly highlight the importance of considering the angle dependence of the local spectrum when computing reprocessed spectra, as was already found in a recent study. The main new result of our work is to show the importance of computing the thermal bump of the spectrum, as this feature can change considerably the observed iron-line complex. Thus, in particular for fitting black hole spins, the full spectrum, rather than only the reflected part, should be computed self-consistently.

Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning.

PubMed

Sadeghi, Zahra; Testolin, Alberto

2017-08-01

In humans, efficient recognition of written symbols is thought to rely on a hierarchical processing system, where simple features are progressively combined into more abstract, high-level representations. Here, we present a computational model of Persian character recognition based on deep belief networks, where increasingly more complex visual features emerge in a completely unsupervised manner by fitting a hierarchical generative model to the sensory data. Crucially, high-level internal representations emerging from unsupervised deep learning can be easily read out by a linear classifier, achieving state-of-the-art recognition accuracy. Furthermore, we tested the hypothesis that handwritten digits and letters share many common visual features: A generative model that captures the statistical structure of the letters distribution should therefore also support the recognition of written digits. To this aim, deep networks trained on Persian letters were used to build high-level representations of Persian digits, which were indeed read out with high accuracy. Our simulations show that complex visual features, such as those mediating the identification of Persian symbols, can emerge from unsupervised learning in multilayered neural networks and can support knowledge transfer across related domains.

The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2016-12-01

There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex and Dynamic Conditions

DTIC Science & Technology

2015-07-14

AFRL-OSR-VA-TR-2015-0202 Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex...Computational Modeling of Team Problem Solving for Decision Making Under Complex and Dynamic Conditions 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...functioning as they solve complex problems, and propose the means to improve the performance of teams, under changing or adversarial conditions. By

Leveraging Mechanism Simplicity and Strategic Averaging to Identify Signals from Highly Heterogeneous Spatial and Temporal Ozone Data

NASA Astrophysics Data System (ADS)

Brown-Steiner, B.; Selin, N. E.; Prinn, R. G.; Monier, E.; Garcia-Menendez, F.; Tilmes, S.; Emmons, L. K.; Lamarque, J. F.; Cameron-Smith, P. J.

2017-12-01

We summarize two methods to aid in the identification of ozone signals from underlying spatially and temporally heterogeneous data in order to help research communities avoid the sometimes burdensome computational costs of high-resolution high-complexity models. The first method utilizes simplified chemical mechanisms (a Reduced Hydrocarbon Mechanism and a Superfast Mechanism) alongside a more complex mechanism (MOZART-4) within CESM CAM-Chem to extend the number of simulated meteorological years (or add additional members to an ensemble) for a given modeling problem. The Reduced Hydrocarbon mechanism is twice as fast, and the Superfast mechanism is three times faster than the MOZART-4 mechanism. We show that simplified chemical mechanisms are largely capable of simulating surface ozone across the globe as well as the more complex chemical mechanisms, and where they are not capable, a simple standardized anomaly emulation approach can correct for their inadequacies. The second method uses strategic averaging over both temporal and spatial scales to filter out the highly heterogeneous noise that underlies ozone observations and simulations. This method allows for a selection of temporal and spatial averaging scales that match a particular signal strength (between 0.5 and 5 ppbv), and enables the identification of regions where an ozone signal can rise above the ozone noise over a given region and a given period of time. In conjunction, these two methods can be used to "scale down" chemical mechanism complexity and quantitatively determine spatial and temporal scales that could enable research communities to utilize simplified representations of atmospheric chemistry and thereby maximize their productivity and efficiency given computational constraints. While this framework is here applied to ozone data, it could also be applied to a broad range of geospatial data sets (observed or modeled) that have spatial and temporal coverage.

A Computer Story: Complexity from Simplicity

ERIC Educational Resources Information Center

DeLeo, Gary; Weidenhammer, Amanda; Wecht, Kristen

2012-01-01

In this technological age, digital devices are conspicuous examples of extraordinary complexity. When a user clicks on computer icons or presses calculator buttons, these devices channel electricity through a complex system of decision-making circuits. Yet, in spite of this remarkable complexity, the hearts of these devices are components that…

Computational adaptive optics for broadband interferometric tomography of tissues and cells

NASA Astrophysics Data System (ADS)

Adie, Steven G.; Mulligan, Jeffrey A.

2016-03-01

Adaptive optics (AO) can shape aberrated optical wavefronts to physically restore the constructive interference needed for high-resolution imaging. With access to the complex optical field, however, many functions of optical hardware can be achieved computationally, including focusing and the compensation of optical aberrations to restore the constructive interference required for diffraction-limited imaging performance. Holography, which employs interferometric detection of the complex optical field, was developed based on this connection between hardware and computational image formation, although this link has only recently been exploited for 3D tomographic imaging in scattering biological tissues. This talk will present the underlying imaging science behind computational image formation with optical coherence tomography (OCT) -- a beam-scanned version of broadband digital holography. Analogous to hardware AO (HAO), we demonstrate computational adaptive optics (CAO) and optimization of the computed pupil correction in 'sensorless mode' (Zernike polynomial corrections with feedback from image metrics) or with the use of 'guide-stars' in the sample. We discuss the concept of an 'isotomic volume' as the volumetric extension of the 'isoplanatic patch' introduced in astronomical AO. Recent CAO results and ongoing work is highlighted to point to the potential biomedical impact of computed broadband interferometric tomography. We also discuss the advantages and disadvantages of HAO vs. CAO for the effective shaping of optical wavefronts, and highlight opportunities for hybrid approaches that synergistically combine the unique advantages of hardware and computational methods for rapid volumetric tomography with cellular resolution.

An Online Gravity Modeling Method Applied for High Precision Free-INS

PubMed Central

Wang, Jing; Yang, Gongliu; Li, Jing; Zhou, Xiao

2016-01-01

For real-time solution of inertial navigation system (INS), the high-degree spherical harmonic gravity model (SHM) is not applicable because of its time and space complexity, in which traditional normal gravity model (NGM) has been the dominant technique for gravity compensation. In this paper, a two-dimensional second-order polynomial model is derived from SHM according to the approximate linear characteristic of regional disturbing potential. Firstly, deflections of vertical (DOVs) on dense grids are calculated with SHM in an external computer. And then, the polynomial coefficients are obtained using these DOVs. To achieve global navigation, the coefficients and applicable region of polynomial model are both updated synchronously in above computer. Compared with high-degree SHM, the polynomial model takes less storage and computational time at the expense of minor precision. Meanwhile, the model is more accurate than NGM. Finally, numerical test and INS experiment show that the proposed method outperforms traditional gravity models applied for high precision free-INS. PMID:27669261

An Online Gravity Modeling Method Applied for High Precision Free-INS.

PubMed

Wang, Jing; Yang, Gongliu; Li, Jing; Zhou, Xiao

2016-09-23

For real-time solution of inertial navigation system (INS), the high-degree spherical harmonic gravity model (SHM) is not applicable because of its time and space complexity, in which traditional normal gravity model (NGM) has been the dominant technique for gravity compensation. In this paper, a two-dimensional second-order polynomial model is derived from SHM according to the approximate linear characteristic of regional disturbing potential. Firstly, deflections of vertical (DOVs) on dense grids are calculated with SHM in an external computer. And then, the polynomial coefficients are obtained using these DOVs. To achieve global navigation, the coefficients and applicable region of polynomial model are both updated synchronously in above computer. Compared with high-degree SHM, the polynomial model takes less storage and computational time at the expense of minor precision. Meanwhile, the model is more accurate than NGM. Finally, numerical test and INS experiment show that the proposed method outperforms traditional gravity models applied for high precision free-INS.

OpenCluster: A Flexible Distributed Computing Framework for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Wei, Shoulin; Wang, Feng; Deng, Hui; Liu, Cuiyin; Dai, Wei; Liang, Bo; Mei, Ying; Shi, Congming; Liu, Yingbo; Wu, Jingping

2017-02-01

The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their limitations and programming difficulties. In this paper, we therefore present OpenCluster, an open-source distributed computing framework to support rapidly developing high-performance processing pipelines of astronomical big data. We first detail the OpenCluster design principles and implementations and present the APIs facilitated by the framework. We then demonstrate a case in which OpenCluster is used to resolve complex data processing problems for developing a pipeline for the Mingantu Ultrawide Spectral Radioheliograph. Finally, we present our OpenCluster performance evaluation. Overall, OpenCluster provides not only high fault tolerance and simple programming interfaces, but also a flexible means of scaling up the number of interacting entities. OpenCluster thereby provides an easily integrated distributed computing framework for quickly developing a high-performance data processing system of astronomical telescopes and for significantly reducing software development expenses.

Multi-threading performance of Geant4, MCNP6, and PHITS Monte Carlo codes for tetrahedral-mesh geometry.

PubMed

Han, Min Cheol; Yeom, Yeon Soo; Lee, Hyun Su; Shin, Bangho; Kim, Chan Hyeong; Furuta, Takuya

2018-05-04

In this study, the multi-threading performance of the Geant4, MCNP6, and PHITS codes was evaluated as a function of the number of threads (N) and the complexity of the tetrahedral-mesh phantom. For this, three tetrahedral-mesh phantoms of varying complexity (simple, moderately complex, and highly complex) were prepared and implemented in the three different Monte Carlo codes, in photon and neutron transport simulations. Subsequently, for each case, the initialization time, calculation time, and memory usage were measured as a function of the number of threads used in the simulation. It was found that for all codes, the initialization time significantly increased with the complexity of the phantom, but not with the number of threads. Geant4 exhibited much longer initialization time than the other codes, especially for the complex phantom (MRCP). The improvement of computation speed due to the use of a multi-threaded code was calculated as the speed-up factor, the ratio of the computation speed on a multi-threaded code to the computation speed on a single-threaded code. Geant4 showed the best multi-threading performance among the codes considered in this study, with the speed-up factor almost linearly increasing with the number of threads, reaching ~30 when N  =  40. PHITS and MCNP6 showed a much smaller increase of the speed-up factor with the number of threads. For PHITS, the speed-up factors were low when N  =  40. For MCNP6, the increase of the speed-up factors was better, but they were still less than ~10 when N  =  40. As for memory usage, Geant4 was found to use more memory than the other codes. In addition, compared to that of the other codes, the memory usage of Geant4 more rapidly increased with the number of threads, reaching as high as ~74 GB when N  =  40 for the complex phantom (MRCP). It is notable that compared to that of the other codes, the memory usage of PHITS was much lower, regardless of both the complexity of the phantom and the number of threads, hardly increasing with the number of threads for the MRCP.

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

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

Schmalz, Mark S

2011-07-24

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G}more » for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.« less

Stochastic Convection Parameterizations

NASA Technical Reports Server (NTRS)

Teixeira, Joao; Reynolds, Carolyn; Suselj, Kay; Matheou, Georgios

2012-01-01

computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts

Field Scale Monitoring and Modeling of Water and Chemical Transfer in the Vadose Zone

USDA-ARS?s Scientific Manuscript database

Natural resource systems involve highly complex interactions of soil-plant-atmosphere-management components that are extremely difficult to quantitatively describe. Computer simulations for prediction and management of watersheds, water supply areas, and agricultural fields and farms have become inc...

A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection

DOE PAGES

Zhang, Guannan; Webster, Clayton G.; Gunzburger, Max D.; ...

2015-06-24

This study proposes and analyzes a hyperspherical adaptive hierarchical sparse-grid method for detecting jump discontinuities of functions in high-dimensional spaces. The method is motivated by the theoretical and computational inefficiencies of well-known adaptive sparse-grid methods for discontinuity detection. Our novel approach constructs a function representation of the discontinuity hypersurface of an N-dimensional discontinuous quantity of interest, by virtue of a hyperspherical transformation. Then, a sparse-grid approximation of the transformed function is built in the hyperspherical coordinate system, whose value at each point is estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of the hypersurface, the newmore » technique can identify jump discontinuities with significantly reduced computational cost, compared to existing methods. In addition, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. Rigorous complexity analyses of the new method are provided as are several numerical examples that illustrate the effectiveness of the approach.« less

A hyper-spherical adaptive sparse-grid method for high-dimensional discontinuity detection

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

Zhang, Guannan; Webster, Clayton G.; Gunzburger, Max D.

This work proposes and analyzes a hyper-spherical adaptive hierarchical sparse-grid method for detecting jump discontinuities of functions in high-dimensional spaces is proposed. The method is motivated by the theoretical and computational inefficiencies of well-known adaptive sparse-grid methods for discontinuity detection. Our novel approach constructs a function representation of the discontinuity hyper-surface of an N-dimensional dis- continuous quantity of interest, by virtue of a hyper-spherical transformation. Then, a sparse-grid approximation of the transformed function is built in the hyper-spherical coordinate system, whose value at each point is estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of themore » hyper-surface, the new technique can identify jump discontinuities with significantly reduced computational cost, compared to existing methods. Moreover, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. Rigorous error estimates and complexity analyses of the new method are provided as are several numerical examples that illustrate the effectiveness of the approach.« less

Autonomic Cluster Management System (ACMS): A Demonstration of Autonomic Principles at Work

NASA Technical Reports Server (NTRS)

Baldassari, James D.; Kopec, Christopher L.; Leshay, Eric S.; Truszkowski, Walt; Finkel, David

2005-01-01

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of achieving significant computational capabilities for high-performance computing applications, while simultaneously affording the ability to. increase that capability simply by adding more (inexpensive) processors. However, the task of manually managing and con.guring a cluster quickly becomes impossible as the cluster grows in size. Autonomic computing is a relatively new approach to managing complex systems that can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Automatic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management.

A high-throughput pipeline for the production of synthetic antibodies for analysis of ribonucleoprotein complexes

PubMed Central

Na, Hong; Laver, John D.; Jeon, Jouhyun; Singh, Fateh; Ancevicius, Kristin; Fan, Yujie; Cao, Wen Xi; Nie, Kun; Yang, Zhenglin; Luo, Hua; Wang, Miranda; Rissland, Olivia; Westwood, J. Timothy; Kim, Philip M.; Smibert, Craig A.; Lipshitz, Howard D.; Sidhu, Sachdev S.

2016-01-01

Post-transcriptional regulation of mRNAs plays an essential role in the control of gene expression. mRNAs are regulated in ribonucleoprotein (RNP) complexes by RNA-binding proteins (RBPs) along with associated protein and noncoding RNA (ncRNA) cofactors. A global understanding of post-transcriptional control in any cell type requires identification of the components of all of its RNP complexes. We have previously shown that these complexes can be purified by immunoprecipitation using anti-RBP synthetic antibodies produced by phage display. To develop the large number of synthetic antibodies required for a global analysis of RNP complex composition, we have established a pipeline that combines (i) a computationally aided strategy for design of antigens located outside of annotated domains, (ii) high-throughput antigen expression and purification in Escherichia coli, and (iii) high-throughput antibody selection and screening. Using this pipeline, we have produced 279 antibodies against 61 different protein components of Drosophila melanogaster RNPs. Together with those produced in our low-throughput efforts, we have a panel of 311 antibodies for 67 RNP complex proteins. Tests of a subset of our antibodies demonstrated that 89% immunoprecipitate their endogenous target from embryo lysate. This panel of antibodies will serve as a resource for global studies of RNP complexes in Drosophila. Furthermore, our high-throughput pipeline permits efficient production of synthetic antibodies against any large set of proteins. PMID:26847261

High-fidelity simulation capability for virtual testing of seismic and acoustic sensors

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Moran, Mark L.; Ketcham, Stephen A.; Lacombe, James; Anderson, Thomas S.; Symons, Neill P.; Aldridge, David F.; Marlin, David H.; Collier, Sandra L.; Ostashev, Vladimir E.

2005-05-01

This paper describes development and application of a high-fidelity, seismic/acoustic simulation capability for battlefield sensors. The purpose is to provide simulated sensor data so realistic that they cannot be distinguished by experts from actual field data. This emerging capability provides rapid, low-cost trade studies of unattended ground sensor network configurations, data processing and fusion strategies, and signatures emitted by prototype vehicles. There are three essential components to the modeling: (1) detailed mechanical signature models for vehicles and walkers, (2) high-resolution characterization of the subsurface and atmospheric environments, and (3) state-of-the-art seismic/acoustic models for propagating moving-vehicle signatures through realistic, complex environments. With regard to the first of these components, dynamic models of wheeled and tracked vehicles have been developed to generate ground force inputs to seismic propagation models. Vehicle models range from simple, 2D representations to highly detailed, 3D representations of entire linked-track suspension systems. Similarly detailed models of acoustic emissions from vehicle engines are under development. The propagation calculations for both the seismics and acoustics are based on finite-difference, time-domain (FDTD) methodologies capable of handling complex environmental features such as heterogeneous geologies, urban structures, surface vegetation, and dynamic atmospheric turbulence. Any number of dynamic sources and virtual sensors may be incorporated into the FDTD model. The computational demands of 3D FDTD simulation over tactical distances require massively parallel computers. Several example calculations of seismic/acoustic wave propagation through complex atmospheric and terrain environments are shown.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

A Two-Stage Reconstruction Processor for Human Detection in Compressive Sensing CMOS Radar

PubMed Central

Tsao, Kuei-Chi; Lee, Ling; Chu, Ta-Shun

2018-01-01

Complementary metal-oxide-semiconductor (CMOS) radar has recently gained much research attraction because small and low-power CMOS devices are very suitable for deploying sensing nodes in a low-power wireless sensing system. This study focuses on the signal processing of a wireless CMOS impulse radar system that can detect humans and objects in the home-care internet-of-things sensing system. The challenges of low-power CMOS radar systems are the weakness of human signals and the high computational complexity of the target detection algorithm. The compressive sensing-based detection algorithm can relax the computational costs by avoiding the utilization of matched filters and reducing the analog-to-digital converter bandwidth requirement. The orthogonal matching pursuit (OMP) is one of the popular signal reconstruction algorithms for compressive sensing radar; however, the complexity is still very high because the high resolution of human respiration leads to high-dimension signal reconstruction. Thus, this paper proposes a two-stage reconstruction algorithm for compressive sensing radar. The proposed algorithm not only has lower complexity than the OMP algorithm by 75% but also achieves better positioning performance than the OMP algorithm especially in noisy environments. This study also designed and implemented the algorithm by using Vertex-7 FPGA chip (Xilinx, San Jose, CA, USA). The proposed reconstruction processor can support the 256×13 real-time radar image display with a throughput of 28.2 frames per second. PMID:29621170

Computation-Guided Backbone Grafting of a Discontinuous Motif onto a Protein Scaffold

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

Azoitei, Mihai L.; Correia, Bruno E.; Ban, Yih-En Andrew

2012-02-07

The manipulation of protein backbone structure to control interaction and function is a challenge for protein engineering. We integrated computational design with experimental selection for grafting the backbone and side chains of a two-segment HIV gp120 epitope, targeted by the cross-neutralizing antibody b12, onto an unrelated scaffold protein. The final scaffolds bound b12 with high specificity and with affinity similar to that of gp120, and crystallographic analysis of a scaffold bound to b12 revealed high structural mimicry of the gp120-b12 complex structure. The method can be generalized to design other functional proteins through backbone grafting.

Accuracy Improvement in Magnetic Field Modeling for an Axisymmetric Electromagnet

NASA Technical Reports Server (NTRS)

Ilin, Andrew V.; Chang-Diaz, Franklin R.; Gurieva, Yana L.; Il,in, Valery P.

2000-01-01

This paper examines the accuracy and calculation speed for the magnetic field computation in an axisymmetric electromagnet. Different numerical techniques, based on an adaptive nonuniform grid, high order finite difference approximations, and semi-analitical calculation of boundary conditions are considered. These techniques are being applied to the modeling of the Variable Specific Impulse Magnetoplasma Rocket. For high-accuracy calculations, a fourth-order scheme offers dramatic advantages over a second order scheme. For complex physical configurations of interest in plasma propulsion, a second-order scheme with nonuniform mesh gives the best results. Also, the relative advantages of various methods are described when the speed of computation is an important consideration.

Sample-space-based feature extraction and class preserving projection for gene expression data.

PubMed

Wang, Wenjun

2013-01-01

In order to overcome the problems of high computational complexity and serious matrix singularity for feature extraction using Principal Component Analysis (PCA) and Fisher's Linear Discrinimant Analysis (LDA) in high-dimensional data, sample-space-based feature extraction is presented, which transforms the computation procedure of feature extraction from gene space to sample space by representing the optimal transformation vector with the weighted sum of samples. The technique is used in the implementation of PCA, LDA, Class Preserving Projection (CPP) which is a new method for discriminant feature extraction proposed, and the experimental results on gene expression data demonstrate the effectiveness of the method.

High-power graphic computers for visual simulation: a real-time--rendering revolution

NASA Technical Reports Server (NTRS)

Kaiser, M. K.

1996-01-01

Advances in high-end graphics computers in the past decade have made it possible to render visual scenes of incredible complexity and realism in real time. These new capabilities make it possible to manipulate and investigate the interactions of observers with their visual world in ways once only dreamed of. This paper reviews how these developments have affected two preexisting domains of behavioral research (flight simulation and motion perception) and have created a new domain (virtual environment research) which provides tools and challenges for the perceptual psychologist. Finally, the current limitations of these technologies are considered, with an eye toward how perceptual psychologist might shape future developments.

Complex Instruction Set Quantum Computing

NASA Astrophysics Data System (ADS)

Sanders, G. D.; Kim, K. W.; Holton, W. C.

1998-03-01

In proposed quantum computers, electromagnetic pulses are used to implement logic gates on quantum bits (qubits). Gates are unitary transformations applied to coherent qubit wavefunctions and a universal computer can be created using a minimal set of gates. By applying many elementary gates in sequence, desired quantum computations can be performed. This reduced instruction set approach to quantum computing (RISC QC) is characterized by serial application of a few basic pulse shapes and a long coherence time. However, the unitary matrix of the overall computation is ultimately a unitary matrix of the same size as any of the elementary matrices. This suggests that we might replace a sequence of reduced instructions with a single complex instruction using an optimally taylored pulse. We refer to this approach as complex instruction set quantum computing (CISC QC). One trades the requirement for long coherence times for the ability to design and generate potentially more complex pulses. We consider a model system of coupled qubits interacting through nearest neighbor coupling and show that CISC QC can reduce the time required to perform quantum computations.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

PubMed

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

VBOT: Motivating computational and complex systems fluencies with constructionist virtual/physical robotics

NASA Astrophysics Data System (ADS)

Berland, Matthew W.

As scientists use the tools of computational and complex systems theory to broaden science perspectives (e.g., Bar-Yam, 1997; Holland, 1995; Wolfram, 2002), so can middle-school students broaden their perspectives using appropriate tools. The goals of this dissertation project are to build, study, evaluate, and compare activities designed to foster both computational and complex systems fluencies through collaborative constructionist virtual and physical robotics. In these activities, each student builds an agent (e.g., a robot-bird) that must interact with fellow students' agents to generate a complex aggregate (e.g., a flock of robot-birds) in a participatory simulation environment (Wilensky & Stroup, 1999a). In a participatory simulation, students collaborate by acting in a common space, teaching each other, and discussing content with one another. As a result, the students improve both their computational fluency and their complex systems fluency, where fluency is defined as the ability to both consume and produce relevant content (DiSessa, 2000). To date, several systems have been designed to foster computational and complex systems fluencies through computer programming and collaborative play (e.g., Hancock, 2003; Wilensky & Stroup, 1999b); this study suggests that, by supporting the relevant fluencies through collaborative play, they become mutually reinforcing. In this work, I will present both the design of the VBOT virtual/physical constructionist robotics learning environment and a comparative study of student interaction with the virtual and physical environments across four middle-school classrooms, focusing on the contrast in systems perspectives differently afforded by the two environments. In particular, I found that while performance gains were similar overall, the physical environment supported agent perspectives on aggregate behavior, and the virtual environment supported aggregate perspectives on agent behavior. The primary research questions are: (1) What are the relative affordances of virtual and physical constructionist robotics systems towards computational and complex systems fluencies? (2) What can middle school students learn using computational/complex systems learning environments in a collaborative setting? (3) In what ways are these environments and activities effective in teaching students computational and complex systems fluencies?

Online System for Faster Multipoint Linkage Analysis via Parallel Execution on Thousands of Personal Computers

PubMed Central

Silberstein, M.; Tzemach, A.; Dovgolevsky, N.; Fishelson, M.; Schuster, A.; Geiger, D.

2006-01-01

Computation of LOD scores is a valuable tool for mapping disease-susceptibility genes in the study of Mendelian and complex diseases. However, computation of exact multipoint likelihoods of large inbred pedigrees with extensive missing data is often beyond the capabilities of a single computer. We present a distributed system called “SUPERLINK-ONLINE,” for the computation of multipoint LOD scores of large inbred pedigrees. It achieves high performance via the efficient parallelization of the algorithms in SUPERLINK, a state-of-the-art serial program for these tasks, and through the use of the idle cycles of thousands of personal computers. The main algorithmic challenge has been to efficiently split a large task for distributed execution in a highly dynamic, nondedicated running environment. Notably, the system is available online, which allows computationally intensive analyses to be performed with no need for either the installation of software or the maintenance of a complicated distributed environment. As the system was being developed, it was extensively tested by collaborating medical centers worldwide on a variety of real data sets, some of which are presented in this article. PMID:16685644

A Review of High-Performance Computational Strategies for Modeling and Imaging of Electromagnetic Induction Data

NASA Astrophysics Data System (ADS)

Newman, Gregory A.

2014-01-01

Many geoscientific applications exploit electrostatic and electromagnetic fields to interrogate and map subsurface electrical resistivity—an important geophysical attribute for characterizing mineral, energy, and water resources. In complex three-dimensional geologies, where many of these resources remain to be found, resistivity mapping requires large-scale modeling and imaging capabilities, as well as the ability to treat significant data volumes, which can easily overwhelm single-core and modest multicore computing hardware. To treat such problems requires large-scale parallel computational resources, necessary for reducing the time to solution to a time frame acceptable to the exploration process. The recognition that significant parallel computing processes must be brought to bear on these problems gives rise to choices that must be made in parallel computing hardware and software. In this review, some of these choices are presented, along with the resulting trade-offs. We also discuss future trends in high-performance computing and the anticipated impact on electromagnetic (EM) geophysics. Topics discussed in this review article include a survey of parallel computing platforms, graphics processing units to multicore CPUs with a fast interconnect, along with effective parallel solvers and associated solver libraries effective for inductive EM modeling and imaging.

MS-CASPT2 study of hole transfer in guanine-indole complexes using the generalized Mulliken-Hush method: effective two-state treatment.

PubMed

Butchosa, C; Simon, S; Blancafort, L; Voityuk, A

2012-07-12

Because hole transfer from nucleobases to amino acid residues in DNA-protein complexes can prevent oxidative damage of DNA in living cells, computational modeling of the process is of high interest. We performed MS-CASPT2 calculations of several model structures of π-stacked guanine and indole and derived electron-transfer (ET) parameters for these systems using the generalized Mulliken-Hush (GMH) method. We show that the two-state model commonly applied to treat thermal ET between adjacent donor and acceptor is of limited use for the considered systems because of the small gap between the ground and first excited states in the indole radical cation. The ET parameters obtained within the two-state GMH scheme can deviate significantly from the corresponding matrix elements of the two-state effective Hamiltonian based on the GMH treatment of three adiabatic states. The computed values of diabatic energies and electronic couplings provide benchmarks to assess the performance of less sophisticated computational methods.

Improved dense trajectories for action recognition based on random projection and Fisher vectors

NASA Astrophysics Data System (ADS)

Ai, Shihui; Lu, Tongwei; Xiong, Yudian

2018-03-01

As an important application of intelligent monitoring system, the action recognition in video has become a very important research area of computer vision. In order to improve the accuracy rate of the action recognition in video with improved dense trajectories, one advanced vector method is introduced. Improved dense trajectories combine Fisher Vector with Random Projection. The method realizes the reduction of the characteristic trajectory though projecting the high-dimensional trajectory descriptor into the low-dimensional subspace based on defining and analyzing Gaussian mixture model by Random Projection. And a GMM-FV hybrid model is introduced to encode the trajectory feature vector and reduce dimension. The computational complexity is reduced by Random Projection which can drop Fisher coding vector. Finally, a Linear SVM is used to classifier to predict labels. We tested the algorithm in UCF101 dataset and KTH dataset. Compared with existed some others algorithm, the result showed that the method not only reduce the computational complexity but also improved the accuracy of action recognition.