Parallel grid library for rapid and flexible simulation development

NASA Astrophysics Data System (ADS)

Honkonen, I.; von Alfthan, S.; Sandroos, A.; Janhunen, P.; Palmroth, M.

2013-04-01

We present an easy to use and flexible grid library for developing highly scalable parallel simulations. The distributed cartesian cell-refinable grid (dccrg) supports adaptive mesh refinement and allows an arbitrary C++ class to be used as cell data. The amount of data in grid cells can vary both in space and time allowing dccrg to be used in very different types of simulations, for example in fluid and particle codes. Dccrg transfers the data between neighboring cells on different processes transparently and asynchronously allowing one to overlap computation and communication. This enables excellent scalability at least up to 32 k cores in magnetohydrodynamic tests depending on the problem and hardware. In the version of dccrg presented here part of the mesh metadata is replicated between MPI processes reducing the scalability of adaptive mesh refinement (AMR) to between 200 and 600 processes. Dccrg is free software that anyone can use, study and modify and is available at https://gitorious.org/dccrg. Users are also kindly requested to cite this work when publishing results obtained with dccrg. Catalogue identifier: AEOM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOM_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU Lesser General Public License version 3 No. of lines in distributed program, including test data, etc.: 54975 No. of bytes in distributed program, including test data, etc.: 974015 Distribution format: tar.gz Programming language: C++. Computer: PC, cluster, supercomputer. Operating system: POSIX. The code has been parallelized using MPI and tested with 1-32768 processes RAM: 10 MB-10 GB per process Classification: 4.12, 4.14, 6.5, 19.3, 19.10, 20. External routines: MPI-2 [1], boost [2], Zoltan [3], sfc++ [4] Nature of problem: Grid library supporting arbitrary data in grid cells, parallel adaptive mesh refinement, transparent remote neighbor data updates and load balancing. Solution method: The simulation grid is represented by an adjacency list (graph) with vertices stored into a hash table and edges into contiguous arrays. Message Passing Interface standard is used for parallelization. Cell data is given as a template parameter when instantiating the grid. Restrictions: Logically cartesian grid. Running time: Running time depends on the hardware, problem and the solution method. Small problems can be solved in under a minute and very large problems can take weeks. The examples and tests provided with the package take less than about one minute using default options. In the version of dccrg presented here the speed of adaptive mesh refinement is at most of the order of 106 total created cells per second. http://www.mpi-forum.org/. http://www.boost.org/. K. Devine, E. Boman, R. Heaphy, B. Hendrickson, C. Vaughan, Zoltan data management services for parallel dynamic applications, Comput. Sci. Eng. 4 (2002) 90-97. http://dx.doi.org/10.1109/5992.988653. https://gitorious.org/sfc++.

Grace: A cross-platform micromagnetic simulator on graphics processing units

NASA Astrophysics Data System (ADS)

Zhu, Ru

2015-12-01

A micromagnetic simulator running on graphics processing units (GPUs) is presented. Different from GPU implementations of other research groups which are predominantly running on NVidia's CUDA platform, this simulator is developed with C++ Accelerated Massive Parallelism (C++ AMP) and is hardware platform independent. It runs on GPUs from venders including NVidia, AMD and Intel, and achieves significant performance boost as compared to previous central processing unit (CPU) simulators, up to two orders of magnitude. The simulator paved the way for running large size micromagnetic simulations on both high-end workstations with dedicated graphics cards and low-end personal computers with integrated graphics cards, and is freely available to download.

GPU-accelerated FDTD modeling of radio-frequency field-tissue interactions in high-field MRI.

PubMed

Chi, Jieru; Liu, Feng; Weber, Ewald; Li, Yu; Crozier, Stuart

2011-06-01

The analysis of high-field RF field-tissue interactions requires high-performance finite-difference time-domain (FDTD) computing. Conventional CPU-based FDTD calculations offer limited computing performance in a PC environment. This study presents a graphics processing unit (GPU)-based parallel-computing framework, producing substantially boosted computing efficiency (with a two-order speedup factor) at a PC-level cost. Specific details of implementing the FDTD method on a GPU architecture have been presented and the new computational strategy has been successfully applied to the design of a novel 8-element transceive RF coil system at 9.4 T. Facilitated by the powerful GPU-FDTD computing, the new RF coil array offers optimized fields (averaging 25% improvement in sensitivity, and 20% reduction in loop coupling compared with conventional array structures of the same size) for small animal imaging with a robust RF configuration. The GPU-enabled acceleration paves the way for FDTD to be applied for both detailed forward modeling and inverse design of MRI coils, which were previously impractical.

National Laboratory for Advanced Scientific Visualization at UNAM - Mexico

NASA Astrophysics Data System (ADS)

Manea, Marina; Constantin Manea, Vlad; Varela, Alfredo

2016-04-01

In 2015, the National Autonomous University of Mexico (UNAM) joined the family of Universities and Research Centers where advanced visualization and computing plays a key role to promote and advance missions in research, education, community outreach, as well as business-oriented consulting. This initiative provides access to a great variety of advanced hardware and software resources and offers a range of consulting services that spans a variety of areas related to scientific visualization, among which are: neuroanatomy, embryonic development, genome related studies, geosciences, geography, physics and mathematics related disciplines. The National Laboratory for Advanced Scientific Visualization delivers services through three main infrastructure environments: the 3D fully immersive display system Cave, the high resolution parallel visualization system Powerwall, the high resolution spherical displays Earth Simulator. The entire visualization infrastructure is interconnected to a high-performance-computing-cluster (HPCC) called ADA in honor to Ada Lovelace, considered to be the first computer programmer. The Cave is an extra large 3.6m wide room with projected images on the front, left and right, as well as floor walls. Specialized crystal eyes LCD-shutter glasses provide a strong stereo depth perception, and a variety of tracking devices allow software to track the position of a user's hand, head and wand. The Powerwall is designed to bring large amounts of complex data together through parallel computing for team interaction and collaboration. This system is composed by 24 (6x4) high-resolution ultra-thin (2 mm) bezel monitors connected to a high-performance GPU cluster. The Earth Simulator is a large (60") high-resolution spherical display used for global-scale data visualization like geophysical, meteorological, climate and ecology data. The HPCC-ADA, is a 1000+ computing core system, which offers parallel computing resources to applications that requires large quantity of memory as well as large and fast parallel storage systems. The entire system temperature is controlled by an energy and space efficient cooling solution, based on large rear door liquid cooled heat exchangers. This state-of-the-art infrastructure will boost research activities in the region, offer a powerful scientific tool for teaching at undergraduate and graduate levels, and enhance association and cooperation with business-oriented organizations.

Learning and Parallelization Boost Constraint Search

ERIC Educational Resources Information Center

Yun, Xi

2013-01-01

Constraint satisfaction problems are a powerful way to abstract and represent academic and real-world problems from both artificial intelligence and operations research. A constraint satisfaction problem is typically addressed by a sequential constraint solver running on a single processor. Rather than construct a new, parallel solver, this work…

GASPRNG: GPU accelerated scalable parallel random number generator library

NASA Astrophysics Data System (ADS)

Gao, Shuang; Peterson, Gregory D.

2013-04-01

Graphics processors represent a promising technology for accelerating computational science applications. Many computational science applications require fast and scalable random number generation with good statistical properties, so they use the Scalable Parallel Random Number Generators library (SPRNG). We present the GPU Accelerated SPRNG library (GASPRNG) to accelerate SPRNG in GPU-based high performance computing systems. GASPRNG includes code for a host CPU and CUDA code for execution on NVIDIA graphics processing units (GPUs) along with a programming interface to support various usage models for pseudorandom numbers and computational science applications executing on the CPU, GPU, or both. This paper describes the implementation approach used to produce high performance and also describes how to use the programming interface. The programming interface allows a user to be able to use GASPRNG the same way as SPRNG on traditional serial or parallel computers as well as to develop tightly coupled programs executing primarily on the GPU. We also describe how to install GASPRNG and use it. To help illustrate linking with GASPRNG, various demonstration codes are included for the different usage models. GASPRNG on a single GPU shows up to 280x speedup over SPRNG on a single CPU core and is able to scale for larger systems in the same manner as SPRNG. Because GASPRNG generates identical streams of pseudorandom numbers as SPRNG, users can be confident about the quality of GASPRNG for scalable computational science applications. Catalogue identifier: AEOI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOI_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: UTK license. No. of lines in distributed program, including test data, etc.: 167900 No. of bytes in distributed program, including test data, etc.: 1422058 Distribution format: tar.gz Programming language: C and CUDA. Computer: Any PC or workstation with NVIDIA GPU (Tested on Fermi GTX480, Tesla C1060, Tesla M2070). Operating system: Linux with CUDA version 4.0 or later. Should also run on MacOS, Windows, or UNIX. Has the code been vectorized or parallelized?: Yes. Parallelized using MPI directives. RAM: 512 MB˜ 732 MB (main memory on host CPU, depending on the data type of random numbers.) / 512 MB (GPU global memory) Classification: 4.13, 6.5. Nature of problem: Many computational science applications are able to consume large numbers of random numbers. For example, Monte Carlo simulations are able to consume limitless random numbers for the computation as long as resources for the computing are supported. Moreover, parallel computational science applications require independent streams of random numbers to attain statistically significant results. The SPRNG library provides this capability, but at a significant computational cost. The GASPRNG library presented here accelerates the generators of independent streams of random numbers using graphical processing units (GPUs). Solution method: Multiple copies of random number generators in GPUs allow a computational science application to consume large numbers of random numbers from independent, parallel streams. GASPRNG is a random number generators library to allow a computational science application to employ multiple copies of random number generators to boost performance. Users can interface GASPRNG with software code executing on microprocessors and/or GPUs. Running time: The tests provided take a few minutes to run.

Integrating DC/DC Conversion with Possible Reconfiguration within Submodule Solar Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Huang, Peter Jen-Hung

This research first proposes a method to merge photovoltaic (PV) cells or PV panels within the internal components DC-DC converters. The purpose of this merged structure is to reconfigure the PV modules between series and parallel connections using high switching frequencies (hundreds of kHz). This leads to multi-levels of voltages and currents that become applied to the output filter of the converter. Further, this research introduces a concept of a switching cell that utilizes the reconfiguration of series and parallel connections in DC-DC converters. The switching occurs at high switching frequency and the switches can be integrated to be within the solar panels or in between the solar cells. The concept is generalized and applied to basic buck and boost topologies. As examples of the new types of converters: reconfigurable PV-buck and PV-boost converter topologies are presented. It is also possible to create other reconfigurable power converters: non-isolated and isolated topologies. Analysis, simulation and experimental verification for the reconfigurable PV-buck and PV-boost converters are presented extensively to illustrate proof of concept. Benefits and drawbacks of the new approach are discussed. The second part of this research proposes to utilize the internal solar cell capacitance and internal solar module wire parasitic inductances to replace the input capacitor and filter inductor in boost derived DC-DC converters for energy harvesting applications. High switching frequency (MHz) hard switched and resonant boost converters are proposed. Their analysis, simulation and experimental prototypes are presented. A specific proof-of-concept application is especially tested for foldable PV panels, which are known for their high internal wire inductance. The experimental converters successfully boost solar module voltage without adding any external input capacitance or filter inductor. Benefits and drawbacks of new proposed PV submodule integrated boost converters are discussed.

Treatment Techniques and Site Considerations Regarding Dysphagia-Related Quality of Life in Cancer of the Oropharynx and Nasopharynx

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

Teguh, David N.; Levendag, Peter C.; Noever, Inge

2008-11-15

Purpose: To assess the relationship for oropharyngeal (OP) cancer and nasopharyngeal (NP) cancer between the dose received by the swallowing structures and the dysphagia related quality of life (QoL). Methods and Materials: Between 2000 and 2005, 85 OP and 47 NP cancer patients were treated by radiation therapy. After 46 Gy, OP cancer is boosted by intensity-modulated radiation therapy (IMRT), brachytherapy (BT), or frameless stereotactic radiation/cyberknife (CBK). After 46 Gy, the NP cancer was boosted with parallel-opposed fields or IMRT to a total dose of 70 Gy; subsequently, a second boost was given by either BT (11 Gy) or stereotacticmore » radiation (SRT)/CBK (11.2 Gy). Sixty OP and 21 NP cancer patients responded to functional and QoL questionnaires (i.e., the Performance Status Scales, European Organization for Research and Treatment of Cancer H and N35, and M.D. Anderson Dysphagia Inventory). The swallowing muscles were delineated and the mean dose calculated using the original three-dimensional computed tomography-based treatment plans. Univariate analyses were performed using logistic regression analysis. Results: Most dysphagia problems were observed in the base of tongue tumors. For OP cancer, boosting with IMRT resulted in more dysphagia as opposed to BT or SRT/CBK. For NPC patients, in contrast to the first booster dose (46-70 Gy), no additional increase of dysphagia by the second boost was observed. Conclusions: The lowest mean doses of radiation to the swallowing muscles were achieved when using BT as opposed to SRT/CBK or IMRT. For the 81 patients alive with no evidence of disease for at least 1 year, a dose-effect relationship was observed between the dose in the superior constrictor muscle and the 'normalcy of diet' (Performance Status Scales) or 'swallowing scale' (H and N35) scores (p < 0.01)« less

Discrete event performance prediction of speculatively parallel temperature-accelerated dynamics

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

Zamora, Richard James; Voter, Arthur F.; Perez, Danny

Due to its unrivaled ability to predict the dynamical evolution of interacting atoms, molecular dynamics (MD) is a widely used computational method in theoretical chemistry, physics, biology, and engineering. Despite its success, MD is only capable of modeling time scales within several orders of magnitude of thermal vibrations, leaving out many important phenomena that occur at slower rates. The Temperature Accelerated Dynamics (TAD) method overcomes this limitation by thermally accelerating the state-to-state evolution captured by MD. Due to the algorithmically complex nature of the serial TAD procedure, implementations have yet to improve performance by parallelizing the concurrent exploration of multiplemore » states. Here we utilize a discrete event-based application simulator to introduce and explore a new Speculatively Parallel TAD (SpecTAD) method. We investigate the SpecTAD algorithm, without a full-scale implementation, by constructing an application simulator proxy (SpecTADSim). Finally, following this method, we discover that a nontrivial relationship exists between the optimal SpecTAD parameter set and the number of CPU cores available at run-time. Furthermore, we find that a majority of the available SpecTAD boost can be achieved within an existing TAD application using relatively simple algorithm modifications.« less

Discrete event performance prediction of speculatively parallel temperature-accelerated dynamics

DOE PAGES

Zamora, Richard James; Voter, Arthur F.; Perez, Danny; ...

2016-12-01

Due to its unrivaled ability to predict the dynamical evolution of interacting atoms, molecular dynamics (MD) is a widely used computational method in theoretical chemistry, physics, biology, and engineering. Despite its success, MD is only capable of modeling time scales within several orders of magnitude of thermal vibrations, leaving out many important phenomena that occur at slower rates. The Temperature Accelerated Dynamics (TAD) method overcomes this limitation by thermally accelerating the state-to-state evolution captured by MD. Due to the algorithmically complex nature of the serial TAD procedure, implementations have yet to improve performance by parallelizing the concurrent exploration of multiplemore » states. Here we utilize a discrete event-based application simulator to introduce and explore a new Speculatively Parallel TAD (SpecTAD) method. We investigate the SpecTAD algorithm, without a full-scale implementation, by constructing an application simulator proxy (SpecTADSim). Finally, following this method, we discover that a nontrivial relationship exists between the optimal SpecTAD parameter set and the number of CPU cores available at run-time. Furthermore, we find that a majority of the available SpecTAD boost can be achieved within an existing TAD application using relatively simple algorithm modifications.« less

Lorentz boosted frame simulation technique in Particle-in-cell methods

NASA Astrophysics Data System (ADS)

Yu, Peicheng

In this dissertation, we systematically explore the use of a simulation method for modeling laser wakefield acceleration (LWFA) using the particle-in-cell (PIC) method, called the Lorentz boosted frame technique. In the lab frame the plasma length is typically four orders of magnitude larger than the laser pulse length. Using this technique, simulations are performed in a Lorentz boosted frame in which the plasma length, which is Lorentz contracted, and the laser length, which is Lorentz expanded, are now comparable. This technique has the potential to reduce the computational needs of a LWFA simulation by more than four orders of magnitude, and is useful if there is no or negligible reflection of the laser in the lab frame. To realize the potential of Lorentz boosted frame simulations for LWFA, the first obstacle to overcome is a robust and violent numerical instability, called the Numerical Cerenkov Instability (NCI), that leads to unphysical energy exchange between relativistically drifting particles and their radiation. This leads to unphysical noise that dwarfs the real physical processes. In this dissertation, we first present a theoretical analysis of this instability, and show that the NCI comes from the unphysical coupling of the electromagnetic (EM) modes and Langmuir modes (both main and aliasing) of the relativistically drifting plasma. We then discuss the methods to eliminate them. However, the use of FFTs can lead to parallel scalability issues when there are many more cells along the drifting direction than in the transverse direction(s). We then describe an algorithm that has the potential to address this issue by using a higher order finite difference operator for the derivative in the plasma drifting direction, while using the standard second order operators in the transverse direction(s). The NCI for this algorithm is analyzed, and it is shown that the NCI can be eliminated using the same strategies that were used for the hybrid FFT/Finite Difference solver. This scheme also requires a current correction and filtering which require FFTs. However, we show that in this case the FFTs can be done locally on each parallel partition. We also describe how the use of the hybrid FFT/Finite Difference or the hybrid higher order finite difference/second order finite difference methods permit combining the Lorentz boosted frame simulation technique with another "speed up" technique, called the quasi-3D algorithm, to gain unprecedented speed up for the LWFA simulations. In the quasi-3D algorithm the fields and currents are defined on an r--z PIC grid and expanded in azimuthal harmonics. The expansion is truncated with only a few modes so it has similar computational needs of a 2D r--z PIC code. We show that NCI has similar properties in r--z as in z-x slab geometry and show that the same strategies for eliminating the NCI in Cartesian geometry can be effective for the quasi-3D algorithm leading to the possibility of unprecedented speed up. We also describe a new code called UPIC-EMMA that is based on fully spectral (FFT) solver. The new code includes implementation of a moving antenna that can launch lasers in the boosted frame. We also describe how the new hybrid algorithms were implemented into OSIRIS. Examples of LWFA using the boosted frame using both UPIC-EMMA and OSIRIS are given, including the comparisons against the lab frame results. We also describe how to efficiently obtain the boosted frame simulations data that are needed to generate the transformed lab frame data, as well as how to use a moving window in the boosted frame. The NCI is also a major issue for modeling relativistic shocks with PIC algorithm. In relativistic shock simulations two counter-propagating plasmas drifting at relativistic speeds are colliding against each other. We show that the strategies for eliminating the NCI developed in this dissertation are enabling such simulations being run for much longer simulation times, which should open a path for major advances in relativistic shock research. (Abstract shortened by ProQuest.).

RBOOST: RIEMANNIAN DISTANCE BASED REGULARIZED BOOSTING

PubMed Central

Liu, Meizhu; Vemuri, Baba C.

2011-01-01

Boosting is a versatile machine learning technique that has numerous applications including but not limited to image processing, computer vision, data mining etc. It is based on the premise that the classification performance of a set of weak learners can be boosted by some weighted combination of them. There have been a number of boosting methods proposed in the literature, such as the AdaBoost, LPBoost, SoftBoost and their variations. However, the learning update strategies used in these methods usually lead to overfitting and instabilities in the classification accuracy. Improved boosting methods via regularization can overcome such difficulties. In this paper, we propose a Riemannian distance regularized LPBoost, dubbed RBoost. RBoost uses Riemannian distance between two square-root densities (in closed form) – used to represent the distribution over the training data and the classification error respectively – to regularize the error distribution in an iterative update formula. Since this distance is in closed form, RBoost requires much less computational cost compared to other regularized Boosting algorithms. We present several experimental results depicting the performance of our algorithm in comparison to recently published methods, LP-Boost and CAVIAR, on a variety of datasets including the publicly available OASIS database, a home grown Epilepsy database and the well known UCI repository. Results depict that the RBoost algorithm performs better than the competing methods in terms of accuracy and efficiency. PMID:21927643

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

PubMed

Zheng, Qi; Grice, Elizabeth A

2016-10-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.

CUDAMPF: a multi-tiered parallel framework for accelerating protein sequence search in HMMER on CUDA-enabled GPU.

PubMed

Jiang, Hanyu; Ganesan, Narayan

2016-02-27

HMMER software suite is widely used for analysis of homologous protein and nucleotide sequences with high sensitivity. The latest version of hmmsearch in HMMER 3.x, utilizes heuristic-pipeline which consists of MSV/SSV (Multiple/Single ungapped Segment Viterbi) stage, P7Viterbi stage and the Forward scoring stage to accelerate homology detection. Since the latest version is highly optimized for performance on modern multi-core CPUs with SSE capabilities, only a few acceleration attempts report speedup. However, the most compute intensive tasks within the pipeline (viz., MSV/SSV and P7Viterbi stages) still stand to benefit from the computational capabilities of massively parallel processors. A Multi-Tiered Parallel Framework (CUDAMPF) implemented on CUDA-enabled GPUs presented here, offers a finer-grained parallelism for MSV/SSV and Viterbi algorithms. We couple SIMT (Single Instruction Multiple Threads) mechanism with SIMD (Single Instructions Multiple Data) video instructions with warp-synchronism to achieve high-throughput processing and eliminate thread idling. We also propose a hardware-aware optimal allocation scheme of scarce resources like on-chip memory and caches in order to boost performance and scalability of CUDAMPF. In addition, runtime compilation via NVRTC available with CUDA 7.0 is incorporated into the presented framework that not only helps unroll innermost loop to yield upto 2 to 3-fold speedup than static compilation but also enables dynamic loading and switching of kernels depending on the query model size, in order to achieve optimal performance. CUDAMPF is designed as a hardware-aware parallel framework for accelerating computational hotspots within the hmmsearch pipeline as well as other sequence alignment applications. It achieves significant speedup by exploiting hierarchical parallelism on single GPU and takes full advantage of limited resources based on their own performance features. In addition to exceeding performance of other acceleration attempts, comprehensive evaluations against high-end CPUs (Intel i5, i7 and Xeon) shows that CUDAMPF yields upto 440 GCUPS for SSV, 277 GCUPS for MSV and 14.3 GCUPS for P7Viterbi all with 100 % accuracy, which translates to a maximum speedup of 37.5, 23.1 and 11.6-fold for MSV, SSV and P7Viterbi respectively. The source code is available at https://github.com/Super-Hippo/CUDAMPF.

Boosted protease inhibitor monotherapy versus boosted protease inhibitor plus lamivudine dual therapy as second-line maintenance treatment for HIV-1-infected patients in sub-Saharan Africa (ANRS12 286/MOBIDIP): a multicentre, randomised, parallel, open-label, superiority trial.

PubMed

Ciaffi, Laura; Koulla-Shiro, Sinata; Sawadogo, Adrien Bruno; Ndour, Cheik Tidiane; Eymard-Duvernay, Sabrina; Mbouyap, Pretty Rosereine; Ayangma, Liliane; Zoungrana, Jacques; Gueye, Ndeye Fatou Ngom; Diallo, Mohamadou; Izard, Suzanne; Bado, Guillaume; Kane, Coumba Toure; Aghokeng, Avelin Fobang; Peeters, Martine; Girard, Pierre Marie; Le Moing, Vincent; Reynes, Jacques; Delaporte, Eric

2017-09-01

Despite satisfactory efficacy of WHO-recommended second-line antiretroviral treatment for patients with HIV in low-income countries, the need for simplified, low-cost, and less-toxic maintenance strategies remains high. We compared boosted protease inhibitor monotherapy with dual therapy with boosted protease inhibitor plus lamivudine in patients on second-line antiretrovial therapy (ART). We did a multicentre, randomised, parallel, open-label, superiority, trial in the HIV services of five hospitals in sub-Saharan Africa (Yaoundé, Cameroon; Dakar, Senegal; and Bobo Dioulasso, Burkina Faso). We recruited patients from the long-term, post-trial cohort of the ANRS 12169/2LADY study that compared the efficacy of three second-line combinations based on boosted protease inhibitors. Participants for our study were HIV-1 infected with multiple mutations including M184V, at first-line failure, aged 18 years and older, on boosted protease inhibitor plus two nucleoside reverse transcriptase inhibitors (NRTI) for at least 48 weeks with at least 48 weeks follow-up in the 2LADY trial, with two viral load measurements of less than 200 copies per mL in the previous 6 months, CD4 counts of more than 100 cells per μL, adherence of at least 90%, and no change to ART in the past 3 months. We randomly assigned participants (1:1) to receive either monotherapy with their boosted protease inhibitor (once-daily darunavir 800 mg [two 400 mg tablets] boosted with ritonavir 100 mg [one tablet] or coformulation of lopinavir 200 mg with ritonavir 50 mg [two tablets taken twice per day]) or to boosted protease inhibitor plus once-daily lamivudine 300 mg (one 300 mg tablet or two 150 mg tablets). Computer-generated randomisation was stratified by study site and viral load at screening (< 50 copies per mL, and 50-200 copies per mL), and concealed from study personnel throughout the inclusion period. After randomisation, treatment allocation was not masked from clinicians or patients]. Patients had follow-up visits at weeks 4 and 12, and every 3 months until 96 weeks; if viral load exceeded 500 copies per mL at any visit, NRTI (tenofovir and lamivudine) were reintroduced into treatment. The primary outcome was the proportion of participants who had treatment failure at 96 weeks in the intention-to-treat analysis, where treatment failure was defined as one of the following: a confirmed viral load of more than 500 copies per mL, reintroduction of NRTI, or interruption of boosted protease inhibitor. We designed the study to detect a difference of 12% between groups in the primary outcome, with an expected 20% of patients having treatment failure in the monotherapy group. This study is registered with ClinicalTrials.gov, number NCT01905059. Between March 5, 2014, and Jan 26, 2015, 265 participants were assigned to receive monotherapy (133) or boosted protease inhibitor plus lamivudine (132). At week 48, an independent data safety monitoring board reviewed data, and advised discontinuation of the monotherapy group because the number of failures had exceeded the expected 20%; therefore results here are for week 48. At this point, treatment failure occurred in four (3·0%; 95% CI 0·8-7·6) of 132 participants on dual therapy and 33 (24·8%; 17·7-33·0) of 133 participants on monotherapy (relative risk 8·2, 95% CI 3·0-22·5; odds ratio 10·6, 95% CI 3·6-42·1). The difference between groups (21·8%, 95% CI 13·9-29·7; p<0·0001) showed superiority of dual therapy compared with monotherapy. We recorded 46 severe adverse events of grade 3 or 4 (29 in the monotherapy group, 17 in the boosted protease inhibitor plus lamivudine group); one event in the montherapy group (intoxication resulting from co-administration of ritonavir-boosted lopinavir with an ergotamine derivate) was deemed related to study drug. Two participants in the monotherapy group and one in the dual therapy group died, all from causes not related to study drugs or procedures (one from complications from gastric cancer surgery, one in a work accident, and one from a lung disease of unknown cause). After viral suppression with boosted protease inhibitor plus NRTI in second-line ART, maintenance therapy with boosted protease inhibitor plus lamivudine was associated with a high rate of success, despite the presence of M184V mutations at first-line treatment failure. Results indicated that boosted protease inhibitor monotherapy cannot be recommended for these patients. Agence National de Recherche sur le Sida et les hépatites and Janssen Pharmaceutica. Copyright © 2017 Elsevier Ltd. All rights reserved.

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework

PubMed Central

Zheng, Qi; Grice, Elizabeth A.

2016-01-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost’s algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost. PMID:27706155

Collectively loading an application in a parallel computer

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

Aho, Michael E.; Attinella, John E.; Gooding, Thomas M.

Collectively loading an application in a parallel computer, the parallel computer comprising a plurality of compute nodes, including: identifying, by a parallel computer control system, a subset of compute nodes in the parallel computer to execute a job; selecting, by the parallel computer control system, one of the subset of compute nodes in the parallel computer as a job leader compute node; retrieving, by the job leader compute node from computer memory, an application for executing the job; and broadcasting, by the job leader to the subset of compute nodes in the parallel computer, the application for executing the job.

Limits to high-speed simulations of spiking neural networks using general-purpose computers.

PubMed

Zenke, Friedemann; Gerstner, Wulfram

2014-01-01

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

Monte Carlo MP2 on Many Graphical Processing Units.

PubMed

Doran, Alexander E; Hirata, So

2016-10-11

In the Monte Carlo second-order many-body perturbation (MC-MP2) method, the long sum-of-product matrix expression of the MP2 energy, whose literal evaluation may be poorly scalable, is recast into a single high-dimensional integral of functions of electron pair coordinates, which is evaluated by the scalable method of Monte Carlo integration. The sampling efficiency is further accelerated by the redundant-walker algorithm, which allows a maximal reuse of electron pairs. Here, a multitude of graphical processing units (GPUs) offers a uniquely ideal platform to expose multilevel parallelism: fine-grain data-parallelism for the redundant-walker algorithm in which millions of threads compute and share orbital amplitudes on each GPU; coarse-grain instruction-parallelism for near-independent Monte Carlo integrations on many GPUs with few and infrequent interprocessor communications. While the efficiency boost by the redundant-walker algorithm on central processing units (CPUs) grows linearly with the number of electron pairs and tends to saturate when the latter exceeds the number of orbitals, on a GPU it grows quadratically before it increases linearly and then eventually saturates at a much larger number of pairs. This is because the orbital constructions are nearly perfectly parallelized on a GPU and thus completed in a near-constant time regardless of the number of pairs. In consequence, an MC-MP2/cc-pVDZ calculation of a benzene dimer is 2700 times faster on 256 GPUs (using 2048 electron pairs) than on two CPUs, each with 8 cores (which can use only up to 256 pairs effectively). We also numerically determine that the cost to achieve a given relative statistical uncertainty in an MC-MP2 energy increases as O(n 3 ) or better with system size n, which may be compared with the O(n 5 ) scaling of the conventional implementation of deterministic MP2. We thus establish the scalability of MC-MP2 with both system and computer sizes.

Use of nonlinear design optimization techniques in the comparison of battery discharger topologies for the space platform

NASA Technical Reports Server (NTRS)

Sable, Dan M.; Cho, Bo H.; Lee, Fred C.

1990-01-01

A detailed comparison of a boost converter, a voltage-fed, autotransformer converter, and a multimodule boost converter, designed specifically for the space platform battery discharger, is performed. Computer-based nonlinear optimization techniques are used to facilitate an objective comparison. The multimodule boost converter is shown to be the optimum topology at all efficiencies. The margin is greatest at 97 percent efficiency. The multimodule, multiphase boost converter combines the advantages of high efficiency, light weight, and ample margin on the component stresses, thus ensuring high reliability.

Analysis and design of a high power, digitally-controlled spacecraft power system

NASA Technical Reports Server (NTRS)

Lee, F. C.; Cho, B. H.

1990-01-01

The progress to date on the analysis and design of a high power, digitally controlled spacecraft power system is described. Several battery discharger topologies were compared for use in the space platform application. Updated information has been provided on the battery voltage specification. Initially it was thought to be in the 30 to 40 V range. It is now specified to be 53 V to 84 V. This eliminated the tapped-boost and the current-fed auto-transformer converters from consideration. After consultations with NASA, it was decided to trade-off the following topologies: (1) boost converter; (2) multi-module, multi-phase boost converter; and (3) voltage-fed push-pull with auto-transformer. A non-linear design optimization software tool was employed to facilitate an objective comparison. Non-linear design optimization insures that the best design of each topology is compared. The results indicate that a four-module, boost converter with each module operating 90 degrees out of phase is the optimum converter for the space platform. Large-signal and small-signal models were generated for the shunt, charger, discharger, battery, and the mode controller. The models were first tested individually according to the space platform power system specifications supplied by NASA. The effect of battery voltage imbalance on parallel dischargers was investigated with respect to dc and small-signal responses. Similarly, the effects of paralleling dischargers and chargers were also investigated. A solar array and shunt model was included in these simulations. A model for the bus mode controller (power control unit) was also developed to interface the Orbital replacement Unit (ORU) model to the platform power system. Small signal models were used to generate the bus impedance plots in the various operating modes. The large signal models were integrated into a system model, and time domain simulations were performed to verify bus regulation during mode transitions. Some changes have subsequently been incorporated into the models. The changes include the use of a four module boost discharger, and a new model for the mode controller, which includes the effects of saturation. The new simulations for the boost discharger show the improvement in bus ripple that can be achieved by phase-shifted operation of each of the boost modules.

Global Dirac bispinor entanglement under Lorentz boosts

NASA Astrophysics Data System (ADS)

Bittencourt, Victor A. S. V.; Bernardini, Alex E.; Blasone, Massimo

2018-03-01

The effects of Lorentz boosts on the quantum entanglement encoded by a pair of massive spin-1/2 particles are described according to the Lorentz covariant structure described by Dirac bispinors. The quantum system considered incorporates four degrees of freedom: two of them related to the bispinor intrinsic parity and the other two related to the bispinor spin projection, i.e., the Dirac particle helicity. Because of the natural multipartite structure involved, the Meyer-Wallach global measure of entanglement is preliminarily used for computing global quantum correlations, while the entanglement separately encoded by spin degrees of freedom is measured through the negativity of the reduced two-particle spin-spin state. A general framework to compute the changes on quantum entanglement induced by a boost is developed and then specialized to describe three particular antisymmetric two-particle states. According to the results obtained, two-particle spin-spin entanglement cannot be created by the action of a Lorentz boost in a spin-spin separable antisymmetric state. On the other hand, the maximal spin-spin entanglement encoded by antisymmetric superpositions is degraded by Lorentz boosts driven by high-speed frame transformations. Finally, the effects of boosts on chiral states are shown to exhibit interesting invariance properties, which can only be obtained through such a Lorentz covariant formulation of the problem.

Aggregating job exit statuses of a plurality of compute nodes executing a parallel application

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

Aho, Michael E.; Attinella, John E.; Gooding, Thomas M.

Aggregating job exit statuses of a plurality of compute nodes executing a parallel application, including: identifying a subset of compute nodes in the parallel computer to execute the parallel application; selecting one compute node in the subset of compute nodes in the parallel computer as a job leader compute node; initiating execution of the parallel application on the subset of compute nodes; receiving an exit status from each compute node in the subset of compute nodes, where the exit status for each compute node includes information describing execution of some portion of the parallel application by the compute node; aggregatingmore » each exit status from each compute node in the subset of compute nodes; and sending an aggregated exit status for the subset of compute nodes in the parallel computer.« less

EDIN design study alternate space shuttle booster replacement concepts. Volume 1: Engineering analysis

NASA Technical Reports Server (NTRS)

Demakes, P. T.; Hirsch, G. N.; Stewart, W. A.; Glatt, C. R.

1976-01-01

The use of a recoverable liquid rocket booster (LRB) system to replace the existing solid rocket booster (SRB) system for the shuttle was studied. Historical weight estimating relationships were developed for the LRB using Saturn technology and modified as required. Mission performance was computed using February 1975 shuttle configuration groundrules to allow reasonable comparison of the existing shuttle with the study designs. The launch trajectory was constrained to pass through both the RTLS/AOA and main engine cut off points of the shuttle reference mission 1. Performance analysis is based on a point design trajectory model which optimizes initial tilt rate and exoatmospheric pitch profile. A gravity turn was employed during the boost phase in place of the shuttle angle of attack profile. Engine throttling add/or shutdown was used to constrain dynamic pressure and/or longitudinal acceleration where necessary. Four basic configurations were investigated: a parallel burn vehicle with an F-1 engine powered LRB; a parallel burn vehicle with a high pressure engine powered LRB; a series burn vehicle with a high pressure engine powered LRB. The relative sizes of the LRB and the ET are optimized to minimize GLOW in most cases.

Research on the supercapacitor support schemes for LVRT of variable-frequency drive in the thermal power plant

NASA Astrophysics Data System (ADS)

Han, Qiguo; Zhu, Kai; Shi, Wenming; Wu, Kuayu; Chen, Kai

2018-02-01

In order to solve the problem of low voltage ride through(LVRT) of the major auxiliary equipment’s variable-frequency drive (VFD) in thermal power plant, the scheme of supercapacitor paralleled in the DC link of VFD is put forward, furthermore, two solutions of direct parallel support and voltage boost parallel support of supercapacitor are proposed. The capacitor values for the relevant motor loads are calculated according to the law of energy conservation, and they are verified by Matlab simulation. At last, a set of test prototype is set up, and the test results prove the feasibility of the proposed schemes.

Rebooting Computers as Learning Machines

DOE PAGES

DeBenedictis, Erik P.

2016-06-13

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

Rebooting Computers as Learning Machines

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

DeBenedictis, Erik P.

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

Evaluating architecture impact on system energy efficiency

PubMed Central

Yu, Shijie; Wang, Rui; Luan, Zhongzhi; Qian, Depei

2017-01-01

As the energy consumption has been surging in an unsustainable way, it is important to understand the impact of existing architecture designs from energy efficiency perspective, which is especially valuable for High Performance Computing (HPC) and datacenter environment hosting tens of thousands of servers. One obstacle hindering the advance of comprehensive evaluation on energy efficiency is the deficient power measuring approach. Most of the energy study relies on either external power meters or power models, both of these two methods contain intrinsic drawbacks in their practical adoption and measuring accuracy. Fortunately, the advent of Intel Running Average Power Limit (RAPL) interfaces has promoted the power measurement ability into next level, with higher accuracy and finer time resolution. Therefore, we argue it is the exact time to conduct an in-depth evaluation of the existing architecture designs to understand their impact on system energy efficiency. In this paper, we leverage representative benchmark suites including serial and parallel workloads from diverse domains to evaluate the architecture features such as Non Uniform Memory Access (NUMA), Simultaneous Multithreading (SMT) and Turbo Boost. The energy is tracked at subcomponent level such as Central Processing Unit (CPU) cores, uncore components and Dynamic Random-Access Memory (DRAM) through exploiting the power measurement ability exposed by RAPL. The experiments reveal non-intuitive results: 1) the mismatch between local compute and remote memory node caused by NUMA effect not only generates dramatic power and energy surge but also deteriorates the energy efficiency significantly; 2) for multithreaded application such as the Princeton Application Repository for Shared-Memory Computers (PARSEC), most of the workloads benefit a notable increase of energy efficiency using SMT, with more than 40% decline in average power consumption; 3) Turbo Boost is effective to accelerate the workload execution and further preserve the energy, however it may not be applicable on system with tight power budget. PMID:29161317

Evaluating architecture impact on system energy efficiency.

PubMed

Yu, Shijie; Yang, Hailong; Wang, Rui; Luan, Zhongzhi; Qian, Depei

2017-01-01

As the energy consumption has been surging in an unsustainable way, it is important to understand the impact of existing architecture designs from energy efficiency perspective, which is especially valuable for High Performance Computing (HPC) and datacenter environment hosting tens of thousands of servers. One obstacle hindering the advance of comprehensive evaluation on energy efficiency is the deficient power measuring approach. Most of the energy study relies on either external power meters or power models, both of these two methods contain intrinsic drawbacks in their practical adoption and measuring accuracy. Fortunately, the advent of Intel Running Average Power Limit (RAPL) interfaces has promoted the power measurement ability into next level, with higher accuracy and finer time resolution. Therefore, we argue it is the exact time to conduct an in-depth evaluation of the existing architecture designs to understand their impact on system energy efficiency. In this paper, we leverage representative benchmark suites including serial and parallel workloads from diverse domains to evaluate the architecture features such as Non Uniform Memory Access (NUMA), Simultaneous Multithreading (SMT) and Turbo Boost. The energy is tracked at subcomponent level such as Central Processing Unit (CPU) cores, uncore components and Dynamic Random-Access Memory (DRAM) through exploiting the power measurement ability exposed by RAPL. The experiments reveal non-intuitive results: 1) the mismatch between local compute and remote memory node caused by NUMA effect not only generates dramatic power and energy surge but also deteriorates the energy efficiency significantly; 2) for multithreaded application such as the Princeton Application Repository for Shared-Memory Computers (PARSEC), most of the workloads benefit a notable increase of energy efficiency using SMT, with more than 40% decline in average power consumption; 3) Turbo Boost is effective to accelerate the workload execution and further preserve the energy, however it may not be applicable on system with tight power budget.

Enabling High-performance Interactive Geoscience Data Analysis Through Data Placement and Movement Optimization

NASA Astrophysics Data System (ADS)

Zhu, F.; Yu, H.; Rilee, M. L.; Kuo, K. S.; Yu, L.; Pan, Y.; Jiang, H.

2017-12-01

Since the establishment of data archive centers and the standardization of file formats, scientists are required to search metadata catalogs for data needed and download the data files to their local machines to carry out data analysis. This approach has facilitated data discovery and access for decades, but it inevitably leads to data transfer from data archive centers to scientists' computers through low-bandwidth Internet connections. Data transfer becomes a major performance bottleneck in such an approach. Combined with generally constrained local compute/storage resources, they limit the extent of scientists' studies and deprive them of timely outcomes. Thus, this conventional approach is not scalable with respect to both the volume and variety of geoscience data. A much more viable solution is to couple analysis and storage systems to minimize data transfer. In our study, we compare loosely coupled approaches (exemplified by Spark and Hadoop) and tightly coupled approaches (exemplified by parallel distributed database management systems, e.g., SciDB). In particular, we investigate the optimization of data placement and movement to effectively tackle the variety challenge, and boost the popularization of parallelization to address the volume challenge. Our goal is to enable high-performance interactive analysis for a good portion of geoscience data analysis exercise. We show that tightly coupled approaches can concentrate data traffic between local storage systems and compute units, and thereby optimizing bandwidth utilization to achieve a better throughput. Based on our observations, we develop a geoscience data analysis system that tightly couples analysis engines with storages, which has direct access to the detailed map of data partition locations. Through an innovation data partitioning and distribution scheme, our system has demonstrated scalable and interactive performance in real-world geoscience data analysis applications.

A High Voltage Ratio and Low Ripple Interleaved DC-DC Converter for Fuel Cell Applications

PubMed Central

Chang, Long-Yi; Chao, Kuei-Hsiang; Chang, Tsang-Chih

2012-01-01

This paper proposes a high voltage ratio and low ripple interleaved boost DC-DC converter, which can be used to reduce the output voltage ripple. This converter transfers the low DC voltage of fuel cell to high DC voltage in DC link. The structure of the converter is parallel with two voltage-doubler boost converters by interleaving their output voltages to reduce the voltage ripple ratio. Besides, it can lower the current stress for the switches and inductors in the system. First, the PSIM software was used to establish a proton exchange membrane fuel cell and a converter circuit model. The simulated and measured results of the fuel cell output characteristic curve are made to verify the correctness of the established simulation model. In addition, some experimental results are made to validate the effectiveness in improving output voltage ripple of the proposed high voltage ratio interleaved boost DC-DC converters. PMID:23365536

A high voltage ratio and low ripple interleaved DC-DC converter for fuel cell applications.

PubMed

Chang, Long-Yi; Chao, Kuei-Hsiang; Chang, Tsang-Chih

2012-01-01

This paper proposes a high voltage ratio and low ripple interleaved boost DC-DC converter, which can be used to reduce the output voltage ripple. This converter transfers the low DC voltage of fuel cell to high DC voltage in DC link. The structure of the converter is parallel with two voltage-doubler boost converters by interleaving their output voltages to reduce the voltage ripple ratio. Besides, it can lower the current stress for the switches and inductors in the system. First, the PSIM software was used to establish a proton exchange membrane fuel cell and a converter circuit model. The simulated and measured results of the fuel cell output characteristic curve are made to verify the correctness of the established simulation model. In addition, some experimental results are made to validate the effectiveness in improving output voltage ripple of the proposed high voltage ratio interleaved boost DC-DC converters.

A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising.

PubMed

Khan, Khan Bahadar; Khaliq, Amir A; Jalil, Abdul; Shahid, Muhammad

2018-01-01

The exploration of retinal vessel structure is colossally important on account of numerous diseases including stroke, Diabetic Retinopathy (DR) and coronary heart diseases, which can damage the retinal vessel structure. The retinal vascular network is very hard to be extracted due to its spreading and diminishing geometry and contrast variation in an image. The proposed technique consists of unique parallel processes for denoising and extraction of blood vessels in retinal images. In the preprocessing section, an adaptive histogram equalization enhances dissimilarity between the vessels and the background and morphological top-hat filters are employed to eliminate macula and optic disc, etc. To remove local noise, the difference of images is computed from the top-hat filtered image and the high-boost filtered image. Frangi filter is applied at multi scale for the enhancement of vessels possessing diverse widths. Segmentation is performed by using improved Otsu thresholding on the high-boost filtered image and Frangi's enhanced image, separately. In the postprocessing steps, a Vessel Location Map (VLM) is extracted by using raster to vector transformation. Postprocessing steps are employed in a novel way to reject misclassified vessel pixels. The final segmented image is obtained by using pixel-by-pixel AND operation between VLM and Frangi output image. The method has been rigorously analyzed on the STARE, DRIVE and HRF datasets.

Complexified boost invariance and holographic heavy ion collisions

DOE PAGES

Gubser, Steven S.; van der Schee, Wilke

2015-01-08

At strong coupling holographic studies have shown that heavy ion collisions do not obey normal boost invariance. Here we study a modified boost invariance through a complex shift in time, and show that this leads to surprisingly good agreement with numerical holographic computations. When including perturbations the agreement becomes even better, both in the hydrodynamic and the far-from-equilibrium regime. Finally, one of the main advantages is an analytic formulation of the stress-energy tensor of the longitudinal dynamics of holographic heavy ion collisions.

Parallel computational fluid dynamics '91; Conference Proceedings, Stuttgart, Germany, Jun. 10-12, 1991

NASA Technical Reports Server (NTRS)

Reinsch, K. G. (Editor); Schmidt, W. (Editor); Ecer, A. (Editor); Haeuser, Jochem (Editor); Periaux, J. (Editor)

1992-01-01

A conference was held on parallel computational fluid dynamics and produced related papers. Topics discussed in these papers include: parallel implicit and explicit solvers for compressible flow, parallel computational techniques for Euler and Navier-Stokes equations, grid generation techniques for parallel computers, and aerodynamic simulation om massively parallel systems.

The Research of the Parallel Computing Development from the Angle of Cloud Computing

NASA Astrophysics Data System (ADS)

Peng, Zhensheng; Gong, Qingge; Duan, Yanyu; Wang, Yun

2017-10-01

Cloud computing is the development of parallel computing, distributed computing and grid computing. The development of cloud computing makes parallel computing come into people’s lives. Firstly, this paper expounds the concept of cloud computing and introduces two several traditional parallel programming model. Secondly, it analyzes and studies the principles, advantages and disadvantages of OpenMP, MPI and Map Reduce respectively. Finally, it takes MPI, OpenMP models compared to Map Reduce from the angle of cloud computing. The results of this paper are intended to provide a reference for the development of parallel computing.

Spatial data analytics on heterogeneous multi- and many-core parallel architectures using python

USGS Publications Warehouse

Laura, Jason R.; Rey, Sergio J.

2017-01-01

Parallel vector spatial analysis concerns the application of parallel computational methods to facilitate vector-based spatial analysis. The history of parallel computation in spatial analysis is reviewed, and this work is placed into the broader context of high-performance computing (HPC) and parallelization research. The rise of cyber infrastructure and its manifestation in spatial analysis as CyberGIScience is seen as a main driver of renewed interest in parallel computation in the spatial sciences. Key problems in spatial analysis that have been the focus of parallel computing are covered. Chief among these are spatial optimization problems, computational geometric problems including polygonization and spatial contiguity detection, the use of Monte Carlo Markov chain simulation in spatial statistics, and parallel implementations of spatial econometric methods. Future directions for research on parallelization in computational spatial analysis are outlined.

Parallel ICA and its hardware implementation in hyperspectral image analysis

NASA Astrophysics Data System (ADS)

Du, Hongtao; Qi, Hairong; Peterson, Gregory D.

2004-04-01

Advances in hyperspectral images have dramatically boosted remote sensing applications by providing abundant information using hundreds of contiguous spectral bands. However, the high volume of information also results in excessive computation burden. Since most materials have specific characteristics only at certain bands, a lot of these information is redundant. This property of hyperspectral images has motivated many researchers to study various dimensionality reduction algorithms, including Projection Pursuit (PP), Principal Component Analysis (PCA), wavelet transform, and Independent Component Analysis (ICA), where ICA is one of the most popular techniques. It searches for a linear or nonlinear transformation which minimizes the statistical dependence between spectral bands. Through this process, ICA can eliminate superfluous but retain practical information given only the observations of hyperspectral images. One hurdle of applying ICA in hyperspectral image (HSI) analysis, however, is its long computation time, especially for high volume hyperspectral data sets. Even the most efficient method, FastICA, is a very time-consuming process. In this paper, we present a parallel ICA (pICA) algorithm derived from FastICA. During the unmixing process, pICA divides the estimation of weight matrix into sub-processes which can be conducted in parallel on multiple processors. The decorrelation process is decomposed into the internal decorrelation and the external decorrelation, which perform weight vector decorrelations within individual processors and between cooperative processors, respectively. In order to further improve the performance of pICA, we seek hardware solutions in the implementation of pICA. Until now, there are very few hardware designs for ICA-related processes due to the complicated and iterant computation. This paper discusses capacity limitation of FPGA implementations for pICA in HSI analysis. A synthesis of Application-Specific Integrated Circuit (ASIC) is designed for pICA-based dimensionality reduction in HSI analysis. The pICA design is implemented using standard-height cells and aimed at TSMC 0.18 micron process. During the synthesis procedure, three ICA-related reconfigurable components are developed for the reuse and retargeting purpose. Preliminary results show that the standard-height cell based ASIC synthesis provide an effective solution for pICA and ICA-related processes in HSI analysis.

Chaste: A test-driven approach to software development for biological modelling

NASA Astrophysics Data System (ADS)

Pitt-Francis, Joe; Pathmanathan, Pras; Bernabeu, Miguel O.; Bordas, Rafel; Cooper, Jonathan; Fletcher, Alexander G.; Mirams, Gary R.; Murray, Philip; Osborne, James M.; Walter, Alex; Chapman, S. Jon; Garny, Alan; van Leeuwen, Ingeborg M. M.; Maini, Philip K.; Rodríguez, Blanca; Waters, Sarah L.; Whiteley, Jonathan P.; Byrne, Helen M.; Gavaghan, David J.

2009-12-01

Chaste ('Cancer, heart and soft-tissue environment') is a software library and a set of test suites for computational simulations in the domain of biology. Current functionality has arisen from modelling in the fields of cancer, cardiac physiology and soft-tissue mechanics. It is released under the LGPL 2.1 licence. Chaste has been developed using agile programming methods. The project began in 2005 when it was reasoned that the modelling of a variety of physiological phenomena required both a generic mathematical modelling framework, and a generic computational/simulation framework. The Chaste project evolved from the Integrative Biology (IB) e-Science Project, an inter-institutional project aimed at developing a suitable IT infrastructure to support physiome-level computational modelling, with a primary focus on cardiac and cancer modelling. Program summaryProgram title: Chaste Catalogue identifier: AEFD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFD_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: LGPL 2.1 No. of lines in distributed program, including test data, etc.: 5 407 321 No. of bytes in distributed program, including test data, etc.: 42 004 554 Distribution format: tar.gz Programming language: C++ Operating system: Unix Has the code been vectorised or parallelized?: Yes. Parallelized using MPI. RAM:<90 Megabytes for two of the scenarios described in Section 6 of the manuscript (Monodomain re-entry on a slab or Cylindrical crypt simulation). Up to 16 Gigabytes (distributed across processors) for full resolution bidomain cardiac simulation. Classification: 3. External routines: Boost, CodeSynthesis XSD, CxxTest, HDF5, METIS, MPI, PETSc, Triangle, Xerces Nature of problem: Chaste may be used for solving coupled ODE and PDE systems arising from modelling biological systems. Use of Chaste in two application areas are described in this paper: cardiac electrophysiology and intestinal crypt dynamics. Solution method: Coupled multi-physics with PDE, ODE and discrete mechanics simulation. Running time: The largest cardiac simulation described in the manuscript takes about 6 hours to run on a single 3 GHz core. See results section (Section 6) of the manuscript for discussion on parallel scaling.

Senior Adults and Computers in the 1990s.

ERIC Educational Resources Information Center

Lawhon, Tommie; And Others

1996-01-01

Older adults use computers for entertainment, education, and creative and business endeavors. Computer training helps them increase productivity, learn skills, and boost short-term memory. Electronic mail, online services, and the Internet encourage socialization. Adapted technology helps disabled and ill elders use computers. (SK)

Reconcile Planck-scale discreteness and the Lorentz-Fitzgerald contraction

NASA Astrophysics Data System (ADS)

Rovelli, Carlo; Speziale, Simone

2003-03-01

A Planck-scale minimal observable length appears in many approaches to quantum gravity. It is sometimes argued that this minimal length might conflict with Lorentz invariance, because a boosted observer can see the minimal length further Lorentz contracted. We show that this is not the case within loop quantum gravity. In loop quantum gravity the minimal length (more precisely, minimal area) does not appear as a fixed property of geometry, but rather as the minimal (nonzero) eigenvalue of a quantum observable. The boosted observer can see the same observable spectrum, with the same minimal area. What changes continuously in the boost transformation is not the value of the minimal length: it is the probability distribution of seeing one or the other of the discrete eigenvalues of the area. We discuss several difficulties associated with boosts and area measurement in quantum gravity. We compute the transformation of the area operator under a local boost, propose an explicit expression for the generator of local boosts, and give the conditions under which its action is unitary.

Constructing Nucleon Operators on a Lattice for Form Factors with High Momentum Transfer

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

Syritsyn, Sergey; Gambhir, Arjun S.; Musch, Bernhard U.

We present preliminary results of computing nucleon form factor at high momentum transfer using the 'boosted' or 'momentum' smearing. We use gauge configurations generated with N f = 2 + 1dynamical Wilson-clover fermions and study the connected as well as disconnected contributions to the nucleon form factors. Our initial results indicate that boosted smearing helps to improve the signal for nucleon correlators at high momentum. However, we also find evidence for large excited state contributions, which will likely require variational analysis to isolate the boosted nucleon ground state.

Broadcasting collective operation contributions throughout a parallel computer

DOEpatents

Faraj, Ahmad [Rochester, MN

2012-02-21

Methods, systems, and products are disclosed for broadcasting collective operation contributions throughout a parallel computer. The parallel computer includes a plurality of compute nodes connected together through a data communications network. Each compute node has a plurality of processors for use in collective parallel operations on the parallel computer. Broadcasting collective operation contributions throughout a parallel computer according to embodiments of the present invention includes: transmitting, by each processor on each compute node, that processor's collective operation contribution to the other processors on that compute node using intra-node communications; and transmitting on a designated network link, by each processor on each compute node according to a serial processor transmission sequence, that processor's collective operation contribution to the other processors on the other compute nodes using inter-node communications.

Application Portable Parallel Library

NASA Technical Reports Server (NTRS)

Cole, Gary L.; Blech, Richard A.; Quealy, Angela; Townsend, Scott

1995-01-01

Application Portable Parallel Library (APPL) computer program is subroutine-based message-passing software library intended to provide consistent interface to variety of multiprocessor computers on market today. Minimizes effort needed to move application program from one computer to another. User develops application program once and then easily moves application program from parallel computer on which created to another parallel computer. ("Parallel computer" also include heterogeneous collection of networked computers). Written in C language with one FORTRAN 77 subroutine for UNIX-based computers and callable from application programs written in C language or FORTRAN 77.

Performance of parallel computation using CUDA for solving the one-dimensional elasticity equations

NASA Astrophysics Data System (ADS)

Darmawan, J. B. B.; Mungkasi, S.

2017-01-01

In this paper, we investigate the performance of parallel computation in solving the one-dimensional elasticity equations. Elasticity equations are usually implemented in engineering science. Solving these equations fast and efficiently is desired. Therefore, we propose the use of parallel computation. Our parallel computation uses CUDA of the NVIDIA. Our research results show that parallel computation using CUDA has a great advantage and is powerful when the computation is of large scale.

Increasing processor utilization during parallel computation rundown

NASA Technical Reports Server (NTRS)

Jones, W. H.

1986-01-01

Some parallel processing environments provide for asynchronous execution and completion of general purpose parallel computations from a single computational phase. When all the computations from such a phase are complete, a new parallel computational phase is begun. Depending upon the granularity of the parallel computations to be performed, there may be a shortage of available work as a particular computational phase draws to a close (computational rundown). This can result in the waste of computing resources and the delay of the overall problem. In many practical instances, strict sequential ordering of phases of parallel computation is not totally required. In such cases, the beginning of one phase can be correctly computed before the end of a previous phase is completed. This allows additional work to be generated somewhat earlier to keep computing resources busy during each computational rundown. The conditions under which this can occur are identified and the frequency of occurrence of such overlapping in an actual parallel Navier-Stokes code is reported. A language construct is suggested and possible control strategies for the management of such computational phase overlapping are discussed.

Broadcasting a message in a parallel computer

DOEpatents

Berg, Jeremy E [Rochester, MN; Faraj, Ahmad A [Rochester, MN

2011-08-02

Methods, systems, and products are disclosed for broadcasting a message in a parallel computer. The parallel computer includes a plurality of compute nodes connected together using a data communications network. The data communications network optimized for point to point data communications and is characterized by at least two dimensions. The compute nodes are organized into at least one operational group of compute nodes for collective parallel operations of the parallel computer. One compute node of the operational group assigned to be a logical root. Broadcasting a message in a parallel computer includes: establishing a Hamiltonian path along all of the compute nodes in at least one plane of the data communications network and in the operational group; and broadcasting, by the logical root to the remaining compute nodes, the logical root's message along the established Hamiltonian path.

Force user's manual: A portable, parallel FORTRAN

NASA Technical Reports Server (NTRS)

Jordan, Harry F.; Benten, Muhammad S.; Arenstorf, Norbert S.; Ramanan, Aruna V.

1990-01-01

The use of Force, a parallel, portable FORTRAN on shared memory parallel computers is described. Force simplifies writing code for parallel computers and, once the parallel code is written, it is easily ported to computers on which Force is installed. Although Force is nearly the same for all computers, specific details are included for the Cray-2, Cray-YMP, Convex 220, Flex/32, Encore, Sequent, Alliant computers on which it is installed.

Simulated Raman Spectral Analysis of Organic Molecules

NASA Astrophysics Data System (ADS)

Lu, Lu

The advent of the laser technology in the 1960s solved the main difficulty of Raman spectroscopy, resulted in simplified Raman spectroscopy instruments and also boosted the sensitivity of the technique. Up till now, Raman spectroscopy is commonly used in chemistry and biology. As vibrational information is specific to the chemical bonds, Raman spectroscopy provides fingerprints to identify the type of molecules in the sample. In this thesis, we simulate the Raman Spectrum of organic and inorganic materials by General Atomic and Molecular Electronic Structure System (GAMESS) and Gaussian, two computational codes that perform several general chemistry calculations. We run these codes on our CPU-based high-performance cluster (HPC). Through the message passing interface (MPI), a standardized and portable message-passing system which can make the codes run in parallel, we are able to decrease the amount of time for computation and increase the sizes and capacities of systems simulated by the codes. From our simulations, we will set up a database that allows search algorithm to quickly identify N-H and O-H bonds in different materials. Our ultimate goal is to analyze and identify the spectra of organic matter compositions from meteorites and compared these spectra with terrestrial biologically-produced amino acids and residues.

Accelerating image recognition on mobile devices using GPGPU

NASA Astrophysics Data System (ADS)

Bordallo López, Miguel; Nykänen, Henri; Hannuksela, Jari; Silvén, Olli; Vehviläinen, Markku

2011-01-01

The future multi-modal user interfaces of battery-powered mobile devices are expected to require computationally costly image analysis techniques. The use of Graphic Processing Units for computing is very well suited for parallel processing and the addition of programmable stages and high precision arithmetic provide for opportunities to implement energy-efficient complete algorithms. At the moment the first mobile graphics accelerators with programmable pipelines are available, enabling the GPGPU implementation of several image processing algorithms. In this context, we consider a face tracking approach that uses efficient gray-scale invariant texture features and boosting. The solution is based on the Local Binary Pattern (LBP) features and makes use of the GPU on the pre-processing and feature extraction phase. We have implemented a series of image processing techniques in the shader language of OpenGL ES 2.0, compiled them for a mobile graphics processing unit and performed tests on a mobile application processor platform (OMAP3530). In our contribution, we describe the challenges of designing on a mobile platform, present the performance achieved and provide measurement results for the actual power consumption in comparison to using the CPU (ARM) on the same platform.

Rapid prototyping and evaluation of programmable SIMD SDR processors in LISA

NASA Astrophysics Data System (ADS)

Chen, Ting; Liu, Hengzhu; Zhang, Botao; Liu, Dongpei

2013-03-01

With the development of international wireless communication standards, there is an increase in computational requirement for baseband signal processors. Time-to-market pressure makes it impossible to completely redesign new processors for the evolving standards. Due to its high flexibility and low power, software defined radio (SDR) digital signal processors have been proposed as promising technology to replace traditional ASIC and FPGA fashions. In addition, there are large numbers of parallel data processed in computation-intensive functions, which fosters the development of single instruction multiple data (SIMD) architecture in SDR platform. So a new way must be found to prototype the SDR processors efficiently. In this paper we present a bit-and-cycle accurate model of programmable SIMD SDR processors in a machine description language LISA. LISA is a language for instruction set architecture which can gain rapid model at architectural level. In order to evaluate the availability of our proposed processor, three common baseband functions, FFT, FIR digital filter and matrix multiplication have been mapped on the SDR platform. Analytical results showed that the SDR processor achieved the maximum of 47.1% performance boost relative to the opponent processor.

Architecture Adaptive Computing Environment

NASA Technical Reports Server (NTRS)

Dorband, John E.

2006-01-01

Architecture Adaptive Computing Environment (aCe) is a software system that includes a language, compiler, and run-time library for parallel computing. aCe was developed to enable programmers to write programs, more easily than was previously possible, for a variety of parallel computing architectures. Heretofore, it has been perceived to be difficult to write parallel programs for parallel computers and more difficult to port the programs to different parallel computing architectures. In contrast, aCe is supportable on all high-performance computing architectures. Currently, it is supported on LINUX clusters. aCe uses parallel programming constructs that facilitate writing of parallel programs. Such constructs were used in single-instruction/multiple-data (SIMD) programming languages of the 1980s, including Parallel Pascal, Parallel Forth, C*, *LISP, and MasPar MPL. In aCe, these constructs are extended and implemented for both SIMD and multiple- instruction/multiple-data (MIMD) architectures. Two new constructs incorporated in aCe are those of (1) scalar and virtual variables and (2) pre-computed paths. The scalar-and-virtual-variables construct increases flexibility in optimizing memory utilization in various architectures. The pre-computed-paths construct enables the compiler to pre-compute part of a communication operation once, rather than computing it every time the communication operation is performed.

Parallel computing works

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

Not Available

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

Distributing an executable job load file to compute nodes in a parallel computer

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

Gooding, Thomas M.

Distributing an executable job load file to compute nodes in a parallel computer, the parallel computer comprising a plurality of compute nodes, including: determining, by a compute node in the parallel computer, whether the compute node is participating in a job; determining, by the compute node in the parallel computer, whether a descendant compute node is participating in the job; responsive to determining that the compute node is participating in the job or that the descendant compute node is participating in the job, communicating, by the compute node to a parent compute node, an identification of a data communications linkmore » over which the compute node receives data from the parent compute node; constructing a class route for the job, wherein the class route identifies all compute nodes participating in the job; and broadcasting the executable load file for the job along the class route for the job.« less

Estimation of energetic efficiency of heat supply in front of the aircraft at supersonic accelerated flight. Part II. Mathematical model of the trajectory boost part and computational results

NASA Astrophysics Data System (ADS)

Latypov, A. F.

2009-03-01

The fuel economy was estimated at boost trajectory of aerospace plane during energy supply to the free stream. Initial and final velocities of the flight were given. A model of planning flight above cold air in infinite isobaric thermal wake was used. The comparison of fuel consumption was done at optimal trajectories. The calculations were done using a combined power plant consisting of ramjet and liquid-propellant engine. An exergy model was constructed in the first part of the paper for estimating the ramjet thrust and specific impulse. To estimate the aerodynamic drag of aircraft a quadratic dependence on aerodynamic lift is used. The energy for flow heating is obtained at the sacrifice of an equivalent decrease of exergy of combustion products. The dependencies are obtained for increasing the range coefficient of cruise flight at different Mach numbers. In the second part of the paper, a mathematical model is presented for the boost part of the flight trajectory of the flying vehicle and computational results for reducing the fuel expenses at the boost trajectory at a given value of the energy supplied in front of the aircraft.

Bayesian Mapping Reveals That Attention Boosts Neural Responses to Predicted and Unpredicted Stimuli.

PubMed

Garrido, Marta I; Rowe, Elise G; Halász, Veronika; Mattingley, Jason B

2018-05-01

Predictive coding posits that the human brain continually monitors the environment for regularities and detects inconsistencies. It is unclear, however, what effect attention has on expectation processes, as there have been relatively few studies and the results of these have yielded contradictory findings. Here, we employed Bayesian model comparison to adjudicate between 2 alternative computational models. The "Opposition" model states that attention boosts neural responses equally to predicted and unpredicted stimuli, whereas the "Interaction" model assumes that attentional boosting of neural signals depends on the level of predictability. We designed a novel, audiospatial attention task that orthogonally manipulated attention and prediction by playing oddball sequences in either the attended or unattended ear. We observed sensory prediction error responses, with electroencephalography, across all attentional manipulations. Crucially, posterior probability maps revealed that, overall, the Opposition model better explained scalp and source data, suggesting that attention boosts responses to predicted and unpredicted stimuli equally. Furthermore, Dynamic Causal Modeling showed that these Opposition effects were expressed in plastic changes within the mismatch negativity network. Our findings provide empirical evidence for a computational model of the opposing interplay of attention and expectation in the brain.

Matching pursuit parallel decomposition of seismic data

NASA Astrophysics Data System (ADS)

Li, Chuanhui; Zhang, Fanchang

2017-07-01

In order to improve the computation speed of matching pursuit decomposition of seismic data, a matching pursuit parallel algorithm is designed in this paper. We pick a fixed number of envelope peaks from the current signal in every iteration according to the number of compute nodes and assign them to the compute nodes on average to search the optimal Morlet wavelets in parallel. With the help of parallel computer systems and Message Passing Interface, the parallel algorithm gives full play to the advantages of parallel computing to significantly improve the computation speed of the matching pursuit decomposition and also has good expandability. Besides, searching only one optimal Morlet wavelet by every compute node in every iteration is the most efficient implementation.

Computer hardware fault administration

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-09-14

Computer hardware fault administration carried out in a parallel computer, where the parallel computer includes a plurality of compute nodes. The compute nodes are coupled for data communications by at least two independent data communications networks, where each data communications network includes data communications links connected to the compute nodes. Typical embodiments carry out hardware fault administration by identifying a location of a defective link in the first data communications network of the parallel computer and routing communications data around the defective link through the second data communications network of the parallel computer.

Using injectable hydrogel markers to assess resimulation for boost target volume definition in a patient undergoing whole-breast radiotherapy

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

Patel, Henal; Goyal, Sharad; Kim, Leonard, E-mail: kimlh@rutgers.edu

Several publications have recommended that patients undergoing whole-breast radiotherapy be resimulated for boost planning. The rationale for this is that the seroma may be smaller when compared with the initial simulation. However, the decision remains whether to use the earlier or later images to define an appropriate boost target volume. A patient undergoing whole-breast radiotherapy had new, injectable, temporary hydrogel fiducial markers placed 1 to 3 cm from the seroma at the time of initial simulation. The patient was resimulated 4.5 weeks later for conformal photon boost planning. Computed tomography (CT) scans acquired at the beginning and the end ofmore » whole-breast radiotherapy showed that shrinkage of the lumpectomy cavity was not matched by a corresponding reduction in the surrounding tissue volume, as demarcated by hydrogel markers. This observation called into question the usual interpretation of cavity shrinkage for boost target definition. For this patient, it was decided to define the boost target volume on the initial planning CT instead of the new CT.« less

Data communications in a parallel active messaging interface of a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2014-02-11

Data communications in a parallel active messaging interface ('PAMI') or a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution of a compute node, including specification of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications instruction, the instruction characterized by instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance witht the instruction type, the transfer data from the origin endpoin to the target endpoint.

High-performance computing — an overview

NASA Astrophysics Data System (ADS)

Marksteiner, Peter

1996-08-01

An overview of high-performance computing (HPC) is given. Different types of computer architectures used in HPC are discussed: vector supercomputers, high-performance RISC processors, various parallel computers like symmetric multiprocessors, workstation clusters, massively parallel processors. Software tools and programming techniques used in HPC are reviewed: vectorizing compilers, optimization and vector tuning, optimization for RISC processors; parallel programming techniques like shared-memory parallelism, message passing and data parallelism; and numerical libraries.

Vaccination of Mice Using the West Nile Virus E-Protein in a DNA Prime-Protein Boost Strategy Stimulates Cell-Mediated Immunity and Protects Mice against a Lethal Challenge

PubMed Central

De Filette, Marina; Soehle, Silke; Ulbert, Sebastian; Richner, Justin; Diamond, Michael S.; Sinigaglia, Alessandro; Barzon, Luisa; Roels, Stefan; Lisziewicz, Julianna; Lorincz, Orsolya; Sanders, Niek N.

2014-01-01

West Nile virus (WNV) is a mosquito-borne flavivirus that is endemic in Africa, the Middle East, Europe and the United States. There is currently no antiviral treatment or human vaccine available to treat or prevent WNV infection. DNA plasmid-based vaccines represent a new approach for controlling infectious diseases. In rodents, DNA vaccines have been shown to induce B cell and cytotoxic T cell responses and protect against a wide range of infections. In this study, we formulated a plasmid DNA vector expressing the ectodomain of the E-protein of WNV into nanoparticles by using linear polyethyleneimine (lPEI) covalently bound to mannose and examined the potential of this vaccine to protect against lethal WNV infection in mice. Mice were immunized twice (prime – boost regime) with the WNV DNA vaccine formulated with lPEI-mannose using different administration routes (intramuscular, intradermal and topical). In parallel a heterologous boost with purified recombinant WNV envelope (E) protein was evaluated. While no significant E-protein specific humoral response was generated after DNA immunization, protein boosting of DNA-primed mice resulted in a marked increase in total neutralizing antibody titer. In addition, E-specific IL-4 T-cell immune responses were detected by ELISPOT after protein boost and CD8+ specific IFN-γ expression was observed by flow cytometry. Challenge experiments using the heterologous immunization regime revealed protective immunity to homologous and virulent WNV infection. PMID:24503579

Radiotherapy Breast Boost With Reduced Whole-Breast Dose Is Associated With Improved Cosmesis: The Results of a Comprehensive Assessment From the St. George and Wollongong Randomized Breast Boost Trial

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

Hau, Eric, E-mail: helloerico@yahoo.com; Browne, Lois H.; Khanna, Sam

Purpose: To evaluate comprehensively the effect of a radiotherapy boost on breast cosmetic outcomes after 5 years in patients treated with breast-conserving surgery. Methods: The St. George and Wollongong trial (NCT00138814) randomized 688 patients with histologically proven Tis-2, N 0-1, M0 carcinoma to the control arm of 50 Gy in 25 fractions (342 patients) and the boost arm of 45 Gy in 25 fractions to the whole breast followed by a 16 Gy in 8 fraction electron boost (346 patients). Five-year cosmetic outcomes were assessed by a panel subjectively in 385 patients and objectively using pBRA (relative breast retraction assessment).more » A subset of patients also had absolute BRA measurements. Clinician assessment and patient self-assessment of overall cosmetic and specific items as well as computer BCCT.core analysis were also performed. Results: The boost arm had improved cosmetic overall outcomes as scored by the panel and BCCT.core software with 79% (p = 0.016) and 81% (p = 0.004) excellent/good cosmesis respectively compared with 68% in no-boost arm. The boost arm also had lower pBRA and BRA values with a mean difference of 0.60 and 1.82 mm, respectively, but was not statistically significant. There was a very high proportion of overall excellent/good cosmetic outcome in 95% and 93% in the boost and no-boost arms using patient self-assessment. However, no difference in overall and specific items scored by clinician assessment and patient self-assessment was found. Conclusion: The results show the negative cosmetic effect of a 16-Gy boost is offset by a lower whole-breast dose of 45 Gy.« less

Small Private Key PKS on an Embedded Microprocessor

PubMed Central

Seo, Hwajeong; Kim, Jihyun; Choi, Jongseok; Park, Taehwan; Liu, Zhe; Kim, Howon

2014-01-01

Multivariate quadratic ( ) cryptography requires the use of long public and private keys to ensure a sufficient security level, but this is not favorable to embedded systems, which have limited system resources. Recently, various approaches to cryptography using reduced public keys have been studied. As a result of this, at CHES2011 (Cryptographic Hardware and Embedded Systems, 2011), a small public key scheme, was proposed, and its feasible implementation on an embedded microprocessor was reported at CHES2012. However, the implementation of a small private key scheme was not reported. For efficient implementation, random number generators can contribute to reduce the key size, but the cost of using a random number generator is much more complex than computing on modern microprocessors. Therefore, no feasible results have been reported on embedded microprocessors. In this paper, we propose a feasible implementation on embedded microprocessors for a small private key scheme using a pseudo-random number generator and hash function based on a block-cipher exploiting a hardware Advanced Encryption Standard (AES) accelerator. To speed up the performance, we apply various implementation methods, including parallel computation, on-the-fly computation, optimized logarithm representation, vinegar monomials and assembly programming. The proposed method reduces the private key size by about 99.9% and boosts signature generation and verification by 5.78% and 12.19% than previous results in CHES2012. PMID:24651722

Small private key MQPKS on an embedded microprocessor.

PubMed

Seo, Hwajeong; Kim, Jihyun; Choi, Jongseok; Park, Taehwan; Liu, Zhe; Kim, Howon

2014-03-19

Multivariate quadratic (MQ) cryptography requires the use of long public and private keys to ensure a sufficient security level, but this is not favorable to embedded systems, which have limited system resources. Recently, various approaches to MQ cryptography using reduced public keys have been studied. As a result of this, at CHES2011 (Cryptographic Hardware and Embedded Systems, 2011), a small public key MQ scheme, was proposed, and its feasible implementation on an embedded microprocessor was reported at CHES2012. However, the implementation of a small private key MQ scheme was not reported. For efficient implementation, random number generators can contribute to reduce the key size, but the cost of using a random number generator is much more complex than computing MQ on modern microprocessors. Therefore, no feasible results have been reported on embedded microprocessors. In this paper, we propose a feasible implementation on embedded microprocessors for a small private key MQ scheme using a pseudo-random number generator and hash function based on a block-cipher exploiting a hardware Advanced Encryption Standard (AES) accelerator. To speed up the performance, we apply various implementation methods, including parallel computation, on-the-fly computation, optimized logarithm representation, vinegar monomials and assembly programming. The proposed method reduces the private key size by about 99.9% and boosts signature generation and verification by 5.78% and 12.19% than previous results in CHES2012.

The 2nd Symposium on the Frontiers of Massively Parallel Computations

NASA Technical Reports Server (NTRS)

Mills, Ronnie (Editor)

1988-01-01

Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.

Data communications in a parallel active messaging interface of a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2013-11-12

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.

Parallel Computation of the Jacobian Matrix for Nonlinear Equation Solvers Using MATLAB

NASA Technical Reports Server (NTRS)

Rose, Geoffrey K.; Nguyen, Duc T.; Newman, Brett A.

2017-01-01

Demonstrating speedup for parallel code on a multicore shared memory PC can be challenging in MATLAB due to underlying parallel operations that are often opaque to the user. This can limit potential for improvement of serial code even for the so-called embarrassingly parallel applications. One such application is the computation of the Jacobian matrix inherent to most nonlinear equation solvers. Computation of this matrix represents the primary bottleneck in nonlinear solver speed such that commercial finite element (FE) and multi-body-dynamic (MBD) codes attempt to minimize computations. A timing study using MATLAB's Parallel Computing Toolbox was performed for numerical computation of the Jacobian. Several approaches for implementing parallel code were investigated while only the single program multiple data (spmd) method using composite objects provided positive results. Parallel code speedup is demonstrated but the goal of linear speedup through the addition of processors was not achieved due to PC architecture.

Performance Evaluation in Network-Based Parallel Computing

NASA Technical Reports Server (NTRS)

Dezhgosha, Kamyar

1996-01-01

Network-based parallel computing is emerging as a cost-effective alternative for solving many problems which require use of supercomputers or massively parallel computers. The primary objective of this project has been to conduct experimental research on performance evaluation for clustered parallel computing. First, a testbed was established by augmenting our existing SUNSPARCs' network with PVM (Parallel Virtual Machine) which is a software system for linking clusters of machines. Second, a set of three basic applications were selected. The applications consist of a parallel search, a parallel sort, a parallel matrix multiplication. These application programs were implemented in C programming language under PVM. Third, we conducted performance evaluation under various configurations and problem sizes. Alternative parallel computing models and workload allocations for application programs were explored. The performance metric was limited to elapsed time or response time which in the context of parallel computing can be expressed in terms of speedup. The results reveal that the overhead of communication latency between processes in many cases is the restricting factor to performance. That is, coarse-grain parallelism which requires less frequent communication between processes will result in higher performance in network-based computing. Finally, we are in the final stages of installing an Asynchronous Transfer Mode (ATM) switch and four ATM interfaces (each 155 Mbps) which will allow us to extend our study to newer applications, performance metrics, and configurations.

What's New in Software? Current Sources of Information Boost Effectiveness of Computer-Assisted Instruction.

ERIC Educational Resources Information Center

Ellsworth, Nancy J.

1990-01-01

This article reviews current resources on computer-assisted instruction. Included are sources of software and hardware evaluations, advances in current technology, research, an information hotline, and inventories of available technological assistance. (DB)

Parallel Computing Using Web Servers and "Servlets".

ERIC Educational Resources Information Center

Lo, Alfred; Bloor, Chris; Choi, Y. K.

2000-01-01

Describes parallel computing and presents inexpensive ways to implement a virtual parallel computer with multiple Web servers. Highlights include performance measurement of parallel systems; models for using Java and intranet technology including single server, multiple clients and multiple servers, single client; and a comparison of CGI (common…

A class of parallel algorithms for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

Parallel and parallel/pipeline algorithms for computation of the manipulator inertia matrix are presented. An algorithm based on composite rigid-body spatial inertia method, which provides better features for parallelization, is used for the computation of the inertia matrix. Two parallel algorithms are developed which achieve the time lower bound in computation. Also described is the mapping of these algorithms with topological variation on a two-dimensional processor array, with nearest-neighbor connection, and with cardinality variation on a linear processor array. An efficient parallel/pipeline algorithm for the linear array was also developed, but at significantly higher efficiency.

Parallel computing of a climate model on the dawn 1000 by domain decomposition method

NASA Astrophysics Data System (ADS)

Bi, Xunqiang

1997-12-01

In this paper the parallel computing of a grid-point nine-level atmospheric general circulation model on the Dawn 1000 is introduced. The model was developed by the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS). The Dawn 1000 is a MIMD massive parallel computer made by National Research Center for Intelligent Computer (NCIC), CAS. A two-dimensional domain decomposition method is adopted to perform the parallel computing. The potential ways to increase the speed-up ratio and exploit more resources of future massively parallel supercomputation are also discussed.

Parallel Computing Strategies for Irregular Algorithms

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Oliker, Leonid; Shan, Hongzhang; Biegel, Bryan (Technical Monitor)

2002-01-01

Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.

Parallel solution of sparse one-dimensional dynamic programming problems

NASA Technical Reports Server (NTRS)

Nicol, David M.

1989-01-01

Parallel computation offers the potential for quickly solving large computational problems. However, it is often a non-trivial task to effectively use parallel computers. Solution methods must sometimes be reformulated to exploit parallelism; the reformulations are often more complex than their slower serial counterparts. We illustrate these points by studying the parallelization of sparse one-dimensional dynamic programming problems, those which do not obviously admit substantial parallelization. We propose a new method for parallelizing such problems, develop analytic models which help us to identify problems which parallelize well, and compare the performance of our algorithm with existing algorithms on a multiprocessor.

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

PubMed

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

2018-04-20

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

Entanglement asymmetry for boosted black branes and the bound

NASA Astrophysics Data System (ADS)

Mishra, Rohit; Singh, Harvendra

2017-06-01

We study the effects of asymmetry in the entanglement thermodynamics of CFT subsystems. It is found that “boosted” Dp-brane backgrounds give rise to the first law of the entanglement thermodynamics where the CFT pressure asymmetry plays a decisive role in the entanglement. Two different strip like subsystems, one parallel to the boost and the other perpendicular, are studied in the perturbative regime Tthermal ≪ TE. We mainly seek to quantify this entanglement asymmetry as a ratio of the first-order entanglement entropies of the excitations. We discuss the AdS-wave backgrounds at zero temperature having maximum asymmetry from where a bound on entanglement asymmetry is obtained. The entanglement asymmetry reduces as we switch on finite temperature in the CFT while it is maximum at zero temperature.

Summary Report of Working Group 2: Computation

NASA Astrophysics Data System (ADS)

Stoltz, P. H.; Tsung, R. S.

2009-01-01

The working group on computation addressed three physics areas: (i) plasma-based accelerators (laser-driven and beam-driven), (ii) high gradient structure-based accelerators, and (iii) electron beam sources and transport [1]. Highlights of the talks in these areas included new models of breakdown on the microscopic scale, new three-dimensional multipacting calculations with both finite difference and finite element codes, and detailed comparisons of new electron gun models with standard models such as PARMELA. The group also addressed two areas of advances in computation: (i) new algorithms, including simulation in a Lorentz-boosted frame that can reduce computation time orders of magnitude, and (ii) new hardware architectures, like graphics processing units and Cell processors that promise dramatic increases in computing power. Highlights of the talks in these areas included results from the first large-scale parallel finite element particle-in-cell code (PIC), many order-of-magnitude speedup of, and details of porting the VPIC code to the Roadrunner supercomputer. The working group featured two plenary talks, one by Brian Albright of Los Alamos National Laboratory on the performance of the VPIC code on the Roadrunner supercomputer, and one by David Bruhwiler of Tech-X Corporation on recent advances in computation for advanced accelerators. Highlights of the talk by Albright included the first one trillion particle simulations, a sustained performance of 0.3 petaflops, and an eight times speedup of science calculations, including back-scatter in laser-plasma interaction. Highlights of the talk by Bruhwiler included simulations of 10 GeV accelerator laser wakefield stages including external injection, new developments in electromagnetic simulations of electron guns using finite difference and finite element approaches.

Summary Report of Working Group 2: Computation

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

Stoltz, P. H.; Tsung, R. S.

2009-01-22

The working group on computation addressed three physics areas: (i) plasma-based accelerators (laser-driven and beam-driven), (ii) high gradient structure-based accelerators, and (iii) electron beam sources and transport [1]. Highlights of the talks in these areas included new models of breakdown on the microscopic scale, new three-dimensional multipacting calculations with both finite difference and finite element codes, and detailed comparisons of new electron gun models with standard models such as PARMELA. The group also addressed two areas of advances in computation: (i) new algorithms, including simulation in a Lorentz-boosted frame that can reduce computation time orders of magnitude, and (ii) newmore » hardware architectures, like graphics processing units and Cell processors that promise dramatic increases in computing power. Highlights of the talks in these areas included results from the first large-scale parallel finite element particle-in-cell code (PIC), many order-of-magnitude speedup of, and details of porting the VPIC code to the Roadrunner supercomputer. The working group featured two plenary talks, one by Brian Albright of Los Alamos National Laboratory on the performance of the VPIC code on the Roadrunner supercomputer, and one by David Bruhwiler of Tech-X Corporation on recent advances in computation for advanced accelerators. Highlights of the talk by Albright included the first one trillion particle simulations, a sustained performance of 0.3 petaflops, and an eight times speedup of science calculations, including back-scatter in laser-plasma interaction. Highlights of the talk by Bruhwiler included simulations of 10 GeV accelerator laser wakefield stages including external injection, new developments in electromagnetic simulations of electron guns using finite difference and finite element approaches.« less

Advanced Techniques for Simulating the Behavior of Sand

NASA Astrophysics Data System (ADS)

Clothier, M.; Bailey, M.

2009-12-01

Computer graphics and visualization techniques continue to provide untapped research opportunities, particularly when working with earth science disciplines. Through collaboration with the Oregon Space Grant and IGERT Ecosystem Informatics programs we are developing new techniques for simulating sand. In addition, through collaboration with the Oregon Space Grant, we’ve been communicating with the Jet Propulsion Laboratory (JPL) to exchange ideas and gain feedback on our work. More specifically, JPL’s DARTS Laboratory specializes in planetary vehicle simulation, such as the Mars rovers. This simulation utilizes a virtual "sand box" to test how planetary rovers respond to different terrains while traversing them. Unfortunately, this simulation is unable to fully mimic the harsh, sandy environments of those found on Mars. Ideally, these simulations should allow a rover to interact with the sand beneath it, particularly for different sand granularities and densities. In particular, there may be situations where a rover may become stuck in sand due to lack of friction between the sand and wheels. In fact, in May 2009, the Spirit rover became stuck in the Martian sand and has provided additional motivation for this research. In order to develop a new sand simulation model, high performance computing will play a very important role in this work. More specifically, graphics processing units (GPUs) are useful due to their ability to run general purpose algorithms and ability to perform massively parallel computations. In prior research, simulating vast quantities of sand has been difficult to compute in real-time due to the computational complexity of many colliding particles. With the use of GPUs however, each particle collision will be parallelized, allowing for a dramatic performance increase. In addition, spatial partitioning will also provide a speed boost as this will help limit the number of particle collision calculations. However, since the goal of this research is to simulate the look and behavior of sand, this work will go beyond simple particle collision. In particular, we can continue to use our parallel algorithms not only on single particles but on particle “clumps” that consist of multiple combined particles. Since sand is typically not spherical in nature, these particle “clumps” help to simulate the coarse nature of sand. In a simulation environment, multiple combined particles could be used to simulate the polygonal and granular nature of sand grains. Thus, a diversity of sand particles can be generated. The interaction between these particles can then be parallelized using GPU hardware. As such, this research will investigate different graphics and physics techniques and determine the tradeoffs in performance and visual quality for sand simulation. An enhanced sand model through the use of high performance computing and GPUs has great potential to impact research for both earth and space scientists. Interaction with JPL has provided an opportunity for us to refine our simulation techniques that can ultimately be used for their vehicle simulator. As an added benefit of this work, advancements in simulating sand can also benefit scientists here on earth, especially in regard to understanding landslides and debris flows.

MPI_XSTAR: MPI-based Parallelization of the XSTAR Photoionization Program

NASA Astrophysics Data System (ADS)

Danehkar, Ashkbiz; Nowak, Michael A.; Lee, Julia C.; Smith, Randall K.

2018-02-01

We describe a program for the parallel implementation of multiple runs of XSTAR, a photoionization code that is used to predict the physical properties of an ionized gas from its emission and/or absorption lines. The parallelization program, called MPI_XSTAR, has been developed and implemented in the C++ language by using the Message Passing Interface (MPI) protocol, a conventional standard of parallel computing. We have benchmarked parallel multiprocessing executions of XSTAR, using MPI_XSTAR, against a serial execution of XSTAR, in terms of the parallelization speedup and the computing resource efficiency. Our experience indicates that the parallel execution runs significantly faster than the serial execution, however, the efficiency in terms of the computing resource usage decreases with increasing the number of processors used in the parallel computing.

Data communications in a parallel active messaging interface of a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2013-10-29

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a data communications instruction, the instruction characterized by an instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance with the instruction type, the transfer data from the origin endpoint to the target endpoint.

A CFD Heterogeneous Parallel Solver Based on Collaborating CPU and GPU

NASA Astrophysics Data System (ADS)

Lai, Jianqi; Tian, Zhengyu; Li, Hua; Pan, Sha

2018-03-01

Since Graphic Processing Unit (GPU) has a strong ability of floating-point computation and memory bandwidth for data parallelism, it has been widely used in the areas of common computing such as molecular dynamics (MD), computational fluid dynamics (CFD) and so on. The emergence of compute unified device architecture (CUDA), which reduces the complexity of compiling program, brings the great opportunities to CFD. There are three different modes for parallel solution of NS equations: parallel solver based on CPU, parallel solver based on GPU and heterogeneous parallel solver based on collaborating CPU and GPU. As we can see, GPUs are relatively rich in compute capacity but poor in memory capacity and the CPUs do the opposite. We need to make full use of the GPUs and CPUs, so a CFD heterogeneous parallel solver based on collaborating CPU and GPU has been established. Three cases are presented to analyse the solver’s computational accuracy and heterogeneous parallel efficiency. The numerical results agree well with experiment results, which demonstrate that the heterogeneous parallel solver has high computational precision. The speedup on a single GPU is more than 40 for laminar flow, it decreases for turbulent flow, but it still can reach more than 20. What’s more, the speedup increases as the grid size becomes larger.

Radiobiological and treatment planning study of a simultaneously integrated boost for canine nasal tumors using helical tomotherapy.

PubMed

Gutíerrez, Alonso N; Deveau, Michael; Forrest, Lisa J; Tomé, Wolfgang A; Mackie, Thomas R

2007-01-01

Feasibility of delivering a simultaneously integrated boost to canine nasal tumors using helical tomotherapy to improve tumor control probability (TCP) via an increase in total biological equivalent uniform dose (EUD) was evaluated. Eight dogs with varying size nasal tumors (5.8-110.9 cc) were replanned to 42 Gy to the nasal cavity and integrated dose boosts to gross disease of 45.2, 48.3, and 51.3 Gy in 10 fractions. EUD values were calculated for tumors and mean normalized total doses (NTD(mean)) for organs at risk (OAR). Normal Tissue Complication Probability (NTCP) values were obtained for OARs, and estimated TCP values were computed using a logistic dose-response model and based on deliverable EUD boost doses. Significant increases in estimated TCP to 54%, 74%, and 86% can be achieved with 10%, 23%, and 37% mean relative EUD boosts to the gross disease, respectively. NTCP values for blindness of either eye and for brain necrosis were < 0.01% for all boosts. Values for cataract development were 31%, 42%, and 46% for studied boost schemas, respectively. Average NTD(mean) to eyes and brain for mean EUD boosts were 10.2, 11.3, and 12.1 Gy3, and 7.5, 7.2, and 7.9 Gy2, respectively. Using helical tomotherapy, simultaneously integrated dose boosts can be delivered to increase the estimated TCP at 1-year without significantly increasing the NTD(mean) to eyes and brain. Delivery of these treatments in a prospective trial may allow quantification of a dose-response relationship in canine nasal tumors.

RBoost: Label Noise-Robust Boosting Algorithm Based on a Nonconvex Loss Function and the Numerically Stable Base Learners.

PubMed

Miao, Qiguang; Cao, Ying; Xia, Ge; Gong, Maoguo; Liu, Jiachen; Song, Jianfeng

2016-11-01

AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong classifiers. However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly, improving the antinoise ability of AdaBoost plays an important role in many applications. The sensitiveness to the noisy data of AdaBoost stems from the exponential loss function, which puts unrestricted penalties to the misclassified samples with very large margins. In this paper, we propose two boosting algorithms, referred to as RBoost1 and RBoost2, which are more robust to the noisy data compared with AdaBoost. RBoost1 and RBoost2 optimize a nonconvex loss function of the classification margin. Because the penalties to the misclassified samples are restricted to an amount less than one, RBoost1 and RBoost2 do not overfocus on the samples that are always misclassified by the previous base learners. Besides the loss function, at each boosting iteration, RBoost1 and RBoost2 use numerically stable ways to compute the base learners. These two improvements contribute to the robustness of the proposed algorithms to the noisy training and testing samples. Experimental results on the synthetic Gaussian data set, the UCI data sets, and a real malware behavior data set illustrate that the proposed RBoost1 and RBoost2 algorithms perform better when the training data sets contain noisy data.

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

Gooding, Thomas M.

Distributing an executable job load file to compute nodes in a parallel computer, the parallel computer comprising a plurality of compute nodes, including: determining, by a compute node in the parallel computer, whether the compute node is participating in a job; determining, by the compute node in the parallel computer, whether a descendant compute node is participating in the job; responsive to determining that the compute node is participating in the job or that the descendant compute node is participating in the job, communicating, by the compute node to a parent compute node, an identification of a data communications linkmore » over which the compute node receives data from the parent compute node; constructing a class route for the job, wherein the class route identifies all compute nodes participating in the job; and broadcasting the executable load file for the job along the class route for the job.« less

SIAM Conference on Parallel Processing for Scientific Computing, 4th, Chicago, IL, Dec. 11-13, 1989, Proceedings

NASA Technical Reports Server (NTRS)

Dongarra, Jack (Editor); Messina, Paul (Editor); Sorensen, Danny C. (Editor); Voigt, Robert G. (Editor)

1990-01-01

Attention is given to such topics as an evaluation of block algorithm variants in LAPACK and presents a large-grain parallel sparse system solver, a multiprocessor method for the solution of the generalized Eigenvalue problem on an interval, and a parallel QR algorithm for iterative subspace methods on the CM2. A discussion of numerical methods includes the topics of asynchronous numerical solutions of PDEs on parallel computers, parallel homotopy curve tracking on a hypercube, and solving Navier-Stokes equations on the Cedar Multi-Cluster system. A section on differential equations includes a discussion of a six-color procedure for the parallel solution of elliptic systems using the finite quadtree structure, data parallel algorithms for the finite element method, and domain decomposition methods in aerodynamics. Topics dealing with massively parallel computing include hypercube vs. 2-dimensional meshes and massively parallel computation of conservation laws. Performance and tools are also discussed.

Users guide for guidance and control Launch and Abort Simulation for Spacecraft (LASS), volume 1

NASA Technical Reports Server (NTRS)

Havig, T. F.; Backman, H. D.

1972-01-01

The mathematical models and computer program which are used to implement LASS are described. The computer program provides for a simulation of boost to orbit and abort capability from boost trajectories to a prescribed target. The abort target provides a decision point for engine shutdown from which the vehicle coasts to the vicinity of the selected abort recovery site. The simulation is a six degree of freedom simulation describing a rigid body. The vehicle is influenced by forces and moments from nondistributed aerodynamics. An adaptive autopilot is provided to control vehicle attitudes during powered and unpowered flight. A conventional autopilot is provided for study of vehicle during powered flight.

Boosting Contextual Information for Deep Neural Network Based Voice Activity Detection

DTIC Science & Technology

2015-02-01

multi-resolution stacking (MRS), which is a stack of ensemble classifiers. Each classifier in a building block inputs the concatenation of the predictions ...a base classifier in MRS, named boosted deep neural network (bDNN). bDNN first generates multiple base predictions from different contexts of a single...frame by only one DNN and then aggregates the base predictions for a better prediction of the frame, and it is different from computationally

Handling Big Data in Medical Imaging: Iterative Reconstruction with Large-Scale Automated Parallel Computation

PubMed Central

Lee, Jae H.; Yao, Yushu; Shrestha, Uttam; Gullberg, Grant T.; Seo, Youngho

2014-01-01

The primary goal of this project is to implement the iterative statistical image reconstruction algorithm, in this case maximum likelihood expectation maximum (MLEM) used for dynamic cardiac single photon emission computed tomography, on Spark/GraphX. This involves porting the algorithm to run on large-scale parallel computing systems. Spark is an easy-to- program software platform that can handle large amounts of data in parallel. GraphX is a graph analytic system running on top of Spark to handle graph and sparse linear algebra operations in parallel. The main advantage of implementing MLEM algorithm in Spark/GraphX is that it allows users to parallelize such computation without any expertise in parallel computing or prior knowledge in computer science. In this paper we demonstrate a successful implementation of MLEM in Spark/GraphX and present the performance gains with the goal to eventually make it useable in clinical setting. PMID:27081299

Handling Big Data in Medical Imaging: Iterative Reconstruction with Large-Scale Automated Parallel Computation.

PubMed

Lee, Jae H; Yao, Yushu; Shrestha, Uttam; Gullberg, Grant T; Seo, Youngho

2014-11-01

The primary goal of this project is to implement the iterative statistical image reconstruction algorithm, in this case maximum likelihood expectation maximum (MLEM) used for dynamic cardiac single photon emission computed tomography, on Spark/GraphX. This involves porting the algorithm to run on large-scale parallel computing systems. Spark is an easy-to- program software platform that can handle large amounts of data in parallel. GraphX is a graph analytic system running on top of Spark to handle graph and sparse linear algebra operations in parallel. The main advantage of implementing MLEM algorithm in Spark/GraphX is that it allows users to parallelize such computation without any expertise in parallel computing or prior knowledge in computer science. In this paper we demonstrate a successful implementation of MLEM in Spark/GraphX and present the performance gains with the goal to eventually make it useable in clinical setting.

Towards the clinical implementation of iterative low-dose cone-beam CT reconstruction in image-guided radiation therapy: Cone/ring artifact correction and multiple GPU implementation

PubMed Central

Yan, Hao; Wang, Xiaoyu; Shi, Feng; Bai, Ti; Folkerts, Michael; Cervino, Laura; Jiang, Steve B.; Jia, Xun

2014-01-01

Purpose: Compressed sensing (CS)-based iterative reconstruction (IR) techniques are able to reconstruct cone-beam CT (CBCT) images from undersampled noisy data, allowing for imaging dose reduction. However, there are a few practical concerns preventing the clinical implementation of these techniques. On the image quality side, data truncation along the superior–inferior direction under the cone-beam geometry produces severe cone artifacts in the reconstructed images. Ring artifacts are also seen in the half-fan scan mode. On the reconstruction efficiency side, the long computation time hinders clinical use in image-guided radiation therapy (IGRT). Methods: Image quality improvement methods are proposed to mitigate the cone and ring image artifacts in IR. The basic idea is to use weighting factors in the IR data fidelity term to improve projection data consistency with the reconstructed volume. In order to improve the computational efficiency, a multiple graphics processing units (GPUs)-based CS-IR system was developed. The parallelization scheme, detailed analyses of computation time at each step, their relationship with image resolution, and the acceleration factors were studied. The whole system was evaluated in various phantom and patient cases. Results: Ring artifacts can be mitigated by properly designing a weighting factor as a function of the spatial location on the detector. As for the cone artifact, without applying a correction method, it contaminated 13 out of 80 slices in a head-neck case (full-fan). Contamination was even more severe in a pelvis case under half-fan mode, where 36 out of 80 slices were affected, leading to poorer soft tissue delineation and reduced superior–inferior coverage. The proposed method effectively corrects those contaminated slices with mean intensity differences compared to FDK results decreasing from ∼497 and ∼293 HU to ∼39 and ∼27 HU for the full-fan and half-fan cases, respectively. In terms of efficiency boost, an overall 3.1 × speedup factor has been achieved with four GPU cards compared to a single GPU-based reconstruction. The total computation time is ∼30 s for typical clinical cases. Conclusions: The authors have developed a low-dose CBCT IR system for IGRT. By incorporating data consistency-based weighting factors in the IR model, cone/ring artifacts can be mitigated. A boost in computational efficiency is achieved by multi-GPU implementation. PMID:25370645

Towards the clinical implementation of iterative low-dose cone-beam CT reconstruction in image-guided radiation therapy: Cone/ring artifact correction and multiple GPU implementation

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

Yan, Hao, E-mail: steve.jiang@utsouthwestern.edu, E-mail: xun.jia@utsouthwestern.edu; Shi, Feng; Jiang, Steve B.

Purpose: Compressed sensing (CS)-based iterative reconstruction (IR) techniques are able to reconstruct cone-beam CT (CBCT) images from undersampled noisy data, allowing for imaging dose reduction. However, there are a few practical concerns preventing the clinical implementation of these techniques. On the image quality side, data truncation along the superior–inferior direction under the cone-beam geometry produces severe cone artifacts in the reconstructed images. Ring artifacts are also seen in the half-fan scan mode. On the reconstruction efficiency side, the long computation time hinders clinical use in image-guided radiation therapy (IGRT). Methods: Image quality improvement methods are proposed to mitigate the conemore » and ring image artifacts in IR. The basic idea is to use weighting factors in the IR data fidelity term to improve projection data consistency with the reconstructed volume. In order to improve the computational efficiency, a multiple graphics processing units (GPUs)-based CS-IR system was developed. The parallelization scheme, detailed analyses of computation time at each step, their relationship with image resolution, and the acceleration factors were studied. The whole system was evaluated in various phantom and patient cases. Results: Ring artifacts can be mitigated by properly designing a weighting factor as a function of the spatial location on the detector. As for the cone artifact, without applying a correction method, it contaminated 13 out of 80 slices in a head-neck case (full-fan). Contamination was even more severe in a pelvis case under half-fan mode, where 36 out of 80 slices were affected, leading to poorer soft tissue delineation and reduced superior–inferior coverage. The proposed method effectively corrects those contaminated slices with mean intensity differences compared to FDK results decreasing from ∼497 and ∼293 HU to ∼39 and ∼27 HU for the full-fan and half-fan cases, respectively. In terms of efficiency boost, an overall 3.1 × speedup factor has been achieved with four GPU cards compared to a single GPU-based reconstruction. The total computation time is ∼30 s for typical clinical cases. Conclusions: The authors have developed a low-dose CBCT IR system for IGRT. By incorporating data consistency-based weighting factors in the IR model, cone/ring artifacts can be mitigated. A boost in computational efficiency is achieved by multi-GPU implementation.« less

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

Parallel approach in RDF query processing

NASA Astrophysics Data System (ADS)

Vajgl, Marek; Parenica, Jan

2017-07-01

Parallel approach is nowadays a very cheap solution to increase computational power due to possibility of usage of multithreaded computational units. This hardware became typical part of nowadays personal computers or notebooks and is widely spread. This contribution deals with experiments how evaluation of computational complex algorithm of the inference over RDF data can be parallelized over graphical cards to decrease computational time.

A comparative study of serial and parallel aeroelastic computations of wings

NASA Technical Reports Server (NTRS)

Byun, Chansup; Guruswamy, Guru P.

1994-01-01

A procedure for computing the aeroelasticity of wings on parallel multiple-instruction, multiple-data (MIMD) computers is presented. In this procedure, fluids are modeled using Euler equations, and structures are modeled using modal or finite element equations. The procedure is designed in such a way that each discipline can be developed and maintained independently by using a domain decomposition approach. In the present parallel procedure, each computational domain is scalable. A parallel integration scheme is used to compute aeroelastic responses by solving fluid and structural equations concurrently. The computational efficiency issues of parallel integration of both fluid and structural equations are investigated in detail. This approach, which reduces the total computational time by a factor of almost 2, is demonstrated for a typical aeroelastic wing by using various numbers of processors on the Intel iPSC/860.

Research in parallel computing

NASA Technical Reports Server (NTRS)

Ortega, James M.; Henderson, Charles

1994-01-01

This report summarizes work on parallel computations for NASA Grant NAG-1-1529 for the period 1 Jan. - 30 June 1994. Short summaries on highly parallel preconditioners, target-specific parallel reductions, and simulation of delta-cache protocols are provided.

Parallel computations and control of adaptive structures

NASA Technical Reports Server (NTRS)

Park, K. C.; Alvin, Kenneth F.; Belvin, W. Keith; Chong, K. P. (Editor); Liu, S. C. (Editor); Li, J. C. (Editor)

1991-01-01

The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.

Design of a massively parallel computer using bit serial processing elements

NASA Technical Reports Server (NTRS)

Aburdene, Maurice F.; Khouri, Kamal S.; Piatt, Jason E.; Zheng, Jianqing

1995-01-01

A 1-bit serial processor designed for a parallel computer architecture is described. This processor is used to develop a massively parallel computational engine, with a single instruction-multiple data (SIMD) architecture. The computer is simulated and tested to verify its operation and to measure its performance for further development.

LOKI WIND CORRECTION COMPUTER AND WIND STUDIES FOR LOKI

DTIC Science & Technology

which relates burnout deviation of flight path with the distributed wind along the boost trajectory. The wind influence function was applied to...electrical outputs. A complete wind correction computer system based on the influence function and the results of wind studies was designed.

L2-Boosting algorithm applied to high-dimensional problems in genomic selection.

PubMed

González-Recio, Oscar; Weigel, Kent A; Gianola, Daniel; Naya, Hugo; Rosa, Guilherme J M

2010-06-01

The L(2)-Boosting algorithm is one of the most promising machine-learning techniques that has appeared in recent decades. It may be applied to high-dimensional problems such as whole-genome studies, and it is relatively simple from a computational point of view. In this study, we used this algorithm in a genomic selection context to make predictions of yet to be observed outcomes. Two data sets were used: (1) productive lifetime predicted transmitting abilities from 4702 Holstein sires genotyped for 32 611 single nucleotide polymorphisms (SNPs) derived from the Illumina BovineSNP50 BeadChip, and (2) progeny averages of food conversion rate, pre-corrected by environmental and mate effects, in 394 broilers genotyped for 3481 SNPs. Each of these data sets was split into training and testing sets, the latter comprising dairy or broiler sires whose ancestors were in the training set. Two weak learners, ordinary least squares (OLS) and non-parametric (NP) regression were used for the L2-Boosting algorithm, to provide a stringent evaluation of the procedure. This algorithm was compared with BL [Bayesian LASSO (least absolute shrinkage and selection operator)] and BayesA regression. Learning tasks were carried out in the training set, whereas validation of the models was performed in the testing set. Pearson correlations between predicted and observed responses in the dairy cattle (broiler) data set were 0.65 (0.33), 0.53 (0.37), 0.66 (0.26) and 0.63 (0.27) for OLS-Boosting, NP-Boosting, BL and BayesA, respectively. The smallest bias and mean-squared errors (MSEs) were obtained with OLS-Boosting in both the dairy cattle (0.08 and 1.08, respectively) and broiler (-0.011 and 0.006) data sets, respectively. In the dairy cattle data set, the BL was more accurate (bias=0.10 and MSE=1.10) than BayesA (bias=1.26 and MSE=2.81), whereas no differences between these two methods were found in the broiler data set. L2-Boosting with a suitable learner was found to be a competitive alternative for genomic selection applications, providing high accuracy and low bias in genomic-assisted evaluations with a relatively short computational time.

Performance Evaluation of Parallel Branch and Bound Search with the Intel iPSC (Intel Personal SuperComputer) Hypercube Computer.

DTIC Science & Technology

1986-12-01

17 III. Analysis of Parallel Design ................................................ 18 Parallel Abstract Data ...Types ........................................... 18 Abstract Data Type .................................................. 19 Parallel ADT...22 Data -Structure Design ........................................... 23 Object-Oriented Design

'Designing Ambient Interactions - Pervasive Ergonomic Interfaces for Ageing Well' (DAI'10)

NASA Astrophysics Data System (ADS)

Geven, Arjan; Prost, Sebastian; Tscheligi, Manfred; Soldatos, John; Gonzalez, Mari Feli

The workshop will focus on novel computer based interaction mechanisms and interfaces, which boost natural interactivity and obviate the need for conventional tedious interfaces. Such interfaces are increasingly used in ambient intelligence environments and related applications, including application boosting elderly cognitive support, cognitive rehabilitation and Ambient Assisted Living (AAL). The aim of the workshop is to provide insights on the technological underpinnings of such interfaces, along with tools and techniques for their design and evaluation.

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

Gubser, Steven S.; van der Schee, Wilke

At strong coupling holographic studies have shown that heavy ion collisions do not obey normal boost invariance. Here we study a modified boost invariance through a complex shift in time, and show that this leads to surprisingly good agreement with numerical holographic computations. When including perturbations the agreement becomes even better, both in the hydrodynamic and the far-from-equilibrium regime. Finally, one of the main advantages is an analytic formulation of the stress-energy tensor of the longitudinal dynamics of holographic heavy ion collisions.

Hypercluster Parallel Processor

NASA Technical Reports Server (NTRS)

Blech, Richard A.; Cole, Gary L.; Milner, Edward J.; Quealy, Angela

1992-01-01

Hypercluster computer system includes multiple digital processors, operation of which coordinated through specialized software. Configurable according to various parallel-computing architectures of shared-memory or distributed-memory class, including scalar computer, vector computer, reduced-instruction-set computer, and complex-instruction-set computer. Designed as flexible, relatively inexpensive system that provides single programming and operating environment within which one can investigate effects of various parallel-computing architectures and combinations on performance in solution of complicated problems like those of three-dimensional flows in turbomachines. Hypercluster software and architectural concepts are in public domain.

Parallel processing architecture for computing inverse differential kinematic equations of the PUMA arm

NASA Technical Reports Server (NTRS)

Hsia, T. C.; Lu, G. Z.; Han, W. H.

1987-01-01

In advanced robot control problems, on-line computation of inverse Jacobian solution is frequently required. Parallel processing architecture is an effective way to reduce computation time. A parallel processing architecture is developed for the inverse Jacobian (inverse differential kinematic equation) of the PUMA arm. The proposed pipeline/parallel algorithm can be inplemented on an IC chip using systolic linear arrays. This implementation requires 27 processing cells and 25 time units. Computation time is thus significantly reduced.

Real-time acquisition and tracking system with multiple Kalman filters

NASA Astrophysics Data System (ADS)

Beard, Gary C.; McCarter, Timothy G.; Spodeck, Walter; Fletcher, James E.

1994-07-01

The design of a real-time, ground-based, infrared tracking system with proven field success in tracking boost vehicles through burnout is presented with emphasis on the software design. The system was originally developed to deliver relative angular positions during boost, and thrust termination time to a sensor fusion station in real-time. Autonomous target acquisition and angle-only tracking features were developed to ensure success under stressing conditions. A unique feature of the system is the incorporation of multiple copies of a Kalman filter tracking algorithm running in parallel in order to minimize run-time. The system is capable of updating the state vector for an object at measurement rates approaching 90 Hz. This paper will address the top-level software design, details of the algorithms employed, system performance history in the field, and possible future upgrades.

A scalable parallel black oil simulator on distributed memory parallel computers

NASA Astrophysics Data System (ADS)

Wang, Kun; Liu, Hui; Chen, Zhangxin

2015-11-01

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

Automatic Generation of OpenMP Directives and Its Application to Computational Fluid Dynamics Codes

NASA Technical Reports Server (NTRS)

Yan, Jerry; Jin, Haoqiang; Frumkin, Michael; Yan, Jerry (Technical Monitor)

2000-01-01

The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. As great progress was made in hardware and software technologies, performance of parallel programs with compiler directives has demonstrated large improvement. The introduction of OpenMP directives, the industrial standard for shared-memory programming, has minimized the issue of portability. In this study, we have extended CAPTools, a computer-aided parallelization toolkit, to automatically generate OpenMP-based parallel programs with nominal user assistance. We outline techniques used in the implementation of the tool and discuss the application of this tool on the NAS Parallel Benchmarks and several computational fluid dynamics codes. This work demonstrates the great potential of using the tool to quickly port parallel programs and also achieve good performance that exceeds some of the commercial tools.

Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

NASA Astrophysics Data System (ADS)

Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

2017-07-01

Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

OpenGeoSys-GEMS: Hybrid parallelization of a reactive transport code with MPI and threads

NASA Astrophysics Data System (ADS)

Kosakowski, G.; Kulik, D. A.; Shao, H.

2012-04-01

OpenGeoSys-GEMS is a generic purpose reactive transport code based on the operator splitting approach. The code couples the Finite-Element groundwater flow and multi-species transport modules of the OpenGeoSys (OGS) project (http://www.ufz.de/index.php?en=18345) with the GEM-Selektor research package to model thermodynamic equilibrium of aquatic (geo)chemical systems utilizing the Gibbs Energy Minimization approach (http://gems.web.psi.ch/). The combination of OGS and the GEM-Selektor kernel (GEMS3K) is highly flexible due to the object-oriented modular code structures and the well defined (memory based) data exchange modules. Like other reactive transport codes, the practical applicability of OGS-GEMS is often hampered by the long calculation time and large memory requirements. • For realistic geochemical systems which might include dozens of mineral phases and several (non-ideal) solid solutions the time needed to solve the chemical system with GEMS3K may increase exceptionally. • The codes are coupled in a sequential non-iterative loop. In order to keep the accuracy, the time step size is restricted. In combination with a fine spatial discretization the time step size may become very small which increases calculation times drastically even for small 1D problems. • The current version of OGS is not optimized for memory use and the MPI version of OGS does not distribute data between nodes. Even for moderately small 2D problems the number of MPI processes that fit into memory of up-to-date workstations or HPC hardware is limited. One strategy to overcome the above mentioned restrictions of OGS-GEMS is to parallelize the coupled code. For OGS a parallelized version already exists. It is based on a domain decomposition method implemented with MPI and provides a parallel solver for fluid and mass transport processes. In the coupled code, after solving fluid flow and solute transport, geochemical calculations are done in form of a central loop over all finite element nodes with calls to GEMS3K and consecutive calculations of changed material parameters. In a first step the existing MPI implementation was utilized to parallelize this loop. Calculations were split between the MPI processes and afterwards data was synchronized by using MPI communication routines. Furthermore, multi-threaded calculation of the loop was implemented with help of the boost thread library (http://www.boost.org). This implementation provides a flexible environment to distribute calculations between several threads. For each MPI process at least one and up to several dozens of worker threads are spawned. These threads do not replicate the complete OGS-GEM data structure and use only a limited amount of memory. Calculation of the central geochemical loop is shared between all threads. Synchronization between the threads is done by barrier commands. The overall number of local threads times MPI processes should match the number of available computing nodes. The combination of multi-threading and MPI provides an effective and flexible environment to speed up OGS-GEMS calculations while limiting the required memory use. Test calculations on different hardware show that for certain types of applications tremendous speedups are possible.

[Series: Medical Applications of the PHITS Code (2): Acceleration by Parallel Computing].

PubMed

Furuta, Takuya; Sato, Tatsuhiko

2015-01-01

Time-consuming Monte Carlo dose calculation becomes feasible owing to the development of computer technology. However, the recent development is due to emergence of the multi-core high performance computers. Therefore, parallel computing becomes a key to achieve good performance of software programs. A Monte Carlo simulation code PHITS contains two parallel computing functions, the distributed-memory parallelization using protocols of message passing interface (MPI) and the shared-memory parallelization using open multi-processing (OpenMP) directives. Users can choose the two functions according to their needs. This paper gives the explanation of the two functions with their advantages and disadvantages. Some test applications are also provided to show their performance using a typical multi-core high performance workstation.

Evolving binary classifiers through parallel computation of multiple fitness cases.

PubMed

Cagnoni, Stefano; Bergenti, Federico; Mordonini, Monica; Adorni, Giovanni

2005-06-01

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed in parallel. Runtime performance is optimized explicitly using parallel computation in the case of cellular programming or implicitly taking advantage of the intrinsic parallelism of bitwise operators on standard sequential architectures in the case of genetic programming. The approach was tested on a digit recognition problem and compared with a reference classifier.

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.

A Debugger for Computational Grid Applications

NASA Technical Reports Server (NTRS)

Hood, Robert; Jost, Gabriele; Biegel, Bryan (Technical Monitor)

2001-01-01

This viewgraph presentation gives an overview of a debugger for computational grid applications. Details are given on NAS parallel tools groups (including parallelization support tools, evaluation of various parallelization strategies, and distributed and aggregated computing), debugger dependencies, scalability, initial implementation, the process grid, and information on Globus.

Application of a Scalable, Parallel, Unstructured-Grid-Based Navier-Stokes Solver

NASA Technical Reports Server (NTRS)

Parikh, Paresh

2001-01-01

A parallel version of an unstructured-grid based Navier-Stokes solver, USM3Dns, previously developed for efficient operation on a variety of parallel computers, has been enhanced to incorporate upgrades made to the serial version. The resultant parallel code has been extensively tested on a variety of problems of aerospace interest and on two sets of parallel computers to understand and document its characteristics. An innovative grid renumbering construct and use of non-blocking communication are shown to produce superlinear computing performance. Preliminary results from parallelization of a recently introduced "porous surface" boundary condition are also presented.

How to Build an AppleSeed: A Parallel Macintosh Cluster for Numerically Intensive Computing

NASA Astrophysics Data System (ADS)

Decyk, V. K.; Dauger, D. E.

We have constructed a parallel cluster consisting of a mixture of Apple Macintosh G3 and G4 computers running the Mac OS, and have achieved very good performance on numerically intensive, parallel plasma particle-incell simulations. A subset of the MPI message-passing library was implemented in Fortran77 and C. This library enabled us to port code, without modification, from other parallel processors to the Macintosh cluster. Unlike Unix-based clusters, no special expertise in operating systems is required to build and run the cluster. This enables us to move parallel computing from the realm of experts to the main stream of computing.

Parallel simulation of tsunami inundation on a large-scale supercomputer

NASA Astrophysics Data System (ADS)

Oishi, Y.; Imamura, F.; Sugawara, D.

2013-12-01

An accurate prediction of tsunami inundation is important for disaster mitigation purposes. One approach is to approximate the tsunami wave source through an instant inversion analysis using real-time observation data (e.g., Tsushima et al., 2009) and then use the resulting wave source data in an instant tsunami inundation simulation. However, a bottleneck of this approach is the large computational cost of the non-linear inundation simulation and the computational power of recent massively parallel supercomputers is helpful to enable faster than real-time execution of a tsunami inundation simulation. Parallel computers have become approximately 1000 times faster in 10 years (www.top500.org), and so it is expected that very fast parallel computers will be more and more prevalent in the near future. Therefore, it is important to investigate how to efficiently conduct a tsunami simulation on parallel computers. In this study, we are targeting very fast tsunami inundation simulations on the K computer, currently the fastest Japanese supercomputer, which has a theoretical peak performance of 11.2 PFLOPS. One computing node of the K computer consists of 1 CPU with 8 cores that share memory, and the nodes are connected through a high-performance torus-mesh network. The K computer is designed for distributed-memory parallel computation, so we have developed a parallel tsunami model. Our model is based on TUNAMI-N2 model of Tohoku University, which is based on a leap-frog finite difference method. A grid nesting scheme is employed to apply high-resolution grids only at the coastal regions. To balance the computation load of each CPU in the parallelization, CPUs are first allocated to each nested layer in proportion to the number of grid points of the nested layer. Using CPUs allocated to each layer, 1-D domain decomposition is performed on each layer. In the parallel computation, three types of communication are necessary: (1) communication to adjacent neighbours for the finite difference calculation, (2) communication between adjacent layers for the calculations to connect each layer, and (3) global communication to obtain the time step which satisfies the CFL condition in the whole domain. A preliminary test on the K computer showed the parallel efficiency on 1024 cores was 57% relative to 64 cores. We estimate that the parallel efficiency will be considerably improved by applying a 2-D domain decomposition instead of the present 1-D domain decomposition in future work. The present parallel tsunami model was applied to the 2011 Great Tohoku tsunami. The coarsest resolution layer covers a 758 km × 1155 km region with a 405 m grid spacing. A nesting of five layers was used with the resolution ratio of 1/3 between nested layers. The finest resolution region has 5 m resolution and covers most of the coastal region of Sendai city. To complete 2 hours of simulation time, the serial (non-parallel) computation took approximately 4 days on a workstation. To complete the same simulation on 1024 cores of the K computer, it took 45 minutes which is more than two times faster than real-time. This presentation discusses the updated parallel computational performance and the efficient use of the K computer when considering the characteristics of the tsunami inundation simulation model in relation to the characteristics and capabilities of the K computer.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

PubMed

Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

2014-01-16

To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

2014-01-01

Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

Parallel CE/SE Computations via Domain Decomposition

NASA Technical Reports Server (NTRS)

Himansu, Ananda; Jorgenson, Philip C. E.; Wang, Xiao-Yen; Chang, Sin-Chung

2000-01-01

This paper describes the parallelization strategy and achieved parallel efficiency of an explicit time-marching algorithm for solving conservation laws. The Space-Time Conservation Element and Solution Element (CE/SE) algorithm for solving the 2D and 3D Euler equations is parallelized with the aid of domain decomposition. The parallel efficiency of the resultant algorithm on a Silicon Graphics Origin 2000 parallel computer is checked.

Change in Seroma Volume During Whole-Breast Radiation Therapy

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

Sharma, Rajiv; Spierer, Marnee; Mutyala, Subhakar

2009-09-01

Purpose: After breast-conserving surgery, a seroma often forms in the surgical cavity. If not drained, it may affect the volume of tumor bed requiring a boost after whole-breast radiation therapy (WBRT). Our objective was to evaluate the change in seroma volume that occurs during WBRT, before boost planning. Methods and Materials: A retrospective review was performed of women receiving breast-conserving therapy with evidence of seroma at the time of WBRT planning. Computed tomography (CT) simulation was performed before WBRT and before the tumor bed boost. All patients received either a hypofractionated (42.4 Gy/16 fraction + 9.6 Gy/4 fraction boost) ormore » standard fractionated (50.4 Gy/28 fraction + 10 Gy/5 fraction boost) regimen. Seroma volumes were contoured and compared on CT at the time of WBRT simulation and tumor bed boost planning. Results: Twenty-four patients with evidence of seroma were identified and all patients received WBRT without drainage of the seroma. Mean seroma volume before WBRT and at boost planning were significantly different at 65.7 cm{sup 3} (SD, 50.5 cm{sup 3}) and 35.6 cm{sup 3} (SD, 24.8 cm{sup 3}), respectively (p < 0.001). Mean and median reduction in seroma volume during radiation were 39.6% (SD, 23.8%) and 46.2% (range, 10.7-76.7%), respectively. Fractionation schedule was not correlated with change in seroma volume. Length of time from surgery to start of radiation therapy showed an inverse correlation with change in seroma volume (Pearson correlation r = -0.53, p < 0.01). Conclusions: The volume of seroma changes significantly during WBRT. Consequently, the accuracy of breast boost planning is likely affected, as is the volume of normal breast tissue irradiated. CT-based boost planning before boost irradiation is suggested to ensure appropriate coverage.« less

Parallel Algorithms for Least Squares and Related Computations.

DTIC Science & Technology

1991-03-22

for dense computations in linear algebra . The work has recently been published in a general reference book on parallel algorithms by SIAM. AFO SR...written his Ph.D. dissertation with the principal investigator. (See publication 6.) • Parallel Algorithms for Dense Linear Algebra Computations. Our...and describe and to put into perspective a selection of the more important parallel algorithms for numerical linear algebra . We give a major new

Reliability models for dataflow computer systems

NASA Technical Reports Server (NTRS)

Kavi, K. M.; Buckles, B. P.

1985-01-01

The demands for concurrent operation within a computer system and the representation of parallelism in programming languages have yielded a new form of program representation known as data flow (DENN 74, DENN 75, TREL 82a). A new model based on data flow principles for parallel computations and parallel computer systems is presented. Necessary conditions for liveness and deadlock freeness in data flow graphs are derived. The data flow graph is used as a model to represent asynchronous concurrent computer architectures including data flow computers.

Parallel computing method for simulating hydrological processesof large rivers under climate change

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.

2016-12-01

Climate change is one of the proverbial global environmental problems in the world.Climate change has altered the watershed hydrological processes in time and space distribution, especially in worldlarge rivers.Watershed hydrological process simulation based on physically based distributed hydrological model can could have better results compared with the lumped models.However, watershed hydrological process simulation includes large amount of calculations, especially in large rivers, thus needing huge computing resources that may not be steadily available for the researchers or at high expense, this seriously restricted the research and application. To solve this problem, the current parallel method are mostly parallel computing in space and time dimensions.They calculate the natural features orderly thatbased on distributed hydrological model by grid (unit, a basin) from upstream to downstream.This articleproposes ahigh-performancecomputing method of hydrological process simulation with high speedratio and parallel efficiency.It combinedthe runoff characteristics of time and space of distributed hydrological model withthe methods adopting distributed data storage, memory database, distributed computing, parallel computing based on computing power unit.The method has strong adaptability and extensibility,which means it canmake full use of the computing and storage resources under the condition of limited computing resources, and the computing efficiency can be improved linearly with the increase of computing resources .This method can satisfy the parallel computing requirements ofhydrological process simulation in small, medium and large rivers.

Engineering RENTA, a DNA prime-MVA boost HIV vaccine tailored for Eastern and Central Africa.

PubMed

Nkolola, J P; Wee, E G-T; Im, E-J; Jewell, C P; Chen, N; Xu, X-N; McMichael, A J; Hanke, T

2004-07-01

For the development of human immunodeficiency virus type 1 (HIV-1) vaccines, traditional approaches inducing virus-neutralizing antibodies have so far failed. Thus the effort is now focused on elicitation of cellular immunity. We are currently testing in clinical trials in the United Kingdom and East Africa a T-cell vaccine consisting of HIV-1 clade A Gag-derived immunogen HIVA delivered in a prime-boost regimen by a DNA plasmid and modified vaccinia virus Ankara (MVA). Here, we describe engineering and preclinical development of a second immunogen RENTA, which will be used in combination with the present vaccine in a four-component DNA/HIVA-RENTA prime-MVA/HIVA-RENTA boost formulation. RENTA is a fusion protein derived from consensus HIV clade A sequences of Tat, reverse transcriptase, Nef and gp41. We inactivated the natural biological activities of the HIV components and confirmed immunogenicities of the pTHr.RENTA and MVA.RENTA vaccines in mice. Furthermore, we demonstrated in mice and rhesus monkeys broadening of HIVA-elicited T-cell responses by a parallel induction of HIVA- and RENTA-specific responses recognizing multiple HIV epitopes.

Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm.

PubMed

Kamath, Uday; Domeniconi, Carlotta; De Jong, Kenneth

2018-01-01

Many real-world problems involve massive amounts of data. Under these circumstances learning algorithms often become prohibitively expensive, making scalability a pressing issue to be addressed. A common approach is to perform sampling to reduce the size of the dataset and enable efficient learning. Alternatively, one customizes learning algorithms to achieve scalability. In either case, the key challenge is to obtain algorithmic efficiency without compromising the quality of the results. In this article we discuss a meta-learning algorithm (PSBML) that combines concepts from spatially structured evolutionary algorithms (SSEAs) with concepts from ensemble and boosting methodologies to achieve the desired scalability property. We present both theoretical and empirical analyses which show that PSBML preserves a critical property of boosting, specifically, convergence to a distribution centered around the margin. We then present additional empirical analyses showing that this meta-level algorithm provides a general and effective framework that can be used in combination with a variety of learning classifiers. We perform extensive experiments to investigate the trade-off achieved between scalability and accuracy, and robustness to noise, on both synthetic and real-world data. These empirical results corroborate our theoretical analysis, and demonstrate the potential of PSBML in achieving scalability without sacrificing accuracy.

Endpoint-based parallel data processing in a parallel active messaging interface of a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael E; Ratterman, Joseph D; Smith, Brian E

2014-02-11

Endpoint-based parallel data processing in a parallel active messaging interface ('PAMI') of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective opeartion through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.

Endpoint-based parallel data processing in a parallel active messaging interface of a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.

2014-08-12

Endpoint-based parallel data processing in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective operation through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.

Orbit Transfer Vehicle (OTV) advanced expander cycle engine point design study. Volume 2: Study results

NASA Technical Reports Server (NTRS)

1980-01-01

Detailed computer models of the engine were developed to predict both the steady state and transient operation of the engine system. Mechanical design layout drawings were prepared for the following components: thrust chamber and nozzle; extendible nozzle actuating mechanism and seal; LOX turbopump and boost pump; hydrogen turbopump and boost pump; and the propellant control valves. The necessary heat transfer, stress, fluid flow, dynamic, and performance analyses were performed to support the mechanical design.

Why not make a PC cluster of your own? 5. AppleSeed: A Parallel Macintosh Cluster for Scientific Computing

NASA Astrophysics Data System (ADS)

Decyk, Viktor K.; Dauger, Dean E.

We have constructed a parallel cluster consisting of Apple Macintosh G4 computers running both Classic Mac OS as well as the Unix-based Mac OS X, and have achieved very good performance on numerically intensive, parallel plasma particle-in-cell simulations. Unlike other Unix-based clusters, no special expertise in operating systems is required to build and run the cluster. This enables us to move parallel computing from the realm of experts to the mainstream of computing.

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.

A parallel Jacobson-Oksman optimization algorithm. [parallel processing (computers)

NASA Technical Reports Server (NTRS)

Straeter, T. A.; Markos, A. T.

1975-01-01

A gradient-dependent optimization technique which exploits the vector-streaming or parallel-computing capabilities of some modern computers is presented. The algorithm, derived by assuming that the function to be minimized is homogeneous, is a modification of the Jacobson-Oksman serial minimization method. In addition to describing the algorithm, conditions insuring the convergence of the iterates of the algorithm and the results of numerical experiments on a group of sample test functions are presented. The results of these experiments indicate that this algorithm will solve optimization problems in less computing time than conventional serial methods on machines having vector-streaming or parallel-computing capabilities.

Methods of parallel computation applied on granular simulations

NASA Astrophysics Data System (ADS)

Martins, Gustavo H. B.; Atman, Allbens P. F.

2017-06-01

Every year, parallel computing has becoming cheaper and more accessible. As consequence, applications were spreading over all research areas. Granular materials is a promising area for parallel computing. To prove this statement we study the impact of parallel computing in simulations of the BNE (Brazil Nut Effect). This property is due the remarkable arising of an intruder confined to a granular media when vertically shaken against gravity. By means of DEM (Discrete Element Methods) simulations, we study the code performance testing different methods to improve clock time. A comparison between serial and parallel algorithms, using OpenMP® is also shown. The best improvement was obtained by optimizing the function that find contacts using Verlet's cells.

Parallel computation using boundary elements in solid mechanics

NASA Technical Reports Server (NTRS)

Chien, L. S.; Sun, C. T.

1990-01-01

The inherent parallelism of the boundary element method is shown. The boundary element is formulated by assuming the linear variation of displacements and tractions within a line element. Moreover, MACSYMA symbolic program is employed to obtain the analytical results for influence coefficients. Three computational components are parallelized in this method to show the speedup and efficiency in computation. The global coefficient matrix is first formed concurrently. Then, the parallel Gaussian elimination solution scheme is applied to solve the resulting system of equations. Finally, and more importantly, the domain solutions of a given boundary value problem are calculated simultaneously. The linear speedups and high efficiencies are shown for solving a demonstrated problem on Sequent Symmetry S81 parallel computing system.

Parallel Algorithms for the Exascale Era

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

Robey, Robert W.

New parallel algorithms are needed to reach the Exascale level of parallelism with millions of cores. We look at some of the research developed by students in projects at LANL. The research blends ideas from the early days of computing while weaving in the fresh approach brought by students new to the field of high performance computing. We look at reproducibility of global sums and why it is important to parallel computing. Next we look at how the concept of hashing has led to the development of more scalable algorithms suitable for next-generation parallel computers. Nearly all of this workmore » has been done by undergraduates and published in leading scientific journals.« less

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1986-01-01

Various graduate research activities in the field of computer science are reported. Among the topics discussed are: (1) failure probabilities in multi-version software; (2) Gaussian Elimination on parallel computers; (3) three dimensional Poisson solvers on parallel/vector computers; (4) automated task decomposition for multiple robot arms; (5) multi-color incomplete cholesky conjugate gradient methods on the Cyber 205; and (6) parallel implementation of iterative methods for solving linear equations.

A high-speed linear algebra library with automatic parallelism

NASA Technical Reports Server (NTRS)

Boucher, Michael L.

1994-01-01

Parallel or distributed processing is key to getting highest performance workstations. However, designing and implementing efficient parallel algorithms is difficult and error-prone. It is even more difficult to write code that is both portable to and efficient on many different computers. Finally, it is harder still to satisfy the above requirements and include the reliability and ease of use required of commercial software intended for use in a production environment. As a result, the application of parallel processing technology to commercial software has been extremely small even though there are numerous computationally demanding programs that would significantly benefit from application of parallel processing. This paper describes DSSLIB, which is a library of subroutines that perform many of the time-consuming computations in engineering and scientific software. DSSLIB combines the high efficiency and speed of parallel computation with a serial programming model that eliminates many undesirable side-effects of typical parallel code. The result is a simple way to incorporate the power of parallel processing into commercial software without compromising maintainability, reliability, or ease of use. This gives significant advantages over less powerful non-parallel entries in the market.

RRAM-based parallel computing architecture using k-nearest neighbor classification for pattern recognition

NASA Astrophysics Data System (ADS)

Jiang, Yuning; Kang, Jinfeng; Wang, Xinan

2017-03-01

Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.

Symplectic molecular dynamics simulations on specially designed parallel computers.

PubMed

Borstnik, Urban; Janezic, Dusanka

2005-01-01

We have developed a computer program for molecular dynamics (MD) simulation that implements the Split Integration Symplectic Method (SISM) and is designed to run on specialized parallel computers. The MD integration is performed by the SISM, which analytically treats high-frequency vibrational motion and thus enables the use of longer simulation time steps. The low-frequency motion is treated numerically on specially designed parallel computers, which decreases the computational time of each simulation time step. The combination of these approaches means that less time is required and fewer steps are needed and so enables fast MD simulations. We study the computational performance of MD simulation of molecular systems on specialized computers and provide a comparison to standard personal computers. The combination of the SISM with two specialized parallel computers is an effective way to increase the speed of MD simulations up to 16-fold over a single PC processor.

Outer boundary as arrested history in general relativity

NASA Astrophysics Data System (ADS)

Lau, Stephen R.

2002-06-01

We present explicit outer boundary conditions for the canonical variables of general relativity. The conditions are associated with the causal evolution of a finite Cauchy domain, a so-called quasilocal boost, and they suggest a consistent scheme for modelling such an evolution numerically. The scheme involves a continuous boost in the spacetime orthogonal complement ⊥Tp(B) of the tangent space Tp(B) belonging to each point p on the system boundary B. We show how the boost rate may be computed numerically via equations similar to those appearing in canonical investigations of black-hole thermodynamics (although here holding at an outer two-surface rather than the bifurcate two-surface of a Killing horizon). We demonstrate the numerical scheme on a model example, the quasilocal boost of a spherical three-ball in Minkowski spacetime. Developing our general formalism with recent hyperbolic formulations of the Einstein equations in mind, we use Anderson and York's 'Einstein-Christoffel' hyperbolic system as the evolution equations for our numerical simulation of the model.

Streamlining the Design-to-Build Transition with Build-Optimization Software Tools.

PubMed

Oberortner, Ernst; Cheng, Jan-Fang; Hillson, Nathan J; Deutsch, Samuel

2017-03-17

Scaling-up capabilities for the design, build, and test of synthetic biology constructs holds great promise for the development of new applications in fuels, chemical production, or cellular-behavior engineering. Construct design is an essential component in this process; however, not every designed DNA sequence can be readily manufactured, even using state-of-the-art DNA synthesis methods. Current biological computer-aided design and manufacture tools (bioCAD/CAM) do not adequately consider the limitations of DNA synthesis technologies when generating their outputs. Designed sequences that violate DNA synthesis constraints may require substantial sequence redesign or lead to price-premiums and temporal delays, which adversely impact the efficiency of the DNA manufacturing process. We have developed a suite of build-optimization software tools (BOOST) to streamline the design-build transition in synthetic biology engineering workflows. BOOST incorporates knowledge of DNA synthesis success determinants into the design process to output ready-to-build sequences, preempting the need for sequence redesign. The BOOST web application is available at https://boost.jgi.doe.gov and its Application Program Interfaces (API) enable integration into automated, customized DNA design processes. The herein presented results highlight the effectiveness of BOOST in reducing DNA synthesis costs and timelines.

Regulation of the Output Voltage of an Inverter in Case of Load Variation

NASA Astrophysics Data System (ADS)

Diouri, Omar; Errahimi, Fatima; Es-Sbai, Najia

2018-05-01

In a DC/AC photovoltaic application, the stability of the output voltage of the inverter plays a very important role in the electrical systems. Such a photovoltaic system is constituted by an inverter, which makes it possible to convert the continuous energy to the alternative energy used in systems which operate under a voltage of 230V. The output of this inverter can be connected to a single load or more, at which time a second load is added in parallel with the first load. In this case, it proves a voltage drop at the output of the inverter. This problem influences the proper functioning of the electrical loads. Therefore, our contribution is to give a solution to this by compensating this voltage drop using a boost converter at the input of the inverter. This boost converter will play the role of the compensator that will provide the necessary voltage to the inverter in order to increase the voltage across the loads. But the use of this boost without controlling it is not enough because it generates a voltage that depends on the duty cycle of the control signal. To stabilize the output voltage of the inverter, we used a Proportional, Integral, and Derivative control (PID), which makes it possible to generate the necessary control signal for the voltage boost in order to have a good regulation of the output voltage of the inverter. Finally, we have solved the problem of the voltage drop even though there is loads variation.

An optimized posterior axillary boost technique in radiation therapy to supraclavicular and axillary lymph nodes: A comparative study

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

Hernandez, Victor, E-mail: vhernandezmasgrau@gmail.com; Arenas, Meritxell; Müller, Katrin

2013-01-01

To assess the advantages of an optimized posterior axillary (AX) boost technique for the irradiation of supraclavicular (SC) and AX lymph nodes. Five techniques for the treatment of SC and levels I, II, and III AX lymph nodes were evaluated for 10 patients selected at random: a direct anterior field (AP); an anterior to posterior parallel pair (AP-PA); an anterior field with a posterior axillary boost (PAB); an anterior field with an anterior axillary boost (AAB); and an optimized PAB technique (OptPAB). The target coverage, hot spots, irradiated volume, and dose to organs at risk were evaluated and a statisticalmore » analysis comparison was performed. The AP technique delivered insufficient dose to the deeper AX nodes. The AP-PA technique produced larger irradiated volumes and higher mean lung doses than the other techniques. The PAB and AAB techniques originated excessive hot spots in most of the cases. The OptPAB technique produced moderate hot spots while maintaining a similar planning target volume (PTV) coverage, irradiated volume, and dose to organs at risk. This optimized technique combines the advantages of the PAB and AP-PA techniques, with moderate hot spots, sufficient target coverage, and adequate sparing of normal tissues. The presented technique is simple, fast, and easy to implement in routine clinical practice and is superior to the techniques historically used for the treatment of SC and AX lymph nodes.« less

Experiences modeling ocean circulation problems on a 30 node commodity cluster with 3840 GPU processor cores.

NASA Astrophysics Data System (ADS)

Hill, C.

2008-12-01

Low cost graphic cards today use many, relatively simple, compute cores to deliver support for memory bandwidth of more than 100GB/s and theoretical floating point performance of more than 500 GFlop/s. Right now this performance is, however, only accessible to highly parallel algorithm implementations that, (i) can use a hundred or more, 32-bit floating point, concurrently executing cores, (ii) can work with graphics memory that resides on the graphics card side of the graphics bus and (iii) can be partially expressed in a language that can be compiled by a graphics programming tool. In this talk we describe our experiences implementing a complete, but relatively simple, time dependent shallow-water equations simulation targeting a cluster of 30 computers each hosting one graphics card. The implementation takes into account the considerations (i), (ii) and (iii) listed previously. We code our algorithm as a series of numerical kernels. Each kernel is designed to be executed by multiple threads of a single process. Kernels are passed memory blocks to compute over which can be persistent blocks of memory on a graphics card. Each kernel is individually implemented using the NVidia CUDA language but driven from a higher level supervisory code that is almost identical to a standard model driver. The supervisory code controls the overall simulation timestepping, but is written to minimize data transfer between main memory and graphics memory (a massive performance bottle-neck on current systems). Using the recipe outlined we can boost the performance of our cluster by nearly an order of magnitude, relative to the same algorithm executing only on the cluster CPU's. Achieving this performance boost requires that many threads are available to each graphics processor for execution within each numerical kernel and that the simulations working set of data can fit into the graphics card memory. As we describe, this puts interesting upper and lower bounds on the problem sizes for which this technology is currently most useful. However, many interesting problems fit within this envelope. Looking forward, we extrapolate our experience to estimate full-scale ocean model performance and applicability. Finally we describe preliminary hybrid mixed 32-bit and 64-bit experiments with graphics cards that support 64-bit arithmetic, albeit at a lower performance.

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

Parallel algorithms for mapping pipelined and parallel computations

NASA Technical Reports Server (NTRS)

Nicol, David M.

1988-01-01

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

Synthesizing parallel imaging applications using the CAP (computer-aided parallelization) tool

NASA Astrophysics Data System (ADS)

Gennart, Benoit A.; Mazzariol, Marc; Messerli, Vincent; Hersch, Roger D.

1997-12-01

Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of computing power when applied to large data sets. These applications would potentially benefit from the use of parallel processing. However, dedicated parallel computers are expensive and their processing power per node lags behind that of the most recent commodity components. Furthermore, developing parallel applications remains a difficult task: writing and debugging the application is difficult (deadlocks), programs may not be portable from one parallel architecture to the other, and performance often comes short of expectations. In order to facilitate the development of parallel applications, we propose the CAP computer-aided parallelization tool which enables application programmers to specify at a high-level of abstraction the flow of data between pipelined-parallel operations. In addition, the CAP tool supports the programmer in developing parallel imaging and storage operations. CAP enables combining efficiently parallel storage access routines and image processing sequential operations. This paper shows how processing and I/O intensive imaging applications must be implemented to take advantage of parallelism and pipelining between data access and processing. This paper's contribution is (1) to show how such implementations can be compactly specified in CAP, and (2) to demonstrate that CAP specified applications achieve the performance of custom parallel code. The paper analyzes theoretically the performance of CAP specified applications and demonstrates the accuracy of the theoretical analysis through experimental measurements.

CSM parallel structural methods research

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1989-01-01

Parallel structural methods, research team activities, advanced architecture computers for parallel computational structural mechanics (CSM) research, the FLEX/32 multicomputer, a parallel structural analyses testbed, blade-stiffened aluminum panel with a circular cutout and the dynamic characteristics of a 60 meter, 54-bay, 3-longeron deployable truss beam are among the topics discussed.

Parallelized direct execution simulation of message-passing parallel programs

NASA Technical Reports Server (NTRS)

Dickens, Phillip M.; Heidelberger, Philip; Nicol, David M.

1994-01-01

As massively parallel computers proliferate, there is growing interest in findings ways by which performance of massively parallel codes can be efficiently predicted. This problem arises in diverse contexts such as parallelizing computers, parallel performance monitoring, and parallel algorithm development. In this paper we describe one solution where one directly executes the application code, but uses a discrete-event simulator to model details of the presumed parallel machine such as operating system and communication network behavior. Because this approach is computationally expensive, we are interested in its own parallelization specifically the parallelization of the discrete-event simulator. We describe methods suitable for parallelized direct execution simulation of message-passing parallel programs, and report on the performance of such a system, Large Application Parallel Simulation Environment (LAPSE), we have built on the Intel Paragon. On all codes measured to date, LAPSE predicts performance well typically within 10 percent relative error. Depending on the nature of the application code, we have observed low slowdowns (relative to natively executing code) and high relative speedups using up to 64 processors.

Automatic Generation of Directive-Based Parallel Programs for Shared Memory Parallel Systems

NASA Technical Reports Server (NTRS)

Jin, Hao-Qiang; Yan, Jerry; Frumkin, Michael

2000-01-01

The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. As great progress was made in hardware and software technologies, performance of parallel programs with compiler directives has demonstrated large improvement. The introduction of OpenMP directives, the industrial standard for shared-memory programming, has minimized the issue of portability. Due to its ease of programming and its good performance, the technique has become very popular. In this study, we have extended CAPTools, a computer-aided parallelization toolkit, to automatically generate directive-based, OpenMP, parallel programs. We outline techniques used in the implementation of the tool and present test results on the NAS parallel benchmarks and ARC3D, a CFD application. This work demonstrates the great potential of using computer-aided tools to quickly port parallel programs and also achieve good performance.

The science of computing - Parallel computation

NASA Technical Reports Server (NTRS)

Denning, P. J.

1985-01-01

Although parallel computation architectures have been known for computers since the 1920s, it was only in the 1970s that microelectronic components technologies advanced to the point where it became feasible to incorporate multiple processors in one machine. Concommitantly, the development of algorithms for parallel processing also lagged due to hardware limitations. The speed of computing with solid-state chips is limited by gate switching delays. The physical limit implies that a 1 Gflop operational speed is the maximum for sequential processors. A computer recently introduced features a 'hypercube' architecture with 128 processors connected in networks at 5, 6 or 7 points per grid, depending on the design choice. Its computing speed rivals that of supercomputers, but at a fraction of the cost. The added speed with less hardware is due to parallel processing, which utilizes algorithms representing different parts of an equation that can be broken into simpler statements and processed simultaneously. Present, highly developed computer languages like FORTRAN, PASCAL, COBOL, etc., rely on sequential instructions. Thus, increased emphasis will now be directed at parallel processing algorithms to exploit the new architectures.

Parallel-Processing Test Bed For Simulation Software

NASA Technical Reports Server (NTRS)

Blech, Richard; Cole, Gary; Townsend, Scott

1996-01-01

Second-generation Hypercluster computing system is multiprocessor test bed for research on parallel algorithms for simulation in fluid dynamics, electromagnetics, chemistry, and other fields with large computational requirements but relatively low input/output requirements. Built from standard, off-shelf hardware readily upgraded as improved technology becomes available. System used for experiments with such parallel-processing concepts as message-passing algorithms, debugging software tools, and computational steering. First-generation Hypercluster system described in "Hypercluster Parallel Processor" (LEW-15283).

SemiBoost: boosting for semi-supervised learning.

PubMed

Mallapragada, Pavan Kumar; Jin, Rong; Jain, Anil K; Liu, Yi

2009-11-01

Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most previous studies have focused on designing special algorithms to effectively exploit the unlabeled data in conjunction with labeled data. Our goal is to improve the classification accuracy of any given supervised learning algorithm by using the available unlabeled examples. We call this as the Semi-supervised improvement problem, to distinguish the proposed approach from the existing approaches. We design a metasemi-supervised learning algorithm that wraps around the underlying supervised algorithm and improves its performance using unlabeled data. This problem is particularly important when we need to train a supervised learning algorithm with a limited number of labeled examples and a multitude of unlabeled examples. We present a boosting framework for semi-supervised learning, termed as SemiBoost. The key advantages of the proposed semi-supervised learning approach are: 1) performance improvement of any supervised learning algorithm with a multitude of unlabeled data, 2) efficient computation by the iterative boosting algorithm, and 3) exploiting both manifold and cluster assumption in training classification models. An empirical study on 16 different data sets and text categorization demonstrates that the proposed framework improves the performance of several commonly used supervised learning algorithms, given a large number of unlabeled examples. We also show that the performance of the proposed algorithm, SemiBoost, is comparable to the state-of-the-art semi-supervised learning algorithms.

System-wide power management control via clock distribution network

DOEpatents

Coteus, Paul W.; Gara, Alan; Gooding, Thomas M.; Haring, Rudolf A.; Kopcsay, Gerard V.; Liebsch, Thomas A.; Reed, Don D.

2015-05-19

An apparatus, method and computer program product for automatically controlling power dissipation of a parallel computing system that includes a plurality of processors. A computing device issues a command to the parallel computing system. A clock pulse-width modulator encodes the command in a system clock signal to be distributed to the plurality of processors. The plurality of processors in the parallel computing system receive the system clock signal including the encoded command, and adjusts power dissipation according to the encoded command.

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.

Implementation of DFT application on ternary optical computer

NASA Astrophysics Data System (ADS)

Junjie, Peng; Youyi, Fu; Xiaofeng, Zhang; Shuai, Kong; Xinyu, Wei

2018-03-01

As its characteristics of huge number of data bits and low energy consumption, optical computing may be used in the applications such as DFT etc. which needs a lot of computation and can be implemented in parallel. According to this, DFT implementation methods in full parallel as well as in partial parallel are presented. Based on resources ternary optical computer (TOC), extensive experiments were carried out. Experimental results show that the proposed schemes are correct and feasible. They provide a foundation for further exploration of the applications on TOC that needs a large amount calculation and can be processed in parallel.

Special purpose parallel computer architecture for real-time control and simulation in robotic applications

NASA Technical Reports Server (NTRS)

Fijany, Amir (Inventor); Bejczy, Antal K. (Inventor)

1993-01-01

This is a real-time robotic controller and simulator which is a MIMD-SIMD parallel architecture for interfacing with an external host computer and providing a high degree of parallelism in computations for robotic control and simulation. It includes a host processor for receiving instructions from the external host computer and for transmitting answers to the external host computer. There are a plurality of SIMD microprocessors, each SIMD processor being a SIMD parallel processor capable of exploiting fine grain parallelism and further being able to operate asynchronously to form a MIMD architecture. Each SIMD processor comprises a SIMD architecture capable of performing two matrix-vector operations in parallel while fully exploiting parallelism in each operation. There is a system bus connecting the host processor to the plurality of SIMD microprocessors and a common clock providing a continuous sequence of clock pulses. There is also a ring structure interconnecting the plurality of SIMD microprocessors and connected to the clock for providing the clock pulses to the SIMD microprocessors and for providing a path for the flow of data and instructions between the SIMD microprocessors. The host processor includes logic for controlling the RRCS by interpreting instructions sent by the external host computer, decomposing the instructions into a series of computations to be performed by the SIMD microprocessors, using the system bus to distribute associated data among the SIMD microprocessors, and initiating activity of the SIMD microprocessors to perform the computations on the data by procedure call.

Exact parallel algorithms for some members of the traveling salesman problem family

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

Pekny, J.F.

1989-01-01

The traveling salesman problem and its many generalizations comprise one of the best known combinatorial optimization problem families. Most members of the family are NP-complete problems so that exact algorithms require an unpredictable and sometimes large computational effort. Parallel computers offer hope for providing the power required to meet these demands. A major barrier to applying parallel computers is the lack of parallel algorithms. The contributions presented in this thesis center around new exact parallel algorithms for the asymmetric traveling salesman problem (ATSP), prize collecting traveling salesman problem (PCTSP), and resource constrained traveling salesman problem (RCTSP). The RCTSP is amore » particularly difficult member of the family since finding a feasible solution is an NP-complete problem. An exact sequential algorithm is also presented for the directed hamiltonian cycle problem (DHCP). The DHCP algorithm is superior to current heuristic approaches and represents the first exact method applicable to large graphs. Computational results presented for each of the algorithms demonstrates the effectiveness of combining efficient algorithms with parallel computing methods. Performance statistics are reported for randomly generated ATSPs with 7,500 cities, PCTSPs with 200 cities, RCTSPs with 200 cities, DHCPs with 3,500 vertices, and assignment problems of size 10,000. Sequential results were collected on a Sun 4/260 engineering workstation, while parallel results were collected using a 14 and 100 processor BBN Butterfly Plus computer. The computational results represent the largest instances ever solved to optimality on any type of computer.« less

Use of parallel computing in mass processing of laser data

NASA Astrophysics Data System (ADS)

Będkowski, J.; Bratuś, R.; Prochaska, M.; Rzonca, A.

2015-12-01

The first part of the paper includes a description of the rules used to generate the algorithm needed for the purpose of parallel computing and also discusses the origins of the idea of research on the use of graphics processors in large scale processing of laser scanning data. The next part of the paper includes the results of an efficiency assessment performed for an array of different processing options, all of which were substantially accelerated with parallel computing. The processing options were divided into the generation of orthophotos using point clouds, coloring of point clouds, transformations, and the generation of a regular grid, as well as advanced processes such as the detection of planes and edges, point cloud classification, and the analysis of data for the purpose of quality control. Most algorithms had to be formulated from scratch in the context of the requirements of parallel computing. A few of the algorithms were based on existing technology developed by the Dephos Software Company and then adapted to parallel computing in the course of this research study. Processing time was determined for each process employed for a typical quantity of data processed, which helped confirm the high efficiency of the solutions proposed and the applicability of parallel computing to the processing of laser scanning data. The high efficiency of parallel computing yields new opportunities in the creation and organization of processing methods for laser scanning data.

Chaos minimization in DC-DC boost converter using circuit parameter optimization

NASA Astrophysics Data System (ADS)

Sudhakar, N.; Natarajan, Rajasekar; Gourav, Kumar; Padmavathi, P.

2017-11-01

DC-DC converters are prone to several types of nonlinear phenomena including bifurcation, quasi periodicity, intermittency and chaos. These undesirable effects must be controlled for periodic operation of the converter to ensure the stability. In this paper an effective solution to control of chaos in solar fed DC-DC boost converter is proposed. Controlling of chaos is significantly achieved using optimal circuit parameters obtained through Bacterial Foraging Optimization Algorithm. The optimization renders the suitable parameters in minimum computational time. The obtained results are compared with the operation of traditional boost converter. Further the obtained results with BFA optimized parameter ensures the operations of the converter are within the controllable region. To elaborate the study of bifurcation analysis with optimized and unoptimized parameters are also presented.

Parallelized computation for computer simulation of electrocardiograms using personal computers with multi-core CPU and general-purpose GPU.

PubMed

Shen, Wenfeng; Wei, Daming; Xu, Weimin; Zhu, Xin; Yuan, Shizhong

2010-10-01

Biological computations like electrocardiological modelling and simulation usually require high-performance computing environments. This paper introduces an implementation of parallel computation for computer simulation of electrocardiograms (ECGs) in a personal computer environment with an Intel CPU of Core (TM) 2 Quad Q6600 and a GPU of Geforce 8800GT, with software support by OpenMP and CUDA. It was tested in three parallelization device setups: (a) a four-core CPU without a general-purpose GPU, (b) a general-purpose GPU plus 1 core of CPU, and (c) a four-core CPU plus a general-purpose GPU. To effectively take advantage of a multi-core CPU and a general-purpose GPU, an algorithm based on load-prediction dynamic scheduling was developed and applied to setting (c). In the simulation with 1600 time steps, the speedup of the parallel computation as compared to the serial computation was 3.9 in setting (a), 16.8 in setting (b), and 20.0 in setting (c). This study demonstrates that a current PC with a multi-core CPU and a general-purpose GPU provides a good environment for parallel computations in biological modelling and simulation studies. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Creating a Parallel Version of VisIt for Microsoft Windows

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

Whitlock, B J; Biagas, K S; Rawson, P L

2011-12-07

VisIt is a popular, free interactive parallel visualization and analysis tool for scientific data. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images or movies for presentations. VisIt was designed from the ground up to work on many scales of computers from modest desktops up to massively parallel clusters. VisIt is comprised of a set of cooperating programs. All programs can be run locally or in client/server mode in which some run locally and some run remotely on compute clusters. The VisIt program most able to harness today's computing powermore » is the VisIt compute engine. The compute engine is responsible for reading simulation data from disk, processing it, and sending results or images back to the VisIt viewer program. In a parallel environment, the compute engine runs several processes, coordinating using the Message Passing Interface (MPI) library. Each MPI process reads some subset of the scientific data and filters the data in various ways to create useful visualizations. By using MPI, VisIt has been able to scale well into the thousands of processors on large computers such as dawn and graph at LLNL. The advent of multicore CPU's has made parallelism the 'new' way to achieve increasing performance. With today's computers having at least 2 cores and in many cases up to 8 and beyond, it is more important than ever to deploy parallel software that can use that computing power not only on clusters but also on the desktop. We have created a parallel version of VisIt for Windows that uses Microsoft's MPI implementation (MSMPI) to process data in parallel on the Windows desktop as well as on a Windows HPC cluster running Microsoft Windows Server 2008. Initial desktop parallel support for Windows was deployed in VisIt 2.4.0. Windows HPC cluster support has been completed and will appear in the VisIt 2.5.0 release. We plan to continue supporting parallel VisIt on Windows so our users will be able to take full advantage of their multicore resources.« less

HeNCE: A Heterogeneous Network Computing Environment

DOE PAGES

Beguelin, Adam; Dongarra, Jack J.; Geist, George Al; ...

1994-01-01

Network computing seeks to utilize the aggregate resources of many networked computers to solve a single problem. In so doing it is often possible to obtain supercomputer performance from an inexpensive local area network. The drawback is that network computing is complicated and error prone when done by hand, especially if the computers have different operating systems and data formats and are thus heterogeneous. The heterogeneous network computing environment (HeNCE) is an integrated graphical environment for creating and running parallel programs over a heterogeneous collection of computers. It is built on a lower level package called parallel virtual machine (PVM).more » The HeNCE philosophy of parallel programming is to have the programmer graphically specify the parallelism of a computation and to automate, as much as possible, the tasks of writing, compiling, executing, debugging, and tracing the network computation. Key to HeNCE is a graphical language based on directed graphs that describe the parallelism and data dependencies of an application. Nodes in the graphs represent conventional Fortran or C subroutines and the arcs represent data and control flow. This article describes the present state of HeNCE, its capabilities, limitations, and areas of future research.« less

Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

PubMed Central

Tankam, Patrice; Santhanam, Anand P.; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P.

2014-01-01

Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing. PMID:24695868

Parallelized multi-graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy.

PubMed

Tankam, Patrice; Santhanam, Anand P; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P

2014-07-01

Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing.

Seeing the forest for the trees: Networked workstations as a parallel processing computer

NASA Technical Reports Server (NTRS)

Breen, J. O.; Meleedy, D. M.

1992-01-01

Unlike traditional 'serial' processing computers in which one central processing unit performs one instruction at a time, parallel processing computers contain several processing units, thereby, performing several instructions at once. Many of today's fastest supercomputers achieve their speed by employing thousands of processing elements working in parallel. Few institutions can afford these state-of-the-art parallel processors, but many already have the makings of a modest parallel processing system. Workstations on existing high-speed networks can be harnessed as nodes in a parallel processing environment, bringing the benefits of parallel processing to many. While such a system can not rival the industry's latest machines, many common tasks can be accelerated greatly by spreading the processing burden and exploiting idle network resources. We study several aspects of this approach, from algorithms to select nodes to speed gains in specific tasks. With ever-increasing volumes of astronomical data, it becomes all the more necessary to utilize our computing resources fully.

Six Years of Parallel Computing at NAS (1987 - 1993): What Have we Learned?

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Cooper, D. M. (Technical Monitor)

1994-01-01

In the fall of 1987 the age of parallelism at NAS began with the installation of a 32K processor CM-2 from Thinking Machines. In 1987 this was described as an "experiment" in parallel processing. In the six years since, NAS acquired a series of parallel machines, and conducted an active research and development effort focused on the use of highly parallel machines for applications in the computational aerosciences. In this time period parallel processing for scientific applications evolved from a fringe research topic into the one of main activities at NAS. In this presentation I will review the history of parallel computing at NAS in the context of the major progress, which has been made in the field in general. I will attempt to summarize the lessons we have learned so far, and the contributions NAS has made to the state of the art. Based on these insights I will comment on the current state of parallel computing (including the HPCC effort) and try to predict some trends for the next six years.

Endpoint-based parallel data processing with non-blocking collective instructions in a parallel active messaging interface of a parallel computer

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

Archer, Charles J; Blocksome, Michael A; Cernohous, Bob R

Methods, apparatuses, and computer program products for endpoint-based parallel data processing with non-blocking collective instructions in a parallel active messaging interface (`PAMI`) of a parallel computer are provided. Embodiments include establishing by a parallel application a data communications geometry, the geometry specifying a set of endpoints that are used in collective operations of the PAMI, including associating with the geometry a list of collective algorithms valid for use with the endpoints of the geometry. Embodiments also include registering in each endpoint in the geometry a dispatch callback function for a collective operation and executing without blocking, through a single onemore » of the endpoints in the geometry, an instruction for the collective operation.« less

A parallel variable metric optimization algorithm

NASA Technical Reports Server (NTRS)

Straeter, T. A.

1973-01-01

An algorithm, designed to exploit the parallel computing or vector streaming (pipeline) capabilities of computers is presented. When p is the degree of parallelism, then one cycle of the parallel variable metric algorithm is defined as follows: first, the function and its gradient are computed in parallel at p different values of the independent variable; then the metric is modified by p rank-one corrections; and finally, a single univariant minimization is carried out in the Newton-like direction. Several properties of this algorithm are established. The convergence of the iterates to the solution is proved for a quadratic functional on a real separable Hilbert space. For a finite-dimensional space the convergence is in one cycle when p equals the dimension of the space. Results of numerical experiments indicate that the new algorithm will exploit parallel or pipeline computing capabilities to effect faster convergence than serial techniques.

Endpoint-based parallel data processing with non-blocking collective instructions in a parallel active messaging interface of a parallel computer

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

Archer, Charles J; Blocksome, Michael A; Cernohous, Bob R

Endpoint-based parallel data processing with non-blocking collective instructions in a PAMI of a parallel computer is disclosed. The PAMI is composed of data communications endpoints, each including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task. The compute nodes are coupled for data communications through the PAMI. The parallel application establishes a data communications geometry specifying a set of endpoints that are used in collective operations of the PAMI by associating with the geometry a list of collective algorithms valid for use with themore » endpoints of the geometry; registering in each endpoint in the geometry a dispatch callback function for a collective operation; and executing without blocking, through a single one of the endpoints in the geometry, an instruction for the collective operation.« less

Template based parallel checkpointing in a massively parallel computer system

DOEpatents

Archer, Charles Jens [Rochester, MN; Inglett, Todd Alan [Rochester, MN

2009-01-13

A method and apparatus for a template based parallel checkpoint save for a massively parallel super computer system using a parallel variation of the rsync protocol, and network broadcast. In preferred embodiments, the checkpoint data for each node is compared to a template checkpoint file that resides in the storage and that was previously produced. Embodiments herein greatly decrease the amount of data that must be transmitted and stored for faster checkpointing and increased efficiency of the computer system. Embodiments are directed to a parallel computer system with nodes arranged in a cluster with a high speed interconnect that can perform broadcast communication. The checkpoint contains a set of actual small data blocks with their corresponding checksums from all nodes in the system. The data blocks may be compressed using conventional non-lossy data compression algorithms to further reduce the overall checkpoint size.

Four-Dimensional Positron Emission Tomography: Implications for Dose Painting of High-Uptake Regions

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

Aristophanous, Michalis, E-mail: maristophanous@lroc.harvard.edu; Yap, Jeffrey T.; Killoran, Joseph H.

Purpose: To investigate the behavior of tumor subvolumes of high [18F]-fluorodeoxyglucose (FDG) uptake as seen on clinical four-dimensional (4D) FDG-positron emission tomography (PET) scans. Methods and Materials: Four-dimensional FDG-PET/computed tomography scans from 13 patients taken before radiotherapy were available. The analysis was focused on regions of high uptake that are potential dose-painting targets. A total of 17 lesions (primary tumors and lymph nodes) were analyzed. On each one of the five phases of the 4D scan a classification algorithm was applied to obtain the region of highest uptake and segment the tumor volume. We looked at the behavior of bothmore » the high-uptake subvolume, called 'Boost,' and the segmented tumor volume, called 'Target.' We measured several quantities that characterize the Target and Boost volumes and quantified correlations between them. Results: The behavior of the Target could not always predict the behavior of the Boost. The shape deformation of the Boost regions was on average 133% higher than that of the Target. The gross to internal target volume expansion was on average 27.4% for the Target and 64% for the Boost, a statistically significant difference (p < 0.05). Finally, the inhale-to-exhale phase (20%) had the highest shape deformation for the Boost regions. Conclusions: A complex relationship between the measured quantities for the Boost and Target volumes is revealed. The results suggest that in cases in which advanced therapy techniques such as dose painting are being used, a close examination of the 4D PET scan should be performed.« less

Computational strategies for three-dimensional flow simulations on distributed computer systems. Ph.D. Thesis Semiannual Status Report, 15 Aug. 1993 - 15 Feb. 1994

NASA Technical Reports Server (NTRS)

Weed, Richard Allen; Sankar, L. N.

1994-01-01

An increasing amount of research activity in computational fluid dynamics has been devoted to the development of efficient algorithms for parallel computing systems. The increasing performance to price ratio of engineering workstations has led to research to development procedures for implementing a parallel computing system composed of distributed workstations. This thesis proposal outlines an ongoing research program to develop efficient strategies for performing three-dimensional flow analysis on distributed computing systems. The PVM parallel programming interface was used to modify an existing three-dimensional flow solver, the TEAM code developed by Lockheed for the Air Force, to function as a parallel flow solver on clusters of workstations. Steady flow solutions were generated for three different wing and body geometries to validate the code and evaluate code performance. The proposed research will extend the parallel code development to determine the most efficient strategies for unsteady flow simulations.

Concurrent extensions to the FORTRAN language for parallel programming of computational fluid dynamics algorithms

NASA Technical Reports Server (NTRS)

Weeks, Cindy Lou

1986-01-01

Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.

Parallelization of interpolation, solar radiation and water flow simulation modules in GRASS GIS using OpenMP

NASA Astrophysics Data System (ADS)

Hofierka, Jaroslav; Lacko, Michal; Zubal, Stanislav

2017-10-01

In this paper, we describe the parallelization of three complex and computationally intensive modules of GRASS GIS using the OpenMP application programming interface for multi-core computers. These include the v.surf.rst module for spatial interpolation, the r.sun module for solar radiation modeling and the r.sim.water module for water flow simulation. We briefly describe the functionality of the modules and parallelization approaches used in the modules. Our approach includes the analysis of the module's functionality, identification of source code segments suitable for parallelization and proper application of OpenMP parallelization code to create efficient threads processing the subtasks. We document the efficiency of the solutions using the airborne laser scanning data representing land surface in the test area and derived high-resolution digital terrain model grids. We discuss the performance speed-up and parallelization efficiency depending on the number of processor threads. The study showed a substantial increase in computation speeds on a standard multi-core computer while maintaining the accuracy of results in comparison to the output from original modules. The presented parallelization approach showed the simplicity and efficiency of the parallelization of open-source GRASS GIS modules using OpenMP, leading to an increased performance of this geospatial software on standard multi-core computers.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

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

Jin, Shuangshuang; Chen, Yousu; Wu, Di

2015-12-09

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Messagemore » Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.« less

A hybrid parallel architecture for electrostatic interactions in the simulation of dissipative particle dynamics

NASA Astrophysics Data System (ADS)

Yang, Sheng-Chun; Lu, Zhong-Yuan; Qian, Hu-Jun; Wang, Yong-Lei; Han, Jie-Ping

2017-11-01

In this work, we upgraded the electrostatic interaction method of CU-ENUF (Yang, et al., 2016) which first applied CUNFFT (nonequispaced Fourier transforms based on CUDA) to the reciprocal-space electrostatic computation and made the computation of electrostatic interaction done thoroughly in GPU. The upgraded edition of CU-ENUF runs concurrently in a hybrid parallel way that enables the computation parallelizing on multiple computer nodes firstly, then further on the installed GPU in each computer. By this parallel strategy, the size of simulation system will be never restricted to the throughput of a single CPU or GPU. The most critical technical problem is how to parallelize a CUNFFT in the parallel strategy, which is conquered effectively by deep-seated research of basic principles and some algorithm skills. Furthermore, the upgraded method is capable of computing electrostatic interactions for both the atomistic molecular dynamics (MD) and the dissipative particle dynamics (DPD). Finally, the benchmarks conducted for validation and performance indicate that the upgraded method is able to not only present a good precision when setting suitable parameters, but also give an efficient way to compute electrostatic interactions for huge simulation systems. Program Files doi:http://dx.doi.org/10.17632/zncf24fhpv.1 Licensing provisions: GNU General Public License 3 (GPL) Programming language: C, C++, and CUDA C Supplementary material: The program is designed for effective electrostatic interactions of large-scale simulation systems, which runs on particular computers equipped with NVIDIA GPUs. It has been tested on (a) single computer node with Intel(R) Core(TM) i7-3770@ 3.40 GHz (CPU) and GTX 980 Ti (GPU), and (b) MPI parallel computer nodes with the same configurations. Nature of problem: For molecular dynamics simulation, the electrostatic interaction is the most time-consuming computation because of its long-range feature and slow convergence in simulation space, which approximately take up most of the total simulation time. Although the parallel method CU-ENUF (Yang et al., 2016) based on GPU has achieved a qualitative leap compared with previous methods in electrostatic interactions computation, the computation capability is limited to the throughput capacity of a single GPU for super-scale simulation system. Therefore, we should look for an effective method to handle the calculation of electrostatic interactions efficiently for a simulation system with super-scale size. Solution method: We constructed a hybrid parallel architecture, in which CPU and GPU are combined to accelerate the electrostatic computation effectively. Firstly, the simulation system is divided into many subtasks via domain-decomposition method. Then MPI (Message Passing Interface) is used to implement the CPU-parallel computation with each computer node corresponding to a particular subtask, and furthermore each subtask in one computer node will be executed in GPU in parallel efficiently. In this hybrid parallel method, the most critical technical problem is how to parallelize a CUNFFT (nonequispaced fast Fourier transform based on CUDA) in the parallel strategy, which is conquered effectively by deep-seated research of basic principles and some algorithm skills. Restrictions: The HP-ENUF is mainly oriented to super-scale system simulations, in which the performance superiority is shown adequately. However, for a small simulation system containing less than 106 particles, the mode of multiple computer nodes has no apparent efficiency advantage or even lower efficiency due to the serious network delay among computer nodes, than the mode of single computer node. References: (1) S.-C. Yang, H.-J. Qian, Z.-Y. Lu, Appl. Comput. Harmon. Anal. 2016, http://dx.doi.org/10.1016/j.acha.2016.04.009. (2) S.-C. Yang, Y.-L. Wang, G.-S. Jiao, H.-J. Qian, Z.-Y. Lu, J. Comput. Chem. 37 (2016) 378. (3) S.-C. Yang, Y.-L. Zhu, H.-J. Qian, Z.-Y. Lu, Appl. Chem. Res. Chin. Univ., 2017, http://dx.doi.org/10.1007/s40242-016-6354-5. (4) Y.-L. Zhu, H. Liu, Z.-W. Li, H.-J. Qian, G. Milano, Z.-Y. Lu, J. Comput. Chem. 34 (2013) 2197.

Holographic screening length in a hot plasma of two sphere

NASA Astrophysics Data System (ADS)

Atmaja, A. Nata; Kassim, H. Abu; Yusof, N.

2015-11-01

We study the screening length L_{max} of a moving quark-antiquark pair in a hot plasma, which lives in a two sphere, S^2, using the AdS/CFT correspondence in which the corresponding background metric is the four-dimensional Schwarzschild-AdS black hole. The geodesic of both ends of the string at the boundary, interpreted as the quark-antiquark pair, is given by a stationary motion in the equatorial plane by which the separation length L of both ends of the string is parallel to the angular velocity ω . The screening length and total energy H of the quark-antiquark pair are computed numerically and show that the plots are bounded from below by some functions related to the momentum transfer P_c of the drag force configuration. We compare the result by computing the screening length in the reference frame of the moving quark-antiquark pair, in which the background metrics are "Boost-AdS" and Kerr-AdS black holes. Comparing both black holes, we argue that the mass parameters M_{Sch} of the Schwarzschild-AdS black hole and M_{Kerr} of the Kerr-AdS black hole are related at high temperature by M_{Kerr}=M_{Sch}(1-a^2l^2)^{3/2}, where a is the angular momentum parameter and l is the AdS curvature.

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

PubMed Central

Páll, Szilárd; Fechner, Martin; Esztermann, Ansgar; de Groot, Bert L.; Grubmüller, Helmut

2015-01-01

The molecular dynamics simulation package GROMACS runs efficiently on a wide variety of hardware from commodity workstations to high performance computing clusters. Hardware features are well‐exploited with a combination of single instruction multiple data, multithreading, and message passing interface (MPI)‐based single program multiple data/multiple program multiple data parallelism while graphics processing units (GPUs) can be used as accelerators to compute interactions off‐loaded from the CPU. Here, we evaluate which hardware produces trajectories with GROMACS 4.6 or 5.0 in the most economical way. We have assembled and benchmarked compute nodes with various CPU/GPU combinations to identify optimal compositions in terms of raw trajectory production rate, performance‐to‐price ratio, energy efficiency, and several other criteria. Although hardware prices are naturally subject to trends and fluctuations, general tendencies are clearly visible. Adding any type of GPU significantly boosts a node's simulation performance. For inexpensive consumer‐class GPUs this improvement equally reflects in the performance‐to‐price ratio. Although memory issues in consumer‐class GPUs could pass unnoticed as these cards do not support error checking and correction memory, unreliable GPUs can be sorted out with memory checking tools. Apart from the obvious determinants for cost‐efficiency like hardware expenses and raw performance, the energy consumption of a node is a major cost factor. Over the typical hardware lifetime until replacement of a few years, the costs for electrical power and cooling can become larger than the costs of the hardware itself. Taking that into account, nodes with a well‐balanced ratio of CPU and consumer‐class GPU resources produce the maximum amount of GROMACS trajectory over their lifetime. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:26238484

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations.

PubMed

Kutzner, Carsten; Páll, Szilárd; Fechner, Martin; Esztermann, Ansgar; de Groot, Bert L; Grubmüller, Helmut

2015-10-05

The molecular dynamics simulation package GROMACS runs efficiently on a wide variety of hardware from commodity workstations to high performance computing clusters. Hardware features are well-exploited with a combination of single instruction multiple data, multithreading, and message passing interface (MPI)-based single program multiple data/multiple program multiple data parallelism while graphics processing units (GPUs) can be used as accelerators to compute interactions off-loaded from the CPU. Here, we evaluate which hardware produces trajectories with GROMACS 4.6 or 5.0 in the most economical way. We have assembled and benchmarked compute nodes with various CPU/GPU combinations to identify optimal compositions in terms of raw trajectory production rate, performance-to-price ratio, energy efficiency, and several other criteria. Although hardware prices are naturally subject to trends and fluctuations, general tendencies are clearly visible. Adding any type of GPU significantly boosts a node's simulation performance. For inexpensive consumer-class GPUs this improvement equally reflects in the performance-to-price ratio. Although memory issues in consumer-class GPUs could pass unnoticed as these cards do not support error checking and correction memory, unreliable GPUs can be sorted out with memory checking tools. Apart from the obvious determinants for cost-efficiency like hardware expenses and raw performance, the energy consumption of a node is a major cost factor. Over the typical hardware lifetime until replacement of a few years, the costs for electrical power and cooling can become larger than the costs of the hardware itself. Taking that into account, nodes with a well-balanced ratio of CPU and consumer-class GPU resources produce the maximum amount of GROMACS trajectory over their lifetime. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Cooperative storage of shared files in a parallel computing system with dynamic block size

DOEpatents

Bent, John M.; Faibish, Sorin; Grider, Gary

2015-11-10

Improved techniques are provided for parallel writing of data to a shared object in a parallel computing system. A method is provided for storing data generated by a plurality of parallel processes to a shared object in a parallel computing system. The method is performed by at least one of the processes and comprises: dynamically determining a block size for storing the data; exchanging a determined amount of the data with at least one additional process to achieve a block of the data having the dynamically determined block size; and writing the block of the data having the dynamically determined block size to a file system. The determined block size comprises, e.g., a total amount of the data to be stored divided by the number of parallel processes. The file system comprises, for example, a log structured virtual parallel file system, such as a Parallel Log-Structured File System (PLFS).

Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

NASA Technical Reports Server (NTRS)

Sun, Xian-He

1997-01-01

Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm and Reduced Parallel Diagonal Dominant (RPDD) algorithm have been carefully studied on different parallel platforms for different applications, and a NASA simulation code developed by Man M. Rai and his colleagues has been parallelized and implemented based on data dependency analysis. These achievements are addressed in detail in the paper.

Reducing power consumption while synchronizing a plurality of compute nodes during execution of a parallel application

DOEpatents

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Peters, Amanda A [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian E [Rochester, MN

2012-01-10

Methods, apparatus, and products are disclosed for reducing power consumption while synchronizing a plurality of compute nodes during execution of a parallel application that include: beginning, by each compute node, performance of a blocking operation specified by the parallel application, each compute node beginning the blocking operation asynchronously with respect to the other compute nodes; reducing, for each compute node, power to one or more hardware components of that compute node in response to that compute node beginning the performance of the blocking operation; and restoring, for each compute node, the power to the hardware components having power reduced in response to all of the compute nodes beginning the performance of the blocking operation.

Reducing power consumption while synchronizing a plurality of compute nodes during execution of a parallel application

DOEpatents

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Peters, Amanda E [Cambridge, MA; Ratterman, Joseph D [Rochester, MN; Smith, Brian E [Rochester, MN

2012-04-17

Methods, apparatus, and products are disclosed for reducing power consumption while synchronizing a plurality of compute nodes during execution of a parallel application that include: beginning, by each compute node, performance of a blocking operation specified by the parallel application, each compute node beginning the blocking operation asynchronously with respect to the other compute nodes; reducing, for each compute node, power to one or more hardware components of that compute node in response to that compute node beginning the performance of the blocking operation; and restoring, for each compute node, the power to the hardware components having power reduced in response to all of the compute nodes beginning the performance of the blocking operation.

MPI implementation of PHOENICS: A general purpose computational fluid dynamics code

NASA Astrophysics Data System (ADS)

Simunovic, S.; Zacharia, T.; Baltas, N.; Spalding, D. B.

1995-03-01

PHOENICS is a suite of computational analysis programs that are used for simulation of fluid flow, heat transfer, and dynamical reaction processes. The parallel version of the solver EARTH for the Computational Fluid Dynamics (CFD) program PHOENICS has been implemented using Message Passing Interface (MPI) standard. Implementation of MPI version of PHOENICS makes this computational tool portable to a wide range of parallel machines and enables the use of high performance computing for large scale computational simulations. MPI libraries are available on several parallel architectures making the program usable across different architectures as well as on heterogeneous computer networks. The Intel Paragon NX and MPI versions of the program have been developed and tested on massively parallel supercomputers Intel Paragon XP/S 5, XP/S 35, and Kendall Square Research, and on the multiprocessor SGI Onyx computer at Oak Ridge National Laboratory. The preliminary testing results of the developed program have shown scalable performance for reasonably sized computational domains.

MPI implementation of PHOENICS: A general purpose computational fluid dynamics code

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

Simunovic, S.; Zacharia, T.; Baltas, N.

1995-04-01

PHOENICS is a suite of computational analysis programs that are used for simulation of fluid flow, heat transfer, and dynamical reaction processes. The parallel version of the solver EARTH for the Computational Fluid Dynamics (CFD) program PHOENICS has been implemented using Message Passing Interface (MPI) standard. Implementation of MPI version of PHOENICS makes this computational tool portable to a wide range of parallel machines and enables the use of high performance computing for large scale computational simulations. MPI libraries are available on several parallel architectures making the program usable across different architectures as well as on heterogeneous computer networks. Themore » Intel Paragon NX and MPI versions of the program have been developed and tested on massively parallel supercomputers Intel Paragon XP/S 5, XP/S 35, and Kendall Square Research, and on the multiprocessor SGI Onyx computer at Oak Ridge National Laboratory. The preliminary testing results of the developed program have shown scalable performance for reasonably sized computational domains.« less

The gradient boosting algorithm and random boosting for genome-assisted evaluation in large data sets.

PubMed

González-Recio, O; Jiménez-Montero, J A; Alenda, R

2013-01-01

In the next few years, with the advent of high-density single nucleotide polymorphism (SNP) arrays and genome sequencing, genomic evaluation methods will need to deal with a large number of genetic variants and an increasing sample size. The boosting algorithm is a machine-learning technique that may alleviate the drawbacks of dealing with such large data sets. This algorithm combines different predictors in a sequential manner with some shrinkage on them; each predictor is applied consecutively to the residuals from the committee formed by the previous ones to form a final prediction based on a subset of covariates. Here, a detailed description is provided and examples using a toy data set are included. A modification of the algorithm called "random boosting" was proposed to increase predictive ability and decrease computation time of genome-assisted evaluation in large data sets. Random boosting uses a random selection of markers to add a subsequent weak learner to the predictive model. These modifications were applied to a real data set composed of 1,797 bulls genotyped for 39,714 SNP. Deregressed proofs of 4 yield traits and 1 type trait from January 2009 routine evaluations were used as dependent variables. A 2-fold cross-validation scenario was implemented. Sires born before 2005 were used as a training sample (1,576 and 1,562 for production and type traits, respectively), whereas younger sires were used as a testing sample to evaluate predictive ability of the algorithm on yet-to-be-observed phenotypes. Comparison with the original algorithm was provided. The predictive ability of the algorithm was measured as Pearson correlations between observed and predicted responses. Further, estimated bias was computed as the average difference between observed and predicted phenotypes. The results showed that the modification of the original boosting algorithm could be run in 1% of the time used with the original algorithm and with negligible differences in accuracy and bias. This modification may be used to speed the calculus of genome-assisted evaluation in large data sets such us those obtained from consortiums. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

Research in Parallel Algorithms and Software for Computational Aerosciences

NASA Technical Reports Server (NTRS)

Domel, Neal D.

1996-01-01

Phase I is complete for the development of a Computational Fluid Dynamics parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Research in Parallel Algorithms and Software for Computational Aerosciences

NASA Technical Reports Server (NTRS)

Domel, Neal D.

1996-01-01

Phase 1 is complete for the development of a computational fluid dynamics CFD) parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Performance analysis of three dimensional integral equation computations on a massively parallel computer. M.S. Thesis

NASA Technical Reports Server (NTRS)

Logan, Terry G.

1994-01-01

The purpose of this study is to investigate the performance of the integral equation computations using numerical source field-panel method in a massively parallel processing (MPP) environment. A comparative study of computational performance of the MPP CM-5 computer and conventional Cray-YMP supercomputer for a three-dimensional flow problem is made. A serial FORTRAN code is converted into a parallel CM-FORTRAN code. Some performance results are obtained on CM-5 with 32, 62, 128 nodes along with those on Cray-YMP with a single processor. The comparison of the performance indicates that the parallel CM-FORTRAN code near or out-performs the equivalent serial FORTRAN code for some cases.

Parallel aeroelastic computations for wing and wing-body configurations

NASA Technical Reports Server (NTRS)

Byun, Chansup

1994-01-01

The objective of this research is to develop computationally efficient methods for solving fluid-structural interaction problems by directly coupling finite difference Euler/Navier-Stokes equations for fluids and finite element dynamics equations for structures on parallel computers. This capability will significantly impact many aerospace projects of national importance such as Advanced Subsonic Civil Transport (ASCT), where the structural stability margin becomes very critical at the transonic region. This research effort will have direct impact on the High Performance Computing and Communication (HPCC) Program of NASA in the area of parallel computing.

Implementation of a 3D mixing layer code on parallel computers

NASA Technical Reports Server (NTRS)

Roe, K.; Thakur, R.; Dang, T.; Bogucz, E.

1995-01-01

This paper summarizes our progress and experience in the development of a Computational-Fluid-Dynamics code on parallel computers to simulate three-dimensional spatially-developing mixing layers. In this initial study, the three-dimensional time-dependent Euler equations are solved using a finite-volume explicit time-marching algorithm. The code was first programmed in Fortran 77 for sequential computers. The code was then converted for use on parallel computers using the conventional message-passing technique, while we have not been able to compile the code with the present version of HPF compilers.

NASA Workshop on Computational Structural Mechanics 1987, part 1

NASA Technical Reports Server (NTRS)

Sykes, Nancy P. (Editor)

1989-01-01

Topics in Computational Structural Mechanics (CSM) are reviewed. CSM parallel structural methods, a transputer finite element solver, architectures for multiprocessor computers, and parallel eigenvalue extraction are among the topics discussed.

Parallel computation with molecular-motor-propelled agents in nanofabricated networks.

PubMed

Nicolau, Dan V; Lard, Mercy; Korten, Till; van Delft, Falco C M J M; Persson, Malin; Bengtsson, Elina; Månsson, Alf; Diez, Stefan; Linke, Heiner; Nicolau, Dan V

2016-03-08

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.

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.

A highly efficient multi-core algorithm for clustering extremely large datasets

PubMed Central

2010-01-01

Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922

Support for Debugging Automatically Parallelized Programs

NASA Technical Reports Server (NTRS)

Hood, Robert; Jost, Gabriele; Biegel, Bryan (Technical Monitor)

2001-01-01

This viewgraph presentation provides information on the technical aspects of debugging computer code that has been automatically converted for use in a parallel computing system. Shared memory parallelization and distributed memory parallelization entail separate and distinct challenges for a debugging program. A prototype system has been developed which integrates various tools for the debugging of automatically parallelized programs including the CAPTools Database which provides variable definition information across subroutines as well as array distribution information.

Parallel language constructs for tensor product computations on loosely coupled architectures

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Van Rosendale, John

1989-01-01

A set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level is described. The authors focus on tensor product array computations, a simple but important class of numerical algorithms. They consider first the problem of programming one-dimensional kernel routines, such as parallel tridiagonal solvers, and then look at how such parallel kernels can be combined to form parallel tensor product algorithms.

Development of a Distributed Parallel Computing Framework to Facilitate Regional/Global Gridded Crop Modeling with Various Scenarios

NASA Astrophysics Data System (ADS)

Jang, W.; Engda, T. A.; Neff, J. C.; Herrick, J.

2017-12-01

Many crop models are increasingly used to evaluate crop yields at regional and global scales. However, implementation of these models across large areas using fine-scale grids is limited by computational time requirements. In order to facilitate global gridded crop modeling with various scenarios (i.e., different crop, management schedule, fertilizer, and irrigation) using the Environmental Policy Integrated Climate (EPIC) model, we developed a distributed parallel computing framework in Python. Our local desktop with 14 cores (28 threads) was used to test the distributed parallel computing framework in Iringa, Tanzania which has 406,839 grid cells. High-resolution soil data, SoilGrids (250 x 250 m), and climate data, AgMERRA (0.25 x 0.25 deg) were also used as input data for the gridded EPIC model. The framework includes a master file for parallel computing, input database, input data formatters, EPIC model execution, and output analyzers. Through the master file for parallel computing, the user-defined number of threads of CPU divides the EPIC simulation into jobs. Then, Using EPIC input data formatters, the raw database is formatted for EPIC input data and the formatted data moves into EPIC simulation jobs. Then, 28 EPIC jobs run simultaneously and only interesting results files are parsed and moved into output analyzers. We applied various scenarios with seven different slopes and twenty-four fertilizer ranges. Parallelized input generators create different scenarios as a list for distributed parallel computing. After all simulations are completed, parallelized output analyzers are used to analyze all outputs according to the different scenarios. This saves significant computing time and resources, making it possible to conduct gridded modeling at regional to global scales with high-resolution data. For example, serial processing for the Iringa test case would require 113 hours, while using the framework developed in this study requires only approximately 6 hours, a nearly 95% reduction in computing time.

Continuous development of schemes for parallel computing of the electrostatics in biological systems: implementation in DelPhi.

PubMed

Li, Chuan; Petukh, Marharyta; Li, Lin; Alexov, Emil

2013-08-15

Due to the enormous importance of electrostatics in molecular biology, calculating the electrostatic potential and corresponding energies has become a standard computational approach for the study of biomolecules and nano-objects immersed in water and salt phase or other media. However, the electrostatics of large macromolecules and macromolecular complexes, including nano-objects, may not be obtainable via explicit methods and even the standard continuum electrostatics methods may not be applicable due to high computational time and memory requirements. Here, we report further development of the parallelization scheme reported in our previous work (Li, et al., J. Comput. Chem. 2012, 33, 1960) to include parallelization of the molecular surface and energy calculations components of the algorithm. The parallelization scheme utilizes different approaches such as space domain parallelization, algorithmic parallelization, multithreading, and task scheduling, depending on the quantity being calculated. This allows for efficient use of the computing resources of the corresponding computer cluster. The parallelization scheme is implemented in the popular software DelPhi and results in speedup of several folds. As a demonstration of the efficiency and capability of this methodology, the electrostatic potential, and electric field distributions are calculated for the bovine mitochondrial supercomplex illustrating their complex topology, which cannot be obtained by modeling the supercomplex components alone. Copyright © 2013 Wiley Periodicals, Inc.

Boost-phase discrimination research

NASA Technical Reports Server (NTRS)

Langhoff, Stephen R.; Feiereisen, William J.

1993-01-01

The final report describes the combined work of the Computational Chemistry and Aerothermodynamics branches within the Thermosciences Division at NASA Ames Research Center directed at understanding the signatures of shock-heated air. Considerable progress was made in determining accurate transition probabilities for the important band systems of NO that account for much of the emission in the ultraviolet region. Research carried out under this project showed that in order to reproduce the observed radiation from the bow shock region of missiles in their boost phase it is necessary to include the Burnett terms in the constituent equation, account for the non-Boltzmann energy distribution, correctly model the NO formation and rotational excitation process, and use accurate transition probabilities for the NO band systems. This work resulted in significant improvements in the computer code NEQAIR that models both the radiation and fluid dynamics in the shock region.

Redundant binary number representation for an inherently parallel arithmetic on optical computers.

PubMed

De Biase, G A; Massini, A

1993-02-10

A simple redundant binary number representation suitable for digital-optical computers is presented. By means of this representation it is possible to build an arithmetic with carry-free parallel algebraic sums carried out in constant time and parallel multiplication in log N time. This redundant number representation naturally fits the 2's complement binary number system and permits the construction of inherently parallel arithmetic units that are used in various optical technologies. Some properties of this number representation and several examples of computation are presented.

Backtracking and Re-execution in the Automatic Debugging of Parallelized Programs

NASA Technical Reports Server (NTRS)

Matthews, Gregory; Hood, Robert; Johnson, Stephen; Leggett, Peter; Biegel, Bryan (Technical Monitor)

2002-01-01

In this work we describe a new approach using relative debugging to find differences in computation between a serial program and a parallel version of th it program. We use a combination of re-execution and backtracking in order to find the first difference in computation that may ultimately lead to an incorrect value that the user has indicated. In our prototype implementation we use static analysis information from a parallelization tool in order to perform the backtracking as well as the mapping required between serial and parallel computations.

Traffic Simulations on Parallel Computers Using Domain Decomposition Techniques

DOT National Transportation Integrated Search

1995-01-01

Large scale simulations of Intelligent Transportation Systems (ITS) can only be acheived by using the computing resources offered by parallel computing architectures. Domain decomposition techniques are proposed which allow the performance of traffic...

A Multi-Level Parallelization Concept for High-Fidelity Multi-Block Solvers

NASA Technical Reports Server (NTRS)

Hatay, Ferhat F.; Jespersen, Dennis C.; Guruswamy, Guru P.; Rizk, Yehia M.; Byun, Chansup; Gee, Ken; VanDalsem, William R. (Technical Monitor)

1997-01-01

The integration of high-fidelity Computational Fluid Dynamics (CFD) analysis tools with the industrial design process benefits greatly from the robust implementations that are transportable across a wide range of computer architectures. In the present work, a hybrid domain-decomposition and parallelization concept was developed and implemented into the widely-used NASA multi-block Computational Fluid Dynamics (CFD) packages implemented in ENSAERO and OVERFLOW. The new parallel solver concept, PENS (Parallel Euler Navier-Stokes Solver), employs both fine and coarse granularity in data partitioning as well as data coalescing to obtain the desired load-balance characteristics on the available computer platforms. This multi-level parallelism implementation itself introduces no changes to the numerical results, hence the original fidelity of the packages are identically preserved. The present implementation uses the Message Passing Interface (MPI) library for interprocessor message passing and memory accessing. By choosing an appropriate combination of the available partitioning and coalescing capabilities only during the execution stage, the PENS solver becomes adaptable to different computer architectures from shared-memory to distributed-memory platforms with varying degrees of parallelism. The PENS implementation on the IBM SP2 distributed memory environment at the NASA Ames Research Center obtains 85 percent scalable parallel performance using fine-grain partitioning of single-block CFD domains using up to 128 wide computational nodes. Multi-block CFD simulations of complete aircraft simulations achieve 75 percent perfect load-balanced executions using data coalescing and the two levels of parallelism. SGI PowerChallenge, SGI Origin 2000, and a cluster of workstations are the other platforms where the robustness of the implementation is tested. The performance behavior on the other computer platforms with a variety of realistic problems will be included as this on-going study progresses.

Parallel computing on Unix workstation arrays

NASA Astrophysics Data System (ADS)

Reale, F.; Bocchino, F.; Sciortino, S.

1994-12-01

We have tested arrays of general-purpose Unix workstations used as MIMD systems for massive parallel computations. In particular we have solved numerically a demanding test problem with a 2D hydrodynamic code, generally developed to study astrophysical flows, by exucuting it on arrays either of DECstations 5000/200 on Ethernet LAN, or of DECstations 3000/400, equipped with powerful Alpha processors, on FDDI LAN. The code is appropriate for data-domain decomposition, and we have used a library for parallelization previously developed in our Institute, and easily extended to work on Unix workstation arrays by using the PVM software toolset. We have compared the parallel efficiencies obtained on arrays of several processors to those obtained on a dedicated MIMD parallel system, namely a Meiko Computing Surface (CS-1), equipped with Intel i860 processors. We discuss the feasibility of using non-dedicated parallel systems and conclude that the convenience depends essentially on the size of the computational domain as compared to the relative processor power and network bandwidth. We point out that for future perspectives a parallel development of processor and network technology is important, and that the software still offers great opportunities of improvement, especially in terms of latency times in the message-passing protocols. In conditions of significant gain in terms of speedup, such workstation arrays represent a cost-effective approach to massive parallel computations.

Parallelization strategies for continuum-generalized method of moments on the multi-thread systems

NASA Astrophysics Data System (ADS)

Bustamam, A.; Handhika, T.; Ernastuti, Kerami, D.

2017-07-01

Continuum-Generalized Method of Moments (C-GMM) covers the Generalized Method of Moments (GMM) shortfall which is not as efficient as Maximum Likelihood estimator by using the continuum set of moment conditions in a GMM framework. However, this computation would take a very long time since optimizing regularization parameter. Unfortunately, these calculations are processed sequentially whereas in fact all modern computers are now supported by hierarchical memory systems and hyperthreading technology, which allowing for parallel computing. This paper aims to speed up the calculation process of C-GMM by designing a parallel algorithm for C-GMM on the multi-thread systems. First, parallel regions are detected for the original C-GMM algorithm. There are two parallel regions in the original C-GMM algorithm, that are contributed significantly to the reduction of computational time: the outer-loop and the inner-loop. Furthermore, this parallel algorithm will be implemented with standard shared-memory application programming interface, i.e. Open Multi-Processing (OpenMP). The experiment shows that the outer-loop parallelization is the best strategy for any number of observations.

Multirate-based fast parallel algorithms for 2-D DHT-based real-valued discrete Gabor transform.

PubMed

Tao, Liang; Kwan, Hon Keung

2012-07-01

Novel algorithms for the multirate and fast parallel implementation of the 2-D discrete Hartley transform (DHT)-based real-valued discrete Gabor transform (RDGT) and its inverse transform are presented in this paper. A 2-D multirate-based analysis convolver bank is designed for the 2-D RDGT, and a 2-D multirate-based synthesis convolver bank is designed for the 2-D inverse RDGT. The parallel channels in each of the two convolver banks have a unified structure and can apply the 2-D fast DHT algorithm to speed up their computations. The computational complexity of each parallel channel is low and is independent of the Gabor oversampling rate. All the 2-D RDGT coefficients of an image are computed in parallel during the analysis process and can be reconstructed in parallel during the synthesis process. The computational complexity and time of the proposed parallel algorithms are analyzed and compared with those of the existing fastest algorithms for 2-D discrete Gabor transforms. The results indicate that the proposed algorithms are the fastest, which make them attractive for real-time image processing.

Parallel Computational Fluid Dynamics: Current Status and Future Requirements

NASA Technical Reports Server (NTRS)

Simon, Horst D.; VanDalsem, William R.; Dagum, Leonardo; Kutler, Paul (Technical Monitor)

1994-01-01

One or the key objectives of the Applied Research Branch in the Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Allies Research Center is the accelerated introduction of highly parallel machines into a full operational environment. In this report we discuss the performance results obtained from the implementation of some computational fluid dynamics (CFD) applications on the Connection Machine CM-2 and the Intel iPSC/860. We summarize some of the experiences made so far with the parallel testbed machines at the NAS Applied Research Branch. Then we discuss the long term computational requirements for accomplishing some of the grand challenge problems in computational aerosciences. We argue that only massively parallel machines will be able to meet these grand challenge requirements, and we outline the computer science and algorithm research challenges ahead.

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

NASA Astrophysics Data System (ADS)

Yu, Leiming; Nina-Paravecino, Fanny; Kaeli, David; Fang, Qianqian

2018-01-01

We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs.

A parallel-processing approach to computing for the geographic sciences; applications and systems enhancements

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Liu, Shu-Guang; Nichols, Erin; Haga, Jim; Maddox, Brian; Bilderback, Chris; Feller, Mark; Homer, George

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost, personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting information science research into parallel computing systems and applications.

Going beyond a First Reader: A Machine Learning Methodology for Optimizing Cost and Performance in Breast Ultrasound Diagnosis.

PubMed

Venkatesh, Santosh S; Levenback, Benjamin J; Sultan, Laith R; Bouzghar, Ghizlane; Sehgal, Chandra M

2015-12-01

The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two independent feature sets consisting of visual features based on a radiologist's interpretation of images and computer-extracted features when used as first and second readers and combined by adaptive boosting (AdaBoost) and a pruning classifier resulted in a very high level of diagnostic performance (area under the receiver operating characteristic curve = 0.98) at a cost of pruning a fraction (20%) of the cases for further evaluation by independent methods. AdaBoost also improved the diagnostic performance of the individual human observers and increased the agreement between their analyses. Pairing AdaBoost with selective pruning is a principled methodology for achieving high diagnostic performance without the added cost of an additional reader for differentiating solid breast masses by ultrasound. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations.

PubMed

Sinko, William; de Oliveira, César Augusto F; Pierce, Levi C T; McCammon, J Andrew

2012-01-10

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations.

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

Parallelizing flow-accumulation calculations on graphics processing units—From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

NASA Astrophysics Data System (ADS)

Qin, Cheng-Zhi; Zhan, Lijun

2012-06-01

As one of the important tasks in digital terrain analysis, the calculation of flow accumulations from gridded digital elevation models (DEMs) usually involves two steps in a real application: (1) using an iterative DEM preprocessing algorithm to remove the depressions and flat areas commonly contained in real DEMs, and (2) using a recursive flow-direction algorithm to calculate the flow accumulation for every cell in the DEM. Because both algorithms are computationally intensive, quick calculation of the flow accumulations from a DEM (especially for a large area) presents a practical challenge to personal computer (PC) users. In recent years, rapid increases in hardware capacity of the graphics processing units (GPUs) provided in modern PCs have made it possible to meet this challenge in a PC environment. Parallel computing on GPUs using a compute-unified-device-architecture (CUDA) programming model has been explored to speed up the execution of the single-flow-direction algorithm (SFD). However, the parallel implementation on a GPU of the multiple-flow-direction (MFD) algorithm, which generally performs better than the SFD algorithm, has not been reported. Moreover, GPU-based parallelization of the DEM preprocessing step in the flow-accumulation calculations has not been addressed. This paper proposes a parallel approach to calculate flow accumulations (including both iterative DEM preprocessing and a recursive MFD algorithm) on a CUDA-compatible GPU. For the parallelization of an MFD algorithm (MFD-md), two different parallelization strategies using a GPU are explored. The first parallelization strategy, which has been used in the existing parallel SFD algorithm on GPU, has the problem of computing redundancy. Therefore, we designed a parallelization strategy based on graph theory. The application results show that the proposed parallel approach to calculate flow accumulations on a GPU performs much faster than either sequential algorithms or other parallel GPU-based algorithms based on existing parallelization strategies.

Parallelized Stochastic Cutoff Method for Long-Range Interacting Systems

NASA Astrophysics Data System (ADS)

Endo, Eishin; Toga, Yuta; Sasaki, Munetaka

2015-07-01

We present a method of parallelizing the stochastic cutoff (SCO) method, which is a Monte-Carlo method for long-range interacting systems. After interactions are eliminated by the SCO method, we subdivide a lattice into noninteracting interpenetrating sublattices. This subdivision enables us to parallelize the Monte-Carlo calculation in the SCO method. Such subdivision is found by numerically solving the vertex coloring of a graph created by the SCO method. We use an algorithm proposed by Kuhn and Wattenhofer to solve the vertex coloring by parallel computation. This method was applied to a two-dimensional magnetic dipolar system on an L × L square lattice to examine its parallelization efficiency. The result showed that, in the case of L = 2304, the speed of computation increased about 102 times by parallel computation with 288 processors.

An AdaBoost Based Approach to Automatic Classification and Detection of Buildings Footprints, Vegetation Areas and Roads from Satellite Images

NASA Astrophysics Data System (ADS)

Gonulalan, Cansu

In recent years, there has been an increasing demand for applications to monitor the targets related to land-use, using remote sensing images. Advances in remote sensing satellites give rise to the research in this area. Many applications ranging from urban growth planning to homeland security have already used the algorithms for automated object recognition from remote sensing imagery. However, they have still problems such as low accuracy on detection of targets, specific algorithms for a specific area etc. In this thesis, we focus on an automatic approach to classify and detect building foot-prints, road networks and vegetation areas. The automatic interpretation of visual data is a comprehensive task in computer vision field. The machine learning approaches improve the capability of classification in an intelligent way. We propose a method, which has high accuracy on detection and classification. The multi class classification is developed for detecting multiple objects. We present an AdaBoost-based approach along with the supervised learning algorithm. The combi- nation of AdaBoost with "Attentional Cascade" is adopted from Viola and Jones [1]. This combination decreases the computation time and gives opportunity to real time applications. For the feature extraction step, our contribution is to combine Haar-like features that include corner, rectangle and Gabor. Among all features, AdaBoost selects only critical features and generates in extremely efficient cascade structured classifier. Finally, we present and evaluate our experimental results. The overall system is tested and high performance of detection is achieved. The precision rate of the final multi-class classifier is over 98%.

Identifying failure in a tree network of a parallel computer

DOEpatents

Archer, Charles J.; Pinnow, Kurt W.; Wallenfelt, Brian P.

2010-08-24

Methods, parallel computers, and products are provided for identifying failure in a tree network of a parallel computer. The parallel computer includes one or more processing sets including an I/O node and a plurality of compute nodes. For each processing set embodiments include selecting a set of test compute nodes, the test compute nodes being a subset of the compute nodes of the processing set; measuring the performance of the I/O node of the processing set; measuring the performance of the selected set of test compute nodes; calculating a current test value in dependence upon the measured performance of the I/O node of the processing set, the measured performance of the set of test compute nodes, and a predetermined value for I/O node performance; and comparing the current test value with a predetermined tree performance threshold. If the current test value is below the predetermined tree performance threshold, embodiments include selecting another set of test compute nodes. If the current test value is not below the predetermined tree performance threshold, embodiments include selecting from the test compute nodes one or more potential problem nodes and testing individually potential problem nodes and links to potential problem nodes.

Design of on-board parallel computer on nano-satellite

NASA Astrophysics Data System (ADS)

You, Zheng; Tian, Hexiang; Yu, Shijie; Meng, Li

2007-11-01

This paper provides one scheme of the on-board parallel computer system designed for the Nano-satellite. Based on the development request that the Nano-satellite should have a small volume, low weight, low power cost, and intelligence, this scheme gets rid of the traditional one-computer system and dual-computer system with endeavor to improve the dependability, capability and intelligence simultaneously. According to the method of integration design, it employs the parallel computer system with shared memory as the main structure, connects the telemetric system, attitude control system, and the payload system by the intelligent bus, designs the management which can deal with the static tasks and dynamic task-scheduling, protect and recover the on-site status and so forth in light of the parallel algorithms, and establishes the fault diagnosis, restoration and system restructure mechanism. It accomplishes an on-board parallel computer system with high dependability, capability and intelligence, a flexible management on hardware resources, an excellent software system, and a high ability in extension, which satisfies with the conception and the tendency of the integration electronic design sufficiently.

Optical Symbolic Computing

NASA Astrophysics Data System (ADS)

Neff, John A.

1989-12-01

Experiments originating from Gestalt psychology have shown that representing information in a symbolic form provides a more effective means to understanding. Computer scientists have been struggling for the last two decades to determine how best to create, manipulate, and store collections of symbolic structures. In the past, much of this struggling led to software innovations because that was the path of least resistance. For example, the development of heuristics for organizing the searching through knowledge bases was much less expensive than building massively parallel machines that could search in parallel. That is now beginning to change with the emergence of parallel architectures which are showing the potential for handling symbolic structures. This paper will review the relationships between symbolic computing and parallel computing architectures, and will identify opportunities for optics to significantly impact the performance of such computing machines. Although neural networks are an exciting subset of massively parallel computing structures, this paper will not touch on this area since it is receiving a great deal of attention in the literature. That is, the concepts presented herein do not consider the distributed representation of knowledge.

Parallel rendering

NASA Technical Reports Server (NTRS)

Crockett, Thomas W.

1995-01-01

This article provides a broad introduction to the subject of parallel rendering, encompassing both hardware and software systems. The focus is on the underlying concepts and the issues which arise in the design of parallel rendering algorithms and systems. We examine the different types of parallelism and how they can be applied in rendering applications. Concepts from parallel computing, such as data decomposition, task granularity, scalability, and load balancing, are considered in relation to the rendering problem. We also explore concepts from computer graphics, such as coherence and projection, which have a significant impact on the structure of parallel rendering algorithms. Our survey covers a number of practical considerations as well, including the choice of architectural platform, communication and memory requirements, and the problem of image assembly and display. We illustrate the discussion with numerous examples from the parallel rendering literature, representing most of the principal rendering methods currently used in computer graphics.

Enhancing PC Cluster-Based Parallel Branch-and-Bound Algorithms for the Graph Coloring Problem

NASA Astrophysics Data System (ADS)

Taoka, Satoshi; Takafuji, Daisuke; Watanabe, Toshimasa

A branch-and-bound algorithm (BB for short) is the most general technique to deal with various combinatorial optimization problems. Even if it is used, computation time is likely to increase exponentially. So we consider its parallelization to reduce it. It has been reported that the computation time of a parallel BB heavily depends upon node-variable selection strategies. And, in case of a parallel BB, it is also necessary to prevent increase in communication time. So, it is important to pay attention to how many and what kind of nodes are to be transferred (called sending-node selection strategy). In this paper, for the graph coloring problem, we propose some sending-node selection strategies for a parallel BB algorithm by adopting MPI for parallelization and experimentally evaluate how these strategies affect computation time of a parallel BB on a PC cluster network.

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.

Modelling parallel programs and multiprocessor architectures with AXE

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Fineman, Charles E.

1991-01-01

AXE, An Experimental Environment for Parallel Systems, was designed to model and simulate for parallel systems at the process level. It provides an integrated environment for specifying computation models, multiprocessor architectures, data collection, and performance visualization. AXE is being used at NASA-Ames for developing resource management strategies, parallel problem formulation, multiprocessor architectures, and operating system issues related to the High Performance Computing and Communications Program. AXE's simple, structured user-interface enables the user to model parallel programs and machines precisely and efficiently. Its quick turn-around time keeps the user interested and productive. AXE models multicomputers. The user may easily modify various architectural parameters including the number of sites, connection topologies, and overhead for operating system activities. Parallel computations in AXE are represented as collections of autonomous computing objects known as players. Their use and behavior is described. Performance data of the multiprocessor model can be observed on a color screen. These include CPU and message routing bottlenecks, and the dynamic status of the software.

Efficient parallel resolution of the simplified transport equations in mixed-dual formulation

NASA Astrophysics Data System (ADS)

Barrault, M.; Lathuilière, B.; Ramet, P.; Roman, J.

2011-03-01

A reactivity computation consists of computing the highest eigenvalue of a generalized eigenvalue problem, for which an inverse power algorithm is commonly used. Very fine modelizations are difficult to treat for our sequential solver, based on the simplified transport equations, in terms of memory consumption and computational time. A first implementation of a Lagrangian based domain decomposition method brings to a poor parallel efficiency because of an increase in the power iterations [1]. In order to obtain a high parallel efficiency, we improve the parallelization scheme by changing the location of the loop over the subdomains in the overall algorithm and by benefiting from the characteristics of the Raviart-Thomas finite element. The new parallel algorithm still allows us to locally adapt the numerical scheme (mesh, finite element order). However, it can be significantly optimized for the matching grid case. The good behavior of the new parallelization scheme is demonstrated for the matching grid case on several hundreds of nodes for computations based on a pin-by-pin discretization.

Performing an allreduce operation on a plurality of compute nodes of a parallel computer

DOEpatents

Faraj, Ahmad [Rochester, MN

2012-04-17

Methods, apparatus, and products are disclosed for performing an allreduce operation on a plurality of compute nodes of a parallel computer. Each compute node includes at least two processing cores. Each processing core has contribution data for the allreduce operation. Performing an allreduce operation on a plurality of compute nodes of a parallel computer includes: establishing one or more logical rings among the compute nodes, each logical ring including at least one processing core from each compute node; performing, for each logical ring, a global allreduce operation using the contribution data for the processing cores included in that logical ring, yielding a global allreduce result for each processing core included in that logical ring; and performing, for each compute node, a local allreduce operation using the global allreduce results for each processing core on that compute node.

Hybrid massively parallel fast sweeping method for static Hamilton-Jacobi equations

NASA Astrophysics Data System (ADS)

Detrixhe, Miles; Gibou, Frédéric

2016-10-01

The fast sweeping method is a popular algorithm for solving a variety of static Hamilton-Jacobi equations. Fast sweeping algorithms for parallel computing have been developed, but are severely limited. In this work, we present a multilevel, hybrid parallel algorithm that combines the desirable traits of two distinct parallel methods. The fine and coarse grained components of the algorithm take advantage of heterogeneous computer architecture common in high performance computing facilities. We present the algorithm and demonstrate its effectiveness on a set of example problems including optimal control, dynamic games, and seismic wave propagation. We give results for convergence, parallel scaling, and show state-of-the-art speedup values for the fast sweeping method.

Turbomachinery CFD on parallel computers

NASA Technical Reports Server (NTRS)

Blech, Richard A.; Milner, Edward J.; Quealy, Angela; Townsend, Scott E.

1992-01-01

The role of multistage turbomachinery simulation in the development of propulsion system models is discussed. Particularly, the need for simulations with higher fidelity and faster turnaround time is highlighted. It is shown how such fast simulations can be used in engineering-oriented environments. The use of parallel processing to achieve the required turnaround times is discussed. Current work by several researchers in this area is summarized. Parallel turbomachinery CFD research at the NASA Lewis Research Center is then highlighted. These efforts are focused on implementing the average-passage turbomachinery model on MIMD, distributed memory parallel computers. Performance results are given for inviscid, single blade row and viscous, multistage applications on several parallel computers, including networked workstations.

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.

Toward an automated parallel computing environment for geosciences

NASA Astrophysics Data System (ADS)

Zhang, Huai; Liu, Mian; Shi, Yaolin; Yuen, David A.; Yan, Zhenzhen; Liang, Guoping

2007-08-01

Software for geodynamic modeling has not kept up with the fast growing computing hardware and network resources. In the past decade supercomputing power has become available to most researchers in the form of affordable Beowulf clusters and other parallel computer platforms. However, to take full advantage of such computing power requires developing parallel algorithms and associated software, a task that is often too daunting for geoscience modelers whose main expertise is in geosciences. We introduce here an automated parallel computing environment built on open-source algorithms and libraries. Users interact with this computing environment by specifying the partial differential equations, solvers, and model-specific properties using an English-like modeling language in the input files. The system then automatically generates the finite element codes that can be run on distributed or shared memory parallel machines. This system is dynamic and flexible, allowing users to address different problems in geosciences. It is capable of providing web-based services, enabling users to generate source codes online. This unique feature will facilitate high-performance computing to be integrated with distributed data grids in the emerging cyber-infrastructures for geosciences. In this paper we discuss the principles of this automated modeling environment and provide examples to demonstrate its versatility.

Computer architecture evaluation for structural dynamics computations: Project summary

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1989-01-01

The intent of the proposed effort is the examination of the impact of the elements of parallel architectures on the performance realized in a parallel computation. To this end, three major projects are developed: a language for the expression of high level parallelism, a statistical technique for the synthesis of multicomputer interconnection networks based upon performance prediction, and a queueing model for the analysis of shared memory hierarchies.

Multi-threading: A new dimension to massively parallel scientific computation

NASA Astrophysics Data System (ADS)

Nielsen, Ida M. B.; Janssen, Curtis L.

2000-06-01

Multi-threading is becoming widely available for Unix-like operating systems, and the application of multi-threading opens new ways for performing parallel computations with greater efficiency. We here briefly discuss the principles of multi-threading and illustrate the application of multi-threading for a massively parallel direct four-index transformation of electron repulsion integrals. Finally, other potential applications of multi-threading in scientific computing are outlined.

Surface Modification Engineered Assembly of Novel Quantum Dot Architectures for Advanced Applications

DTIC Science & Technology

2008-02-09

Campbell, S. Ogata, and F. Shimojo, “ Multimillion atom simulations of nanosystems on parallel computers,” in Proceedings of the International...nanomesas: multimillion -atom molecular dynamics simulations on parallel computers,” J. Appl. Phys. 94, 6762 (2003). 21. P. Vashishta, R. K. Kalia...and A. Nakano, “ Multimillion atom molecular dynamics simulations of nanoparticles on parallel computers,” Journal of Nanoparticle Research 5, 119-135

Dynamical Generation of Quasi-Stationary Alfvenic Double Layers and Charge Holes and Unified Theory of Quasi-Static and Alfvenic Auroral Arc Formation

NASA Astrophysics Data System (ADS)

Song, Y.; Lysak, R. L.

2015-12-01

Parallel E-fields play a crucial role for the acceleration of charged particles, creating discrete aurorae. However, once the parallel electric fields are produced, they will disappear right away, unless the electric fields can be continuously generated and sustained for a fairly long time. Thus, the crucial question in auroral physics is how to generate such a powerful and self-sustained parallel electric fields which can effectively accelerate charge particles to high energy during a fairly long time. We propose that nonlinear interaction of incident and reflected Alfven wave packets in inhomogeneous auroral acceleration region can produce quasi-stationary non-propagating electromagnetic plasma structures, such as Alfvenic double layers (DLs) and Charge Holes. Such Alfvenic quasi-static structures often constitute powerful high energy particle accelerators. The Alfvenic DL consists of localized self-sustained powerful electrostatic electric fields nested in a low density cavity and surrounded by enhanced magnetic and mechanical stresses. The enhanced magnetic and velocity fields carrying the free energy serve as a local dynamo, which continuously create the electrostatic parallel electric field for a fairly long time. The generated parallel electric fields will deepen the seed low density cavity, which then further quickly boosts the stronger parallel electric fields creating both Alfvenic and quasi-static discrete aurorae. The parallel electrostatic electric field can also cause ion outflow, perpendicular ion acceleration and heating, and may excite Auroral Kilometric Radiation.

Using parallel computing for the display and simulation of the space debris environment

NASA Astrophysics Data System (ADS)

Möckel, M.; Wiedemann, C.; Flegel, S.; Gelhaus, J.; Vörsmann, P.; Klinkrad, H.; Krag, H.

2011-07-01

Parallelism is becoming the leading paradigm in today's computer architectures. In order to take full advantage of this development, new algorithms have to be specifically designed for parallel execution while many old ones have to be upgraded accordingly. One field in which parallel computing has been firmly established for many years is computer graphics. Calculating and displaying three-dimensional computer generated imagery in real time requires complex numerical operations to be performed at high speed on a large number of objects. Since most of these objects can be processed independently, parallel computing is applicable in this field. Modern graphics processing units (GPUs) have become capable of performing millions of matrix and vector operations per second on multiple objects simultaneously. As a side project, a software tool is currently being developed at the Institute of Aerospace Systems that provides an animated, three-dimensional visualization of both actual and simulated space debris objects. Due to the nature of these objects it is possible to process them individually and independently from each other. Therefore, an analytical orbit propagation algorithm has been implemented to run on a GPU. By taking advantage of all its processing power a huge performance increase, compared to its CPU-based counterpart, could be achieved. For several years efforts have been made to harness this computing power for applications other than computer graphics. Software tools for the simulation of space debris are among those that could profit from embracing parallelism. With recently emerged software development tools such as OpenCL it is possible to transfer the new algorithms used in the visualization outside the field of computer graphics and implement them, for example, into the space debris simulation environment. This way they can make use of parallel hardware such as GPUs and Multi-Core-CPUs for faster computation. In this paper the visualization software will be introduced, including a comparison between the serial and the parallel method of orbit propagation. Ways of how to use the benefits of the latter method for space debris simulation will be discussed. An introduction to OpenCL will be given as well as an exemplary algorithm from the field of space debris simulation.

Using parallel computing for the display and simulation of the space debris environment

NASA Astrophysics Data System (ADS)

Moeckel, Marek; Wiedemann, Carsten; Flegel, Sven Kevin; Gelhaus, Johannes; Klinkrad, Heiner; Krag, Holger; Voersmann, Peter

Parallelism is becoming the leading paradigm in today's computer architectures. In order to take full advantage of this development, new algorithms have to be specifically designed for parallel execution while many old ones have to be upgraded accordingly. One field in which parallel computing has been firmly established for many years is computer graphics. Calculating and displaying three-dimensional computer generated imagery in real time requires complex numerical operations to be performed at high speed on a large number of objects. Since most of these objects can be processed independently, parallel computing is applicable in this field. Modern graphics processing units (GPUs) have become capable of performing millions of matrix and vector operations per second on multiple objects simultaneously. As a side project, a software tool is currently being developed at the Institute of Aerospace Systems that provides an animated, three-dimensional visualization of both actual and simulated space debris objects. Due to the nature of these objects it is possible to process them individually and independently from each other. Therefore, an analytical orbit propagation algorithm has been implemented to run on a GPU. By taking advantage of all its processing power a huge performance increase, compared to its CPU-based counterpart, could be achieved. For several years efforts have been made to harness this computing power for applications other than computer graphics. Software tools for the simulation of space debris are among those that could profit from embracing parallelism. With recently emerged software development tools such as OpenCL it is possible to transfer the new algorithms used in the visualization outside the field of computer graphics and implement them, for example, into the space debris simulation environment. This way they can make use of parallel hardware such as GPUs and Multi-Core-CPUs for faster computation. In this paper the visualization software will be introduced, including a comparison between the serial and the parallel method of orbit propagation. Ways of how to use the benefits of the latter method for space debris simulation will be discussed. An introduction of OpenCL will be given as well as an exemplary algorithm from the field of space debris simulation.

Quantum information, cognition, and music.

PubMed

Dalla Chiara, Maria L; Giuntini, Roberto; Leporini, Roberto; Negri, Eleonora; Sergioli, Giuseppe

2015-01-01

Parallelism represents an essential aspect of human mind/brain activities. One can recognize some common features between psychological parallelism and the characteristic parallel structures that arise in quantum theory and in quantum computation. The article is devoted to a discussion of the following questions: a comparison between classical probabilistic Turing machines and quantum Turing machines.possible applications of the quantum computational semantics to cognitive problems.parallelism in music.

Quantum information, cognition, and music

PubMed Central

Dalla Chiara, Maria L.; Giuntini, Roberto; Leporini, Roberto; Negri, Eleonora; Sergioli, Giuseppe

2015-01-01

Parallelism represents an essential aspect of human mind/brain activities. One can recognize some common features between psychological parallelism and the characteristic parallel structures that arise in quantum theory and in quantum computation. The article is devoted to a discussion of the following questions: a comparison between classical probabilistic Turing machines and quantum Turing machines.possible applications of the quantum computational semantics to cognitive problems.parallelism in music. PMID:26539139

Restricted access Improved hydrogeophysical characterization and monitoring through parallel modeling and inversion of time-domain resistivity andinduced-polarization data

USGS Publications Warehouse

Johnson, Timothy C.; Versteeg, Roelof J.; Ward, Andy; Day-Lewis, Frederick D.; Revil, André

2010-01-01

Electrical geophysical methods have found wide use in the growing discipline of hydrogeophysics for characterizing the electrical properties of the subsurface and for monitoring subsurface processes in terms of the spatiotemporal changes in subsurface conductivity, chargeability, and source currents they govern. Presently, multichannel and multielectrode data collections systems can collect large data sets in relatively short periods of time. Practitioners, however, often are unable to fully utilize these large data sets and the information they contain because of standard desktop-computer processing limitations. These limitations can be addressed by utilizing the storage and processing capabilities of parallel computing environments. We have developed a parallel distributed-memory forward and inverse modeling algorithm for analyzing resistivity and time-domain induced polar-ization (IP) data. The primary components of the parallel computations include distributed computation of the pole solutions in forward mode, distributed storage and computation of the Jacobian matrix in inverse mode, and parallel execution of the inverse equation solver. We have tested the corresponding parallel code in three efforts: (1) resistivity characterization of the Hanford 300 Area Integrated Field Research Challenge site in Hanford, Washington, U.S.A., (2) resistivity characterization of a volcanic island in the southern Tyrrhenian Sea in Italy, and (3) resistivity and IP monitoring of biostimulation at a Superfund site in Brandywine, Maryland, U.S.A. Inverse analysis of each of these data sets would be limited or impossible in a standard serial computing environment, which underscores the need for parallel high-performance computing to fully utilize the potential of electrical geophysical methods in hydrogeophysical applications.

Locating hardware faults in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-01-12

Hardware faults location in a data communications network of a parallel computer. Such a parallel computer includes a plurality of compute nodes and a data communications network that couples the compute nodes for data communications and organizes the compute node as a tree. Locating hardware faults includes identifying a next compute node as a parent node and a root of a parent test tree, identifying for each child compute node of the parent node a child test tree having the child compute node as root, running a same test suite on the parent test tree and each child test tree, and identifying the parent compute node as having a defective link connected from the parent compute node to a child compute node if the test suite fails on the parent test tree and succeeds on all the child test trees.

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.

Parallel implementation of geometrical shock dynamics for two dimensional converging shock waves

NASA Astrophysics Data System (ADS)

Qiu, Shi; Liu, Kuang; Eliasson, Veronica

2016-10-01

Geometrical shock dynamics (GSD) theory is an appealing method to predict the shock motion in the sense that it is more computationally efficient than solving the traditional Euler equations, especially for converging shock waves. However, to solve and optimize large scale configurations, the main bottleneck is the computational cost. Among the existing numerical GSD schemes, there is only one that has been implemented on parallel computers, with the purpose to analyze detonation waves. To extend the computational advantage of the GSD theory to more general applications such as converging shock waves, a numerical implementation using a spatial decomposition method has been coupled with a front tracking approach on parallel computers. In addition, an efficient tridiagonal system solver for massively parallel computers has been applied to resolve the most expensive function in this implementation, resulting in an efficiency of 0.93 while using 32 HPCC cores. Moreover, symmetric boundary conditions have been developed to further reduce the computational cost, achieving a speedup of 19.26 for a 12-sided polygonal converging shock.

Perforin and gamma interferon expression are required for CD4+ and CD8+ T-cell-dependent protective immunity against a human parasite, Trypanosoma cruzi, elicited by heterologous plasmid DNA prime-recombinant adenovirus 5 boost vaccination.

PubMed

de Alencar, Bruna C G; Persechini, Pedro M; Haolla, Filipe A; de Oliveira, Gabriel; Silverio, Jaline C; Lannes-Vieira, Joseli; Machado, Alexandre V; Gazzinelli, Ricardo T; Bruna-Romero, Oscar; Rodrigues, Mauricio M

2009-10-01

A heterologous prime-boost strategy using plasmid DNA, followed by replication-defective recombinant adenovirus 5, is being proposed as a powerful way to elicit CD4(+) and CD8(+) T-cell-mediated protective immunity against intracellular pathogens. We confirmed this concept and furthered existing research by providing evidence that the heterologous prime-boost regimen using the gene encoding amastigote surface protein 2 elicited CD4(+) and CD8(+) T-cell-mediated protective immunity (reduction of acute parasitemia and prolonged survival) against experimental infection with Trypanosoma cruzi. Protective immunity correlated with the presence of in vivo antigen-specific cytotoxic activity prior to challenge. Based on this, our second goal was to determine the outcome of infection after heterologous prime-boost immunization of perforin-deficient mice. These mice were highly susceptible to infection. A detailed analysis of the cell-mediated immune responses in immunized perforin-deficient mice showed an impaired gamma interferon (IFN-gamma) secretion by immune spleen cells upon restimulation in vitro with soluble recombinant antigen. In spite of a normal numeric expansion, specific CD8(+) T cells presented several functional defects detected in vivo (cytotoxicity) and in vitro (simultaneous expression of CD107a/IFN-gamma or IFN-gamma/tumor necrosis factor alpha) paralleled by a decreased expression of CD44 and KLRG-1. Our final goal was to determine the importance of IFN-gamma in the presence of highly cytotoxic T cells. Vaccinated IFN-gamma-deficient mice developed highly cytotoxic cells but failed to develop any protective immunity. Our study thus demonstrated a role for perforin and IFN-gamma in a number of T-cell-mediated effector functions and in the antiparasitic immunity generated by a heterologous plasmid DNA prime-adenovirus boost vaccination strategy.

Perforin and Gamma Interferon Expression Are Required for CD4+ and CD8+ T-Cell-Dependent Protective Immunity against a Human Parasite, Trypanosoma cruzi, Elicited by Heterologous Plasmid DNA Prime-Recombinant Adenovirus 5 Boost Vaccination▿

PubMed Central

de Alencar, Bruna C. G.; Persechini, Pedro M.; Haolla, Filipe A.; de Oliveira, Gabriel; Silverio, Jaline C.; Lannes-Vieira, Joseli; Machado, Alexandre V.; Gazzinelli, Ricardo T.; Bruna-Romero, Oscar; Rodrigues, Mauricio M.

2009-01-01

A heterologous prime-boost strategy using plasmid DNA, followed by replication-defective recombinant adenovirus 5, is being proposed as a powerful way to elicit CD4+ and CD8+ T-cell-mediated protective immunity against intracellular pathogens. We confirmed this concept and furthered existing research by providing evidence that the heterologous prime-boost regimen using the gene encoding amastigote surface protein 2 elicited CD4+ and CD8+ T-cell-mediated protective immunity (reduction of acute parasitemia and prolonged survival) against experimental infection with Trypanosoma cruzi. Protective immunity correlated with the presence of in vivo antigen-specific cytotoxic activity prior to challenge. Based on this, our second goal was to determine the outcome of infection after heterologous prime-boost immunization of perforin-deficient mice. These mice were highly susceptible to infection. A detailed analysis of the cell-mediated immune responses in immunized perforin-deficient mice showed an impaired gamma interferon (IFN-γ) secretion by immune spleen cells upon restimulation in vitro with soluble recombinant antigen. In spite of a normal numeric expansion, specific CD8+ T cells presented several functional defects detected in vivo (cytotoxicity) and in vitro (simultaneous expression of CD107a/IFN-γ or IFN-γ/tumor necrosis factor alpha) paralleled by a decreased expression of CD44 and KLRG-1. Our final goal was to determine the importance of IFN-γ in the presence of highly cytotoxic T cells. Vaccinated IFN-γ-deficient mice developed highly cytotoxic cells but failed to develop any protective immunity. Our study thus demonstrated a role for perforin and IFN-γ in a number of T-cell-mediated effector functions and in the antiparasitic immunity generated by a heterologous plasmid DNA prime-adenovirus boost vaccination strategy. PMID:19651871

A Comparison of Automatic Parallelization Tools/Compilers on the SGI Origin 2000 Using the NAS Benchmarks

NASA Technical Reports Server (NTRS)

Saini, Subhash; Frumkin, Michael; Hribar, Michelle; Jin, Hao-Qiang; Waheed, Abdul; Yan, Jerry

1998-01-01

Porting applications to new high performance parallel and distributed computing platforms is a challenging task. Since writing parallel code by hand is extremely time consuming and costly, porting codes would ideally be automated by using some parallelization tools and compilers. In this paper, we compare the performance of the hand written NAB Parallel Benchmarks against three parallel versions generated with the help of tools and compilers: 1) CAPTools: an interactive computer aided parallelization too] that generates message passing code, 2) the Portland Group's HPF compiler and 3) using compiler directives with the native FORTAN77 compiler on the SGI Origin2000.

A transient FETI methodology for large-scale parallel implicit computations in structural mechanics

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Crivelli, Luis; Roux, Francois-Xavier

1992-01-01

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because explicit schemes are also easier to parallelize than implicit ones. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet -- and perhaps will never -- be offset by the speed of parallel hardware. Therefore, it is essential to develop efficient and robust alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating low-frequency dynamics. Here we present a domain decomposition method for implicit schemes that requires significantly less storage than factorization algorithms, that is several times faster than other popular direct and iterative methods, that can be easily implemented on both shared and local memory parallel processors, and that is both computationally and communication-wise efficient. The proposed transient domain decomposition method is an extension of the method of Finite Element Tearing and Interconnecting (FETI) developed by Farhat and Roux for the solution of static problems. Serial and parallel performance results on the CRAY Y-MP/8 and the iPSC-860/128 systems are reported and analyzed for realistic structural dynamics problems. These results establish the superiority of the FETI method over both the serial/parallel conjugate gradient algorithm with diagonal scaling and the serial/parallel direct method, and contrast the computational power of the iPSC-860/128 parallel processor with that of the CRAY Y-MP/8 system.

From Desktop to Teraflop: Exploiting the U.S. Lead in High Performance Computing. NSF Blue Ribbon Panel on High Performance Computing.

ERIC Educational Resources Information Center

National Science Foundation, Washington, DC.

This report addresses an opportunity to accelerate progress in virtually every branch of science and engineering concurrently, while also boosting the American economy as business firms also learn to exploit these new capabilities. The successful rapid advancement in both science and technology creates its own challenges, four of which are…

Massively parallel sparse matrix function calculations with NTPoly

NASA Astrophysics Data System (ADS)

Dawson, William; Nakajima, Takahito

2018-04-01

We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.

Parallel Domain Decomposition Formulation and Software for Large-Scale Sparse Symmetrical/Unsymmetrical Aeroacoustic Applications

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Watson, Willie R. (Technical Monitor)

2005-01-01

The overall objectives of this research work are to formulate and validate efficient parallel algorithms, and to efficiently design/implement computer software for solving large-scale acoustic problems, arised from the unified frameworks of the finite element procedures. The adopted parallel Finite Element (FE) Domain Decomposition (DD) procedures should fully take advantages of multiple processing capabilities offered by most modern high performance computing platforms for efficient parallel computation. To achieve this objective. the formulation needs to integrate efficient sparse (and dense) assembly techniques, hybrid (or mixed) direct and iterative equation solvers, proper pre-conditioned strategies, unrolling strategies, and effective processors' communicating schemes. Finally, the numerical performance of the developed parallel finite element procedures will be evaluated by solving series of structural, and acoustic (symmetrical and un-symmetrical) problems (in different computing platforms). Comparisons with existing "commercialized" and/or "public domain" software are also included, whenever possible.

Parallel, Asynchronous Executive (PAX): System concepts, facilities, and architecture

NASA Technical Reports Server (NTRS)

Jones, W. H.

1983-01-01

The Parallel, Asynchronous Executive (PAX) is a software operating system simulation that allows many computers to work on a single problem at the same time. PAX is currently implemented on a UNIVAC 1100/42 computer system. Independent UNIVAC runstreams are used to simulate independent computers. Data are shared among independent UNIVAC runstreams through shared mass-storage files. PAX has achieved the following: (1) applied several computing processes simultaneously to a single, logically unified problem; (2) resolved most parallel processor conflicts by careful work assignment; (3) resolved by means of worker requests to PAX all conflicts not resolved by work assignment; (4) provided fault isolation and recovery mechanisms to meet the problems of an actual parallel, asynchronous processing machine. Additionally, one real-life problem has been constructed for the PAX environment. This is CASPER, a collection of aerodynamic and structural dynamic problem simulation routines. CASPER is not discussed in this report except to provide examples of parallel-processing techniques.

Applications of Parallel Computation in Micro-Mechanics and Finite Element Method

NASA Technical Reports Server (NTRS)

Tan, Hui-Qian

1996-01-01

This project discusses the application of parallel computations related with respect to material analyses. Briefly speaking, we analyze some kind of material by elements computations. We call an element a cell here. A cell is divided into a number of subelements called subcells and all subcells in a cell have the identical structure. The detailed structure will be given later in this paper. It is obvious that the problem is "well-structured". SIMD machine would be a better choice. In this paper we try to look into the potentials of SIMD machine in dealing with finite element computation by developing appropriate algorithms on MasPar, a SIMD parallel machine. In section 2, the architecture of MasPar will be discussed. A brief review of the parallel programming language MPL also is given in that section. In section 3, some general parallel algorithms which might be useful to the project will be proposed. And, combining with the algorithms, some features of MPL will be discussed in more detail. In section 4, the computational structure of cell/subcell model will be given. The idea of designing the parallel algorithm for the model will be demonstrated. Finally in section 5, a summary will be given.

Optics Program Modified for Multithreaded Parallel Computing

NASA Technical Reports Server (NTRS)

Lou, John; Bedding, Dave; Basinger, Scott

2006-01-01

A powerful high-performance computer program for simulating and analyzing adaptive and controlled optical systems has been developed by modifying the serial version of the Modeling and Analysis for Controlled Optical Systems (MACOS) program to impart capabilities for multithreaded parallel processing on computing systems ranging from supercomputers down to Symmetric Multiprocessing (SMP) personal computers. The modifications included the incorporation of OpenMP, a portable and widely supported application interface software, that can be used to explicitly add multithreaded parallelism to an application program under a shared-memory programming model. OpenMP was applied to parallelize ray-tracing calculations, one of the major computing components in MACOS. Multithreading is also used in the diffraction propagation of light in MACOS based on pthreads [POSIX Thread, (where "POSIX" signifies a portable operating system for UNIX)]. In tests of the parallelized version of MACOS, the speedup in ray-tracing calculations was found to be linear, or proportional to the number of processors, while the speedup in diffraction calculations ranged from 50 to 60 percent, depending on the type and number of processors. The parallelized version of MACOS is portable, and, to the user, its interface is basically the same as that of the original serial version of MACOS.

PyPele Rewritten To Use MPI

NASA Technical Reports Server (NTRS)

Hockney, George; Lee, Seungwon

2008-01-01

A computer program known as PyPele, originally written as a Pythonlanguage extension module of a C++ language program, has been rewritten in pure Python language. The original version of PyPele dispatches and coordinates parallel-processing tasks on cluster computers and provides a conceptual framework for spacecraft-mission- design and -analysis software tools to run in an embarrassingly parallel mode. The original version of PyPele uses SSH (Secure Shell a set of standards and an associated network protocol for establishing a secure channel between a local and a remote computer) to coordinate parallel processing. Instead of SSH, the present Python version of PyPele uses Message Passing Interface (MPI) [an unofficial de-facto standard language-independent application programming interface for message- passing on a parallel computer] while keeping the same user interface. The use of MPI instead of SSH and the preservation of the original PyPele user interface make it possible for parallel application programs written previously for the original version of PyPele to run on MPI-based cluster computers. As a result, engineers using the previously written application programs can take advantage of embarrassing parallelism without need to rewrite those programs.

Massively parallel information processing systems for space applications

NASA Technical Reports Server (NTRS)

Schaefer, D. H.

1979-01-01

NASA is developing massively parallel systems for ultra high speed processing of digital image data collected by satellite borne instrumentation. Such systems contain thousands of processing elements. Work is underway on the design and fabrication of the 'Massively Parallel Processor', a ground computer containing 16,384 processing elements arranged in a 128 x 128 array. This computer uses existing technology. Advanced work includes the development of semiconductor chips containing thousands of feedthrough paths. Massively parallel image analog to digital conversion technology is also being developed. The goal is to provide compact computers suitable for real-time onboard processing of images.

n-body simulations using message passing parallel computers.

NASA Astrophysics Data System (ADS)

Grama, A. Y.; Kumar, V.; Sameh, A.

The authors present new parallel formulations of the Barnes-Hut method for n-body simulations on message passing computers. These parallel formulations partition the domain efficiently incurring minimal communication overhead. This is in contrast to existing schemes that are based on sorting a large number of keys or on the use of global data structures. The new formulations are augmented by alternate communication strategies which serve to minimize communication overhead. The impact of these communication strategies is experimentally studied. The authors report on experimental results obtained from an astrophysical simulation on an nCUBE2 parallel computer.

A design methodology for portable software on parallel computers

NASA Technical Reports Server (NTRS)

Nicol, David M.; Miller, Keith W.; Chrisman, Dan A.

1993-01-01

This final report for research that was supported by grant number NAG-1-995 documents our progress in addressing two difficulties in parallel programming. The first difficulty is developing software that will execute quickly on a parallel computer. The second difficulty is transporting software between dissimilar parallel computers. In general, we expect that more hardware-specific information will be included in software designs for parallel computers than in designs for sequential computers. This inclusion is an instance of portability being sacrificed for high performance. New parallel computers are being introduced frequently. Trying to keep one's software on the current high performance hardware, a software developer almost continually faces yet another expensive software transportation. The problem of the proposed research is to create a design methodology that helps designers to more precisely control both portability and hardware-specific programming details. The proposed research emphasizes programming for scientific applications. We completed our study of the parallelizability of a subsystem of the NASA Earth Radiation Budget Experiment (ERBE) data processing system. This work is summarized in section two. A more detailed description is provided in Appendix A ('Programming Practices to Support Eventual Parallelism'). Mr. Chrisman, a graduate student, wrote and successfully defended a Ph.D. dissertation proposal which describes our research associated with the issues of software portability and high performance. The list of research tasks are specified in the proposal. The proposal 'A Design Methodology for Portable Software on Parallel Computers' is summarized in section three and is provided in its entirety in Appendix B. We are currently studying a proposed subsystem of the NASA Clouds and the Earth's Radiant Energy System (CERES) data processing system. This software is the proof-of-concept for the Ph.D. dissertation. We have implemented and measured the performance of a portion of this subsystem on the Intel iPSC/2 parallel computer. These results are provided in section four. Our future work is summarized in section five, our acknowledgements are stated in section six, and references for published papers associated with NAG-1-995 are provided in section seven.

Convergence issues in domain decomposition parallel computation of hovering rotor

NASA Astrophysics Data System (ADS)

Xiao, Zhongyun; Liu, Gang; Mou, Bin; Jiang, Xiong

2018-05-01

Implicit LU-SGS time integration algorithm has been widely used in parallel computation in spite of its lack of information from adjacent domains. When applied to parallel computation of hovering rotor flows in a rotating frame, it brings about convergence issues. To remedy the problem, three LU factorization-based implicit schemes (consisting of LU-SGS, DP-LUR and HLU-SGS) are investigated comparatively. A test case of pure grid rotation is designed to verify these algorithms, which show that LU-SGS algorithm introduces errors on boundary cells. When partition boundaries are circumferential, errors arise in proportion to grid speed, accumulating along with the rotation, and leading to computational failure in the end. Meanwhile, DP-LUR and HLU-SGS methods show good convergence owing to boundary treatment which are desirable in domain decomposition parallel computations.

How to make your own response boxes: A step-by-step guide for the construction of reliable and inexpensive parallel-port response pads from computer mice.

PubMed

Voss, Andreas; Leonhart, Rainer; Stahl, Christoph

2007-11-01

Psychological research is based in large parts on response latencies, which are often registered by keypresses on a standard computer keyboard. Recording response latencies with a standard keyboard is problematic because keypresses are buffered within the keyboard hardware before they are signaled to the computer, adding error variance to the recorded latencies. This can be circumvented by using external response pads connected to the computer's parallel port. In this article, we describe how to build inexpensive, reliable, and easy-to-use response pads with six keys from two standard computer mice that can be connected to the PC's parallel port. We also address the problem of recording data from the parallel port with different software packages under Microsoft's Windows XP.

On some methods for improving time of reachability sets computation for the dynamic system control problem

NASA Astrophysics Data System (ADS)

Zimovets, Artem; Matviychuk, Alexander; Ushakov, Vladimir

2016-12-01

The paper presents two different approaches to reduce the time of computer calculation of reachability sets. First of these two approaches use different data structures for storing the reachability sets in the computer memory for calculation in single-threaded mode. Second approach is based on using parallel algorithms with reference to the data structures from the first approach. Within the framework of this paper parallel algorithm of approximate reachability set calculation on computer with SMP-architecture is proposed. The results of numerical modelling are presented in the form of tables which demonstrate high efficiency of parallel computing technology and also show how computing time depends on the used data structure.

Performance analysis of parallel branch and bound search with the hypercube architecture

NASA Technical Reports Server (NTRS)

Mraz, Richard T.

1987-01-01

With the availability of commercial parallel computers, researchers are examining new classes of problems which might benefit from parallel computing. This paper presents results of an investigation of the class of search intensive problems. The specific problem discussed is the Least-Cost Branch and Bound search method of deadline job scheduling. The object-oriented design methodology was used to map the problem into a parallel solution. While the initial design was good for a prototype, the best performance resulted from fine-tuning the algorithm for a specific computer. The experiments analyze the computation time, the speed up over a VAX 11/785, and the load balance of the problem when using loosely coupled multiprocessor system based on the hypercube architecture.

Dynamic modeling of parallel robots for computed-torque control implementation

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

Codourey, A.

1998-12-01

In recent years, increased interest in parallel robots has been observed. Their control with modern theory, such as the computed-torque method, has, however, been restrained, essentially due to the difficulty in establishing a simple dynamic model that can be calculated in real time. In this paper, a simple method based on the virtual work principle is proposed for modeling parallel robots. The mass matrix of the robot, needed for decoupling control strategies, does not explicitly appear in the formulation; however, it can be computed separately, based on kinetic energy considerations. The method is applied to the DELTA parallel robot, leadingmore » to a very efficient model that has been implemented in a real-time computed-torque control algorithm.« less

Architecture-Adaptive Computing Environment: A Tool for Teaching Parallel Programming

NASA Technical Reports Server (NTRS)

Dorband, John E.; Aburdene, Maurice F.

2002-01-01

Recently, networked and cluster computation have become very popular. This paper is an introduction to a new C based parallel language for architecture-adaptive programming, aCe C. The primary purpose of aCe (Architecture-adaptive Computing Environment) is to encourage programmers to implement applications on parallel architectures by providing them the assurance that future architectures will be able to run their applications with a minimum of modification. A secondary purpose is to encourage computer architects to develop new types of architectures by providing an easily implemented software development environment and a library of test applications. This new language should be an ideal tool to teach parallel programming. In this paper, we will focus on some fundamental features of aCe C.

Portability and Cross-Platform Performance of an MPI-Based Parallel Polygon Renderer

NASA Technical Reports Server (NTRS)

Crockett, Thomas W.

1999-01-01

Visualizing the results of computations performed on large-scale parallel computers is a challenging problem, due to the size of the datasets involved. One approach is to perform the visualization and graphics operations in place, exploiting the available parallelism to obtain the necessary rendering performance. Over the past several years, we have been developing algorithms and software to support visualization applications on NASA's parallel supercomputers. Our results have been incorporated into a parallel polygon rendering system called PGL. PGL was initially developed on tightly-coupled distributed-memory message-passing systems, including Intel's iPSC/860 and Paragon, and IBM's SP2. Over the past year, we have ported it to a variety of additional platforms, including the HP Exemplar, SGI Origin2OOO, Cray T3E, and clusters of Sun workstations. In implementing PGL, we have had two primary goals: cross-platform portability and high performance. Portability is important because (1) our manpower resources are limited, making it difficult to develop and maintain multiple versions of the code, and (2) NASA's complement of parallel computing platforms is diverse and subject to frequent change. Performance is important in delivering adequate rendering rates for complex scenes and ensuring that parallel computing resources are used effectively. Unfortunately, these two goals are often at odds. In this paper we report on our experiences with portability and performance of the PGL polygon renderer across a range of parallel computing platforms.

Program scheme using common source lines in channel stacked NAND flash memory with layer selection by multilevel operation

NASA Astrophysics Data System (ADS)

Kim, Do-Bin; Kwon, Dae Woong; Kim, Seunghyun; Lee, Sang-Ho; Park, Byung-Gook

2018-02-01

To obtain high channel boosting potential and reduce a program disturbance in channel stacked NAND flash memory with layer selection by multilevel (LSM) operation, a new program scheme using boosted common source line (CSL) is proposed. The proposed scheme can be achieved by applying proper bias to each layer through its own CSL. Technology computer-aided design (TCAD) simulations are performed to verify the validity of the new method in LSM. Through TCAD simulation, it is revealed that the program disturbance characteristics is effectively improved by the proposed scheme.

A compositional reservoir simulator on distributed memory parallel computers

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

Rame, M.; Delshad, M.

1995-12-31

This paper presents the application of distributed memory parallel computes to field scale reservoir simulations using a parallel version of UTCHEM, The University of Texas Chemical Flooding Simulator. The model is a general purpose highly vectorized chemical compositional simulator that can simulate a wide range of displacement processes at both field and laboratory scales. The original simulator was modified to run on both distributed memory parallel machines (Intel iPSC/960 and Delta, Connection Machine 5, Kendall Square 1 and 2, and CRAY T3D) and a cluster of workstations. A domain decomposition approach has been taken towards parallelization of the code. Amore » portion of the discrete reservoir model is assigned to each processor by a set-up routine that attempts a data layout as even as possible from the load-balance standpoint. Each of these subdomains is extended so that data can be shared between adjacent processors for stencil computation. The added routines that make parallel execution possible are written in a modular fashion that makes the porting to new parallel platforms straight forward. Results of the distributed memory computing performance of Parallel simulator are presented for field scale applications such as tracer flood and polymer flood. A comparison of the wall-clock times for same problems on a vector supercomputer is also presented.« less

Hybrid massively parallel fast sweeping method for static Hamilton–Jacobi equations

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

Detrixhe, Miles, E-mail: mdetrixhe@engineering.ucsb.edu; University of California Santa Barbara, Santa Barbara, CA, 93106; Gibou, Frédéric, E-mail: fgibou@engineering.ucsb.edu

The fast sweeping method is a popular algorithm for solving a variety of static Hamilton–Jacobi equations. Fast sweeping algorithms for parallel computing have been developed, but are severely limited. In this work, we present a multilevel, hybrid parallel algorithm that combines the desirable traits of two distinct parallel methods. The fine and coarse grained components of the algorithm take advantage of heterogeneous computer architecture common in high performance computing facilities. We present the algorithm and demonstrate its effectiveness on a set of example problems including optimal control, dynamic games, and seismic wave propagation. We give results for convergence, parallel scaling,more » and show state-of-the-art speedup values for the fast sweeping method.« less

Hybrid parallel computing architecture for multiview phase shifting

NASA Astrophysics Data System (ADS)

Zhong, Kai; Li, Zhongwei; Zhou, Xiaohui; Shi, Yusheng; Wang, Congjun

2014-11-01

The multiview phase-shifting method shows its powerful capability in achieving high resolution three-dimensional (3-D) shape measurement. Unfortunately, this ability results in very high computation costs and 3-D computations have to be processed offline. To realize real-time 3-D shape measurement, a hybrid parallel computing architecture is proposed for multiview phase shifting. In this architecture, the central processing unit can co-operate with the graphic processing unit (GPU) to achieve hybrid parallel computing. The high computation cost procedures, including lens distortion rectification, phase computation, correspondence, and 3-D reconstruction, are implemented in GPU, and a three-layer kernel function model is designed to simultaneously realize coarse-grained and fine-grained paralleling computing. Experimental results verify that the developed system can perform 50 fps (frame per second) real-time 3-D measurement with 260 K 3-D points per frame. A speedup of up to 180 times is obtained for the performance of the proposed technique using a NVIDIA GT560Ti graphics card rather than a sequential C in a 3.4 GHZ Inter Core i7 3770.

Improved Access to Supercomputers Boosts Chemical Applications.

ERIC Educational Resources Information Center

Borman, Stu

1989-01-01

Supercomputing is described in terms of computing power and abilities. The increase in availability of supercomputers for use in chemical calculations and modeling are reported. Efforts of the National Science Foundation and Cray Research are highlighted. (CW)

Lunar Orbiter 4 - Photographic Mission Summary. Volume 1

NASA Technical Reports Server (NTRS)

1968-01-01

Photographic summary report of Lunar Orbiter 4 mission. The fourth of five Lunar Orbiter spacecraft was successfully launched from Launch Complex 13 at the Air Force Eastern Test Range by an Atlas-Agena launch vehicle at 22:25 GMT on May 4, 1967. Tracking data from the Cape Kennedy and Grand Bahama tracking stations were used to control and guide the launch vehicle during Atlas powered flight. The Agena-spacecraft combination was boosted to the proper coast ellipse by the Atlas booster prior to separation. Final maneuvering and acceleration to the velocity required to maintain the 100-nauticalmile- altitude Earth orbit was controlled by the preset on-board Agena computer. In addition, the Agena computer determined the maneuver and engine-burn period required to inject the spacecraft on the cislunar trajectory 20 minutes after launch. Tracking data from the downrange stations and the Johannesburg, South Africa station were used to monitor the boost trajectory.

Lunar Orbiter 5. Photographic Mission Summary. Volume 1

NASA Technical Reports Server (NTRS)

1968-01-01

Selected photographs and mission summary of Lunar Orbiter 5. The last of five Lunar Orbiter spacecraft was successfully launched from Launch Complex 13 at the Air Force Eastern Test Range by an Atlas-Agena launch vehicle at 22:33 GMT on August 1, 1967. Tracking data from the Cape Kennedy and Grand Bahama tracking stations were used to control and guide the launch vehicle during Atlas powered flight. The Agena-spacecraft combination was boosted to the proper coast ellipse by the Atlas booster prior to separation. Final maneuvering and acceleration to the velocity required to maintain the 100-nautical-mile-altitude Earth orbit were controlled by the preset on-board Agena computer. In addition, the Agena computer determined the maneuver and engine-bum period required to inject the spacecraft on the cislunar trajectory about 33 minutes after launch. Tracking data from the downrange stations and the Johannesburg, South Africa station were used to monitor the boost trajectory.

Lunar Orbiter 3 - Photographic Mission Summary

NASA Technical Reports Server (NTRS)

1968-01-01

Systems performance, lunar photography, and launch operations of Lunar Orbiter 3 photographic mission. The third of five Lunar Orbiter spacecraft was successfully launched from Launch Complex 13 at the Air Force Eastern Test Range by an Atlas-Agena launch vehicle at 01:17 GMT on February 5,1967. Tracking data from the Cape Kennedy and Grand Bahama tracking stations were used to control and guide the launch vehicle during Atlas powered flight. The Agena-spacecraft combination was boosted to the proper coast ellipse by the Atlas booster prior to separation. Final 1 maneuvering and acceleration to the velocity required to maintain the 100-nautical-milealtitude Earth orbit was controlled by the preset on-board Agena computer. In addition, the Agena computer determined the maneuver and engine-burn period required to inject the spacecraft on the cislunar trajectory 20 minutes after launch. Tracking data from the downrange stations and the Johannesburg, South Africa station were used to monitor the entire boost trajectory.

Addition of visual noise boosts evoked potential-based brain-computer interface.

PubMed

Xie, Jun; Xu, Guanghua; Wang, Jing; Zhang, Sicong; Zhang, Feng; Li, Yeping; Han, Chengcheng; Li, Lili

2014-05-14

Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7-36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs.

An ensemble rank learning approach for gene prioritization.

PubMed

Lee, Po-Feng; Soo, Von-Wun

2013-01-01

Several different computational approaches have been developed to solve the gene prioritization problem. We intend to use the ensemble boosting learning techniques to combine variant computational approaches for gene prioritization in order to improve the overall performance. In particular we add a heuristic weighting function to the Rankboost algorithm according to: 1) the absolute ranks generated by the adopted methods for a certain gene, and 2) the ranking relationship between all gene-pairs from each prioritization result. We select 13 known prostate cancer genes in OMIM database as training set and protein coding gene data in HGNC database as test set. We adopt the leave-one-out strategy for the ensemble rank boosting learning. The experimental results show that our ensemble learning approach outperforms the four gene-prioritization methods in ToppGene suite in the ranking results of the 13 known genes in terms of mean average precision, ROC and AUC measures.

On efficiency of fire simulation realization: parallelization with greater number of computational meshes

NASA Astrophysics Data System (ADS)

Valasek, Lukas; Glasa, Jan

2017-12-01

Current fire simulation systems are capable to utilize advantages of high-performance computer (HPC) platforms available and to model fires efficiently in parallel. In this paper, efficiency of a corridor fire simulation on a HPC computer cluster is discussed. The parallel MPI version of Fire Dynamics Simulator is used for testing efficiency of selected strategies of allocation of computational resources of the cluster using a greater number of computational cores. Simulation results indicate that if the number of cores used is not equal to a multiple of the total number of cluster node cores there are allocation strategies which provide more efficient calculations.

A Hybrid MPI/OpenMP Approach for Parallel Groundwater Model Calibration on Multicore Computers

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

Tang, Guoping; D'Azevedo, Ed F; Zhang, Fan

2010-01-01

Groundwater model calibration is becoming increasingly computationally time intensive. We describe a hybrid MPI/OpenMP approach to exploit two levels of parallelism in software and hardware to reduce calibration time on multicore computers with minimal parallelization effort. At first, HydroGeoChem 5.0 (HGC5) is parallelized using OpenMP for a uranium transport model with over a hundred species involving nearly a hundred reactions, and a field scale coupled flow and transport model. In the first application, a single parallelizable loop is identified to consume over 97% of the total computational time. With a few lines of OpenMP compiler directives inserted into the code,more » the computational time reduces about ten times on a compute node with 16 cores. The performance is further improved by selectively parallelizing a few more loops. For the field scale application, parallelizable loops in 15 of the 174 subroutines in HGC5 are identified to take more than 99% of the execution time. By adding the preconditioned conjugate gradient solver and BICGSTAB, and using a coloring scheme to separate the elements, nodes, and boundary sides, the subroutines for finite element assembly, soil property update, and boundary condition application are parallelized, resulting in a speedup of about 10 on a 16-core compute node. The Levenberg-Marquardt (LM) algorithm is added into HGC5 with the Jacobian calculation and lambda search parallelized using MPI. With this hybrid approach, compute nodes at the number of adjustable parameters (when the forward difference is used for Jacobian approximation), or twice that number (if the center difference is used), are used to reduce the calibration time from days and weeks to a few hours for the two applications. This approach can be extended to global optimization scheme and Monte Carol analysis where thousands of compute nodes can be efficiently utilized.« 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.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-06-08

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-11-23

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

A direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL)

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Owen, Jeffrey E.

1988-01-01

A direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL) is presented which overcomes the traditional disadvantages of simulations executed on a digital computer. The incorporation of parallel processing allows the mapping of simulations into a digital computer to be done in the same inherently parallel manner as they are currently mapped onto an analog computer. The direct-execution format maximizes the efficiency of the executed code since the need for a high level language compiler is eliminated. Resolution is greatly increased over that which is available with an analog computer without the sacrifice in execution speed normally expected with digitial computer simulations. Although this report covers all aspects of the new architecture, key emphasis is placed on the processing element configuration and the microprogramming of the ACLS constructs. The execution times for all ACLS constructs are computed using a model of a processing element based on the AMD 29000 CPU and the AMD 29027 FPU. The increase in execution speed provided by parallel processing is exemplified by comparing the derived execution times of two ACSL programs with the execution times for the same programs executed on a similar sequential architecture.

A parallel implementation of an off-lattice individual-based model of multicellular populations

NASA Astrophysics Data System (ADS)

Harvey, Daniel G.; Fletcher, Alexander G.; Osborne, James M.; Pitt-Francis, Joe

2015-07-01

As computational models of multicellular populations include ever more detailed descriptions of biophysical and biochemical processes, the computational cost of simulating such models limits their ability to generate novel scientific hypotheses and testable predictions. While developments in microchip technology continue to increase the power of individual processors, parallel computing offers an immediate increase in available processing power. To make full use of parallel computing technology, it is necessary to develop specialised algorithms. To this end, we present a parallel algorithm for a class of off-lattice individual-based models of multicellular populations. The algorithm divides the spatial domain between computing processes and comprises communication routines that ensure the model is correctly simulated on multiple processors. The parallel algorithm is shown to accurately reproduce the results of a deterministic simulation performed using a pre-existing serial implementation. We test the scaling of computation time, memory use and load balancing as more processes are used to simulate a cell population of fixed size. We find approximate linear scaling of both speed-up and memory consumption on up to 32 processor cores. Dynamic load balancing is shown to provide speed-up for non-regular spatial distributions of cells in the case of a growing population.

Spatiotemporal Domain Decomposition for Massive Parallel Computation of Space-Time Kernel Density

NASA Astrophysics Data System (ADS)

Hohl, A.; Delmelle, E. M.; Tang, W.

2015-07-01

Accelerated processing capabilities are deemed critical when conducting analysis on spatiotemporal datasets of increasing size, diversity and availability. High-performance parallel computing offers the capacity to solve computationally demanding problems in a limited timeframe, but likewise poses the challenge of preventing processing inefficiency due to workload imbalance between computing resources. Therefore, when designing new algorithms capable of implementing parallel strategies, careful spatiotemporal domain decomposition is necessary to account for heterogeneity in the data. In this study, we perform octtree-based adaptive decomposition of the spatiotemporal domain for parallel computation of space-time kernel density. In order to avoid edge effects near subdomain boundaries, we establish spatiotemporal buffers to include adjacent data-points that are within the spatial and temporal kernel bandwidths. Then, we quantify computational intensity of each subdomain to balance workloads among processors. We illustrate the benefits of our methodology using a space-time epidemiological dataset of Dengue fever, an infectious vector-borne disease that poses a severe threat to communities in tropical climates. Our parallel implementation of kernel density reaches substantial speedup compared to sequential processing, and achieves high levels of workload balance among processors due to great accuracy in quantifying computational intensity. Our approach is portable of other space-time analytical tests.

Accelerating EPI distortion correction by utilizing a modern GPU-based parallel computation.

PubMed

Yang, Yao-Hao; Huang, Teng-Yi; Wang, Fu-Nien; Chuang, Tzu-Chao; Chen, Nan-Kuei

2013-04-01

The combination of phase demodulation and field mapping is a practical method to correct echo planar imaging (EPI) geometric distortion. However, since phase dispersion accumulates in each phase-encoding step, the calculation complexity of phase modulation is Ny-fold higher than conventional image reconstructions. Thus, correcting EPI images via phase demodulation is generally a time-consuming task. Parallel computing by employing general-purpose calculations on graphics processing units (GPU) can accelerate scientific computing if the algorithm is parallelized. This study proposes a method that incorporates the GPU-based technique into phase demodulation calculations to reduce computation time. The proposed parallel algorithm was applied to a PROPELLER-EPI diffusion tensor data set. The GPU-based phase demodulation method reduced the EPI distortion correctly, and accelerated the computation. The total reconstruction time of the 16-slice PROPELLER-EPI diffusion tensor images with matrix size of 128 × 128 was reduced from 1,754 seconds to 101 seconds by utilizing the parallelized 4-GPU program. GPU computing is a promising method to accelerate EPI geometric correction. The resulting reduction in computation time of phase demodulation should accelerate postprocessing for studies performed with EPI, and should effectuate the PROPELLER-EPI technique for clinical practice. Copyright © 2011 by the American Society of Neuroimaging.

Flowing BIon

NASA Astrophysics Data System (ADS)

Grignani, Gianluca; Harmark, Troels; Kift, Callum; Marini, Andrea; Orselli, Marta

2017-11-01

In this paper we use the effective blackfold description of branes to extend the study of the thermal BIon, a D-brane, and parallel anti-D-brane connected by a wormhole with F-string charge in hot flat space, by introducing a radial boost along the brane. The boosted system behaves qualitatively differently from both the extremal and the thermal BIon considered previously. Interestingly, we are able to formulate a first law of thermodynamics for the system as a whole, despite the fact that it is not a stationary blackfold. In particular, the global temperature is given by the rest frame temperature times the gamma factor of special relativity which is the inverse transformation compared to the case of stationary blackfolds. In addition we define two new kinds of thermodynamic conjugate variables, the energy flux W and the integrated velocity on the brane. We find that a phase transition occurs by varying the energy flux W . Below a critical value of W the brane separation Δ changes only slightly with W . Instead above the critical value Δ grows exponentially.

Compensating the intensity fall-off effect in cone-beam tomography by an empirical weight formula.

PubMed

Chen, Zikuan; Calhoun, Vince D; Chang, Shengjiang

2008-11-10

The Feldkamp-David-Kress (FDK) algorithm is widely adopted for cone-beam reconstruction due to its one-dimensional filtered backprojection structure and parallel implementation. In a reconstruction volume, the conspicuous cone-beam artifact manifests as intensity fall-off along the longitudinal direction (the gantry rotation axis). This effect is inherent to circular cone-beam tomography due to the fact that a cone-beam dataset acquired from circular scanning fails to meet the data sufficiency condition for volume reconstruction. Upon observations of the intensity fall-off phenomenon associated with the FDK reconstruction of a ball phantom, we propose an empirical weight formula to compensate for the fall-off degradation. Specifically, a reciprocal cosine can be used to compensate the voxel values along longitudinal direction during three-dimensional backprojection reconstruction, in particular for boosting the values of voxels at positions with large cone angles. The intensity degradation within the z plane, albeit insignificant, can also be compensated by using the same weight formula through a parameter for radial distance dependence. Computer simulations and phantom experiments are presented to demonstrate the compensation effectiveness of the fall-off effect inherent in circular cone-beam tomography.

MITHRA 1.0: A full-wave simulation tool for free electron lasers

NASA Astrophysics Data System (ADS)

Fallahi, Arya; Yahaghi, Alireza; Kärtner, Franz X.

2018-07-01

Free Electron Lasers (FELs) are a solution for providing intense, coherent and bright radiation in the hard X-ray regime. Due to the low wall-plug efficiency of FEL facilities, it is crucial and additionally very useful to develop complete and accurate simulation tools for better optimizing a FEL interaction. The highly sophisticated dynamics involved in a FEL process was the main obstacle hindering the development of general simulation tools for this problem. We present a numerical algorithm based on finite difference time domain/Particle in cell (FDTD/PIC) in a Lorentz boosted coordinate system which is able to fulfill a full-wave simulation of a FEL process. The developed software offers a suitable tool for the analysis of FEL interactions without considering any of the usual approximations. A coordinate transformation to bunch rest frame makes the very different length scales of bunch size, optical wavelengths and the undulator period transform to values with the same order. Consequently, FDTD/PIC simulations in conjunction with efficient parallelization techniques make the full-wave simulation feasible using the available computational resources. Several examples of free electron lasers are analyzed using the developed software, the results are benchmarked based on standard FEL codes and discussed in detail.

Super and parallel computers and their impact on civil engineering

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

Kamat, M.P.

1986-01-01

This book presents the papers given at a conference on the use of supercomputers in civil engineering. Topics considered at the conference included solving nonlinear equations on a hypercube, a custom architectured parallel processing system, distributed data processing, algorithms, computer architecture, parallel processing, vector processing, computerized simulation, and cost benefit analysis.

Xyce

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

Thomquist, Heidi K.; Fixel, Deborah A.; Fett, David Brian

The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.

Symmetry boost of the fidelity of Shor factoring

NASA Astrophysics Data System (ADS)

Nam, Y. S.; Blümel, R.

2018-05-01

In Shor's algorithm quantum subroutines occur with the structure F U F-1 , where F is a unitary transform and U is performing a quantum computation. Examples are quantum adders and subunits of quantum modulo adders. In this paper we show, both analytically and numerically, that if, in analogy to spin echoes, F and F-1 can be implemented symmetrically when executing Shor's algorithm on actual, imperfect quantum hardware, such that F and F-1 have the same hardware errors, a symmetry boost in the fidelity of the combined F U F-1 quantum operation results when compared to the case in which the errors in F and F-1 are independently random. Running the complete gate-by-gate implemented Shor algorithm, we show that the symmetry-induced fidelity boost can be as large as a factor 4. While most of our analytical and numerical results concern the case of over- and under-rotation of controlled rotation gates, in the numerically accessible case of Shor's algorithm with a small number of qubits, we show explicitly that the symmetry boost is robust with respect to more general types of errors. While, expectedly, additional error types reduce the symmetry boost, we show explicitly, by implementing general off-diagonal SU (N ) errors (N =2 ,4 ,8 ), that the boost factor scales like a Lorentzian in δ /σ , where σ and δ are the error strengths of the diagonal over- and underrotation errors and the off-diagonal SU (N ) errors, respectively. The Lorentzian shape also shows that, while the boost factor may become small with increasing δ , it declines slowly (essentially like a power law) and is never completely erased. We also investigate the effect of diagonal nonunitary errors, which, in analogy to unitary errors, reduce but never erase the symmetry boost. Going beyond the case of small quantum processors, we present analytical scaling results that show that the symmetry boost persists in the practically interesting case of a large number of qubits. We illustrate this result explicitly for the case of Shor factoring of the semiprime RSA-1024, where, analytically, focusing on over- and underrotation errors, we obtain a boost factor of about 10. In addition, we provide a proof of the fidelity product formula, including its range of applicability.

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning

PubMed Central

Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation. PMID:26681933

Tutorial: Parallel Computing of Simulation Models for Risk Analysis.

PubMed

Reilly, Allison C; Staid, Andrea; Gao, Michael; Guikema, Seth D

2016-10-01

Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time-sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation-based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix. © 2016 Society for Risk Analysis.

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning.

PubMed

Liu, Yang; Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.

A parallel algorithm for the two-dimensional time fractional diffusion equation with implicit difference method.

PubMed

Gong, Chunye; Bao, Weimin; Tang, Guojian; Jiang, Yuewen; Liu, Jie

2014-01-01

It is very time consuming to solve fractional differential equations. The computational complexity of two-dimensional fractional differential equation (2D-TFDE) with iterative implicit finite difference method is O(M(x)M(y)N(2)). In this paper, we present a parallel algorithm for 2D-TFDE and give an in-depth discussion about this algorithm. A task distribution model and data layout with virtual boundary are designed for this parallel algorithm. The experimental results show that the parallel algorithm compares well with the exact solution. The parallel algorithm on single Intel Xeon X5540 CPU runs 3.16-4.17 times faster than the serial algorithm on single CPU core. The parallel efficiency of 81 processes is up to 88.24% compared with 9 processes on a distributed memory cluster system. We do think that the parallel computing technology will become a very basic method for the computational intensive fractional applications in the near future.

Performance Characteristics of the Multi-Zone NAS Parallel Benchmarks

NASA Technical Reports Server (NTRS)

Jin, Haoqiang; VanderWijngaart, Rob F.

2003-01-01

We describe a new suite of computational benchmarks that models applications featuring multiple levels of parallelism. Such parallelism is often available in realistic flow computations on systems of grids, but had not previously been captured in bench-marks. The new suite, named NPB Multi-Zone, is extended from the NAS Parallel Benchmarks suite, and involves solving the application benchmarks LU, BT and SP on collections of loosely coupled discretization meshes. The solutions on the meshes are updated independently, but after each time step they exchange boundary value information. This strategy provides relatively easily exploitable coarse-grain parallelism between meshes. Three reference implementations are available: one serial, one hybrid using the Message Passing Interface (MPI) and OpenMP, and another hybrid using a shared memory multi-level programming model (SMP+OpenMP). We examine the effectiveness of hybrid parallelization paradigms in these implementations on three different parallel computers. We also use an empirical formula to investigate the performance characteristics of the multi-zone benchmarks.

Methods for design and evaluation of parallel computating systems (The PISCES project)

NASA Technical Reports Server (NTRS)

Pratt, Terrence W.; Wise, Robert; Haught, Mary JO

1989-01-01

The PISCES project started in 1984 under the sponsorship of the NASA Computational Structural Mechanics (CSM) program. A PISCES 1 programming environment and parallel FORTRAN were implemented in 1984 for the DEC VAX (using UNIX processes to simulate parallel processes). This system was used for experimentation with parallel programs for scientific applications and AI (dynamic scene analysis) applications. PISCES 1 was ported to a network of Apollo workstations by N. Fitzgerald.

A new parallel-vector finite element analysis software on distributed-memory computers

NASA Technical Reports Server (NTRS)

Qin, Jiangning; Nguyen, Duc T.

1993-01-01

A new parallel-vector finite element analysis software package MPFEA (Massively Parallel-vector Finite Element Analysis) is developed for large-scale structural analysis on massively parallel computers with distributed-memory. MPFEA is designed for parallel generation and assembly of the global finite element stiffness matrices as well as parallel solution of the simultaneous linear equations, since these are often the major time-consuming parts of a finite element analysis. Block-skyline storage scheme along with vector-unrolling techniques are used to enhance the vector performance. Communications among processors are carried out concurrently with arithmetic operations to reduce the total execution time. Numerical results on the Intel iPSC/860 computers (such as the Intel Gamma with 128 processors and the Intel Touchstone Delta with 512 processors) are presented, including an aircraft structure and some very large truss structures, to demonstrate the efficiency and accuracy of MPFEA.

Solving very large, sparse linear systems on mesh-connected parallel computers

NASA Technical Reports Server (NTRS)

Opsahl, Torstein; Reif, John

1987-01-01

The implementation of Pan and Reif's Parallel Nested Dissection (PND) algorithm on mesh connected parallel computers is described. This is the first known algorithm that allows very large, sparse linear systems of equations to be solved efficiently in polylog time using a small number of processors. How the processor bound of PND can be matched to the number of processors available on a given parallel computer by slowing down the algorithm by constant factors is described. Also, for the important class of problems where G(A) is a grid graph, a unique memory mapping that reduces the inter-processor communication requirements of PND to those that can be executed on mesh connected parallel machines is detailed. A description of an implementation on the Goodyear Massively Parallel Processor (MPP), located at Goddard is given. Also, a detailed discussion of data mappings and performance issues is given.

High order parallel numerical schemes for solving incompressible flows

NASA Technical Reports Server (NTRS)

Lin, Avi; Milner, Edward J.; Liou, May-Fun; Belch, Richard A.

1992-01-01

The use of parallel computers for numerically solving flow fields has gained much importance in recent years. This paper introduces a new high order numerical scheme for computational fluid dynamics (CFD) specifically designed for parallel computational environments. A distributed MIMD system gives the flexibility of treating different elements of the governing equations with totally different numerical schemes in different regions of the flow field. The parallel decomposition of the governing operator to be solved is the primary parallel split. The primary parallel split was studied using a hypercube like architecture having clusters of shared memory processors at each node. The approach is demonstrated using examples of simple steady state incompressible flows. Future studies should investigate the secondary split because, depending on the numerical scheme that each of the processors applies and the nature of the flow in the specific subdomain, it may be possible for a processor to seek better, or higher order, schemes for its particular subcase.

Parallelization of the FLAPW method

NASA Astrophysics Data System (ADS)

Canning, A.; Mannstadt, W.; Freeman, A. J.

2000-08-01

The FLAPW (full-potential linearized-augmented plane-wave) method is one of the most accurate first-principles methods for determining structural, electronic and magnetic properties of crystals and surfaces. Until the present work, the FLAPW method has been limited to systems of less than about a hundred atoms due to the lack of an efficient parallel implementation to exploit the power and memory of parallel computers. In this work, we present an efficient parallelization of the method by division among the processors of the plane-wave components for each state. The code is also optimized for RISC (reduced instruction set computer) architectures, such as those found on most parallel computers, making full use of BLAS (basic linear algebra subprograms) wherever possible. Scaling results are presented for systems of up to 686 silicon atoms and 343 palladium atoms per unit cell, running on up to 512 processors on a CRAY T3E parallel supercomputer.

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.

Partitioning problems in parallel, pipelined and distributed computing

NASA Technical Reports Server (NTRS)

Bokhari, S.

1985-01-01

The problem of optimally assigning the modules of a parallel program over the processors of a multiple computer system is addressed. A Sum-Bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple satellite system: partitioning multiple chain structured parallel programs, multiple arbitrarily structured serial programs and single tree structured parallel programs. In addition, the problems of partitioning chain structured parallel programs across chain connected systems and across shared memory (or shared bus) systems are also solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple computer architectures for a wide range of problems of practical interest.

Parallel Directionally Split Solver Based on Reformulation of Pipelined Thomas Algorithm

NASA Technical Reports Server (NTRS)

Povitsky, A.

1998-01-01

In this research an efficient parallel algorithm for 3-D directionally split problems is developed. The proposed algorithm is based on a reformulated version of the pipelined Thomas algorithm that starts the backward step computations immediately after the completion of the forward step computations for the first portion of lines This algorithm has data available for other computational tasks while processors are idle from the Thomas algorithm. The proposed 3-D directionally split solver is based on the static scheduling of processors where local and non-local, data-dependent and data-independent computations are scheduled while processors are idle. A theoretical model of parallelization efficiency is used to define optimal parameters of the algorithm, to show an asymptotic parallelization penalty and to obtain an optimal cover of a global domain with subdomains. It is shown by computational experiments and by the theoretical model that the proposed algorithm reduces the parallelization penalty about two times over the basic algorithm for the range of the number of processors (subdomains) considered and the number of grid nodes per subdomain.

Parallel Algorithms and Patterns

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

Robey, Robert W.

2016-06-16

This is a powerpoint presentation on parallel algorithms and patterns. A parallel algorithm is a well-defined, step-by-step computational procedure that emphasizes concurrency to solve a problem. Examples of problems include: Sorting, searching, optimization, matrix operations. A parallel pattern is a computational step in a sequence of independent, potentially concurrent operations that occurs in diverse scenarios with some frequency. Examples are: Reductions, prefix scans, ghost cell updates. We only touch on parallel patterns in this presentation. It really deserves its own detailed discussion which Gabe Rockefeller would like to develop.

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

NASA Technical Reports Server (NTRS)

Sues, R. H.; Lua, Y. J.; Smith, M. D.

1994-01-01

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations.

Beyond input-output computings: error-driven emergence with parallel non-distributed slime mold computer.

PubMed

Aono, Masashi; Gunji, Yukio-Pegio

2003-10-01

The emergence derived from errors is the key importance for both novel computing and novel usage of the computer. In this paper, we propose an implementable experimental plan for the biological computing so as to elicit the emergent property of complex systems. An individual plasmodium of the true slime mold Physarum polycephalum acts in the slime mold computer. Modifying the Elementary Cellular Automaton as it entails the global synchronization problem upon the parallel computing provides the NP-complete problem solved by the slime mold computer. The possibility to solve the problem by giving neither all possible results nor explicit prescription of solution-seeking is discussed. In slime mold computing, the distributivity in the local computing logic can change dynamically, and its parallel non-distributed computing cannot be reduced into the spatial addition of multiple serial computings. The computing system based on exhaustive absence of the super-system may produce, something more than filling the vacancy.

Reconstruction for time-domain in vivo EPR 3D multigradient oximetric imaging--a parallel processing perspective.

PubMed

Dharmaraj, Christopher D; Thadikonda, Kishan; Fletcher, Anthony R; Doan, Phuc N; Devasahayam, Nallathamby; Matsumoto, Shingo; Johnson, Calvin A; Cook, John A; Mitchell, James B; Subramanian, Sankaran; Krishna, Murali C

2009-01-01

Three-dimensional Oximetric Electron Paramagnetic Resonance Imaging using the Single Point Imaging modality generates unpaired spin density and oxygen images that can readily distinguish between normal and tumor tissues in small animals. It is also possible with fast imaging to track the changes in tissue oxygenation in response to the oxygen content in the breathing air. However, this involves dealing with gigabytes of data for each 3D oximetric imaging experiment involving digital band pass filtering and background noise subtraction, followed by 3D Fourier reconstruction. This process is rather slow in a conventional uniprocessor system. This paper presents a parallelization framework using OpenMP runtime support and parallel MATLAB to execute such computationally intensive programs. The Intel compiler is used to develop a parallel C++ code based on OpenMP. The code is executed on four Dual-Core AMD Opteron shared memory processors, to reduce the computational burden of the filtration task significantly. The results show that the parallel code for filtration has achieved a speed up factor of 46.66 as against the equivalent serial MATLAB code. In addition, a parallel MATLAB code has been developed to perform 3D Fourier reconstruction. Speedup factors of 4.57 and 4.25 have been achieved during the reconstruction process and oximetry computation, for a data set with 23 x 23 x 23 gradient steps. The execution time has been computed for both the serial and parallel implementations using different dimensions of the data and presented for comparison. The reported system has been designed to be easily accessible even from low-cost personal computers through local internet (NIHnet). The experimental results demonstrate that the parallel computing provides a source of high computational power to obtain biophysical parameters from 3D EPR oximetric imaging, almost in real-time.

Comparison of converter topologies for charging capacitors used in pulsed load applications

NASA Technical Reports Server (NTRS)

Nelms, R. M.; Schatz, J. E.; Pollard, Barry

1991-01-01

The authors present a qualitative comparison of different power converter topologies which may be utilized for charging capacitors in pulsed power applications requiring voltages greater than 1 kV. The operation of the converters in capacitor charging applications is described, and relevant advantages are presented. All of the converters except one may be classified in the high-frequency switching category. One of the benefits from high-frequency operation is a reduction in size and weight. The other converter discussed is a member of the command resonant changing category. The authors first describe a boost circuit which functions as a command resonant charging circuit and utilizes a single pulse of current to charge the capacitor. The discussion of high-frequency converters begins with the flyback and Ward converters. Then, the series, parallel, and series/parallel resonant converters are examined.

Access and visualization using clusters and other parallel computers

NASA Technical Reports Server (NTRS)

Katz, Daniel S.; Bergou, Attila; Berriman, Bruce; Block, Gary; Collier, Jim; Curkendall, Dave; Good, John; Husman, Laura; Jacob, Joe; Laity, Anastasia;

CMOS VLSI Layout and Verification of a SIMD Computer

NASA Technical Reports Server (NTRS)

Zheng, Jianqing

1996-01-01

A CMOS VLSI layout and verification of a 3 x 3 processor parallel computer has been completed. The layout was done using the MAGIC tool and the verification using HSPICE. Suggestions for expanding the computer into a million processor network are presented. Many problems that might be encountered when implementing a massively parallel computer are discussed.

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.

Optimistic barrier synchronization

NASA Technical Reports Server (NTRS)

Nicol, David M.

1992-01-01

Barrier synchronization is fundamental operation in parallel computation. In many contexts, at the point a processor enters a barrier it knows that it has already processed all the work required of it prior to synchronization. The alternative case, when a processor cannot enter a barrier with the assurance that it has already performed all the necessary pre-synchronization computation, is treated. The problem arises when the number of pre-sychronization messages to be received by a processor is unkown, for example, in a parallel discrete simulation or any other computation that is largely driven by an unpredictable exchange of messages. We describe an optimistic O(log sup 2 P) barrier algorithm for such problems, study its performance on a large-scale parallel system, and consider extensions to general associative reductions as well as associative parallel prefix computations.

Parallel grid generation algorithm for distributed memory computers

NASA Technical Reports Server (NTRS)

Moitra, Stuti; Moitra, Anutosh

1994-01-01

A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.

Efficient computation of hashes

NASA Astrophysics Data System (ADS)

Lopes, Raul H. C.; Franqueira, Virginia N. L.; Hobson, Peter R.

2014-06-01

The sequential computation of hashes at the core of many distributed storage systems and found, for example, in grid services can hinder efficiency in service quality and even pose security challenges that can only be addressed by the use of parallel hash tree modes. The main contributions of this paper are, first, the identification of several efficiency and security challenges posed by the use of sequential hash computation based on the Merkle-Damgard engine. In addition, alternatives for the parallel computation of hash trees are discussed, and a prototype for a new parallel implementation of the Keccak function, the SHA-3 winner, is introduced.

Methods for operating parallel computing systems employing sequenced communications

DOEpatents

Benner, R.E.; Gustafson, J.L.; Montry, G.R.

1999-08-10

A parallel computing system and method are disclosed having improved performance where a program is concurrently run on a plurality of nodes for reducing total processing time, each node having a processor, a memory, and a predetermined number of communication channels connected to the node and independently connected directly to other nodes. The present invention improves performance of the parallel computing system by providing a system which can provide efficient communication between the processors and between the system and input and output devices. A method is also disclosed which can locate defective nodes with the computing system. 15 figs.

Methods for operating parallel computing systems employing sequenced communications

DOEpatents

Benner, Robert E.; Gustafson, John L.; Montry, Gary R.

1999-01-01

A parallel computing system and method having improved performance where a program is concurrently run on a plurality of nodes for reducing total processing time, each node having a processor, a memory, and a predetermined number of communication channels connected to the node and independently connected directly to other nodes. The present invention improves performance of performance of the parallel computing system by providing a system which can provide efficient communication between the processors and between the system and input and output devices. A method is also disclosed which can locate defective nodes with the computing system.

Managing internode data communications for an uninitialized process in a parallel computer

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

Archer, Charles J; Blocksome, Michael A; Miller, Douglas R

2014-05-20

A parallel computer includes nodes, each having main memory and a messaging unit (MU). Each MU includes computer memory, which in turn includes, MU message buffers. Each MU message buffer is associated with an uninitialized process on the compute node. In the parallel computer, managing internode data communications for an uninitialized process includes: receiving, by an MU of a compute node, one or more data communications messages in an MU message buffer associated with an uninitialized process on the compute node; determining, by an application agent, that the MU message buffer associated with the uninitialized process is full prior tomore » initialization of the uninitialized process; establishing, by the application agent, a temporary message buffer for the uninitialized process in main computer memory; and moving, by the application agent, data communications messages from the MU message buffer associated with the uninitialized process to the temporary message buffer in main computer memory.« less

Managing internode data communications for an uninitialized process in a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Miller, Douglas R; Parker, Jeffrey J; Ratterman, Joseph D; Smith, Brian E

2014-05-20

A parallel computer includes nodes, each having main memory and a messaging unit (MU). Each MU includes computer memory, which in turn includes, MU message buffers. Each MU message buffer is associated with an uninitialized process on the compute node. In the parallel computer, managing internode data communications for an uninitialized process includes: receiving, by an MU of a compute node, one or more data communications messages in an MU message buffer associated with an uninitialized process on the compute node; determining, by an application agent, that the MU message buffer associated with the uninitialized process is full prior to initialization of the uninitialized process; establishing, by the application agent, a temporary message buffer for the uninitialized process in main computer memory; and moving, by the application agent, data communications messages from the MU message buffer associated with the uninitialized process to the temporary message buffer in main computer memory.

Effects of injection parameters, boost, and swirl ratio on gasoline compression ignition operation at idle and low-load conditions

DOE PAGES

Kodavasal, Janardhan; Kolodziej, Christopher P.; Ciatti, Stephen A.; ...

2016-11-03

In this study, we study the effects of injector nozzle inclusion angle, injection pressure, boost, and swirl ratio on gasoline compression ignition combustion. Closed-cycle computational fluid dynamics simulations using a 1/7th sector mesh representing a single cylinder of a four-cylinder 1.9 L diesel engine, operated in gasoline compression ignition mode with 87 anti-knock index (AKI) gasoline, were performed. Two different operating conditions were studied—the first is representative of idle operation (4 mg fuel/cylinder/cycle, 850 r/min), and the second is representative of a low-load condition (10 mg fuel/cylinder/cycle, 1500 r/min). The mixture preparation and reaction space from the simulations were analyzedmore » to gain insights into the effects of injection pressure, nozzle inclusion angle, boost, and swirl ratio on achieving stable low-load to idle gasoline compression ignition operation. It was found that narrower nozzle inclusion angles allow for more reactivity or propensity to ignition (determined qualitatively by computing constant volume ignition delays) and are suitable over a wider range of injection timings. Under idle conditions, it was found that lower injection pressures helped to reduce overmixing of the fuel, resulting in greater reactivity and ignitability (ease with which ignition can be achieved) of the gasoline. However, under the low-load condition, lower injection pressures did not increase ignitability, and it is hypothesized that this is because of reduced chemical residence time resulting from longer injection durations. Reduced swirl was found to maintain higher in-cylinder temperatures through compression, resulting in better ignitability. It was found that boosting the charge also helped to increase reactivity and advanced ignition timing.« less

Effects of injection parameters, boost, and swirl ratio on gasoline compression ignition operation at idle and low-load conditions

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

Kodavasal, Janardhan; Kolodziej, Christopher P.; Ciatti, Stephen A.

In this study, we study the effects of injector nozzle inclusion angle, injection pressure, boost, and swirl ratio on gasoline compression ignition combustion. Closed-cycle computational fluid dynamics simulations using a 1/7th sector mesh representing a single cylinder of a four-cylinder 1.9 L diesel engine, operated in gasoline compression ignition mode with 87 anti-knock index (AKI) gasoline, were performed. Two different operating conditions were studied—the first is representative of idle operation (4 mg fuel/cylinder/cycle, 850 r/min), and the second is representative of a low-load condition (10 mg fuel/cylinder/cycle, 1500 r/min). The mixture preparation and reaction space from the simulations were analyzedmore » to gain insights into the effects of injection pressure, nozzle inclusion angle, boost, and swirl ratio on achieving stable low-load to idle gasoline compression ignition operation. It was found that narrower nozzle inclusion angles allow for more reactivity or propensity to ignition (determined qualitatively by computing constant volume ignition delays) and are suitable over a wider range of injection timings. Under idle conditions, it was found that lower injection pressures helped to reduce overmixing of the fuel, resulting in greater reactivity and ignitability (ease with which ignition can be achieved) of the gasoline. However, under the low-load condition, lower injection pressures did not increase ignitability, and it is hypothesized that this is because of reduced chemical residence time resulting from longer injection durations. Reduced swirl was found to maintain higher in-cylinder temperatures through compression, resulting in better ignitability. It was found that boosting the charge also helped to increase reactivity and advanced ignition timing.« less

Implementing and analyzing the multi-threaded LP-inference

NASA Astrophysics Data System (ADS)

Bolotova, S. Yu; Trofimenko, E. V.; Leschinskaya, M. V.

2018-03-01

The logical production equations provide new possibilities for the backward inference optimization in intelligent production-type systems. The strategy of a relevant backward inference is aimed at minimization of a number of queries to external information source (either to a database or an interactive user). The idea of the method is based on the computing of initial preimages set and searching for the true preimage. The execution of each stage can be organized independently and in parallel and the actual work at a given stage can also be distributed between parallel computers. This paper is devoted to the parallel algorithms of the relevant inference based on the advanced scheme of the parallel computations “pipeline” which allows to increase the degree of parallelism. The author also provides some details of the LP-structures implementation.

A Parallel Processing Algorithm for Remote Sensing Classification

NASA Technical Reports Server (NTRS)

Gualtieri, J. Anthony

2005-01-01

A current thread in parallel computation is the use of cluster computers created by networking a few to thousands of commodity general-purpose workstation-level commuters using the Linux operating system. For example on the Medusa cluster at NASA/GSFC, this provides for super computing performance, 130 G(sub flops) (Linpack Benchmark) at moderate cost, $370K. However, to be useful for scientific computing in the area of Earth science, issues of ease of programming, access to existing scientific libraries, and portability of existing code need to be considered. In this paper, I address these issues in the context of tools for rendering earth science remote sensing data into useful products. In particular, I focus on a problem that can be decomposed into a set of independent tasks, which on a serial computer would be performed sequentially, but with a cluster computer can be performed in parallel, giving an obvious speedup. To make the ideas concrete, I consider the problem of classifying hyperspectral imagery where some ground truth is available to train the classifier. In particular I will use the Support Vector Machine (SVM) approach as applied to hyperspectral imagery. The approach will be to introduce notions about parallel computation and then to restrict the development to the SVM problem. Pseudocode (an outline of the computation) will be described and then details specific to the implementation will be given. Then timing results will be reported to show what speedups are possible using parallel computation. The paper will close with a discussion of the results.

PISCES: An environment for parallel scientific computation

NASA Technical Reports Server (NTRS)

Pratt, T. W.

1985-01-01

The parallel implementation of scientific computing environment (PISCES) is a project to provide high-level programming environments for parallel MIMD computers. Pisces 1, the first of these environments, is a FORTRAN 77 based environment which runs under the UNIX operating system. The Pisces 1 user programs in Pisces FORTRAN, an extension of FORTRAN 77 for parallel processing. The major emphasis in the Pisces 1 design is in providing a carefully specified virtual machine that defines the run-time environment within which Pisces FORTRAN programs are executed. Each implementation then provides the same virtual machine, regardless of differences in the underlying architecture. The design is intended to be portable to a variety of architectures. Currently Pisces 1 is implemented on a network of Apollo workstations and on a DEC VAX uniprocessor via simulation of the task level parallelism. An implementation for the Flexible Computing Corp. FLEX/32 is under construction. An introduction to the Pisces 1 virtual computer and the FORTRAN 77 extensions is presented. An example of an algorithm for the iterative solution of a system of equations is given. The most notable features of the design are the provision for several granularities of parallelism in programs and the provision of a window mechanism for distributed access to large arrays of data.

Parallel Preconditioning for CFD Problems on the CM-5

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Kremenetsky, Mark D.; Richardson, John; Lasinski, T. A. (Technical Monitor)

1994-01-01

Up to today, preconditioning methods on massively parallel systems have faced a major difficulty. The most successful preconditioning methods in terms of accelerating the convergence of the iterative solver such as incomplete LU factorizations are notoriously difficult to implement on parallel machines for two reasons: (1) the actual computation of the preconditioner is not very floating-point intensive, but requires a large amount of unstructured communication, and (2) the application of the preconditioning matrix in the iteration phase (i.e. triangular solves) are difficult to parallelize because of the recursive nature of the computation. Here we present a new approach to preconditioning for very large, sparse, unsymmetric, linear systems, which avoids both difficulties. We explicitly compute an approximate inverse to our original matrix. This new preconditioning matrix can be applied most efficiently for iterative methods on massively parallel machines, since the preconditioning phase involves only a matrix-vector multiplication, with possibly a dense matrix. Furthermore the actual computation of the preconditioning matrix has natural parallelism. For a problem of size n, the preconditioning matrix can be computed by solving n independent small least squares problems. The algorithm and its implementation on the Connection Machine CM-5 are discussed in detail and supported by extensive timings obtained from real problem data.

Applications of Parallel Process HiMAP for Large Scale Multidisciplinary Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Potsdam, Mark; Rodriguez, David; Kwak, Dochay (Technical Monitor)

2000-01-01

HiMAP is a three level parallel middleware that can be interfaced to a large scale global design environment for code independent, multidisciplinary analysis using high fidelity equations. Aerospace technology needs are rapidly changing. Computational tools compatible with the requirements of national programs such as space transportation are needed. Conventional computation tools are inadequate for modern aerospace design needs. Advanced, modular computational tools are needed, such as those that incorporate the technology of massively parallel processors (MPP).

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Byun, Chansup; Kwak, Dochan (Technical Monitor)

2001-01-01

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Parallel algorithms for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Amin-Javaheri, Masoud; Orin, David E.

1989-01-01

The development of an O(log2N) parallel algorithm for the manipulator inertia matrix is presented. It is based on the most efficient serial algorithm which uses the composite rigid body method. Recursive doubling is used to reformulate the linear recurrence equations which are required to compute the diagonal elements of the matrix. It results in O(log2N) levels of computation. Computation of the off-diagonal elements involves N linear recurrences of varying-size and a new method, which avoids redundant computation of position and orientation transforms for the manipulator, is developed. The O(log2N) algorithm is presented in both equation and graphic forms which clearly show the parallelism inherent in the algorithm.

Manyscale Computing for Sensor Processing in Support of Space Situational Awareness

NASA Astrophysics Data System (ADS)

Schmalz, M.; Chapman, W.; Hayden, E.; Sahni, S.; Ranka, S.

2014-09-01

Increasing image and signal data burden associated with sensor data processing in support of space situational awareness implies continuing computational throughput growth beyond the petascale regime. In addition to growing applications data burden and diversity, the breadth, diversity and scalability of high performance computing architectures and their various organizations challenge the development of a single, unifying, practicable model of parallel computation. Therefore, models for scalable parallel processing have exploited architectural and structural idiosyncrasies, yielding potential misapplications when legacy programs are ported among such architectures. In response to this challenge, we have developed a concise, efficient computational paradigm and software called Manyscale Computing to facilitate efficient mapping of annotated application codes to heterogeneous parallel architectures. Our theory, algorithms, software, and experimental results support partitioning and scheduling of application codes for envisioned parallel architectures, in terms of work atoms that are mapped (for example) to threads or thread blocks on computational hardware. Because of the rigor, completeness, conciseness, and layered design of our manyscale approach, application-to-architecture mapping is feasible and scalable for architectures at petascales, exascales, and above. Further, our methodology is simple, relying primarily on a small set of primitive mapping operations and support routines that are readily implemented on modern parallel processors such as graphics processing units (GPUs) and hybrid multi-processors (HMPs). In this paper, we overview the opportunities and challenges of manyscale computing for image and signal processing in support of space situational awareness applications. We discuss applications in terms of a layered hardware architecture (laboratory > supercomputer > rack > processor > component hierarchy). Demonstration applications include performance analysis and results in terms of execution time as well as storage, power, and energy consumption for bus-connected and/or networked architectures. The feasibility of the manyscale paradigm is demonstrated by addressing four principal challenges: (1) architectural/structural diversity, parallelism, and locality, (2) masking of I/O and memory latencies, (3) scalability of design as well as implementation, and (4) efficient representation/expression of parallel applications. Examples will demonstrate how manyscale computing helps solve these challenges efficiently on real-world computing systems.

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

Demeure, I.M.

The research presented here is concerned with representation techniques and tools to support the design, prototyping, simulation, and evaluation of message-based parallel, distributed computations. The author describes ParaDiGM-Parallel, Distributed computation Graph Model-a visual representation technique for parallel, message-based distributed computations. ParaDiGM provides several views of a computation depending on the aspect of concern. It is made of two complementary submodels, the DCPG-Distributed Computing Precedence Graph-model, and the PAM-Process Architecture Model-model. DCPGs are precedence graphs used to express the functionality of a computation in terms of tasks, message-passing, and data. PAM graphs are used to represent the partitioning of a computationmore » into schedulable units or processes, and the pattern of communication among those units. There is a natural mapping between the two models. He illustrates the utility of ParaDiGM as a representation technique by applying it to various computations (e.g., an adaptive global optimization algorithm, the client-server model). ParaDiGM representations are concise. They can be used in documenting the design and the implementation of parallel, distributed computations, in describing such computations to colleagues, and in comparing and contrasting various implementations of the same computation. He then describes VISA-VISual Assistant, a software tool to support the design, prototyping, and simulation of message-based parallel, distributed computations. VISA is based on the ParaDiGM model. In particular, it supports the editing of ParaDiGM graphs to describe the computations of interest, and the animation of these graphs to provide visual feedback during simulations. The graphs are supplemented with various attributes, simulation parameters, and interpretations which are procedures that can be executed by VISA.« less

Scan line graphics generation on the massively parallel processor

NASA Technical Reports Server (NTRS)

Dorband, John E.

1988-01-01

Described here is how researchers implemented a scan line graphics generation algorithm on the Massively Parallel Processor (MPP). Pixels are computed in parallel and their results are applied to the Z buffer in large groups. To perform pixel value calculations, facilitate load balancing across the processors and apply the results to the Z buffer efficiently in parallel requires special virtual routing (sort computation) techniques developed by the author especially for use on single-instruction multiple-data (SIMD) architectures.

The paradigm compiler: Mapping a functional language for the connection machine

NASA Technical Reports Server (NTRS)

Dennis, Jack B.

1989-01-01

The Paradigm Compiler implements a new approach to compiling programs written in high level languages for execution on highly parallel computers. The general approach is to identify the principal data structures constructed by the program and to map these structures onto the processing elements of the target machine. The mapping is chosen to maximize performance as determined through compile time global analysis of the source program. The source language is Sisal, a functional language designed for scientific computations, and the target language is Paris, the published low level interface to the Connection Machine. The data structures considered are multidimensional arrays whose dimensions are known at compile time. Computations that build such arrays usually offer opportunities for highly parallel execution; they are data parallel. The Connection Machine is an attractive target for these computations, and the parallel for construct of the Sisal language is a convenient high level notation for data parallel algorithms. The principles and organization of the Paradigm Compiler are discussed.

Parallel computing in genomic research: advances and applications

PubMed Central

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today’s genomic experiments have to process the so-called “biological big data” that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. PMID:26604801

Parallel computing in genomic research: advances and applications.

PubMed

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system

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

Fijany, A.; Milman, M.; Redding, D.

1994-12-31

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less

Automated Generation of Message-Passing Programs: An Evaluation Using CAPTools

NASA Technical Reports Server (NTRS)

Hribar, Michelle R.; Jin, Haoqiang; Yan, Jerry C.; Saini, Subhash (Technical Monitor)

1998-01-01

Scientists at NASA Ames Research Center have been developing computational aeroscience applications on highly parallel architectures over the past ten years. During that same time period, a steady transition of hardware and system software also occurred, forcing us to expend great efforts into migrating and re-coding our applications. As applications and machine architectures become increasingly complex, the cost and time required for this process will become prohibitive. In this paper, we present the first set of results in our evaluation of interactive parallelization tools. In particular, we evaluate CAPTool's ability to parallelize computational aeroscience applications. CAPTools was tested on serial versions of the NAS Parallel Benchmarks and ARC3D, a computational fluid dynamics application, on two platforms: the SGI Origin 2000 and the Cray T3E. This evaluation includes performance, amount of user interaction required, limitations and portability. Based on these results, a discussion on the feasibility of computer aided parallelization of aerospace applications is presented along with suggestions for future work.

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

A new kind of low-inductance transformer type magnetic switch (TTMS) with coaxial cylindrical conductors

NASA Astrophysics Data System (ADS)

Zhang, Yu; Liu, Jinliang

2013-02-01

As important devices for voltage boosting and switching, respectively, pulse transformer and magnetic switch are widely used in pulsed power technology. In this paper, a new kind of transformer type magnetic switch (TTMS) with coaxial cylindrical conductors is put forward to combine the functions of voltage boosting and switching in one power device. As a compact combination device of discrete pulse transformer and magnetic switch, the compact TTMS decreases the required volume of magnetic cores in a large scale. The primary windings of the TTMS have a parallel combination structure so that the TTMS which only has 3 turns of secondary windings has a step-up ratio at 1:9. Before the magnetic core saturates, the TTMS has low unsaturated inductances of windings and good pulse response characteristics, so it can be used to substitute the Marx generator to charge the pulse forming line (PFL) at the ranges of several hundred kV and several hundred ns. After the core saturates, the cylindrical conductors can decrease the saturated inductance of the secondary windings of TTMS to a level less than 400 nH. As a result, the proposed TTMS can be used as the boosting transformer and main switch of helical Blumlein PFL to form the quasi-square voltage pulse on the 160 Ω load with a short pulse rise time only at 60 ns.

A new kind of low-inductance transformer type magnetic switch (TTMS) with coaxial cylindrical conductors.

PubMed

Zhang, Yu; Liu, Jinliang

2013-02-01

As important devices for voltage boosting and switching, respectively, pulse transformer and magnetic switch are widely used in pulsed power technology. In this paper, a new kind of transformer type magnetic switch (TTMS) with coaxial cylindrical conductors is put forward to combine the functions of voltage boosting and switching in one power device. As a compact combination device of discrete pulse transformer and magnetic switch, the compact TTMS decreases the required volume of magnetic cores in a large scale. The primary windings of the TTMS have a parallel combination structure so that the TTMS which only has 3 turns of secondary windings has a step-up ratio at 1:9. Before the magnetic core saturates, the TTMS has low unsaturated inductances of windings and good pulse response characteristics, so it can be used to substitute the Marx generator to charge the pulse forming line (PFL) at the ranges of several hundred kV and several hundred ns. After the core saturates, the cylindrical conductors can decrease the saturated inductance of the secondary windings of TTMS to a level less than 400 nH. As a result, the proposed TTMS can be used as the boosting transformer and main switch of helical Blumlein PFL to form the quasi-square voltage pulse on the 160 Ω load with a short pulse rise time only at 60 ns.

GPU accelerated dynamic functional connectivity analysis for functional MRI data.

PubMed

Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu

2015-07-01

Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Administering truncated receive functions in a parallel messaging interface

DOEpatents

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2014-12-09

Administering truncated receive functions in a parallel messaging interface (`PMI`) of a parallel computer comprising a plurality of compute nodes coupled for data communications through the PMI and through a data communications network, including: sending, through the PMI on a source compute node, a quantity of data from the source compute node to a destination compute node; specifying, by an application on the destination compute node, a portion of the quantity of data to be received by the application on the destination compute node and a portion of the quantity of data to be discarded; receiving, by the PMI on the destination compute node, all of the quantity of data; providing, by the PMI on the destination compute node to the application on the destination compute node, only the portion of the quantity of data to be received by the application; and discarding, by the PMI on the destination compute node, the portion of the quantity of data to be discarded.

Efficient Predictions of Excited State for Nanomaterials Using Aces 3 and 4

DTIC Science & Technology

2017-12-20

by first-principle methods in the software package ACES by using large parallel computers, growing tothe exascale. 15. SUBJECT TERMS Computer...modeling, excited states, optical properties, structure, stability, activation barriers first principle methods , parallel computing 16. SECURITY...2 Progress with new density functional methods

Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python

USDA-ARS?s Scientific Manuscript database

With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

A Survey of Parallel Computing

DTIC Science & Technology

1988-07-01

Evaluating Two Massively Parallel Machines. Communications of the ACM .9, , , 176 BIBLIOGRAPHY 29, 8 (August), pp. 752-758. Gajski , D.D., Padua, D.A., Kuck...Computer Architecture, edited by Gajski , D. D., Milutinovic, V. M. Siegel, H. J. and Furht, B. P. IEEE Computer Society Press, Washington, D.C., pp. 387-407

Topical perspective on massive threading and parallelism.

PubMed

Farber, Robert M

2011-09-01

Unquestionably computer architectures have undergone a recent and noteworthy paradigm shift that now delivers multi- and many-core systems with tens to many thousands of concurrent hardware processing elements per workstation or supercomputer node. GPGPU (General Purpose Graphics Processor Unit) technology in particular has attracted significant attention as new software development capabilities, namely CUDA (Compute Unified Device Architecture) and OpenCL™, have made it possible for students as well as small and large research organizations to achieve excellent speedup for many applications over more conventional computing architectures. The current scientific literature reflects this shift with numerous examples of GPGPU applications that have achieved one, two, and in some special cases, three-orders of magnitude increased computational performance through the use of massive threading to exploit parallelism. Multi-core architectures are also evolving quickly to exploit both massive-threading and massive-parallelism such as the 1.3 million threads Blue Waters supercomputer. The challenge confronting scientists in planning future experimental and theoretical research efforts--be they individual efforts with one computer or collaborative efforts proposing to use the largest supercomputers in the world is how to capitalize on these new massively threaded computational architectures--especially as not all computational problems will scale to massive parallelism. In particular, the costs associated with restructuring software (and potentially redesigning algorithms) to exploit the parallelism of these multi- and many-threaded machines must be considered along with application scalability and lifespan. This perspective is an overview of the current state of threading and parallelize with some insight into the future. Published by Elsevier Inc.

Software Issues at the User Interface

DTIC Science & Technology

1991-05-01

successful integration of parallel computers into mainstream scientific computing. Clearly a compiler is the most important software tool available to a...Computer Science University of Colorado Boulder, CO 80309 ABSTRACT We review software issues that are critical to the successful integration of parallel...The development of an optimizing compiler of this quality, addressing communicaton instructions as well as computational instructions is a major

A rapid parallelization of cone-beam projection and back-projection operator based on texture fetching interpolation

NASA Astrophysics Data System (ADS)

Xie, Lizhe; Hu, Yining; Chen, Yang; Shi, Luyao

2015-03-01

Projection and back-projection are the most computational consuming parts in Computed Tomography (CT) reconstruction. Parallelization strategies using GPU computing techniques have been introduced. We in this paper present a new parallelization scheme for both projection and back-projection. The proposed method is based on CUDA technology carried out by NVIDIA Corporation. Instead of build complex model, we aimed on optimizing the existing algorithm and make it suitable for CUDA implementation so as to gain fast computation speed. Besides making use of texture fetching operation which helps gain faster interpolation speed, we fixed sampling numbers in the computation of projection, to ensure the synchronization of blocks and threads, thus prevents the latency caused by inconsistent computation complexity. Experiment results have proven the computational efficiency and imaging quality of the proposed method.

Lean coding machine. Facilities target productivity and job satisfaction with coding automation.

PubMed

Rollins, Genna

2010-07-01

Facilities are turning to coding automation to help manage the volume of electronic documentation, streamlining workflow, boosting productivity, and increasing job satisfaction. As EHR adoption increases, computer-assisted coding may become a necessity, not an option.

Electricity generation and microbial community in response to short-term changes in stack connection of self-stacked submersible microbial fuel cell powered by glycerol.

PubMed

Zhao, Nannan; Angelidaki, Irini; Zhang, Yifeng

2017-02-01

Stack connection (i.e., in series or parallel) of microbial fuel cell (MFC) is an efficient way to boost the power output for practical application. However, there is little information available on short-term changes in stack connection and its effect on the electricity generation and microbial community. In this study, a self-stacked submersible microbial fuel cell (SSMFC) powered by glycerol was tested to elucidate this important issue. In series connection, the maximum voltage output reached to 1.15 V, while maximum current density was 5.73 mA in parallel. In both connections, the maximum power density increased with the initial glycerol concentration. However, the glycerol degradation was even faster in parallel connection. When the SSMFC was shifted from series to parallel connection, the reactor reached to a stable power output without any lag phase. Meanwhile, the anodic microbial community compositions were nearly stable. Comparatively, after changing parallel to series connection, there was a lag period for the system to get stable again and the microbial community compositions became greatly different. This study is the first attempt to elucidate the influence of short-term changes in connection on the performance of MFC stack, and could provide insight to the practical utilization of MFC. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploiting parallel computing with limited program changes using a network of microcomputers

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.; Sobieszczanski-Sobieski, J.

1985-01-01

Network computing and multiprocessor computers are two discernible trends in parallel processing. The computational behavior of an iterative distributed process in which some subtasks are completed later than others because of an imbalance in computational requirements is of significant interest. The effects of asynchronus processing was studied. A small existing program was converted to perform finite element analysis by distributing substructure analysis over a network of four Apple IIe microcomputers connected to a shared disk, simulating a parallel computer. The substructure analysis uses an iterative, fully stressed, structural resizing procedure. A framework of beams divided into three substructures is used as the finite element model. The effects of asynchronous processing on the convergence of the design variables are determined by not resizing particular substructures on various iterations.

Massively parallel quantum computer simulator

NASA Astrophysics Data System (ADS)

De Raedt, K.; Michielsen, K.; De Raedt, H.; Trieu, B.; Arnold, G.; Richter, M.; Lippert, Th.; Watanabe, H.; Ito, N.

2007-01-01

We describe portable software to simulate universal quantum computers on massive parallel computers. We illustrate the use of the simulation software by running various quantum algorithms on different computer architectures, such as a IBM BlueGene/L, a IBM Regatta p690+, a Hitachi SR11000/J1, a Cray X1E, a SGI Altix 3700 and clusters of PCs running Windows XP. We study the performance of the software by simulating quantum computers containing up to 36 qubits, using up to 4096 processors and up to 1 TB of memory. Our results demonstrate that the simulator exhibits nearly ideal scaling as a function of the number of processors and suggest that the simulation software described in this paper may also serve as benchmark for testing high-end parallel computers.

Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations

NASA Technical Reports Server (NTRS)

Chrisochoides, Nikos

1995-01-01

We present a multithreaded model for the dynamic load-balancing of numerical, adaptive computations required for the solution of Partial Differential Equations (PDE's) on multiprocessors. Multithreading is used as a means of exploring concurrency in the processor level in order to tolerate synchronization costs inherent to traditional (non-threaded) parallel adaptive PDE solvers. Our preliminary analysis for parallel, adaptive PDE solvers indicates that multithreading can be used an a mechanism to mask overheads required for the dynamic balancing of processor workloads with computations required for the actual numerical solution of the PDE's. Also, multithreading can simplify the implementation of dynamic load-balancing algorithms, a task that is very difficult for traditional data parallel adaptive PDE computations. Unfortunately, multithreading does not always simplify program complexity, often makes code re-usability not an easy task, and increases software complexity.

Efficient parallelization of analytic bond-order potentials for large-scale atomistic simulations

NASA Astrophysics Data System (ADS)

Teijeiro, C.; Hammerschmidt, T.; Drautz, R.; Sutmann, G.

2016-07-01

Analytic bond-order potentials (BOPs) provide a way to compute atomistic properties with controllable accuracy. For large-scale computations of heterogeneous compounds at the atomistic level, both the computational efficiency and memory demand of BOP implementations have to be optimized. Since the evaluation of BOPs is a local operation within a finite environment, the parallelization concepts known from short-range interacting particle simulations can be applied to improve the performance of these simulations. In this work, several efficient parallelization methods for BOPs that use three-dimensional domain decomposition schemes are described. The schemes are implemented into the bond-order potential code BOPfox, and their performance is measured in a series of benchmarks. Systems of up to several millions of atoms are simulated on a high performance computing system, and parallel scaling is demonstrated for up to thousands of processors.

A sweep algorithm for massively parallel simulation of circuit-switched networks

NASA Technical Reports Server (NTRS)

Gaujal, Bruno; Greenberg, Albert G.; Nicol, David M.

1992-01-01

A new massively parallel algorithm is presented for simulating large asymmetric circuit-switched networks, controlled by a randomized-routing policy that includes trunk-reservation. A single instruction multiple data (SIMD) implementation is described, and corresponding experiments on a 16384 processor MasPar parallel computer are reported. A multiple instruction multiple data (MIMD) implementation is also described, and corresponding experiments on an Intel IPSC/860 parallel computer, using 16 processors, are reported. By exploiting parallelism, our algorithm increases the possible execution rate of such complex simulations by as much as an order of magnitude.

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.

1991-01-01

The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.

Numerical characteristics of quantum computer simulation

NASA Astrophysics Data System (ADS)

Chernyavskiy, A.; Khamitov, K.; Teplov, A.; Voevodin, V.; Voevodin, Vl.

2016-12-01

The simulation of quantum circuits is significantly important for the implementation of quantum information technologies. The main difficulty of such modeling is the exponential growth of dimensionality, thus the usage of modern high-performance parallel computations is relevant. As it is well known, arbitrary quantum computation in circuit model can be done by only single- and two-qubit gates, and we analyze the computational structure and properties of the simulation of such gates. We investigate the fact that the unique properties of quantum nature lead to the computational properties of the considered algorithms: the quantum parallelism make the simulation of quantum gates highly parallel, and on the other hand, quantum entanglement leads to the problem of computational locality during simulation. We use the methodology of the AlgoWiki project (algowiki-project.org) to analyze the algorithm. This methodology consists of theoretical (sequential and parallel complexity, macro structure, and visual informational graph) and experimental (locality and memory access, scalability and more specific dynamic characteristics) parts. Experimental part was made by using the petascale Lomonosov supercomputer (Moscow State University, Russia). We show that the simulation of quantum gates is a good base for the research and testing of the development methods for data intense parallel software, and considered methodology of the analysis can be successfully used for the improvement of the algorithms in quantum information science.

Cryogenic performance of slotted brazed Rene 41 honeycomb panels

NASA Technical Reports Server (NTRS)

Hepler, A. K.; Swegle, A. R.

1982-01-01

Two brazed Rene 41 honeycomb panels that would incorporate a frame element were designed, fabricated and tested. The panels were representative of the lower surface of an advanced space transportation vehicle. The first panel was a two span panel supported by a center frame and on edges parallel to it. The second panel was a two span panel supported by a center frame and on edges parallel to it. The second panel was a three span panel supported on two frames and on edges parallel to the frames. Each panel had its outer skin slotted to reduce the thermal stresses of the panel skins. The first panel was tested under simulated boost conditions that included liquid hydrogen exposure of the frame and inner skin and radiant heat to 478K on the outer skins. The first panel was tested to investigate the effect of thermal stresses in skins and core caused by the panel being restrained by a cold integral frame and to observe the effects of frost formation and possible liquid air development in and around outer skin slots.

Computation of parton distributions from the quasi-PDF approach at the physical point

NASA Astrophysics Data System (ADS)

Alexandrou, Constantia; Bacchio, Simone; Cichy, Krzysztof; Constantinou, Martha; Hadjiyiannakou, Kyriakos; Jansen, Karl; Koutsou, Giannis; Scapellato, Aurora; Steffens, Fernanda

2018-03-01

We show the first results for parton distribution functions within the proton at the physical pion mass, employing the method of quasi-distributions. In particular, we present the matrix elements for the iso-vector combination of the unpolarized, helicity and transversity quasi-distributions, obtained with Nf = 2 twisted mass cloverimproved fermions and a proton boosted with momentum |p→| = 0.83 GeV. The momentum smearing technique has been applied to improve the overlap with the proton boosted state. Moreover, we present the renormalized helicity matrix elements in the RI' scheme, following the non-perturbative renormalization prescription recently developed by our group.

Parallel programming of industrial applications

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

Heroux, M; Koniges, A; Simon, H

1998-07-21

In the introductory material, we overview the typical MPP environment for real application computing and the special tools available such as parallel debuggers and performance analyzers. Next, we draw from a series of real applications codes and discuss the specific challenges and problems that are encountered in parallelizing these individual applications. The application areas drawn from include biomedical sciences, materials processing and design, plasma and fluid dynamics, and others. We show how it was possible to get a particular application to run efficiently and what steps were necessary. Finally we end with a summary of the lessons learned from thesemore » applications and predictions for the future of industrial parallel computing. This tutorial is based on material from a forthcoming book entitled: "Industrial Strength Parallel Computing" to be published by Morgan Kaufmann Publishers (ISBN l-55860-54).« less

schwimmbad: A uniform interface to parallel processing pools in Python

NASA Astrophysics Data System (ADS)

Price-Whelan, Adrian M.; Foreman-Mackey, Daniel

2017-09-01

Many scientific and computing problems require doing some calculation on all elements of some data set. If the calculations can be executed in parallel (i.e. without any communication between calculations), these problems are said to be perfectly parallel. On computers with multiple processing cores, these tasks can be distributed and executed in parallel to greatly improve performance. A common paradigm for handling these distributed computing problems is to use a processing "pool": the "tasks" (the data) are passed in bulk to the pool, and the pool handles distributing the tasks to a number of worker processes when available. schwimmbad provides a uniform interface to parallel processing pools and enables switching easily between local development (e.g., serial processing or with multiprocessing) and deployment on a cluster or supercomputer (via, e.g., MPI or JobLib).

F-Nets and Software Cabling: Deriving a Formal Model and Language for Portable Parallel Programming

NASA Technical Reports Server (NTRS)

DiNucci, David C.; Saini, Subhash (Technical Monitor)

1998-01-01

Parallel programming is still being based upon antiquated sequence-based definitions of the terms "algorithm" and "computation", resulting in programs which are architecture dependent and difficult to design and analyze. By focusing on obstacles inherent in existing practice, a more portable model is derived here, which is then formalized into a model called Soviets which utilizes a combination of imperative and functional styles. This formalization suggests more general notions of algorithm and computation, as well as insights into the meaning of structured programming in a parallel setting. To illustrate how these principles can be applied, a very-high-level graphical architecture-independent parallel language, called Software Cabling, is described, with many of the features normally expected from today's computer languages (e.g. data abstraction, data parallelism, and object-based programming constructs).

Processing data communications events by awakening threads in parallel active messaging interface of a parallel computer

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

Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.

Processing data communications events in a parallel active messaging interface (`PAMI`) of a parallel computer that includes compute nodes that execute a parallel application, with the PAMI including data communications endpoints, and the endpoints are coupled for data communications through the PAMI and through other data communications resources, including determining by an advance function that there are no actionable data communications events pending for its context, placing by the advance function its thread of execution into a wait state, waiting for a subsequent data communications event for the context; responsive to occurrence of a subsequent data communications event for themore » context, awakening by the thread from the wait state; and processing by the advance function the subsequent data communications event now pending for the context.« less

A massively parallel computational approach to coupled thermoelastic/porous gas flow problems

NASA Technical Reports Server (NTRS)

Shia, David; Mcmanus, Hugh L.

1995-01-01

A new computational scheme for coupled thermoelastic/porous gas flow problems is presented. Heat transfer, gas flow, and dynamic thermoelastic governing equations are expressed in fully explicit form, and solved on a massively parallel computer. The transpiration cooling problem is used as an example problem. The numerical solutions have been verified by comparison to available analytical solutions. Transient temperature, pressure, and stress distributions have been obtained. Small spatial oscillations in pressure and stress have been observed, which would be impractical to predict with previously available schemes. Comparisons between serial and massively parallel versions of the scheme have also been made. The results indicate that for small scale problems the serial and parallel versions use practically the same amount of CPU time. However, as the problem size increases the parallel version becomes more efficient than the serial version.

NAS Requirements Checklist for Job Queuing/Scheduling Software

NASA Technical Reports Server (NTRS)

Jones, James Patton

1996-01-01

The increasing reliability of parallel systems and clusters of computers has resulted in these systems becoming more attractive for true production workloads. Today, the primary obstacle to production use of clusters of computers is the lack of a functional and robust Job Management System for parallel applications. This document provides a checklist of NAS requirements for job queuing and scheduling in order to make most efficient use of parallel systems and clusters for parallel applications. Future requirements are also identified to assist software vendors with design planning.

The NAS parallel benchmarks

NASA Technical Reports Server (NTRS)

Bailey, David (Editor); Barton, John (Editor); Lasinski, Thomas (Editor); Simon, Horst (Editor)

1993-01-01

A new set of benchmarks was developed for the performance evaluation of highly parallel supercomputers. These benchmarks consist of a set of kernels, the 'Parallel Kernels,' and a simulated application benchmark. Together they mimic the computation and data movement characteristics of large scale computational fluid dynamics (CFD) applications. The principal distinguishing feature of these benchmarks is their 'pencil and paper' specification - all details of these benchmarks are specified only algorithmically. In this way many of the difficulties associated with conventional benchmarking approaches on highly parallel systems are avoided.

Parallel Simulation of Three-Dimensional Free Surface Fluid Flow Problems

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

BAER,THOMAS A.; SACKINGER,PHILIP A.; SUBIA,SAMUEL R.

1999-10-14

Simulation of viscous three-dimensional fluid flow typically involves a large number of unknowns. When free surfaces are included, the number of unknowns increases dramatically. Consequently, this class of problem is an obvious application of parallel high performance computing. We describe parallel computation of viscous, incompressible, free surface, Newtonian fluid flow problems that include dynamic contact fines. The Galerkin finite element method was used to discretize the fully-coupled governing conservation equations and a ''pseudo-solid'' mesh mapping approach was used to determine the shape of the free surface. In this approach, the finite element mesh is allowed to deform to satisfy quasi-staticmore » solid mechanics equations subject to geometric or kinematic constraints on the boundaries. As a result, nodal displacements must be included in the set of unknowns. Other issues discussed are the proper constraints appearing along the dynamic contact line in three dimensions. Issues affecting efficient parallel simulations include problem decomposition to equally distribute computational work among a SPMD computer and determination of robust, scalable preconditioners for the distributed matrix systems that must be solved. Solution continuation strategies important for serial simulations have an enhanced relevance in a parallel coquting environment due to the difficulty of solving large scale systems. Parallel computations will be demonstrated on an example taken from the coating flow industry: flow in the vicinity of a slot coater edge. This is a three dimensional free surface problem possessing a contact line that advances at the web speed in one region but transitions to static behavior in another region. As such, a significant fraction of the computational time is devoted to processing boundary data. Discussion focuses on parallel speed ups for fixed problem size, a class of problems of immediate practical importance.« less

Partitioning and packing mathematical simulation models for calculation on parallel computers

NASA Technical Reports Server (NTRS)

Arpasi, D. J.; Milner, E. J.

1986-01-01

The development of multiprocessor simulations from a serial set of ordinary differential equations describing a physical system is described. Degrees of parallelism (i.e., coupling between the equations) and their impact on parallel processing are discussed. The problem of identifying computational parallelism within sets of closely coupled equations that require the exchange of current values of variables is described. A technique is presented for identifying this parallelism and for partitioning the equations for parallel solution on a multiprocessor. An algorithm which packs the equations into a minimum number of processors is also described. The results of the packing algorithm when applied to a turbojet engine model are presented in terms of processor utilization.

Parallel/distributed direct method for solving linear systems

NASA Technical Reports Server (NTRS)

Lin, Avi

1990-01-01

A new family of parallel schemes for directly solving linear systems is presented and analyzed. It is shown that these schemes exhibit a near optimal performance and enjoy several important features: (1) For large enough linear systems, the design of the appropriate paralleled algorithm is insensitive to the number of processors as its performance grows monotonically with them; (2) It is especially good for large matrices, with dimensions large relative to the number of processors in the system; (3) It can be used in both distributed parallel computing environments and tightly coupled parallel computing systems; and (4) This set of algorithms can be mapped onto any parallel architecture without any major programming difficulties or algorithmical changes.

Vectorization for Molecular Dynamics on Intel Xeon Phi Corpocessors

NASA Astrophysics Data System (ADS)

Yi, Hongsuk

2014-03-01

Many modern processors are capable of exploiting data-level parallelism through the use of single instruction multiple data (SIMD) execution. The new Intel Xeon Phi coprocessor supports 512 bit vector registers for the high performance computing. In this paper, we have developed a hierarchical parallelization scheme for accelerated molecular dynamics simulations with the Terfoff potentials for covalent bond solid crystals on Intel Xeon Phi coprocessor systems. The scheme exploits multi-level parallelism computing. We combine thread-level parallelism using a tightly coupled thread-level and task-level parallelism with 512-bit vector register. The simulation results show that the parallel performance of SIMD implementations on Xeon Phi is apparently superior to their x86 CPU architecture.

Parallel and pipeline computation of fast unitary transforms

NASA Technical Reports Server (NTRS)

Fino, B. J.; Algazi, V. R.

1975-01-01

The letter discusses the parallel and pipeline organization of fast-unitary-transform algorithms such as the fast Fourier transform, and points out the efficiency of a combined parallel-pipeline processor of a transform such as the Haar transform, in which (2 to the n-th power) -1 hardware 'butterflies' generate a transform of order 2 to the n-th power every computation cycle.

Box schemes and their implementation on the iPSC/860

NASA Technical Reports Server (NTRS)

Chattot, J. J.; Merriam, M. L.

1991-01-01

Research on algoriths for efficiently solving fluid flow problems on massively parallel computers is continued in the present paper. Attention is given to the implementation of a box scheme on the iPSC/860, a massively parallel computer with a peak speed of 10 Gflops and a memory of 128 Mwords. A domain decomposition approach to parallelism is used.

Parallel Tensor Compression for Large-Scale Scientific Data.

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

Kolda, Tamara G.; Ballard, Grey; Austin, Woody Nathan

As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memorymore » parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.« less

The orbifolder: A tool to study the low-energy effective theory of heterotic orbifolds

NASA Astrophysics Data System (ADS)

Nilles, H. P.; Ramos-Sánchez, S.; Vaudrevange, P. K. S.; Wingerter, A.

2012-06-01

The orbifolder is a program developed in C++ that computes and analyzes the low-energy effective theory of heterotic orbifold compactifications. The program includes routines to compute the massless spectrum, to identify the allowed couplings in the superpotential, to automatically generate large sets of orbifold models, to identify phenomenologically interesting models (e.g. MSSM-like models) and to analyze their vacuum configurations. Program summaryProgram title: orbifolder Catalogue identifier: AELR_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELR_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 145 572 No. of bytes in distributed program, including test data, etc.: 930 517 Distribution format: tar.gz Programming language:C++ Computer: Personal computer Operating system: Tested on Linux (Fedora 15, Ubuntu 11, SuSE 11) Word size: 32 bits or 64 bits Classification: 11.1 External routines: Boost (http://www.boost.org/), GSL (http://www.gnu.org/software/gsl/) Nature of problem: Calculating the low-energy spectrum of heterotic orbifold compactifications. Solution method: Quadratic equations on a lattice; representation theory; polynomial algebra. Running time: Less than a second per model.

Planning the Breast Boost: Comparison of Three Techniques and Evolution of Tumor Bed During Treatment

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

Hepel, Jaroslaw T.; Department of Radiation Oncology, Brown University, Rhode Island Hospital, Providence, RI; Evans, Suzanne B.

2009-06-01

Purpose: To evaluate the accuracy of two clinical techniques for electron boost planning compared with computed tomography (CT)-based planning. Additionally, we evaluated the tumor bed characteristics at whole breast planning and boost planning. Methods and Materials: A total of 30 women underwent tumor bed boost planning within 2 weeks of completing whole breast radiotherapy using three planning techniques: scar-based planning, palpation/clinical-based planning, and CT-based planning. The plans were analyzed for dosimetric coverage of the CT-delineated tumor bed. The cavity visualization score was used to define the CT-delineated tumor bed as well or poorly defined. Results: Scar-based planning resulted in inferiormore » tumor bed coverage compared with CT-based planning, with the minimal dose received by 90% of the target volume >90% in 53% and a geographic miss in 53%. The results of palpation/clinical-based planning were significantly better: 87% and 10% for the minimal dose received by 90% of the target volume >90% and geographic miss, respectively. Of the 30 tumor beds, 16 were poorly defined by the cavity visualization score. Of these 16, 8 were well demarcated by the surgical clips. The evaluation of the 22 well-defined tumor beds revealed similar results. A comparison of the tumor bed volume from the initial planning CT scan to the boost planning CT scan revealed a decrease in size in 77% of cases. The mean decrease in volume was 52%. Conclusion: The results of our study have shown that CT-based planning allows for optimal tumor bed coverage compared with clinical and scar-based approaches. However, in the setting of a poorly visualized cavity on CT without surgical clips, palpation/clinical-based planning can help delineate the appropriate target volumes and is superior to scar-based planning. CT simulation at boost planning could allow for a reduction in the boost volumes.« less

Parallel conjugate gradient algorithms for manipulator dynamic simulation

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheld, Robert E.

1989-01-01

Parallel conjugate gradient algorithms for the computation of multibody dynamics are developed for the specialized case of a robot manipulator. For an n-dimensional positive-definite linear system, the Classical Conjugate Gradient (CCG) algorithms are guaranteed to converge in n iterations, each with a computation cost of O(n); this leads to a total computational cost of O(n sq) on a serial processor. A conjugate gradient algorithms is presented that provide greater efficiency using a preconditioner, which reduces the number of iterations required, and by exploiting parallelism, which reduces the cost of each iteration. Two Preconditioned Conjugate Gradient (PCG) algorithms are proposed which respectively use a diagonal and a tridiagonal matrix, composed of the diagonal and tridiagonal elements of the mass matrix, as preconditioners. Parallel algorithms are developed to compute the preconditioners and their inversions in O(log sub 2 n) steps using n processors. A parallel algorithm is also presented which, on the same architecture, achieves the computational time of O(log sub 2 n) for each iteration. Simulation results for a seven degree-of-freedom manipulator are presented. Variants of the proposed algorithms are also developed which can be efficiently implemented on the Robot Mathematics Processor (RMP).

Parallel Implementation of Triangular Cellular Automata for Computing Two-Dimensional Elastodynamic Response on Arbitrary Domains

NASA Astrophysics Data System (ADS)

Leamy, Michael J.; Springer, Adam C.

In this research we report parallel implementation of a Cellular Automata-based simulation tool for computing elastodynamic response on complex, two-dimensional domains. Elastodynamic simulation using Cellular Automata (CA) has recently been presented as an alternative, inherently object-oriented technique for accurately and efficiently computing linear and nonlinear wave propagation in arbitrarily-shaped geometries. The local, autonomous nature of the method should lead to straight-forward and efficient parallelization. We address this notion on symmetric multiprocessor (SMP) hardware using a Java-based object-oriented CA code implementing triangular state machines (i.e., automata) and the MPI bindings written in Java (MPJ Express). We use MPJ Express to reconfigure our existing CA code to distribute a domain's automata to cores present on a dual quad-core shared-memory system (eight total processors). We note that this message passing parallelization strategy is directly applicable to computer clustered computing, which will be the focus of follow-on research. Results on the shared memory platform indicate nearly-ideal, linear speed-up. We conclude that the CA-based elastodynamic simulator is easily configured to run in parallel, and yields excellent speed-up on SMP hardware.

Characterization of robotics parallel algorithms and mapping onto a reconfigurable SIMD machine

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Lin, C. T.

1989-01-01

The kinematics, dynamics, Jacobian, and their corresponding inverse computations are six essential problems in the control of robot manipulators. Efficient parallel algorithms for these computations are discussed and analyzed. Their characteristics are identified and a scheme on the mapping of these algorithms to a reconfigurable parallel architecture is presented. Based on the characteristics including type of parallelism, degree of parallelism, uniformity of the operations, fundamental operations, data dependencies, and communication requirement, it is shown that most of the algorithms for robotic computations possess highly regular properties and some common structures, especially the linear recursive structure. Moreover, they are well-suited to be implemented on a single-instruction-stream multiple-data-stream (SIMD) computer with reconfigurable interconnection network. The model of a reconfigurable dual network SIMD machine with internal direct feedback is introduced. A systematic procedure internal direct feedback is introduced. A systematic procedure to map these computations to the proposed machine is presented. A new scheduling problem for SIMD machines is investigated and a heuristic algorithm, called neighborhood scheduling, that reorders the processing sequence of subtasks to reduce the communication time is described. Mapping results of a benchmark algorithm are illustrated and discussed.

A parallel Monte Carlo code for planar and SPECT imaging: implementation, verification and applications in (131)I SPECT.

PubMed

Dewaraja, Yuni K; Ljungberg, Michael; Majumdar, Amitava; Bose, Abhijit; Koral, Kenneth F

2002-02-01

This paper reports the implementation of the SIMIND Monte Carlo code on an IBM SP2 distributed memory parallel computer. Basic aspects of running Monte Carlo particle transport calculations on parallel architectures are described. Our parallelization is based on equally partitioning photons among the processors and uses the Message Passing Interface (MPI) library for interprocessor communication and the Scalable Parallel Random Number Generator (SPRNG) to generate uncorrelated random number streams. These parallelization techniques are also applicable to other distributed memory architectures. A linear increase in computing speed with the number of processors is demonstrated for up to 32 processors. This speed-up is especially significant in Single Photon Emission Computed Tomography (SPECT) simulations involving higher energy photon emitters, where explicit modeling of the phantom and collimator is required. For (131)I, the accuracy of the parallel code is demonstrated by comparing simulated and experimental SPECT images from a heart/thorax phantom. Clinically realistic SPECT simulations using the voxel-man phantom are carried out to assess scatter and attenuation correction.

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

Effecting a broadcast with an allreduce operation on a parallel computer

DOEpatents

Almasi, Gheorghe; Archer, Charles J.; Ratterman, Joseph D.; Smith, Brian E.

2010-11-02

A parallel computer comprises a plurality of compute nodes organized into at least one operational group for collective parallel operations. Each compute node is assigned a unique rank and is coupled for data communications through a global combining network. One compute node is assigned to be a logical root. A send buffer and a receive buffer is configured. Each element of a contribution of the logical root in the send buffer is contributed. One or more zeros corresponding to a size of the element are injected. An allreduce operation with a bitwise OR using the element and the injected zeros is performed. And the result for the allreduce operation is determined and stored in each receive buffer.

Methodologies and systems for heterogeneous concurrent computing

NASA Technical Reports Server (NTRS)

Sunderam, V. S.

1994-01-01

Heterogeneous concurrent computing is gaining increasing acceptance as an alternative or complementary paradigm to multiprocessor-based parallel processing as well as to conventional supercomputing. While algorithmic and programming aspects of heterogeneous concurrent computing are similar to their parallel processing counterparts, system issues, partitioning and scheduling, and performance aspects are significantly different. In this paper, we discuss critical design and implementation issues in heterogeneous concurrent computing, and describe techniques for enhancing its effectiveness. In particular, we highlight the system level infrastructures that are required, aspects of parallel algorithm development that most affect performance, system capabilities and limitations, and tools and methodologies for effective computing in heterogeneous networked environments. We also present recent developments and experiences in the context of the PVM system and comment on ongoing and future work.

Method and apparatus of parallel computing with simultaneously operating stream prefetching and list prefetching engines

DOEpatents

Boyle, Peter A.; Christ, Norman H.; Gara, Alan; Mawhinney, Robert D.; Ohmacht, Martin; Sugavanam, Krishnan

2012-12-11

A prefetch system improves a performance of a parallel computing system. The parallel computing system includes a plurality of computing nodes. A computing node includes at least one processor and at least one memory device. The prefetch system includes at least one stream prefetch engine and at least one list prefetch engine. The prefetch system operates those engines simultaneously. After the at least one processor issues a command, the prefetch system passes the command to a stream prefetch engine and a list prefetch engine. The prefetch system operates the stream prefetch engine and the list prefetch engine to prefetch data to be needed in subsequent clock cycles in the processor in response to the passed command.

DVS-SOFTWARE: An Effective Tool for Applying Highly Parallelized Hardware To Computational Geophysics

NASA Astrophysics Data System (ADS)

Herrera, I.; Herrera, G. S.

2015-12-01

Most geophysical systems are macroscopic physical systems. The behavior prediction of such systems is carried out by means of computational models whose basic models are partial differential equations (PDEs) [1]. Due to the enormous size of the discretized version of such PDEs it is necessary to apply highly parallelized super-computers. For them, at present, the most efficient software is based on non-overlapping domain decomposition methods (DDM). However, a limiting feature of the present state-of-the-art techniques is due to the kind of discretizations used in them. Recently, I. Herrera and co-workers using 'non-overlapping discretizations' have produced the DVS-Software which overcomes this limitation [2]. The DVS-software can be applied to a great variety of geophysical problems and achieves very high parallel efficiencies (90%, or so [3]). It is therefore very suitable for effectively applying the most advanced parallel supercomputers available at present. In a parallel talk, in this AGU Fall Meeting, Graciela Herrera Z. will present how this software is being applied to advance MOD-FLOW. Key Words: Parallel Software for Geophysics, High Performance Computing, HPC, Parallel Computing, Domain Decomposition Methods (DDM)REFERENCES [1]. Herrera Ismael and George F. Pinder, Mathematical Modelling in Science and Engineering: An axiomatic approach", John Wiley, 243p., 2012. [2]. Herrera, I., de la Cruz L.M. and Rosas-Medina A. "Non Overlapping Discretization Methods for Partial, Differential Equations". NUMER METH PART D E, 30: 1427-1454, 2014, DOI 10.1002/num 21852. (Open source) [3]. Herrera, I., & Contreras Iván "An Innovative Tool for Effectively Applying Highly Parallelized Software To Problems of Elasticity". Geofísica Internacional, 2015 (In press)

Hierarchial parallel computer architecture defined by computational multidisciplinary mechanics

NASA Technical Reports Server (NTRS)

Padovan, Joe; Gute, Doug; Johnson, Keith

1989-01-01

The goal is to develop an architecture for parallel processors enabling optimal handling of multi-disciplinary computation of fluid-solid simulations employing finite element and difference schemes. The goals, philosphical and modeling directions, static and dynamic poly trees, example problems, interpolative reduction, the impact on solvers are shown in viewgraph form.

Parallel computer vision

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

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

Assignment Of Finite Elements To Parallel Processors

NASA Technical Reports Server (NTRS)

Salama, Moktar A.; Flower, Jon W.; Otto, Steve W.

1990-01-01

Elements assigned approximately optimally to subdomains. Mapping algorithm based on simulated-annealing concept used to minimize approximate time required to perform finite-element computation on hypercube computer or other network of parallel data processors. Mapping algorithm needed when shape of domain complicated or otherwise not obvious what allocation of elements to subdomains minimizes cost of computation.

Parallel computing in experimental mechanics and optical measurement: A review (II)

NASA Astrophysics Data System (ADS)

Wang, Tianyi; Kemao, Qian

2018-05-01

With advantages such as non-destructiveness, high sensitivity and high accuracy, optical techniques have successfully integrated into various important physical quantities in experimental mechanics (EM) and optical measurement (OM). However, in pursuit of higher image resolutions for higher accuracy, the computation burden of optical techniques has become much heavier. Therefore, in recent years, heterogeneous platforms composing of hardware such as CPUs and GPUs, have been widely employed to accelerate these techniques due to their cost-effectiveness, short development cycle, easy portability, and high scalability. In this paper, we analyze various works by first illustrating their different architectures, followed by introducing their various parallel patterns for high speed computation. Next, we review the effects of CPU and GPU parallel computing specifically in EM & OM applications in a broad scope, which include digital image/volume correlation, fringe pattern analysis, tomography, hyperspectral imaging, computer-generated holograms, and integral imaging. In our survey, we have found that high parallelism can always be exploited in such applications for the development of high-performance systems.

ParallelStructure: A R Package to Distribute Parallel Runs of the Population Genetics Program STRUCTURE on Multi-Core Computers

PubMed Central

Besnier, Francois; Glover, Kevin A.

2013-01-01

This software package provides an R-based framework to make use of multi-core computers when running analyses in the population genetics program STRUCTURE. It is especially addressed to those users of STRUCTURE dealing with numerous and repeated data analyses, and who could take advantage of an efficient script to automatically distribute STRUCTURE jobs among multiple processors. It also consists of additional functions to divide analyses among combinations of populations within a single data set without the need to manually produce multiple projects, as it is currently the case in STRUCTURE. The package consists of two main functions: MPI_structure() and parallel_structure() as well as an example data file. We compared the performance in computing time for this example data on two computer architectures and showed that the use of the present functions can result in several-fold improvements in terms of computation time. ParallelStructure is freely available at https://r-forge.r-project.org/projects/parallstructure/. PMID:23923012

Distributed parallel computing in stochastic modeling of groundwater systems.

PubMed

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1999-01-01

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

Parallelization of the FLAPW method and comparison with the PPW method

NASA Astrophysics Data System (ADS)

Canning, Andrew; Mannstadt, Wolfgang; Freeman, Arthur

2000-03-01

The FLAPW (full-potential linearized-augmented plane-wave) method is one of the most accurate first-principles methods for determining electronic and magnetic properties of crystals and surfaces. In the past the FLAPW method has been limited to systems of about a hundred atoms due to the lack of an efficient parallel implementation to exploit the power and memory of parallel computers. In this work we present an efficient parallelization of the method by division among the processors of the plane-wave components for each state. The code is also optimized for RISC (reduced instruction set computer) architectures, such as those found on most parallel computers, making full use of BLAS (basic linear algebra subprograms) wherever possible. Scaling results are presented for systems of up to 686 silicon atoms and 343 palladium atoms per unit cell running on up to 512 processors on a Cray T3E parallel supercomputer. Some results will also be presented on a comparison of the plane-wave pseudopotential method and the FLAPW method on large systems.

Global Magnetohydrodynamic Simulation Using High Performance FORTRAN on Parallel Computers

NASA Astrophysics Data System (ADS)

Ogino, T.

High Performance Fortran (HPF) is one of modern and common techniques to achieve high performance parallel computation. We have translated a 3-dimensional magnetohydrodynamic (MHD) simulation code of the Earth's magnetosphere from VPP Fortran to HPF/JA on the Fujitsu VPP5000/56 vector-parallel supercomputer and the MHD code was fully vectorized and fully parallelized in VPP Fortran. The entire performance and capability of the HPF MHD code could be shown to be almost comparable to that of VPP Fortran. A 3-dimensional global MHD simulation of the earth's magnetosphere was performed at a speed of over 400 Gflops with an efficiency of 76.5 VPP5000/56 in vector and parallel computation that permitted comparison with catalog values. We have concluded that fluid and MHD codes that are fully vectorized and fully parallelized in VPP Fortran can be translated with relative ease to HPF/JA, and a code in HPF/JA may be expected to perform comparably to the same code written in VPP Fortran.

A parallel simulated annealing algorithm for standard cell placement on a hypercube computer

NASA Technical Reports Server (NTRS)

Jones, Mark Howard

1987-01-01

A parallel version of a simulated annealing algorithm is presented which is targeted to run on a hypercube computer. A strategy for mapping the cells in a two dimensional area of a chip onto processors in an n-dimensional hypercube is proposed such that both small and large distance moves can be applied. Two types of moves are allowed: cell exchanges and cell displacements. The computation of the cost function in parallel among all the processors in the hypercube is described along with a distributed data structure that needs to be stored in the hypercube to support parallel cost evaluation. A novel tree broadcasting strategy is used extensively in the algorithm for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms. An improved uniprocessor algorithm is proposed which is based on the improved results obtained from parallelization of the simulated annealing algorithm.

Paging memory from random access memory to backing storage in a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Inglett, Todd A; Ratterman, Joseph D; Smith, Brian E

2013-05-21

Paging memory from random access memory (`RAM`) to backing storage in a parallel computer that includes a plurality of compute nodes, including: executing a data processing application on a virtual machine operating system in a virtual machine on a first compute node; providing, by a second compute node, backing storage for the contents of RAM on the first compute node; and swapping, by the virtual machine operating system in the virtual machine on the first compute node, a page of memory from RAM on the first compute node to the backing storage on the second compute node.

Efficient Helicopter Aerodynamic and Aeroacoustic Predictions on Parallel Computers

NASA Technical Reports Server (NTRS)

Wissink, Andrew M.; Lyrintzis, Anastasios S.; Strawn, Roger C.; Oliker, Leonid; Biswas, Rupak

1996-01-01

This paper presents parallel implementations of two codes used in a combined CFD/Kirchhoff methodology to predict the aerodynamics and aeroacoustics properties of helicopters. The rotorcraft Navier-Stokes code, TURNS, computes the aerodynamic flowfield near the helicopter blades and the Kirchhoff acoustics code computes the noise in the far field, using the TURNS solution as input. The overall parallel strategy adds MPI message passing calls to the existing serial codes to allow for communication between processors. As a result, the total code modifications required for parallel execution are relatively small. The biggest bottleneck in running the TURNS code in parallel comes from the LU-SGS algorithm that solves the implicit system of equations. We use a new hybrid domain decomposition implementation of LU-SGS to obtain good parallel performance on the SP-2. TURNS demonstrates excellent parallel speedups for quasi-steady and unsteady three-dimensional calculations of a helicopter blade in forward flight. The execution rate attained by the code on 114 processors is six times faster than the same cases run on one processor of the Cray C-90. The parallel Kirchhoff code also shows excellent parallel speedups and fast execution rates. As a performance demonstration, unsteady acoustic pressures are computed at 1886 far-field observer locations for a sample acoustics problem. The calculation requires over two hundred hours of CPU time on one C-90 processor but takes only a few hours on 80 processors of the SP2. The resultant far-field acoustic field is analyzed with state of-the-art audio and video rendering of the propagating acoustic signals.

Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.

PubMed

Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo

2016-07-19

Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .

Speeding up parallel processing

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1988-01-01

In 1967 Amdahl expressed doubts about the ultimate utility of multiprocessors. The formulation, now called Amdahl's law, became part of the computing folklore and has inspired much skepticism about the ability of the current generation of massively parallel processors to efficiently deliver all their computing power to programs. The widely publicized recent results of a group at Sandia National Laboratory, which showed speedup on a 1024 node hypercube of over 500 for three fixed size problems and over 1000 for three scalable problems, have convincingly challenged this bit of folklore and have given new impetus to parallel scientific computing.

A language comparison for scientific computing on MIMD architectures

NASA Technical Reports Server (NTRS)

Jones, Mark T.; Patrick, Merrell L.; Voigt, Robert G.

1989-01-01

Choleski's method for solving banded symmetric, positive definite systems is implemented on a multiprocessor computer using three FORTRAN based parallel programming languages, the Force, PISCES and Concurrent FORTRAN. The capabilities of the language for expressing parallelism and their user friendliness are discussed, including readability of the code, debugging assistance offered, and expressiveness of the languages. The performance of the different implementations is compared. It is argued that PISCES, using the Force for medium-grained parallelism, is the appropriate choice for programming Choleski's method on the multiprocessor computer, Flex/32.

Small file aggregation in a parallel computing system

DOEpatents

Faibish, Sorin; Bent, John M.; Tzelnic, Percy; Grider, Gary; Zhang, Jingwang

2014-09-02

Techniques are provided for small file aggregation in a parallel computing system. An exemplary method for storing a plurality of files generated by a plurality of processes in a parallel computing system comprises aggregating the plurality of files into a single aggregated file; and generating metadata for the single aggregated file. The metadata comprises an offset and a length of each of the plurality of files in the single aggregated file. The metadata can be used to unpack one or more of the files from the single aggregated file.

Computer-aided programming for message-passing system; Problems and a solution

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

Wu, M.Y.; Gajski, D.D.

1989-12-01

As the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. Parallel models of computation, parallelization problems, and tools for computer-aided programming (CAP) are discussed. As an example, a CAP tool that performs scheduling and inserts communication primitives automatically is described. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs.

Directions in parallel programming: HPF, shared virtual memory and object parallelism in pC++

NASA Technical Reports Server (NTRS)

Bodin, Francois; Priol, Thierry; Mehrotra, Piyush; Gannon, Dennis

1994-01-01

Fortran and C++ are the dominant programming languages used in scientific computation. Consequently, extensions to these languages are the most popular for programming massively parallel computers. We discuss two such approaches to parallel Fortran and one approach to C++. The High Performance Fortran Forum has designed HPF with the intent of supporting data parallelism on Fortran 90 applications. HPF works by asking the user to help the compiler distribute and align the data structures with the distributed memory modules in the system. Fortran-S takes a different approach in which the data distribution is managed by the operating system and the user provides annotations to indicate parallel control regions. In the case of C++, we look at pC++ which is based on a concurrent aggregate parallel model.

Locating hardware faults in a parallel computer

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-04-13

Locating hardware faults in a parallel computer, including defining within a tree network of the parallel computer two or more sets of non-overlapping test levels of compute nodes of the network that together include all the data communications links of the network, each non-overlapping test level comprising two or more adjacent tiers of the tree; defining test cells within each non-overlapping test level, each test cell comprising a subtree of the tree including a subtree root compute node and all descendant compute nodes of the subtree root compute node within a non-overlapping test level; performing, separately on each set of non-overlapping test levels, an uplink test on all test cells in a set of non-overlapping test levels; and performing, separately from the uplink tests and separately on each set of non-overlapping test levels, a downlink test on all test cells in a set of non-overlapping test levels.

Final report for the Tera Computer TTI CRADA

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

Davidson, G.S.; Pavlakos, C.; Silva, C.

1997-01-01

Tera Computer and Sandia National Laboratories have completed a CRADA, which examined the Tera Multi-Threaded Architecture (MTA) for use with large codes of importance to industry and DOE. The MTA is an innovative architecture that uses parallelism to mask latency between memories and processors. The physical implementation is a parallel computer with high cross-section bandwidth and GaAs processors designed by Tera, which support many small computation threads and fast, lightweight context switches between them. When any thread blocks while waiting for memory accesses to complete, another thread immediately begins execution so that high CPU utilization is maintained. The Tera MTAmore » parallel computer has a single, global address space, which is appealing when porting existing applications to a parallel computer. This ease of porting is further enabled by compiler technology that helps break computations into parallel threads. DOE and Sandia National Laboratories were interested in working with Tera to further develop this computing concept. While Tera Computer would continue the hardware development and compiler research, Sandia National Laboratories would work with Tera to ensure that their compilers worked well with important Sandia codes, most particularly CTH, a shock physics code used for weapon safety computations. In addition to that important code, Sandia National Laboratories would complete research on a robotic path planning code, SANDROS, which is important in manufacturing applications, and would evaluate the MTA performance on this code. Finally, Sandia would work directly with Tera to develop 3D visualization codes, which would be appropriate for use with the MTA. Each of these tasks has been completed to the extent possible, given that Tera has just completed the MTA hardware. All of the CRADA work had to be done on simulators.« less

Parallel community climate model: Description and user`s guide

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

Drake, J.B.; Flanery, R.E.; Semeraro, B.D.

This report gives an overview of a parallel version of the NCAR Community Climate Model, CCM2, implemented for MIMD massively parallel computers using a message-passing programming paradigm. The parallel implementation was developed on an Intel iPSC/860 with 128 processors and on the Intel Delta with 512 processors, and the initial target platform for the production version of the code is the Intel Paragon with 2048 processors. Because the implementation uses a standard, portable message-passing libraries, the code has been easily ported to other multiprocessors supporting a message-passing programming paradigm. The parallelization strategy used is to decompose the problem domain intomore » geographical patches and assign each processor the computation associated with a distinct subset of the patches. With this decomposition, the physics calculations involve only grid points and data local to a processor and are performed in parallel. Using parallel algorithms developed for the semi-Lagrangian transport, the fast Fourier transform and the Legendre transform, both physics and dynamics are computed in parallel with minimal data movement and modest change to the original CCM2 source code. Sequential or parallel history tapes are written and input files (in history tape format) are read sequentially by the parallel code to promote compatibility with production use of the model on other computer systems. A validation exercise has been performed with the parallel code and is detailed along with some performance numbers on the Intel Paragon and the IBM SP2. A discussion of reproducibility of results is included. A user`s guide for the PCCM2 version 2.1 on the various parallel machines completes the report. Procedures for compilation, setup and execution are given. A discussion of code internals is included for those who may wish to modify and use the program in their own research.« less

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

NASA Technical Reports Server (NTRS)

Ecer, A.; Chien, Y. P.; Boenisch, T.; Akay, H. U.

2000-01-01

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

Application of a hybrid MPI/OpenMP approach for parallel groundwater model calibration using multi-core computers

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

Tang, Guoping; D'Azevedo, Ed F; Zhang, Fan

2010-01-01

Calibration of groundwater models involves hundreds to thousands of forward solutions, each of which may solve many transient coupled nonlinear partial differential equations, resulting in a computationally intensive problem. We describe a hybrid MPI/OpenMP approach to exploit two levels of parallelisms in software and hardware to reduce calibration time on multi-core computers. HydroGeoChem 5.0 (HGC5) is parallelized using OpenMP for direct solutions for a reactive transport model application, and a field-scale coupled flow and transport model application. In the reactive transport model, a single parallelizable loop is identified to account for over 97% of the total computational time using GPROF.more » Addition of a few lines of OpenMP compiler directives to the loop yields a speedup of about 10 on a 16-core compute node. For the field-scale model, parallelizable loops in 14 of 174 HGC5 subroutines that require 99% of the execution time are identified. As these loops are parallelized incrementally, the scalability is found to be limited by a loop where Cray PAT detects over 90% cache missing rates. With this loop rewritten, similar speedup as the first application is achieved. The OpenMP-parallelized code can be run efficiently on multiple workstations in a network or multiple compute nodes on a cluster as slaves using parallel PEST to speedup model calibration. To run calibration on clusters as a single task, the Levenberg Marquardt algorithm is added to HGC5 with the Jacobian calculation and lambda search parallelized using MPI. With this hybrid approach, 100 200 compute cores are used to reduce the calibration time from weeks to a few hours for these two applications. This approach is applicable to most of the existing groundwater model codes for many applications.« less

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

NASA Astrophysics Data System (ADS)

Rostrup, Scott; De Sterck, Hans

2010-12-01

Increasingly, high-performance computing is looking towards data-parallel computational devices to enhance computational performance. Two technologies that have received significant attention are IBM's Cell Processor and NVIDIA's CUDA programming model for graphics processing unit (GPU) computing. In this paper we investigate the acceleration of parallel hyperbolic partial differential equation simulation on structured grids with explicit time integration on clusters with Cell and GPU backends. The message passing interface (MPI) is used for communication between nodes at the coarsest level of parallelism. Optimizations of the simulation code at the several finer levels of parallelism that the data-parallel devices provide are described in terms of data layout, data flow and data-parallel instructions. Optimized Cell and GPU performance are compared with reference code performance on a single x86 central processing unit (CPU) core in single and double precision. We further compare the CPU, Cell and GPU platforms on a chip-to-chip basis, and compare performance on single cluster nodes with two CPUs, two Cell processors or two GPUs in a shared memory configuration (without MPI). We finally compare performance on clusters with 32 CPUs, 32 Cell processors, and 32 GPUs using MPI. Our GPU cluster results use NVIDIA Tesla GPUs with GT200 architecture, but some preliminary results on recently introduced NVIDIA GPUs with the next-generation Fermi architecture are also included. This paper provides computational scientists and engineers who are considering porting their codes to accelerator environments with insight into how structured grid based explicit algorithms can be optimized for clusters with Cell and GPU accelerators. It also provides insight into the speed-up that may be gained on current and future accelerator architectures for this class of applications. Program summaryProgram title: SWsolver Catalogue identifier: AEGY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGY_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL v3 No. of lines in distributed program, including test data, etc.: 59 168 No. of bytes in distributed program, including test data, etc.: 453 409 Distribution format: tar.gz Programming language: C, CUDA Computer: Parallel Computing Clusters. Individual compute nodes may consist of x86 CPU, Cell processor, or x86 CPU with attached NVIDIA GPU accelerator. Operating system: Linux Has the code been vectorised or parallelized?: Yes. Tested on 1-128 x86 CPU cores, 1-32 Cell Processors, and 1-32 NVIDIA GPUs. RAM: Tested on Problems requiring up to 4 GB per compute node. Classification: 12 External routines: MPI, CUDA, IBM Cell SDK Nature of problem: MPI-parallel simulation of Shallow Water equations using high-resolution 2D hyperbolic equation solver on regular Cartesian grids for x86 CPU, Cell Processor, and NVIDIA GPU using CUDA. Solution method: SWsolver provides 3 implementations of a high-resolution 2D Shallow Water equation solver on regular Cartesian grids, for CPU, Cell Processor, and NVIDIA GPU. Each implementation uses MPI to divide work across a parallel computing cluster. Additional comments: Sub-program numdiff is used for the test run.

Parallel implementation of the particle simulation method with dynamic load balancing: Toward realistic geodynamical simulation

NASA Astrophysics Data System (ADS)

Furuichi, M.; Nishiura, D.

2015-12-01

Fully Lagrangian methods such as Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) have been widely used to solve the continuum and particles motions in the computational geodynamics field. These mesh-free methods are suitable for the problems with the complex geometry and boundary. In addition, their Lagrangian nature allows non-diffusive advection useful for tracking history dependent properties (e.g. rheology) of the material. These potential advantages over the mesh-based methods offer effective numerical applications to the geophysical flow and tectonic processes, which are for example, tsunami with free surface and floating body, magma intrusion with fracture of rock, and shear zone pattern generation of granular deformation. In order to investigate such geodynamical problems with the particle based methods, over millions to billion particles are required for the realistic simulation. Parallel computing is therefore important for handling such huge computational cost. An efficient parallel implementation of SPH and DEM methods is however known to be difficult especially for the distributed-memory architecture. Lagrangian methods inherently show workload imbalance problem for parallelization with the fixed domain in space, because particles move around and workloads change during the simulation. Therefore dynamic load balance is key technique to perform the large scale SPH and DEM simulation. In this work, we present the parallel implementation technique of SPH and DEM method utilizing dynamic load balancing algorithms toward the high resolution simulation over large domain using the massively parallel super computer system. Our method utilizes the imbalances of the executed time of each MPI process as the nonlinear term of parallel domain decomposition and minimizes them with the Newton like iteration method. In order to perform flexible domain decomposition in space, the slice-grid algorithm is used. Numerical tests show that our approach is suitable for solving the particles with different calculation costs (e.g. boundary particles) as well as the heterogeneous computer architecture. We analyze the parallel efficiency and scalability on the super computer systems (K-computer, Earth simulator 3, etc.).

3-D Electromagnetic field analysis of wireless power transfer system using K computer

NASA Astrophysics Data System (ADS)

Kawase, Yoshihiro; Yamaguchi, Tadashi; Murashita, Masaya; Tsukada, Shota; Ota, Tomohiro; Yamamoto, Takeshi

2018-05-01

We analyze the electromagnetic field of a wireless power transfer system using the 3-D parallel finite element method on K computer, which is a super computer in Japan. It is clarified that the electromagnetic field of the wireless power transfer system can be analyzed in a practical time using the parallel computation on K computer, moreover, the accuracy of the loss calculation becomes better as the mesh division of the shield becomes fine.

Computational performance of a smoothed particle hydrodynamics simulation for shared-memory parallel computing

NASA Astrophysics Data System (ADS)

Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide

2015-09-01

The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.

A parallel computational model for GATE simulations.

PubMed

Rannou, F R; Vega-Acevedo, N; El Bitar, Z

2013-12-01

GATE/Geant4 Monte Carlo simulations are computationally demanding applications, requiring thousands of processor hours to produce realistic results. The classical strategy of distributing the simulation of individual events does not apply efficiently for Positron Emission Tomography (PET) experiments, because it requires a centralized coincidence processing and large communication overheads. We propose a parallel computational model for GATE that handles event generation and coincidence processing in a simple and efficient way by decentralizing event generation and processing but maintaining a centralized event and time coordinator. The model is implemented with the inclusion of a new set of factory classes that can run the same executable in sequential or parallel mode. A Mann-Whitney test shows that the output produced by this parallel model in terms of number of tallies is equivalent (but not equal) to its sequential counterpart. Computational performance evaluation shows that the software is scalable and well balanced. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Storing files in a parallel computing system based on user-specified parser function

DOEpatents

Faibish, Sorin; Bent, John M; Tzelnic, Percy; Grider, Gary; Manzanares, Adam; Torres, Aaron

2014-10-21

Techniques are provided for storing files in a parallel computing system based on a user-specified parser function. A plurality of files generated by a distributed application in a parallel computing system are stored by obtaining a parser from the distributed application for processing the plurality of files prior to storage; and storing one or more of the plurality of files in one or more storage nodes of the parallel computing system based on the processing by the parser. The plurality of files comprise one or more of a plurality of complete files and a plurality of sub-files. The parser can optionally store only those files that satisfy one or more semantic requirements of the parser. The parser can also extract metadata from one or more of the files and the extracted metadata can be stored with one or more of the plurality of files and used for searching for files.

Methods and apparatus for capture and storage of semantic information with sub-files in a parallel computing system

DOEpatents

Faibish, Sorin; Bent, John M; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-02-03

Techniques are provided for storing files in a parallel computing system using sub-files with semantically meaningful boundaries. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a plurality of sub-files. The method comprises the steps of obtaining a user specification of semantic information related to the file; providing the semantic information as a data structure description to a data formatting library write function; and storing the semantic information related to the file with one or more of the sub-files in one or more storage nodes of the parallel computing system. The semantic information provides a description of data in the file. The sub-files can be replicated based on semantically meaningful boundaries.

Methods and apparatus for multi-resolution replication of files in a parallel computing system using semantic information

DOEpatents

Faibish, Sorin; Bent, John M.; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-10-20

Techniques are provided for storing files in a parallel computing system using different resolutions. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a sub-file. The method comprises the steps of obtaining semantic information related to the file; generating a plurality of replicas of the file with different resolutions based on the semantic information; and storing the file and the plurality of replicas of the file in one or more storage nodes of the parallel computing system. The different resolutions comprise, for example, a variable number of bits and/or a different sub-set of data elements from the file. A plurality of the sub-files can be merged to reproduce the file.

Parallel compression of data chunks of a shared data object using a log-structured file system

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

Bent, John M.; Faibish, Sorin; Grider, Gary

2016-10-25

Techniques are provided for parallel compression of data chunks being written to a shared object. A client executing on a compute node or a burst buffer node in a parallel computing system stores a data chunk generated by the parallel computing system to a shared data object on a storage node by compressing the data chunk; and providing the data compressed data chunk to the storage node that stores the shared object. The client and storage node may employ Log-Structured File techniques. The compressed data chunk can be de-compressed by the client when the data chunk is read. A storagemore » node stores a data chunk as part of a shared object by receiving a compressed version of the data chunk from a compute node; and storing the compressed version of the data chunk to the shared data object on the storage node.« less

A 3D staggered-grid finite difference scheme for poroelastic wave equation

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai

2014-10-01

Three dimensional numerical modeling has been a viable tool for understanding wave propagation in real media. The poroelastic media can better describe the phenomena of hydrocarbon reservoirs than acoustic and elastic media. However, the numerical modeling in 3D poroelastic media demands significantly more computational capacity, including both computational time and memory. In this paper, we present a 3D poroelastic staggered-grid finite difference (SFD) scheme. During the procedure, parallel computing is implemented to reduce the computational time. Parallelization is based on domain decomposition, and communication between processors is performed using message passing interface (MPI). Parallel analysis shows that the parallelized SFD scheme significantly improves the simulation efficiency and 3D decomposition in domain is the most efficient. We also analyze the numerical dispersion and stability condition of the 3D poroelastic SFD method. Numerical results show that the 3D numerical simulation can provide a real description of wave propagation.

Fencing data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-06-02

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task; the compute nodes coupled for data communications through the PAMI and through data communications resources including at least one segment of shared random access memory; including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers through a segment of shared memory; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

Fencing data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-06-09

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task; the compute nodes coupled for data communications through the PAMI and through data communications resources including at least one segment of shared random access memory; including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers through a segment of shared memory; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

Fencing data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-08-11

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

Fencing data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-06-30

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

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.

The new landscape of parallel computer architecture

NASA Astrophysics Data System (ADS)

Shalf, John

2007-07-01

The past few years has seen a sea change in computer architecture that will impact every facet of our society as every electronic device from cell phone to supercomputer will need to confront parallelism of unprecedented scale. Whereas the conventional multicore approach (2, 4, and even 8 cores) adopted by the computing industry will eventually hit a performance plateau, the highest performance per watt and per chip area is achieved using manycore technology (hundreds or even thousands of cores). However, fully unleashing the potential of the manycore approach to ensure future advances in sustained computational performance will require fundamental advances in computer architecture and programming models that are nothing short of reinventing computing. In this paper we examine the reasons behind the movement to exponentially increasing parallelism, and its ramifications for system design, applications and programming models.

The revised solar array synthesis computer program

NASA Technical Reports Server (NTRS)

1970-01-01

The Revised Solar Array Synthesis Computer Program is described. It is a general-purpose program which computes solar array output characteristics while accounting for the effects of temperature, incidence angle, charged-particle irradiation, and other degradation effects on various solar array configurations in either circular or elliptical orbits. Array configurations may consist of up to 75 solar cell panels arranged in any series-parallel combination not exceeding three series-connected panels in a parallel string and no more than 25 parallel strings in an array. Up to 100 separate solar array current-voltage characteristics, corresponding to 100 equal-time increments during the sunlight illuminated portion of an orbit or any 100 user-specified combinations of incidence angle and temperature, can be computed and printed out during one complete computer execution. Individual panel incidence angles may be computed and printed out at the user's option.

Parallel processing and expert systems

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Lau, Sonie

1991-01-01

Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 90's cannot enjoy an increased level of autonomy without the efficient use of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real time demands are met for large expert systems. Speed-up via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial labs in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems was surveyed. The survey is divided into three major sections: (1) multiprocessors for parallel expert systems; (2) parallel languages for symbolic computations; and (3) measurements of parallelism of expert system. Results to date indicate that the parallelism achieved for these systems is small. In order to obtain greater speed-ups, data parallelism and application parallelism must be exploited.

Using the Parallel Computing Toolbox with MATLAB on the Peregrine System |

Science.gov Websites

parallel pool took %g seconds.\\n', toc) % "single program multiple data" spmd fprintf('Worker %d says Hello World!\\n', labindex) end delete(gcp); % close the parallel pool exit To run the script on a compute node, create the file helloWorld.sub: #!/bin/bash #PBS -l walltime=05:00 #PBS -l nodes=1 #PBS -N

A note on parallel and pipeline computation of fast unitary transforms

NASA Technical Reports Server (NTRS)

Fino, B. J.; Algazi, V. R.

1974-01-01

The parallel and pipeline organization of fast unitary transform algorithms such as the Fast Fourier Transform are discussed. The efficiency is pointed out of a combined parallel-pipeline processor of a transform such as the Haar transform in which 2 to the n minus 1 power hardware butterflies generate a transform of order 2 to the n power every computation cycle.

Portable parallel stochastic optimization for the design of aeropropulsion components

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Rhodes, G. S.

1994-01-01

This report presents the results of Phase 1 research to develop a methodology for performing large-scale Multi-disciplinary Stochastic Optimization (MSO) for the design of aerospace systems ranging from aeropropulsion components to complete aircraft configurations. The current research recognizes that such design optimization problems are computationally expensive, and require the use of either massively parallel or multiple-processor computers. The methodology also recognizes that many operational and performance parameters are uncertain, and that uncertainty must be considered explicitly to achieve optimum performance and cost. The objective of this Phase 1 research was to initialize the development of an MSO methodology that is portable to a wide variety of hardware platforms, while achieving efficient, large-scale parallelism when multiple processors are available. The first effort in the project was a literature review of available computer hardware, as well as review of portable, parallel programming environments. The first effort was to implement the MSO methodology for a problem using the portable parallel programming language, Parallel Virtual Machine (PVM). The third and final effort was to demonstrate the example on a variety of computers, including a distributed-memory multiprocessor, a distributed-memory network of workstations, and a single-processor workstation. Results indicate the MSO methodology can be well-applied towards large-scale aerospace design problems. Nearly perfect linear speedup was demonstrated for computation of optimization sensitivity coefficients on both a 128-node distributed-memory multiprocessor (the Intel iPSC/860) and a network of workstations (speedups of almost 19 times achieved for 20 workstations). Very high parallel efficiencies (75 percent for 31 processors and 60 percent for 50 processors) were also achieved for computation of aerodynamic influence coefficients on the Intel. Finally, the multi-level parallelization strategy that will be needed for large-scale MSO problems was demonstrated to be highly efficient. The same parallel code instructions were used on both platforms, demonstrating portability. There are many applications for which MSO can be applied, including NASA's High-Speed-Civil Transport, and advanced propulsion systems. The use of MSO will reduce design and development time and testing costs dramatically.

User's Guide for TOUGH2-MP - A Massively Parallel Version of the TOUGH2 Code

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

Earth Sciences Division; Zhang, Keni; Zhang, Keni

TOUGH2-MP is a massively parallel (MP) version of the TOUGH2 code, designed for computationally efficient parallel simulation of isothermal and nonisothermal flows of multicomponent, multiphase fluids in one, two, and three-dimensional porous and fractured media. In recent years, computational requirements have become increasingly intensive in large or highly nonlinear problems for applications in areas such as radioactive waste disposal, CO2 geological sequestration, environmental assessment and remediation, reservoir engineering, and groundwater hydrology. The primary objective of developing the parallel-simulation capability is to significantly improve the computational performance of the TOUGH2 family of codes. The particular goal for the parallel simulator ismore » to achieve orders-of-magnitude improvement in computational time for models with ever-increasing complexity. TOUGH2-MP is designed to perform parallel simulation on multi-CPU computational platforms. An earlier version of TOUGH2-MP (V1.0) was based on the TOUGH2 Version 1.4 with EOS3, EOS9, and T2R3D modules, a software previously qualified for applications in the Yucca Mountain project, and was designed for execution on CRAY T3E and IBM SP supercomputers. The current version of TOUGH2-MP (V2.0) includes all fluid property modules of the standard version TOUGH2 V2.0. It provides computationally efficient capabilities using supercomputers, Linux clusters, or multi-core PCs, and also offers many user-friendly features. The parallel simulator inherits all process capabilities from V2.0 together with additional capabilities for handling fractured media from V1.4. This report provides a quick starting guide on how to set up and run the TOUGH2-MP program for users with a basic knowledge of running the (standard) version TOUGH2 code, The report also gives a brief technical description of the code, including a discussion of parallel methodology, code structure, as well as mathematical and numerical methods used. To familiarize users with the parallel code, illustrative sample problems are presented.« less

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

PubMed Central

Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

2008-01-01

Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

A parallel method of atmospheric correction for multispectral high spatial resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhao, Shaoshuai; Ni, Chen; Cao, Jing; Li, Zhengqiang; Chen, Xingfeng; Ma, Yan; Yang, Leiku; Hou, Weizhen; Qie, Lili; Ge, Bangyu; Liu, Li; Xing, Jin

2018-03-01

The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework's flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.

An interactive parallel programming environment applied in atmospheric science

NASA Technical Reports Server (NTRS)

vonLaszewski, G.

1996-01-01

This article introduces an interactive parallel programming environment (IPPE) that simplifies the generation and execution of parallel programs. One of the tasks of the environment is to generate message-passing parallel programs for homogeneous and heterogeneous computing platforms. The parallel programs are represented by using visual objects. This is accomplished with the help of a graphical programming editor that is implemented in Java and enables portability to a wide variety of computer platforms. In contrast to other graphical programming systems, reusable parts of the programs can be stored in a program library to support rapid prototyping. In addition, runtime performance data on different computing platforms is collected in a database. A selection process determines dynamically the software and the hardware platform to be used to solve the problem in minimal wall-clock time. The environment is currently being tested on a Grand Challenge problem, the NASA four-dimensional data assimilation system.

pWeb: A High-Performance, Parallel-Computing Framework for Web-Browser-Based Medical Simulation.

PubMed

Halic, Tansel; Ahn, Woojin; De, Suvranu

2014-01-01

This work presents a pWeb - a new language and compiler for parallelization of client-side compute intensive web applications such as surgical simulations. The recently introduced HTML5 standard has enabled creating unprecedented applications on the web. Low performance of the web browser, however, remains the bottleneck of computationally intensive applications including visualization of complex scenes, real time physical simulations and image processing compared to native ones. The new proposed language is built upon web workers for multithreaded programming in HTML5. The language provides fundamental functionalities of parallel programming languages as well as the fork/join parallel model which is not supported by web workers. The language compiler automatically generates an equivalent parallel script that complies with the HTML5 standard. A case study on realistic rendering for surgical simulations demonstrates enhanced performance with a compact set of instructions.

The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

2016-09-01

The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

A Parallel Numerical Algorithm To Solve Linear Systems Of Equations Emerging From 3D Radiative Transfer

NASA Astrophysics Data System (ADS)

Wichert, Viktoria; Arkenberg, Mario; Hauschildt, Peter H.

2016-10-01

Highly resolved state-of-the-art 3D atmosphere simulations will remain computationally extremely expensive for years to come. In addition to the need for more computing power, rethinking coding practices is necessary. We take a dual approach by introducing especially adapted, parallel numerical methods and correspondingly parallelizing critical code passages. In the following, we present our respective work on PHOENIX/3D. With new parallel numerical algorithms, there is a big opportunity for improvement when iteratively solving the system of equations emerging from the operator splitting of the radiative transfer equation J = ΛS. The narrow-banded approximate Λ-operator Λ* , which is used in PHOENIX/3D, occurs in each iteration step. By implementing a numerical algorithm which takes advantage of its characteristic traits, the parallel code's efficiency is further increased and a speed-up in computational time can be achieved.

Parallel, adaptive finite element methods for conservation laws

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Devine, Karen D.; Flaherty, Joseph E.

1994-01-01

We construct parallel finite element methods for the solution of hyperbolic conservation laws in one and two dimensions. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. A posteriori estimates of spatial errors are obtained by a p-refinement technique using superconvergence at Radau points. The resulting method is of high order and may be parallelized efficiently on MIMD computers. We compare results using different limiting schemes and demonstrate parallel efficiency through computations on an NCUBE/2 hypercube. We also present results using adaptive h- and p-refinement to reduce the computational cost of the method.

The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

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

Nomura, K; Seymour, R; Wang, W

2009-02-17

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

Efficiency of parallel direct optimization

NASA Technical Reports Server (NTRS)

Janies, D. A.; Wheeler, W. C.

2001-01-01

Tremendous progress has been made at the level of sequential computation in phylogenetics. However, little attention has been paid to parallel computation. Parallel computing is particularly suited to phylogenetics because of the many ways large computational problems can be broken into parts that can be analyzed concurrently. In this paper, we investigate the scaling factors and efficiency of random addition and tree refinement strategies using the direct optimization software, POY, on a small (10 slave processors) and a large (256 slave processors) cluster of networked PCs running LINUX. These algorithms were tested on several data sets composed of DNA and morphology ranging from 40 to 500 taxa. Various algorithms in POY show fundamentally different properties within and between clusters. All algorithms are efficient on the small cluster for the 40-taxon data set. On the large cluster, multibuilding exhibits excellent parallel efficiency, whereas parallel building is inefficient. These results are independent of data set size. Branch swapping in parallel shows excellent speed-up for 16 slave processors on the large cluster. However, there is no appreciable speed-up for branch swapping with the further addition of slave processors (>16). This result is independent of data set size. Ratcheting in parallel is efficient with the addition of up to 32 processors in the large cluster. This result is independent of data set size. c2001 The Willi Hennig Society.

Performing a global barrier operation in a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2014-12-09

Executing computing tasks on a parallel computer that includes compute nodes coupled for data communications, where each compute node executes tasks, with one task on each compute node designated as a master task, including: for each task on each compute node until all master tasks have joined a global barrier: determining whether the task is a master task; if the task is not a master task, joining a single local barrier; if the task is a master task, joining the global barrier and the single local barrier only after all other tasks on the compute node have joined the single local barrier.

The CP-PACS parallel computer

NASA Astrophysics Data System (ADS)

Ukawa, Akira

1998-05-01

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

Co-occurrence frequency evaluated with large language corpora boosts semantic priming effects.

PubMed

Brunellière, Angèle; Perre, Laetitia; Tran, ThiMai; Bonnotte, Isabelle

2017-09-01

In recent decades, many computational techniques have been developed to analyse the contextual usage of words in large language corpora. The present study examined whether the co-occurrence frequency obtained from large language corpora might boost purely semantic priming effects. Two experiments were conducted: one with conscious semantic priming, the other with subliminal semantic priming. Both experiments contrasted three semantic priming contexts: an unrelated priming context and two related priming contexts with word pairs that are semantically related and that co-occur either frequently or infrequently. In the conscious priming presentation (166-ms stimulus-onset asynchrony, SOA), a semantic priming effect was recorded in both related priming contexts, which was greater with higher co-occurrence frequency. In the subliminal priming presentation (66-ms SOA), no significant priming effect was shown, regardless of the related priming context. These results show that co-occurrence frequency boosts pure semantic priming effects and are discussed with reference to models of semantic network.

Chaos control in solar fed DC-DC boost converter by optimal parameters using nelder-mead algorithm powered enhanced BFOA

NASA Astrophysics Data System (ADS)

Sudhakar, N.; Rajasekar, N.; Akhil, Saya; Jyotheeswara Reddy, K.

2017-11-01

The boost converter is the most desirable DC-DC power converter for renewable energy applications for its favorable continuous input current characteristics. In other hand, these DC-DC converters known as practical nonlinear systems are prone to several types of nonlinear phenomena including bifurcation, quasiperiodicity, intermittency and chaos. These undesirable effects has to be controlled for maintaining normal periodic operation of the converter and to ensure the stability. This paper presents an effective solution to control the chaos in solar fed DC-DC boost converter since the converter experiences wide range of input power variation which leads to chaotic phenomena. Controlling of chaos is significantly achieved using optimal circuit parameters obtained through Nelder-Mead Enhanced Bacterial Foraging Optimization Algorithm. The optimization renders the suitable parameters in minimum computational time. The results are compared with the traditional methods. The obtained results of the proposed system ensures the operation of the converter within the controllable region.

New Parallel computing framework for radiation transport codes

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

Kostin, M.A.; /Michigan State U., NSCL; Mokhov, N.V.

A new parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. The module is significantly independent of radiation transport codes it can be used with, and is connected to the codes by means of a number of interface functions. The framework was integrated with the MARS15 code, and an effort is under way to deploy it in PHITS. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility canmore » be used in single process calculations as well as in the parallel regime. Several checkpoint files can be merged into one thus combining results of several calculations. The framework also corrects some of the known problems with the scheduling and load balancing found in the original implementations of the parallel computing functionality in MARS15 and PHITS. The framework can be used efficiently on homogeneous systems and networks of workstations, where the interference from the other users is possible.« less

Parallel computation and the basis system

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

Smith, G.R.

1993-05-01

A software package has been written that can facilitate efforts to develop powerful, flexible, and easy-to use programs that can run in single-processor, massively parallel, and distributed computing environments. Particular attention has been given to the difficulties posed by a program consisting of many science packages that represent subsystems of a complicated, coupled system. Methods have been found to maintain independence of the packages by hiding data structures without increasing the communications costs in a parallel computing environment. Concepts developed in this work are demonstrated by a prototype program that uses library routines from two existing software systems, Basis andmore » Parallel Virtual Machine (PVM). Most of the details of these libraries have been encapsulated in routines and macros that could be rewritten for alternative libraries that possess certain minimum capabilities. The prototype software uses a flexible master-and-slaves paradigm for parallel computation and supports domain decomposition with message passing for partitioning work among slaves. Facilities are provided for accessing variables that are distributed among the memories of slaves assigned to subdomains. The software is named PROTOPAR.« less

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

PubMed

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

2017-10-01

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

StrAuto: automation and parallelization of STRUCTURE analysis.

PubMed

Chhatre, Vikram E; Emerson, Kevin J

2017-03-24

Population structure inference using the software STRUCTURE has become an integral part of population genetic studies covering a broad spectrum of taxa including humans. The ever-expanding size of genetic data sets poses computational challenges for this analysis. Although at least one tool currently implements parallel computing to reduce computational overload of this analysis, it does not fully automate the use of replicate STRUCTURE analysis runs required for downstream inference of optimal K. There is pressing need for a tool that can deploy population structure analysis on high performance computing clusters. We present an updated version of the popular Python program StrAuto, to streamline population structure analysis using parallel computing. StrAuto implements a pipeline that combines STRUCTURE analysis with the Evanno Δ K analysis and visualization of results using STRUCTURE HARVESTER. Using benchmarking tests, we demonstrate that StrAuto significantly reduces the computational time needed to perform iterative STRUCTURE analysis by distributing runs over two or more processors. StrAuto is the first tool to integrate STRUCTURE analysis with post-processing using a pipeline approach in addition to implementing parallel computation - a set up ideal for deployment on computing clusters. StrAuto is distributed under the GNU GPL (General Public License) and available to download from http://strauto.popgen.org .

A Parallel Compact Multi-Dimensional Numerical Algorithm with Aeroacoustics Applications

NASA Technical Reports Server (NTRS)

Povitsky, Alex; Morris, Philip J.

1999-01-01

In this study we propose a novel method to parallelize high-order compact numerical algorithms for the solution of three-dimensional PDEs (Partial Differential Equations) in a space-time domain. For this numerical integration most of the computer time is spent in computation of spatial derivatives at each stage of the Runge-Kutta temporal update. The most efficient direct method to compute spatial derivatives on a serial computer is a version of Gaussian elimination for narrow linear banded systems known as the Thomas algorithm. In a straightforward pipelined implementation of the Thomas algorithm processors are idle due to the forward and backward recurrences of the Thomas algorithm. To utilize processors during this time, we propose to use them for either non-local data independent computations, solving lines in the next spatial direction, or local data-dependent computations by the Runge-Kutta method. To achieve this goal, control of processor communication and computations by a static schedule is adopted. Thus, our parallel code is driven by a communication and computation schedule instead of the usual "creative, programming" approach. The obtained parallelization speed-up of the novel algorithm is about twice as much as that for the standard pipelined algorithm and close to that for the explicit DRP algorithm.

Predicting pneumonitis risk: a dosimetric alternative to mean lung dose.

PubMed

Tucker, Susan L; Mohan, Radhe; Liengsawangwong, Raweewan; Martel, Mary K; Liao, Zhongxing

2013-02-01

To determine whether the association between mean lung dose (MLD) and risk of severe (grade ≥3) radiation pneumonitis (RP) depends on the dose distribution pattern to normal lung among patients receiving 3-dimensional conformal radiation therapy for non-small-cell lung cancer. Three cohorts treated with different beam arrangements were identified. One cohort (2-field boost [2FB]) received 2 parallel-opposed (anteroposterior-posteroanterior) fields per fraction initially, followed by a sequential boost delivered using 2 oblique beams. The other 2 cohorts received 3 or 4 straight fields (3FS and 4FS, respectively), ie, all fields were irradiated every day. The incidence of severe RP was plotted against MLD in each cohort, and data were analyzed using the Lyman-Kutcher-Burman (LKB) model. The incidence of grade ≥3 RP rose more steeply as a function of MLD in the 2FB cohort (N=120) than in the 4FS cohort (N=138), with an intermediate slope for the 3FS group (N=99). The estimated volume parameter from the LKB model was n=0.41 (95% confidence interval, 0.15-1.0) and led to a significant improvement in fit (P=.05) compared to a fit with volume parameter fixed at n=1 (the MLD model). Unlike the MLD model, the LKB model with n=0.41 provided a consistent description of the risk of severe RP in all three cohorts (2FB, 3FS, 4FS) simultaneously. When predicting risk of grade ≥3 RP, the mean lung dose does not adequately take into account the effects of high doses. Instead, the effective dose, computed from the LKB model using volume parameter n=0.41, may provide a better dosimetric parameter for predicting RP risk. If confirmed, these findings support the conclusion that for the same MLD, high doses to small lung volumes ("a lot to a little") are worse than low doses to large volumes ("a little to a lot"). Copyright © 2013 Elsevier Inc. All rights reserved.

Hierarchical Parallelization of Gene Differential Association Analysis

PubMed Central

2011-01-01

Background Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Results Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. Conclusions The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels. PMID:21936916

Hierarchical parallelization of gene differential association analysis.

PubMed

Needham, Mark; Hu, Rui; Dwarkadas, Sandhya; Qiu, Xing

2011-09-21

Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels.

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

PubMed

Ng, C M

2013-10-01

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

Efficient computation of aerodynamic influence coefficients for aeroelastic analysis on a transputer network

NASA Technical Reports Server (NTRS)

Janetzke, David C.; Murthy, Durbha V.

1991-01-01

Aeroelastic analysis is multi-disciplinary and computationally expensive. Hence, it can greatly benefit from parallel processing. As part of an effort to develop an aeroelastic capability on a distributed memory transputer network, a parallel algorithm for the computation of aerodynamic influence coefficients is implemented on a network of 32 transputers. The aerodynamic influence coefficients are calculated using a 3-D unsteady aerodynamic model and a parallel discretization. Efficiencies up to 85 percent were demonstrated using 32 processors. The effect of subtask ordering, problem size, and network topology are presented. A comparison to results on a shared memory computer indicates that higher speedup is achieved on the distributed memory system.

An O(log sup 2 N) parallel algorithm for computing the eigenvalues of a symmetric tridiagonal matrix

NASA Technical Reports Server (NTRS)

Swarztrauber, Paul N.

1989-01-01

An O(log sup 2 N) parallel algorithm is presented for computing the eigenvalues of a symmetric tridiagonal matrix using a parallel algorithm for computing the zeros of the characteristic polynomial. The method is based on a quadratic recurrence in which the characteristic polynomial is constructed on a binary tree from polynomials whose degree doubles at each level. Intervals that contain exactly one zero are determined by the zeros of polynomials at the previous level which ensures that different processors compute different zeros. The exact behavior of the polynomials at the interval endpoints is used to eliminate the usual problems induced by finite precision arithmetic.

A multiarchitecture parallel-processing development environment

NASA Technical Reports Server (NTRS)

Townsend, Scott; Blech, Richard; Cole, Gary

1993-01-01

A description is given of the hardware and software of a multiprocessor test bed - the second generation Hypercluster system. The Hypercluster architecture consists of a standard hypercube distributed-memory topology, with multiprocessor shared-memory nodes. By using standard, off-the-shelf hardware, the system can be upgraded to use rapidly improving computer technology. The Hypercluster's multiarchitecture nature makes it suitable for researching parallel algorithms in computational field simulation applications (e.g., computational fluid dynamics). The dedicated test-bed environment of the Hypercluster and its custom-built software allows experiments with various parallel-processing concepts such as message passing algorithms, debugging tools, and computational 'steering'. Such research would be difficult, if not impossible, to achieve on shared, commercial systems.

Eigensolver for a Sparse, Large Hermitian Matrix

NASA Technical Reports Server (NTRS)

Tisdale, E. Robert; Oyafuso, Fabiano; Klimeck, Gerhard; Brown, R. Chris

2003-01-01

A parallel-processing computer program finds a few eigenvalues in a sparse Hermitian matrix that contains as many as 100 million diagonal elements. This program finds the eigenvalues faster, using less memory, than do other, comparable eigensolver programs. This program implements a Lanczos algorithm in the American National Standards Institute/ International Organization for Standardization (ANSI/ISO) C computing language, using the Message Passing Interface (MPI) standard to complement an eigensolver in PARPACK. [PARPACK (Parallel Arnoldi Package) is an extension, to parallel-processing computer architectures, of ARPACK (Arnoldi Package), which is a collection of Fortran 77 subroutines that solve large-scale eigenvalue problems.] The eigensolver runs on Beowulf clusters of computers at the Jet Propulsion Laboratory (JPL).

RAMA: A file system for massively parallel computers

NASA Technical Reports Server (NTRS)

Miller, Ethan L.; Katz, Randy H.

1993-01-01

This paper describes a file system design for massively parallel computers which makes very efficient use of a few disks per processor. This overcomes the traditional I/O bottleneck of massively parallel machines by storing the data on disks within the high-speed interconnection network. In addition, the file system, called RAMA, requires little inter-node synchronization, removing another common bottleneck in parallel processor file systems. Support for a large tertiary storage system can easily be integrated in lo the file system; in fact, RAMA runs most efficiently when tertiary storage is used.

Code Optimization and Parallelization on the Origins: Looking from Users' Perspective

NASA Technical Reports Server (NTRS)

Chang, Yan-Tyng Sherry; Thigpen, William W. (Technical Monitor)

2002-01-01

Parallel machines are becoming the main compute engines for high performance computing. Despite their increasing popularity, it is still a challenge for most users to learn the basic techniques to optimize/parallelize their codes on such platforms. In this paper, we present some experiences on learning these techniques for the Origin systems at the NASA Advanced Supercomputing Division. Emphasis of this paper will be on a few essential issues (with examples) that general users should master when they work with the Origins as well as other parallel systems.

The NAS parallel benchmarks

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

Improvement in the Accuracy of Matching by Different Feature Subspaces in Traffic Sign Recognition

NASA Astrophysics Data System (ADS)

Ihara, Arihito; Fujiyoshi, Hironobu; Takaki, Masanari; Kumon, Hiroaki; Tamatsu, Yukimasa

A technique for recognizing traffic signs from an image taken with an in-vehicle camera has already been proposed as driver's drive assist. SIFT feature is used for traffic sign recognition, because it is robust to changes in scaling and rotating of the traffic sign. However, it is difficult to process in real-time because the computation cost of the SIFT feature extraction and matching is expensive. This paper presents a method of traffic sign recognition based on keypoint classifier by AdaBoost using PCA-SIFT features in different feature subspaces. Each subspace is constructed from gradients of traffic sign images and general images respectively. A detected keypoint is projected to both subspaces, and then the AdaBoost employs to classy into whether the keypoint is on the traffic sign or not. Experimental results show that the computation cost for keypoint matching can be reduced to about 1/2 compared with the conventional method.

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

Bailey, David H.

The NAS Parallel Benchmarks (NPB) are a suite of parallel computer performance benchmarks. They were originally developed at the NASA Ames Research Center in 1991 to assess high-end parallel supercomputers. Although they are no longer used as widely as they once were for comparing high-end system performance, they continue to be studied and analyzed a great deal in the high-performance computing community. The acronym 'NAS' originally stood for the Numerical Aeronautical Simulation Program at NASA Ames. The name of this organization was subsequently changed to the Numerical Aerospace Simulation Program, and more recently to the NASA Advanced Supercomputing Center, althoughmore » the acronym remains 'NAS.' The developers of the original NPB suite were David H. Bailey, Eric Barszcz, John Barton, David Browning, Russell Carter, LeoDagum, Rod Fatoohi, Samuel Fineberg, Paul Frederickson, Thomas Lasinski, Rob Schreiber, Horst Simon, V. Venkatakrishnan and Sisira Weeratunga. The original NAS Parallel Benchmarks consisted of eight individual benchmark problems, each of which focused on some aspect of scientific computing. The principal focus was in computational aerophysics, although most of these benchmarks have much broader relevance, since in a much larger sense they are typical of many real-world scientific computing applications. The NPB suite grew out of the need for a more rational procedure to select new supercomputers for acquisition by NASA. The emergence of commercially available highly parallel computer systems in the late 1980s offered an attractive alternative to parallel vector supercomputers that had been the mainstay of high-end scientific computing. However, the introduction of highly parallel systems was accompanied by a regrettable level of hype, not only on the part of the commercial vendors but even, in some cases, by scientists using the systems. As a result, it was difficult to discern whether the new systems offered any fundamental performance advantage over vector supercomputers, and, if so, which of the parallel offerings would be most useful in real-world scientific computation. In part to draw attention to some of the performance reporting abuses prevalent at the time, the present author wrote a humorous essay 'Twelve Ways to Fool the Masses,' which described in a light-hearted way a number of the questionable ways in which both vendor marketing people and scientists were inflating and distorting their performance results. All of this underscored the need for an objective and scientifically defensible measure to compare performance on these systems.« less

Methodology of modeling and measuring computer architectures for plasma simulations

NASA Technical Reports Server (NTRS)

Wang, L. P. T.

1977-01-01

A brief introduction to plasma simulation using computers and the difficulties on currently available computers is given. Through the use of an analyzing and measuring methodology - SARA, the control flow and data flow of a particle simulation model REM2-1/2D are exemplified. After recursive refinements the total execution time may be greatly shortened and a fully parallel data flow can be obtained. From this data flow, a matched computer architecture or organization could be configured to achieve the computation bound of an application problem. A sequential type simulation model, an array/pipeline type simulation model, and a fully parallel simulation model of a code REM2-1/2D are proposed and analyzed. This methodology can be applied to other application problems which have implicitly parallel nature.

Cloud object store for checkpoints of high performance computing applications using decoupling middleware

DOEpatents

Bent, John M.; Faibish, Sorin; Grider, Gary

2016-04-19

Cloud object storage is enabled for checkpoints of high performance computing applications using a middleware process. A plurality of files, such as checkpoint files, generated by a plurality of processes in a parallel computing system are stored by obtaining said plurality of files from said parallel computing system; converting said plurality of files to objects using a log structured file system middleware process; and providing said objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

Merlin - Massively parallel heterogeneous computing

NASA Technical Reports Server (NTRS)

Wittie, Larry; Maples, Creve

1989-01-01

Hardware and software for Merlin, a new kind of massively parallel computing system, are described. Eight computers are linked as a 300-MIPS prototype to develop system software for a larger Merlin network with 16 to 64 nodes, totaling 600 to 3000 MIPS. These working prototypes help refine a mapped reflective memory technique that offers a new, very general way of linking many types of computer to form supercomputers. Processors share data selectively and rapidly on a word-by-word basis. Fast firmware virtual circuits are reconfigured to match topological needs of individual application programs. Merlin's low-latency memory-sharing interfaces solve many problems in the design of high-performance computing systems. The Merlin prototypes are intended to run parallel programs for scientific applications and to determine hardware and software needs for a future Teraflops Merlin network.

Exploration of operator method digital optical computers for application to NASA

NASA Technical Reports Server (NTRS)

1990-01-01

Digital optical computer design has been focused primarily towards parallel (single point-to-point interconnection) implementation. This architecture is compared to currently developing VHSIC systems. Using demonstrated multichannel acousto-optic devices, a figure of merit can be formulated. The focus is on a figure of merit termed Gate Interconnect Bandwidth Product (GIBP). Conventional parallel optical digital computer architecture demonstrates only marginal competitiveness at best when compared to projected semiconductor implements. Global, analog global, quasi-digital, and full digital interconnects are briefly examined as alternative to parallel digital computer architecture. Digital optical computing is becoming a very tough competitor to semiconductor technology since it can support a very high degree of three dimensional interconnect density and high degrees of Fan-In without capacitive loading effects at very low power consumption levels.

Institutional Computing Executive Group Review of Multi-programmatic & Institutional Computing, Fiscal Year 2005 and 2006

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

Langer, S; Rotman, D; Schwegler, E

The Institutional Computing Executive Group (ICEG) review of FY05-06 Multiprogrammatic and Institutional Computing (M and IC) activities is presented in the attached report. In summary, we find that the M and IC staff does an outstanding job of acquiring and supporting a wide range of institutional computing resources to meet the programmatic and scientific goals of LLNL. The responsiveness and high quality of support given to users and the programs investing in M and IC reflects the dedication and skill of the M and IC staff. M and IC has successfully managed serial capacity, parallel capacity, and capability computing resources.more » Serial capacity computing supports a wide range of scientific projects which require access to a few high performance processors within a shared memory computer. Parallel capacity computing supports scientific projects that require a moderate number of processors (up to roughly 1000) on a parallel computer. Capability computing supports parallel jobs that push the limits of simulation science. M and IC has worked closely with Stockpile Stewardship, and together they have made LLNL a premier institution for computational and simulation science. Such a standing is vital to the continued success of laboratory science programs and to the recruitment and retention of top scientists. This report provides recommendations to build on M and IC's accomplishments and improve simulation capabilities at LLNL. We recommend that institution fully fund (1) operation of the atlas cluster purchased in FY06 to support a few large projects; (2) operation of the thunder and zeus clusters to enable 'mid-range' parallel capacity simulations during normal operation and a limited number of large simulations during dedicated application time; (3) operation of the new yana cluster to support a wide range of serial capacity simulations; (4) improvements to the reliability and performance of the Lustre parallel file system; (5) support for the new GDO petabyte-class storage facility on the green network for use in data intensive external collaborations; and (6) continued support for visualization and other methods for analyzing large simulations. We also recommend that M and IC begin planning in FY07 for the next upgrade of its parallel clusters. LLNL investments in M and IC have resulted in a world-class simulation capability leading to innovative science. We thank the LLNL management for its continued support and thank the M and IC staff for its vision and dedicated efforts to make it all happen.« less

Molecular Sticker Model Stimulation on Silicon for a Maximum Clique Problem

PubMed Central

Ning, Jianguo; Li, Yanmei; Yu, Wen

2015-01-01

Molecular computers (also called DNA computers), as an alternative to traditional electronic computers, are smaller in size but more energy efficient, and have massive parallel processing capacity. However, DNA computers may not outperform electronic computers owing to their higher error rates and some limitations of the biological laboratory. The stickers model, as a typical DNA-based computer, is computationally complete and universal, and can be viewed as a bit-vertically operating machine. This makes it attractive for silicon implementation. Inspired by the information processing method on the stickers computer, we propose a novel parallel computing model called DEM (DNA Electronic Computing Model) on System-on-a-Programmable-Chip (SOPC) architecture. Except for the significant difference in the computing medium—transistor chips rather than bio-molecules—the DEM works similarly to DNA computers in immense parallel information processing. Additionally, a plasma display panel (PDP) is used to show the change of solutions, and helps us directly see the distribution of assignments. The feasibility of the DEM is tested by applying it to compute a maximum clique problem (MCP) with eight vertices. Owing to the limited computing sources on SOPC architecture, the DEM could solve moderate-size problems in polynomial time. PMID:26075867

Computational structures for robotic computations

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Chang, P. R.

1987-01-01

The computational problem of inverse kinematics and inverse dynamics of robot manipulators by taking advantage of parallelism and pipelining architectures is discussed. For the computation of inverse kinematic position solution, a maximum pipelined CORDIC architecture has been designed based on a functional decomposition of the closed-form joint equations. For the inverse dynamics computation, an efficient p-fold parallel algorithm to overcome the recurrence problem of the Newton-Euler equations of motion to achieve the time lower bound of O(log sub 2 n) has also been developed.

[Design and study of parallel computing environment of Monte Carlo simulation for particle therapy planning using a public cloud-computing infrastructure].

PubMed

Yokohama, Noriya

2013-07-01

This report was aimed at structuring the design of architectures and studying performance measurement of a parallel computing environment using a Monte Carlo simulation for particle therapy using a high performance computing (HPC) instance within a public cloud-computing infrastructure. Performance measurements showed an approximately 28 times faster speed than seen with single-thread architecture, combined with improved stability. A study of methods of optimizing the system operations also indicated lower cost.

IPython: components for interactive and parallel computing across disciplines. (Invited)

NASA Astrophysics Data System (ADS)

Perez, F.; Bussonnier, M.; Frederic, J. D.; Froehle, B. M.; Granger, B. E.; Ivanov, P.; Kluyver, T.; Patterson, E.; Ragan-Kelley, B.; Sailer, Z.

2013-12-01

Scientific computing is an inherently exploratory activity that requires constantly cycling between code, data and results, each time adjusting the computations as new insights and questions arise. To support such a workflow, good interactive environments are critical. The IPython project (http://ipython.org) provides a rich architecture for interactive computing with: 1. Terminal-based and graphical interactive consoles. 2. A web-based Notebook system with support for code, text, mathematical expressions, inline plots and other rich media. 3. Easy to use, high performance tools for parallel computing. Despite its roots in Python, the IPython architecture is designed in a language-agnostic way to facilitate interactive computing in any language. This allows users to mix Python with Julia, R, Octave, Ruby, Perl, Bash and more, as well as to develop native clients in other languages that reuse the IPython clients. In this talk, I will show how IPython supports all stages in the lifecycle of a scientific idea: 1. Individual exploration. 2. Collaborative development. 3. Production runs with parallel resources. 4. Publication. 5. Education. In particular, the IPython Notebook provides an environment for "literate computing" with a tight integration of narrative and computation (including parallel computing). These Notebooks are stored in a JSON-based document format that provides an "executable paper": notebooks can be version controlled, exported to HTML or PDF for publication, and used for teaching.

Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures

NASA Technical Reports Server (NTRS)

Biegel, Bryan A. (Technical Monitor); Jost, G.; Jin, H.; Labarta J.; Gimenez, J.; Caubet, J.

2003-01-01

Parallel programming paradigms include process level parallelism, thread level parallelization, and multilevel parallelism. This viewgraph presentation describes a detailed performance analysis of these paradigms for Shared Memory Architecture (SMA). This analysis uses the Paraver Performance Analysis System. The presentation includes diagrams of a flow of useful computations.

Effective Parallel Algorithm Animation

DTIC Science & Technology

1994-03-01

parallel computer. The system incorporates the 14 Parallel Processing System us" r User User UMe PMwuM Progra Propu Plropm ýData Dots Data Daft...that produce meaningful animations. The following sections outline characteristics 146 Animation 0 71 r 40 02 I 5 * *2! 4 Idle Bu~sy Send Recv 7...Event Simulation. Technical Report, Georgia Institute of Technology, 1992. 22. Garey, Michael R . and David S. Johnson. Computers and Intractability: A

Computational mechanics analysis tools for parallel-vector supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Baddourah, Majdi; Qin, Jiangning

1993-01-01

Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigensolution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization search analysis and domain decomposition. The source code for many of these algorithms is available.

Image Processing Using a Parallel Architecture.

DTIC Science & Technology

1987-12-01

ENG/87D-25 Abstract This study developed a set o± low level image processing tools on a parallel computer that allows concurrent processing of images...environment, the set of tools offers a significant reduction in the time required to perform some commonly used image processing operations. vI IMAGE...step toward developing these systems, a structured set of image processing tools was implemented using a parallel computer. More important than

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

PubMed

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Design and Evaluation of "CAPTools"--A Computer Aided Parallelization Toolkit

NASA Technical Reports Server (NTRS)

Yan, Jerry; Frumkin, Michael; Hribar, Michelle; Jin, Haoqiang; Waheed, Abdul; Johnson, Steve; Cross, Jark; Evans, Emyr; Ierotheou, Constantinos; Leggett, Pete;

The Automatic Parallelisation of Scientific Application Codes Using a Computer Aided Parallelisation Toolkit

NASA Technical Reports Server (NTRS)

Ierotheou, C.; Johnson, S.; Leggett, P.; Cross, M.; Evans, E.; Jin, Hao-Qiang; Frumkin, M.; Yan, J.; Biegel, Bryan (Technical Monitor)

2001-01-01

The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. Historically, the lack of a programming standard for using directives and the rather limited performance due to scalability have affected the take-up of this programming model approach. Significant progress has been made in hardware and software technologies, as a result the performance of parallel programs with compiler directives has also made improvements. The introduction of an industrial standard for shared-memory programming with directives, OpenMP, has also addressed the issue of portability. In this study, we have extended the computer aided parallelization toolkit (developed at the University of Greenwich), to automatically generate OpenMP based parallel programs with nominal user assistance. We outline the way in which loop types are categorized and how efficient OpenMP directives can be defined and placed using the in-depth interprocedural analysis that is carried out by the toolkit. We also discuss the application of the toolkit on the NAS Parallel Benchmarks and a number of real-world application codes. This work not only demonstrates the great potential of using the toolkit to quickly parallelize serial programs but also the good performance achievable on up to 300 processors for hybrid message passing and directive-based parallelizations.

Parallel processing and expert systems

NASA Technical Reports Server (NTRS)

Lau, Sonie; Yan, Jerry C.

1991-01-01

Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited.

Xyce parallel electronic simulator users guide, version 6.1

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

Keiter, Eric R; Mei, Ting; Russo, Thomas V.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas; Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers; A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models; Device models that are specifically tailored to meet Sandia's needs, including some radiationaware devices (for Sandia users only); and Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase-a message passing parallel implementation-which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less