Sample records for accelerating scientific computations

  1. XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

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

    Geveci, Berk; Maynard, Robert

    The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respectivemore » features into a new visualization toolkit called VTK-m.« less

  2. Terascale Computing in Accelerator Science and Technology

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

    Ko, Kwok

    2002-08-21

    We have entered the age of ''terascale'' scientific computing. Processors and system architecture both continue to evolve; hundred-teraFLOP computers are expected in the next few years, and petaFLOP computers toward the end of this decade are conceivable. This ever-increasing power to solve previously intractable numerical problems benefits almost every field of science and engineering and is revolutionizing some of them, notably including accelerator physics and technology. At existing accelerators, it will help us optimize performance, expand operational parameter envelopes, and increase reliability. Design decisions for next-generation machines will be informed by unprecedented comprehensive and accurate modeling, as well as computer-aidedmore » engineering; all this will increase the likelihood that even their most advanced subsystems can be commissioned on time, within budget, and up to specifications. Advanced computing is also vital to developing new means of acceleration and exploring the behavior of beams under extreme conditions. With continued progress it will someday become reasonable to speak of a complete numerical model of all phenomena important to a particular accelerator.« less

  3. Commnity Petascale Project for Accelerator Science And Simulation: Advancing Computational Science for Future Accelerators And Accelerator Technologies

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

    Spentzouris, Panagiotis; /Fermilab; Cary, John

    The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors.« less

  4. Scientific Discovery through Advanced Computing in Plasma Science

    NASA Astrophysics Data System (ADS)

    Tang, William

    2005-03-01

    Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations

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

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

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

    The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors. ComPASS is in the first year of executing its plan to develop the next-generation HPC accelerator modeling tools. ComPASS aims to develop an integrated simulation environment that will utilize existing and new accelerator physics modules with petascale capabilities, by employing modern computing and solver technologies. The ComPASS vision is to deliver to accelerator scientists a virtual accelerator and virtual prototyping modeling environment, with the necessary multiphysics, multiscale capabilities. The plan for this development includes delivering accelerator modeling applications appropriate for each stage of the ComPASS software evolution. Such applications are already being used to address challenging problems in accelerator design and optimization. The Com

  6. Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators

    PubMed Central

    Wang, Wei; Xu, Lifan; Cavazos, John; Huang, Howie H.; Kay, Matthew

    2014-01-01

    Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requires a high level of expertise that is not available to many scientists. This, plus the fact that parallelized code is usually not portable to different architectures, creates major challenges for exploiting the full capabilities of modern computational accelerators. In this work, we sought to overcome these challenges by studying how to achieve both automated parallelization using OpenACC and enhanced portability using OpenCL. We applied our parallelization schemes using GPUs as well as Intel Many Integrated Core (MIC) coprocessor to reduce the run time of wave propagation simulations. We used a well-established 2D cardiac action potential model as a specific case-study. To the best of our knowledge, we are the first to study auto-parallelization of 2D cardiac wave propagation simulations using OpenACC. Our results identify several approaches that provide substantial speedups. The OpenACC-generated GPU code achieved more than speedup above the sequential implementation and required the addition of only a few OpenACC pragmas to the code. An OpenCL implementation provided speedups on GPUs of at least faster than the sequential implementation and faster than a parallelized OpenMP implementation. An implementation of OpenMP on Intel MIC coprocessor provided speedups of with only a few code changes to the sequential implementation. We highlight that OpenACC provides an automatic, efficient, and portable approach to achieve parallelization of 2D cardiac wave simulations on GPUs. Our approach of using OpenACC, OpenCL, and OpenMP to parallelize this particular model on modern computational accelerators should be applicable to other computational models of wave propagation in

  7. Experimental, Theoretical and Computational Studies of Plasma-Based Concepts for Future High Energy Accelerators

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

    Joshi, Chan; Mori, W.

    2013-10-21

    This is the final report on the DOE grant number DE-FG02-92ER40727 titled, “Experimental, Theoretical and Computational Studies of Plasma-Based Concepts for Future High Energy Accelerators.” During this grant period the UCLA program on Advanced Plasma Based Accelerators, headed by Professor C. Joshi has made many key scientific advances and trained a generation of students, many of whom have stayed in this research field and even started research programs of their own. In this final report however, we will focus on the last three years of the grant and report on the scientific progress made in each of the four tasksmore » listed under this grant. Four tasks are focused on: Plasma Wakefield Accelerator Research at FACET, SLAC National Accelerator Laboratory, In House Research at UCLA’s Neptune and 20 TW Laser Laboratories, Laser-Wakefield Acceleration (LWFA) in Self Guided Regime: Experiments at the Callisto Laser at LLNL, and Theory and Simulations. Major scientific results have been obtained in each of the four tasks described in this report. These have led to publications in the prestigious scientific journals, graduation and continued training of high quality Ph.D. level students and have kept the U.S. at the forefront of plasma-based accelerators research field.« less

  8. Scientific Computing Paradigm

    NASA Technical Reports Server (NTRS)

    VanZandt, John

    1994-01-01

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

  9. 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.

  10. Scientific Computing

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

    Fermilab

    2017-09-01

    Scientists, engineers and programmers at Fermilab are tackling today’s most challenging computational problems. Their solutions, motivated by the needs of worldwide research in particle physics and accelerators, help America stay at the forefront of innovation.

  11. Accelerating scientific discovery : 2007 annual report.

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

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

    2008-11-14

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

  12. Parallel processing for scientific computations

    NASA Technical Reports Server (NTRS)

    Alkhatib, Hasan S.

    1995-01-01

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

  13. Accelerating scientific publication in biology

    PubMed Central

    Vale, Ronald D.

    2015-01-01

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

  14. Computational Accelerator Physics. Proceedings

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

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

    1997-04-01

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

  15. Delivering Insight The History of the Accelerated Strategic Computing Initiative

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

    Larzelere II, A R

    2007-01-03

    The history of the Accelerated Strategic Computing Initiative (ASCI) tells of the development of computational simulation into a third fundamental piece of the scientific method, on a par with theory and experiment. ASCI did not invent the idea, nor was it alone in bringing it to fruition. But ASCI provided the wherewithal - hardware, software, environment, funding, and, most of all, the urgency - that made it happen. On October 1, 2005, the Initiative completed its tenth year of funding. The advances made by ASCI over its first decade are truly incredible. Lawrence Livermore, Los Alamos, and Sandia National Laboratories,more » along with leadership provided by the Department of Energy's Defense Programs Headquarters, fundamentally changed computational simulation and how it is used to enable scientific insight. To do this, astounding advances were made in simulation applications, computing platforms, and user environments. ASCI dramatically changed existing - and forged new - relationships, both among the Laboratories and with outside partners. By its tenth anniversary, despite daunting challenges, ASCI had accomplished all of the major goals set at its beginning. The history of ASCI is about the vision, leadership, endurance, and partnerships that made these advances possible.« less

  16. Institute for scientific computing research;fiscal year 1999 annual report

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

    Keyes, D

    2000-03-28

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

  17. High-End Scientific Computing

    EPA Pesticide Factsheets

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

  18. Computing through Scientific Abstractions in SysBioPS

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

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

    2004-10-13

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

  19. 76 FR 31945 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-02

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

  20. 75 FR 9887 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-04

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

  1. 76 FR 9765 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-22

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

  2. Accelerating Climate Simulations Through Hybrid Computing

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  3. Computers and Computation. Readings from Scientific American.

    ERIC Educational Resources Information Center

    Fenichel, Robert R.; Weizenbaum, Joseph

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

  4. Joint the Center for Applied Scientific Computing

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

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

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

  5. 75 FR 64720 - DOE/Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-20

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

  6. 77 FR 45345 - DOE/Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-31

    ... Recompetition results for Scientific Discovery through Advanced Computing (SciDAC) applications Co-design Public... DEPARTMENT OF ENERGY DOE/Advanced Scientific Computing Advisory Committee AGENCY: Office of... the Advanced Scientific Computing Advisory Committee (ASCAC). The Federal Advisory Committee Act (Pub...

  7. 75 FR 43518 - Advanced Scientific Computing Advisory Committee; Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-26

    ... DEPARTMENT OF ENERGY Advanced Scientific Computing Advisory Committee; Meeting AGENCY: Office of... Scientific Computing Advisory Committee (ASCAC). Federal Advisory Committee Act (Pub. L. 92-463, 86 Stat. 770...: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building; U. S...

  8. 76 FR 41234 - Advanced Scientific Computing Advisory Committee Charter Renewal

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-13

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

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

    PubMed

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

    2013-01-28

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

  10. Accelerating artificial intelligence with reconfigurable computing

    NASA Astrophysics Data System (ADS)

    Cieszewski, Radoslaw

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

  11. Quantum Accelerators for High-performance Computing Systems

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

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

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

  12. Advanced Computing Tools and Models for Accelerator Physics

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

    Ryne, Robert; Ryne, Robert D.

    2008-06-11

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

  13. Computing Models for FPGA-Based Accelerators

    PubMed Central

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

    2011-01-01

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

  14. 78 FR 41046 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-09

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

  15. Comparisons of some large scientific computers

    NASA Technical Reports Server (NTRS)

    Credeur, K. R.

    1981-01-01

    In 1975, the National Aeronautics and Space Administration (NASA) began studies to assess the technical and economic feasibility of developing a computer having sustained computational speed of one billion floating point operations per second and a working memory of at least 240 million words. Such a powerful computer would allow computational aerodynamics to play a major role in aeronautical design and advanced fluid dynamics research. Based on favorable results from these studies, NASA proceeded with developmental plans. The computer was named the Numerical Aerodynamic Simulator (NAS). To help insure that the estimated cost, schedule, and technical scope were realistic, a brief study was made of past large scientific computers. Large discrepancies between inception and operation in scope, cost, or schedule were studied so that they could be minimized with NASA's proposed new compter. The main computers studied were the ILLIAC IV, STAR 100, Parallel Element Processor Ensemble (PEPE), and Shuttle Mission Simulator (SMS) computer. Comparison data on memory and speed were also obtained on the IBM 650, 704, 7090, 360-50, 360-67, 360-91, and 370-195; the CDC 6400, 6600, 7600, CYBER 203, and CYBER 205; CRAY 1; and the Advanced Scientific Computer (ASC). A few lessons learned conclude the report.

  16. Accelerating scientific computations with mixed precision algorithms

    NASA Astrophysics Data System (ADS)

    Baboulin, Marc; Buttari, Alfredo; Dongarra, Jack; Kurzak, Jakub; Langou, Julie; Langou, Julien; Luszczek, Piotr; Tomov, Stanimire

    2009-12-01

    On modern architectures, the performance of 32-bit operations is often at least twice as fast as the performance of 64-bit operations. By using a combination of 32-bit and 64-bit floating point arithmetic, the performance of many dense and sparse linear algebra algorithms can be significantly enhanced while maintaining the 64-bit accuracy of the resulting solution. The approach presented here can apply not only to conventional processors but also to other technologies such as Field Programmable Gate Arrays (FPGA), Graphical Processing Units (GPU), and the STI Cell BE processor. Results on modern processor architectures and the STI Cell BE are presented. Program summaryProgram title: ITER-REF Catalogue identifier: AECO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECO_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 7211 No. of bytes in distributed program, including test data, etc.: 41 862 Distribution format: tar.gz Programming language: FORTRAN 77 Computer: desktop, server Operating system: Unix/Linux RAM: 512 Mbytes Classification: 4.8 External routines: BLAS (optional) Nature of problem: On modern architectures, the performance of 32-bit operations is often at least twice as fast as the performance of 64-bit operations. By using a combination of 32-bit and 64-bit floating point arithmetic, the performance of many dense and sparse linear algebra algorithms can be significantly enhanced while maintaining the 64-bit accuracy of the resulting solution. Solution method: Mixed precision algorithms stem from the observation that, in many cases, a single precision solution of a problem can be refined to the point where double precision accuracy is achieved. A common approach to the solution of linear systems, either dense or sparse, is to perform the LU

  17. Convergence acceleration of viscous flow computations

    NASA Technical Reports Server (NTRS)

    Johnson, G. M.

    1982-01-01

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

  18. Exploring Cloud Computing for Large-scale Scientific Applications

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

    Lin, Guang; Han, Binh; Yin, Jian

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

  19. Accelerating Climate and Weather Simulations through Hybrid Computing

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  20. OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

    NASA Astrophysics Data System (ADS)

    Strayer, Michael

    2005-01-01

    with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds

  1. Parallel processing for scientific computations

    NASA Technical Reports Server (NTRS)

    Alkhatib, Hasan S.

    1991-01-01

    The main contribution of the effort in the last two years is the introduction of the MOPPS system. After doing extensive literature search, we introduced the system which is described next. MOPPS employs a new solution to the problem of managing programs which solve scientific and engineering applications on a distributed processing environment. Autonomous computers cooperate efficiently in solving large scientific problems with this solution. MOPPS has the advantage of not assuming the presence of any particular network topology or configuration, computer architecture, or operating system. It imposes little overhead on network and processor resources while efficiently managing programs concurrently. The core of MOPPS is an intelligent program manager that builds a knowledge base of the execution performance of the parallel programs it is managing under various conditions. The manager applies this knowledge to improve the performance of future runs. The program manager learns from experience.

  2. Introduction to the LaRC central scientific computing complex

    NASA Technical Reports Server (NTRS)

    Shoosmith, John N.

    1993-01-01

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

  3. High-performance scientific computing in the cloud

    NASA Astrophysics Data System (ADS)

    Jorissen, Kevin; Vila, Fernando; Rehr, John

    2011-03-01

    Cloud computing has the potential to open up high-performance computational science to a much broader class of researchers, owing to its ability to provide on-demand, virtualized computational resources. However, before such approaches can become commonplace, user-friendly tools must be developed that hide the unfamiliar cloud environment and streamline the management of cloud resources for many scientific applications. We have recently shown that high-performance cloud computing is feasible for parallelized x-ray spectroscopy calculations. We now present benchmark results for a wider selection of scientific applications focusing on electronic structure and spectroscopic simulation software in condensed matter physics. These applications are driven by an improved portable interface that can manage virtual clusters and run various applications in the cloud. We also describe a next generation of cluster tools, aimed at improved performance and a more robust cluster deployment. Supported by NSF grant OCI-1048052.

  4. A coarse-grid projection method for accelerating incompressible flow computations

    NASA Astrophysics Data System (ADS)

    San, Omer; Staples, Anne E.

    2013-01-01

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

  5. A high performance scientific cloud computing environment for materials simulations

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Kellogg, L. H.

    2016-12-01

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

  7. 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.

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

    DOE PAGES

    Amundson, James; Macridin, Alexandru; Spentzouris, Panagiotis

    2014-07-28

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

  9. Computational thinking and thinking about computing

    PubMed Central

    Wing, Jeannette M.

    2008-01-01

    Computational thinking will influence everyone in every field of endeavour. This vision poses a new educational challenge for our society, especially for our children. In thinking about computing, we need to be attuned to the three drivers of our field: science, technology and society. Accelerating technological advances and monumental societal demands force us to revisit the most basic scientific questions of computing. PMID:18672462

  10. Accelerating sino-atrium computer simulations with graphic processing units.

    PubMed

    Zhang, Hong; Xiao, Zheng; Lin, Shien-fong

    2015-01-01

    Sino-atrial node cells (SANCs) play a significant role in rhythmic firing. To investigate their role in arrhythmia and interactions with the atrium, computer simulations based on cellular dynamic mathematical models are generally used. However, the large-scale computation usually makes research difficult, given the limited computational power of Central Processing Units (CPUs). In this paper, an accelerating approach with Graphic Processing Units (GPUs) is proposed in a simulation consisting of the SAN tissue and the adjoining atrium. By using the operator splitting method, the computational task was made parallel. Three parallelization strategies were then put forward. The strategy with the shortest running time was further optimized by considering block size, data transfer and partition. The results showed that for a simulation with 500 SANCs and 30 atrial cells, the execution time taken by the non-optimized program decreased 62% with respect to a serial program running on CPU. The execution time decreased by 80% after the program was optimized. The larger the tissue was, the more significant the acceleration became. The results demonstrated the effectiveness of the proposed GPU-accelerating methods and their promising applications in more complicated biological simulations.

  11. Software Engineering for Scientific Computer Simulations

    NASA Astrophysics Data System (ADS)

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

    2004-11-01

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

  12. GPU-accelerated computation of electron transfer.

    PubMed

    Höfinger, Siegfried; Acocella, Angela; Pop, Sergiu C; Narumi, Tetsu; Yasuoka, Kenji; Beu, Titus; Zerbetto, Francesco

    2012-11-05

    Electron transfer is a fundamental process that can be studied with the help of computer simulation. The underlying quantum mechanical description renders the problem a computationally intensive application. In this study, we probe the graphics processing unit (GPU) for suitability to this type of problem. Time-critical components are identified via profiling of an existing implementation and several different variants are tested involving the GPU at increasing levels of abstraction. A publicly available library supporting basic linear algebra operations on the GPU turns out to accelerate the computation approximately 50-fold with minor dependence on actual problem size. The performance gain does not compromise numerical accuracy and is of significant value for practical purposes. Copyright © 2012 Wiley Periodicals, Inc.

  13. A Computing Environment to Support Repeatable Scientific Big Data Experimentation of World-Wide Scientific Literature

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

    Schlicher, Bob G; Kulesz, James J; Abercrombie, Robert K

    A principal tenant of the scientific method is that experiments must be repeatable and relies on ceteris paribus (i.e., all other things being equal). As a scientific community, involved in data sciences, we must investigate ways to establish an environment where experiments can be repeated. We can no longer allude to where the data comes from, we must add rigor to the data collection and management process from which our analysis is conducted. This paper describes a computing environment to support repeatable scientific big data experimentation of world-wide scientific literature, and recommends a system that is housed at the Oakmore » Ridge National Laboratory in order to provide value to investigators from government agencies, academic institutions, and industry entities. The described computing environment also adheres to the recently instituted digital data management plan mandated by multiple US government agencies, which involves all stages of the digital data life cycle including capture, analysis, sharing, and preservation. It particularly focuses on the sharing and preservation of digital research data. The details of this computing environment are explained within the context of cloud services by the three layer classification of Software as a Service , Platform as a Service , and Infrastructure as a Service .« less

  14. ASCR Cybersecurity for Scientific Computing Integrity - Research Pathways and Ideas Workshop

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

    Peisert, Sean; Potok, Thomas E.; Jones, Todd

    At the request of the U.S. Department of Energy's (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program office, a workshop was held June 2-3, 2015, in Gaithersburg, MD, to identify potential long term (10 to +20 year) cybersecurity fundamental basic research and development challenges, strategies and roadmap facing future high performance computing (HPC), networks, data centers, and extreme-scale scientific user facilities. This workshop was a follow-on to the workshop held January 7-9, 2015, in Rockville, MD, that examined higher level ideas about scientific computing integrity specific to the mission of the DOE Office of Science. Issues includedmore » research computation and simulation that takes place on ASCR computing facilities and networks, as well as network-connected scientific instruments, such as those run by various DOE Office of Science programs. Workshop participants included researchers and operational staff from DOE national laboratories, as well as academic researchers and industry experts. Participants were selected based on the submission of abstracts relating to the topics discussed in the previous workshop report [1] and also from other ASCR reports, including "Abstract Machine Models and Proxy Architectures for Exascale Computing" [27], the DOE "Preliminary Conceptual Design for an Exascale Computing Initiative" [28], and the January 2015 machine learning workshop [29]. The workshop was also attended by several observers from DOE and other government agencies. The workshop was divided into three topic areas: (1) Trustworthy Supercomputing, (2) Extreme-Scale Data, Knowledge, and Analytics for Understanding and Improving Cybersecurity, and (3) Trust within High-end Networking and Data Centers. Participants were divided into three corresponding teams based on the category of their abstracts. The workshop began with a series of talks from the program manager and workshop chair, followed by the leaders for each of the

  15. I/O-Efficient Scientific Computation Using TPIE

    NASA Technical Reports Server (NTRS)

    Vengroff, Darren Erik; Vitter, Jeffrey Scott

    1996-01-01

    In recent years, input/output (I/O)-efficient algorithms for a wide variety of problems have appeared in the literature. However, systems specifically designed to assist programmers in implementing such algorithms have remained scarce. TPIE is a system designed to support I/O-efficient paradigms for problems from a variety of domains, including computational geometry, graph algorithms, and scientific computation. The TPIE interface frees programmers from having to deal not only with explicit read and write calls, but also the complex memory management that must be performed for I/O-efficient computation. In this paper we discuss applications of TPIE to problems in scientific computation. We discuss algorithmic issues underlying the design and implementation of the relevant components of TPIE and present performance results of programs written to solve a series of benchmark problems using our current TPIE prototype. Some of the benchmarks we present are based on the NAS parallel benchmarks while others are of our own creation. We demonstrate that the central processing unit (CPU) overhead required to manage I/O is small and that even with just a single disk, the I/O overhead of I/O-efficient computation ranges from negligible to the same order of magnitude as CPU time. We conjecture that if we use a number of disks in parallel this overhead can be all but eliminated.

  16. DOE Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee Report on Scientific and Technical Information

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

    Hey, Tony; Agarwal, Deborah; Borgman, Christine

    The Advanced Scientific Computing Advisory Committee (ASCAC) was charged to form a standing subcommittee to review the Department of Energy’s Office of Scientific and Technical Information (OSTI) and to begin by assessing the quality and effectiveness of OSTI’s recent and current products and services and to comment on its mission and future directions in the rapidly changing environment for scientific publication and data. The Committee met with OSTI staff and reviewed available products, services and other materials. This report summaries their initial findings and recommendations.

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

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

    Arumugam, Kamesh

    Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore,more » these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to

  18. Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

    ERIC Educational Resources Information Center

    Pallant, Amy; Lee, Hee-Sun

    2015-01-01

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

  19. Scientific Visualization and Computational Science: Natural Partners

    NASA Technical Reports Server (NTRS)

    Uselton, Samuel P.; Lasinski, T. A. (Technical Monitor)

    1995-01-01

    Scientific visualization is developing rapidly, stimulated by computational science, which is gaining acceptance as a third alternative to theory and experiment. Computational science is based on numerical simulations of mathematical models derived from theory. But each individual simulation is like a hypothetical experiment; initial conditions are specified, and the result is a record of the observed conditions. Experiments can be simulated for situations that can not really be created or controlled. Results impossible to measure can be computed.. Even for observable values, computed samples are typically much denser. Numerical simulations also extend scientific exploration where the mathematics is analytically intractable. Numerical simulations are used to study phenomena from subatomic to intergalactic scales and from abstract mathematical structures to pragmatic engineering of everyday objects. But computational science methods would be almost useless without visualization. The obvious reason is that the huge amounts of data produced require the high bandwidth of the human visual system, and interactivity adds to the power. Visualization systems also provide a single context for all the activities involved from debugging the simulations, to exploring the data, to communicating the results. Most of the presentations today have their roots in image processing, where the fundamental task is: Given an image, extract information about the scene. Visualization has developed from computer graphics, and the inverse task: Given a scene description, make an image. Visualization extends the graphics paradigm by expanding the possible input. The goal is still to produce images; the difficulty is that the input is not a scene description displayable by standard graphics methods. Visualization techniques must either transform the data into a scene description or extend graphics techniques to display this odd input. Computational science is a fertile field for visualization

  20. Educational NASA Computational and Scientific Studies (enCOMPASS)

    NASA Technical Reports Server (NTRS)

    Memarsadeghi, Nargess

    2013-01-01

    Educational NASA Computational and Scientific Studies (enCOMPASS) is an educational project of NASA Goddard Space Flight Center aimed at bridging the gap between computational objectives and needs of NASA's scientific research, missions, and projects, and academia's latest advances in applied mathematics and computer science. enCOMPASS achieves this goal via bidirectional collaboration and communication between NASA and academia. Using developed NASA Computational Case Studies in university computer science/engineering and applied mathematics classes is a way of addressing NASA's goals of contributing to the Science, Technology, Education, and Math (STEM) National Objective. The enCOMPASS Web site at http://encompass.gsfc.nasa.gov provides additional information. There are currently nine enCOMPASS case studies developed in areas of earth sciences, planetary sciences, and astrophysics. Some of these case studies have been published in AIP and IEEE's Computing in Science and Engineering magazines. A few university professors have used enCOMPASS case studies in their computational classes and contributed their findings to NASA scientists. In these case studies, after introducing the science area, the specific problem, and related NASA missions, students are first asked to solve a known problem using NASA data and past approaches used and often published in a scientific/research paper. Then, after learning about the NASA application and related computational tools and approaches for solving the proposed problem, students are given a harder problem as a challenge for them to research and develop solutions for. This project provides a model for NASA scientists and engineers on one side, and university students, faculty, and researchers in computer science and applied mathematics on the other side, to learn from each other's areas of work, computational needs and solutions, and the latest advances in research and development. This innovation takes NASA science and

  1. Understanding the Performance and Potential of Cloud Computing for Scientific Applications

    DOE PAGES

    Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin; ...

    2015-02-19

    In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

  2. Understanding the Performance and Potential of Cloud Computing for Scientific Applications

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

    Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin

    In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

  3. 78 FR 6087 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-29

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

  4. GPU acceleration of Dock6's Amber scoring computation.

    PubMed

    Yang, Hailong; Zhou, Qiongqiong; Li, Bo; Wang, Yongjian; Luan, Zhongzhi; Qian, Depei; Li, Hanlu

    2010-01-01

    Dressing the problem of virtual screening is a long-term goal in the drug discovery field, which if properly solved, can significantly shorten new drugs' R&D cycle. The scoring functionality that evaluates the fitness of the docking result is one of the major challenges in virtual screening. In general, scoring functionality in docking requires a large amount of floating-point calculations, which usually takes several weeks or even months to be finished. This time-consuming procedure is unacceptable, especially when highly fatal and infectious virus arises such as SARS and H1N1, which forces the scoring task to be done in a limited time. This paper presents how to leverage the computational power of GPU to accelerate Dock6's (http://dock.compbio.ucsf.edu/DOCK_6/) Amber (J. Comput. Chem. 25: 1157-1174, 2004) scoring with NVIDIA CUDA (NVIDIA Corporation Technical Staff, Compute Unified Device Architecture - Programming Guide, NVIDIA Corporation, 2008) (Compute Unified Device Architecture) platform. We also discuss many factors that will greatly influence the performance after porting the Amber scoring to GPU, including thread management, data transfer, and divergence hidden. Our experiments show that the GPU-accelerated Amber scoring achieves a 6.5× speedup with respect to the original version running on AMD dual-core CPU for the same problem size. This acceleration makes the Amber scoring more competitive and efficient for large-scale virtual screening problems.

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

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

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

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

  6. Singularity: Scientific containers for mobility of compute.

    PubMed

    Kurtzer, Gregory M; Sochat, Vanessa; Bauer, Michael W

    2017-01-01

    Here we present Singularity, software developed to bring containers and reproducibility to scientific computing. Using Singularity containers, developers can work in reproducible environments of their choosing and design, and these complete environments can easily be copied and executed on other platforms. Singularity is an open source initiative that harnesses the expertise of system and software engineers and researchers alike, and integrates seamlessly into common workflows for both of these groups. As its primary use case, Singularity brings mobility of computing to both users and HPC centers, providing a secure means to capture and distribute software and compute environments. This ability to create and deploy reproducible environments across these centers, a previously unmet need, makes Singularity a game changing development for computational science.

  7. Singularity: Scientific containers for mobility of compute

    PubMed Central

    Kurtzer, Gregory M.; Bauer, Michael W.

    2017-01-01

    Here we present Singularity, software developed to bring containers and reproducibility to scientific computing. Using Singularity containers, developers can work in reproducible environments of their choosing and design, and these complete environments can easily be copied and executed on other platforms. Singularity is an open source initiative that harnesses the expertise of system and software engineers and researchers alike, and integrates seamlessly into common workflows for both of these groups. As its primary use case, Singularity brings mobility of computing to both users and HPC centers, providing a secure means to capture and distribute software and compute environments. This ability to create and deploy reproducible environments across these centers, a previously unmet need, makes Singularity a game changing development for computational science. PMID:28494014

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

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

    Crabtree, George; Glotzer, Sharon; McCurdy, Bill

    abating, has enabled the development of computer simulations and models of unprecedented fidelity. We are at the threshold of a new era where the integrated synthesis, characterization, and modeling of complex materials and chemical processes will transform our ability to understand and design new materials and chemistries with predictive power. In turn, this predictive capability will transform technological innovation by accelerating the development and deployment of new materials and processes in products and manufacturing. Harnessing the potential of computational science and engineering for the discovery and development of materials and chemical processes is essential to maintaining leadership in these foundational fields that underpin energy technologies and industrial competitiveness. Capitalizing on the opportunities presented by simulation-based engineering and science in materials and chemistry will require an integration of experimental capabilities with theoretical and computational modeling; the development of a robust and sustainable infrastructure to support the development and deployment of advanced computational models; and the assembly of a community of scientists and engineers to implement this integration and infrastructure. This community must extend to industry, where incorporating predictive materials science and chemistry into design tools can accelerate the product development cycle and drive economic competitiveness. The confluence of new theories, new materials synthesis capabilities, and new computer platforms has created an unprecedented opportunity to implement a "materials-by-design" paradigm with wide-ranging benefits in technological innovation and scientific discovery. The Workshop on Computational Materials Science and Chemistry for Innovation was convened in Bethesda, Maryland, on July 26-27, 2010. Sponsored by the Department of Energy (DOE) Offices of Advanced Scientific Computing Research and Basic Energy Sciences, the workshop

  9. Multi-GPU Jacobian accelerated computing for soft-field tomography.

    PubMed

    Borsic, A; Attardo, E A; Halter, R J

    2012-10-01

    Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use finite element models (FEMs) to represent the volume of interest and solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are 3D. Although the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in electrical impedance tomography (EIT) applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15-20 min with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Furthermore, providing high-speed reconstructions is essential for some promising clinical application of EIT. For 3D problems, 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In this work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with the use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20

  10. Multi-GPU Jacobian Accelerated Computing for Soft Field Tomography

    PubMed Central

    Borsic, A.; Attardo, E. A.; Halter, R. J.

    2012-01-01

    Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use Finite Element Models to represent the volume of interest and to solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are three-dimensional. Though the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in Electrical Impedance Tomography applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15 to 20 minutes with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Further, providing high-speed reconstructions are essential for some promising clinical application of EIT. For 3D problems 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In the present work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have a much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of

  11. Multidimensional Environmental Data Resource Brokering on Computational Grids and Scientific Clouds

    NASA Astrophysics Data System (ADS)

    Montella, Raffaele; Giunta, Giulio; Laccetti, Giuliano

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

  12. Computer network access to scientific information systems for minority universities

    NASA Astrophysics Data System (ADS)

    Thomas, Valerie L.; Wakim, Nagi T.

    1993-08-01

    The evolution of computer networking technology has lead to the establishment of a massive networking infrastructure which interconnects various types of computing resources at many government, academic, and corporate institutions. A large segment of this infrastructure has been developed to facilitate information exchange and resource sharing within the scientific community. The National Aeronautics and Space Administration (NASA) supports both the development and the application of computer networks which provide its community with access to many valuable multi-disciplinary scientific information systems and on-line databases. Recognizing the need to extend the benefits of this advanced networking technology to the under-represented community, the National Space Science Data Center (NSSDC) in the Space Data and Computing Division at the Goddard Space Flight Center has developed the Minority University-Space Interdisciplinary Network (MU-SPIN) Program: a major networking and education initiative for Historically Black Colleges and Universities (HBCUs) and Minority Universities (MUs). In this paper, we will briefly explain the various components of the MU-SPIN Program while highlighting how, by providing access to scientific information systems and on-line data, it promotes a higher level of collaboration among faculty and students and NASA scientists.

  13. Ontology-Driven Discovery of Scientific Computational Entities

    ERIC Educational Resources Information Center

    Brazier, Pearl W.

    2010-01-01

    Many geoscientists use modern computational resources, such as software applications, Web services, scientific workflows and datasets that are readily available on the Internet, to support their research and many common tasks. These resources are often shared via human contact and sometimes stored in data portals; however, they are not necessarily…

  14. Hardware accelerated high performance neutron transport computation based on AGENT methodology

    NASA Astrophysics Data System (ADS)

    Xiao, Shanjie

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

  15. RAPPORT: running scientific high-performance computing applications on the cloud.

    PubMed

    Cohen, Jeremy; Filippis, Ioannis; Woodbridge, Mark; Bauer, Daniela; Hong, Neil Chue; Jackson, Mike; Butcher, Sarah; Colling, David; Darlington, John; Fuchs, Brian; Harvey, Matt

    2013-01-28

    Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of cloud infrastructure for running many types of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by cloud platforms.

  16. Accelerating Neoproterozoic Research through Scientific Drilling

    NASA Astrophysics Data System (ADS)

    Condon, Daniel; Prave, Anthony; Boggiani, Paulo; Fike, David; Halverson, Galen; Kasemann, Simone; Knoll, Andrew; Zhu, Maoyan

    2014-05-01

    The Neoproterozoic Era (1.0 to 0.541 Ga) and earliest Cambrian (541 to ca. 520 Ma) records geologic changes unlike any other in Earth history: supercontinental tectonics of Rodinia followed by its breakup and dispersal into fragments that form the core of today's continents; a rise in oxygen that, perhaps for the first time in Earth history, resulted in the deep oceans becoming oxic; snowball Earth, which envisages a blanketing of global ice cover for millions of years; and, at the zenith of these combined biogeochemical changes, the evolutionary leap from eukaryotes to animals. Such a concentration of hallmark events in the evolution of our planet is unparalleled and many questions regarding Earth System evolution during times of profound climatic and geological changes remain to be answered. Neoproterozoic successions also offer insight into the genesis of a number of natural resources. These include banded-iron formation, organic-rich shale intervals (with demonstrated hydrocarbon source rocks already economically viable in some countries), base and precious metal ore deposits and REE occurrences, as well as industrial minerals and dimension stone. Developing our understanding of the Neoproterozoic Earth-system, combined with regional geology has the potential to impact the viability of these resources. Our understanding of the Neoproterozoic and early Cambrian, though, is overwhelmingly dependent on outcrop-based studies, which suffer from lack of continuity of outcrop and, in many instances, deep weathering profiles. A limited number of research projects study Precambrian strata have demonstrated the potential impact of scientific drilling to augment and complement ongoing outcrop based studies and advancing research. An ICDP and ECORD sponsored workshop, to be held in March 2014, has been convened to discuss the utility of scientific drilling for accelerating research of the Neoproterozoic through early Cambrian (ca. 0.9 to 0.52 Ga) rock record. The aim is to

  17. Cloud Computing and Validated Learning for Accelerating Innovation in IoT

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  18. Acceleration of FDTD mode solver by high-performance computing techniques.

    PubMed

    Han, Lin; Xi, Yanping; Huang, Wei-Ping

    2010-06-21

    A two-dimensional (2D) compact finite-difference time-domain (FDTD) mode solver is developed based on wave equation formalism in combination with the matrix pencil method (MPM). The method is validated for calculation of both real guided and complex leaky modes of typical optical waveguides against the bench-mark finite-difference (FD) eigen mode solver. By taking advantage of the inherent parallel nature of the FDTD algorithm, the mode solver is implemented on graphics processing units (GPUs) using the compute unified device architecture (CUDA). It is demonstrated that the high-performance computing technique leads to significant acceleration of the FDTD mode solver with more than 30 times improvement in computational efficiency in comparison with the conventional FDTD mode solver running on CPU of a standard desktop computer. The computational efficiency of the accelerated FDTD method is in the same order of magnitude of the standard finite-difference eigen mode solver and yet require much less memory (e.g., less than 10%). Therefore, the new method may serve as an efficient, accurate and robust tool for mode calculation of optical waveguides even when the conventional eigen value mode solvers are no longer applicable due to memory limitation.

  19. Technologies for Large Data Management in Scientific Computing

    NASA Astrophysics Data System (ADS)

    Pace, Alberto

    2014-01-01

    In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago. This paper focuses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project. The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.

  20. Method for computationally efficient design of dielectric laser accelerator structures

    DOE PAGES

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

    2017-06-22

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

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

    PubMed

    Yoo, Won-Gyu

    2015-01-01

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

  2. Computational screening of organic polymer dielectrics for novel accelerator technologies

    DOE PAGES

    Pilania, Ghanshyam; Weis, Eric; Walker, Ethan M.; ...

    2018-06-18

    The use of infrared lasers to power accelerating dielectric structures is a developing area of research. Within this technology, the choice of the dielectric material forming the accelerating structures, such as the photonic band gap (PBG) structures, is dictated by a range of interrelated factors including their dielectric and optical properties, amenability to photo-polymerization, thermochemical stability and other target performance metrics of the particle accelerator. In this direction, electronic structure theory aided computational screening and design of dielectric materials can play a key role in identifying potential candidate materials with the targeted functionalities to guide experimental synthetic efforts. In anmore » attempt to systematically understand the role of chemistry in controlling the electronic structure and dielectric properties of organic polymeric materials, here we employ empirical screening and density functional theory (DFT) computations, as a part of our multi-step hierarchal screening strategy. Our DFT based analysis focused on the bandgap, dielectric permittivity, and frequency-dependent dielectric losses due to lattice absorption as key properties to down-select promising polymer motifs. In addition to the specific application of dielectric laser acceleration, the general methodology presented here is deemed to be valuable in the design of new insulators with an attractive combination of dielectric properties.« less

  3. GPU-Accelerated Molecular Modeling Coming Of Age

    PubMed Central

    Stone, John E.; Hardy, David J.; Ufimtsev, Ivan S.

    2010-01-01

    Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. PMID:20675161

  4. Building Cognition: The Construction of Computational Representations for Scientific Discovery

    ERIC Educational Resources Information Center

    Chandrasekharan, Sanjay; Nersessian, Nancy J.

    2015-01-01

    Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a…

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

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

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

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

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

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

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

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

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

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

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

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

  8. Emerging Nanophotonic Applications Explored with Advanced Scientific Parallel Computing

    NASA Astrophysics Data System (ADS)

    Meng, Xiang

    The domain of nanoscale optical science and technology is a combination of the classical world of electromagnetics and the quantum mechanical regime of atoms and molecules. Recent advancements in fabrication technology allows the optical structures to be scaled down to nanoscale size or even to the atomic level, which are far smaller than the wavelength they are designed for. These nanostructures can have unique, controllable, and tunable optical properties and their interactions with quantum materials can have important near-field and far-field optical response. Undoubtedly, these optical properties can have many important applications, ranging from the efficient and tunable light sources, detectors, filters, modulators, high-speed all-optical switches; to the next-generation classical and quantum computation, and biophotonic medical sensors. This emerging research of nanoscience, known as nanophotonics, is a highly interdisciplinary field requiring expertise in materials science, physics, electrical engineering, and scientific computing, modeling and simulation. It has also become an important research field for investigating the science and engineering of light-matter interactions that take place on wavelength and subwavelength scales where the nature of the nanostructured matter controls the interactions. In addition, the fast advancements in the computing capabilities, such as parallel computing, also become as a critical element for investigating advanced nanophotonic devices. This role has taken on even greater urgency with the scale-down of device dimensions, and the design for these devices require extensive memory and extremely long core hours. Thus distributed computing platforms associated with parallel computing are required for faster designs processes. Scientific parallel computing constructs mathematical models and quantitative analysis techniques, and uses the computing machines to analyze and solve otherwise intractable scientific challenges. In

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

    NASA Astrophysics Data System (ADS)

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

    2017-07-01

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

  10. Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

    NASA Technical Reports Server (NTRS)

    Oliker, Leonid; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; VanderWijngaart, Rob

    2003-01-01

    The growing gap between sustained and peak performance for scientific applications has become a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to bridge this gap for a significant number of computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines a full spectrum of low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks using some simple optimizations. Finally, we evaluate the perfor- mance of several numerical codes from key scientific computing domains. Overall results demonstrate that the SX6 achieves high performance on a large fraction of our application suite and in many cases significantly outperforms the RISC-based architectures. However, certain classes of applications are not easily amenable to vectorization and would likely require extensive reengineering of both algorithm and implementation to utilize the SX6 effectively.

  11. Accelerating Science to Action: NGOs Catalyzing Scientific Research using Philanthropic/Corporate Funding

    NASA Astrophysics Data System (ADS)

    Hamburg, S.

    2017-12-01

    While government funding of scientific research has been the bedrock of scientific advances in the US, it is seldom quick or directly responsive to societal needs. If we are to effectively respond to the increasingly urgent needs for new science to address the environmental and social challenges faced by humanity and the environment we need to deploy new scientific models to augment government-centric approaches. The Environmental Defense Fund has developed an approach that accelerates the development and uptake of new science in pursuit of science-based policy to fill the gap while government research efforts are initiated. We utilized this approach in developing the data necessary to quantify methane emissions from the oil and gas supply chain. This effort was based on five key principles: studies led by an academic researchers; deployment of multiple methods whenever possible (e.g. top-down and bottom-up); all data made public (identity but not location masked when possible); external scientific review; results released in peer-reviewed scientific journals. The research to quantify methane emissions involved > 150 scientists from 40 institutions, resulting in 35 papers published over four years. In addition to the research community companies operating along the oil and gas value chain participated by providing access to sites/vehicles and funding for a portion of the academic research. The bulk of funding came from philanthropic sources. Overall the use of this alternative research/funding model allowed for the more rapid development of a robust body of policy-relevant knowledge that addressed an issue of high societal interest/value.

  12. Dental movement acceleration: Literature review by an alternative scientific evidence method

    PubMed Central

    Camacho, Angela Domínguez; Cujar, Sergio Andres Velásquez

    2014-01-01

    The aim of this study was to analyze the majority of publications using effective methods to speed up orthodontic treatment and determine which publications carry high evidence-based value. The literature published in Pubmed from 1984 to 2013 was reviewed, in addition to well-known reports that were not classified under this database. To facilitate evidence-based decision making, guidelines such as the Consolidation Standards of Reporting Trials, Preferred Reporting items for systematic Reviews and Meta-analyses, and Transparent Reporting of Evaluations with Non-randomized Designs check list were used. The studies were initially divided into three groups: local application of cell mediators, physical stimuli, and techniques that took advantage of the regional acceleration phenomena. The articles were classified according to their level of evidence using an alternative method for orthodontic scientific article classification. 1a: Systematic Reviews (SR) of randomized clinical trials (RCTs), 1b: Individual RCT, 2a: SR of cohort studies, 2b: Individual cohort study, controlled clinical trials and low quality RCT, 3a: SR of case-control studies, 3b: Individual case-control study, low quality cohort study and short time following split mouth designs. 4: Case-series, low quality case-control study and non-systematic review, and 5: Expert opinion. The highest level of evidence for each group was: (1) local application of cell mediators: the highest level of evidence corresponds to a 3B level in Prostaglandins and Vitamin D; (2) physical stimuli: vibratory forces and low level laser irradiation have evidence level 2b, Electrical current is classified as 3b evidence-based level, Pulsed Electromagnetic Field is placed on the 4th level on the evidence scale; and (3) regional acceleration phenomena related techniques: for corticotomy the majority of the reports belong to level 4. Piezocision, dentoalveolar distraction, alveocentesis, monocortical tooth dislocation and ligament

  13. GPU-accelerated molecular modeling coming of age.

    PubMed

    Stone, John E; Hardy, David J; Ufimtsev, Ivan S; Schulten, Klaus

    2010-09-01

    Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. (c) 2010 Elsevier Inc. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

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

    NASA Astrophysics Data System (ADS)

    Chine, Karim

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

  16. InSAR Scientific Computing Environment

    NASA Astrophysics Data System (ADS)

    Gurrola, E. M.; Rosen, P. A.; Sacco, G.; Zebker, H. A.; Simons, M.; Sandwell, D. T.

    2010-12-01

    The InSAR Scientific Computing Environment (ISCE) is a software development effort in its second year within the NASA Advanced Information Systems and Technology program. The ISCE will provide a new computing environment for geodetic image processing for InSAR sensors that will enable scientists to reduce measurements directly from radar satellites and aircraft to new geophysical products without first requiring them to develop detailed expertise in radar processing methods. The environment can serve as the core of a centralized processing center to bring Level-0 raw radar data up to Level-3 data products, but is adaptable to alternative processing approaches for science users interested in new and different ways to exploit mission data. The NRC Decadal Survey-recommended DESDynI mission will deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystem. The InSAR Scientific Computing Environment is planned to become a key element in processing DESDynI data into higher level data products and it is expected to enable a new class of analyses that take greater advantage of the long time and large spatial scales of these new data, than current approaches. At the core of ISCE is both legacy processing software from the JPL/Caltech ROI_PAC repeat-pass interferometry package as well as a new InSAR processing package containing more efficient and more accurate processing algorithms being developed at Stanford for this project that is based on experience gained in developing processors for missions such as SRTM and UAVSAR. Around the core InSAR processing programs we are building object-oriented wrappers to enable their incorporation into a more modern, flexible, extensible software package that is informed by modern programming methods, including rigorous componentization of processing codes, abstraction and generalization of data models, and a robust, intuitive user interface with

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

    PubMed Central

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

    2014-01-01

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

  18. DOE Advanced Scientific Computing Advisory Committee (ASCAC) Report: Exascale Computing Initiative Review

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

    Reed, Daniel; Berzins, Martin; Pennington, Robert

    On November 19, 2014, the Advanced Scientific Computing Advisory Committee (ASCAC) was charged with reviewing the Department of Energy’s conceptual design for the Exascale Computing Initiative (ECI). In particular, this included assessing whether there are significant gaps in the ECI plan or areas that need to be given priority or extra management attention. Given the breadth and depth of previous reviews of the technical challenges inherent in exascale system design and deployment, the subcommittee focused its assessment on organizational and management issues, considering technical issues only as they informed organizational or management priorities and structures. This report presents the observationsmore » and recommendations of the subcommittee.« less

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

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

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

    1997-04-01

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

  20. Review of An Introduction to Parallel and Vector Scientific Computing

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

    Bailey, David H.; Lefton, Lew

    2006-06-30

    On one hand, the field of high-performance scientific computing is thriving beyond measure. Performance of leading-edge systems on scientific calculations, as measured say by the Top500 list, has increased by an astounding factor of 8000 during the 15-year period from 1993 to 2008, which is slightly faster even than Moore's Law. Even more importantly, remarkable advances in numerical algorithms, numerical libraries and parallel programming environments have led to improvements in the scope of what can be computed that are entirely on a par with the advances in computing hardware. And these successes have spread far beyond the confines of largemore » government-operated laboratories, many universities, modest-sized research institutes and private firms now operate clusters that differ only in scale from the behemoth systems at the large-scale facilities. In the wake of these recent successes, researchers from fields that heretofore have not been part of the scientific computing world have been drawn into the arena. For example, at the recent SC07 conference, the exhibit hall, which long has hosted displays from leading computer systems vendors and government laboratories, featured some 70 exhibitors who had not previously participated. In spite of all these exciting developments, and in spite of the clear need to present these concepts to a much broader technical audience, there is a perplexing dearth of training material and textbooks in the field, particularly at the introductory level. Only a handful of universities offer coursework in the specific area of highly parallel scientific computing, and instructors of such courses typically rely on custom-assembled material. For example, the present reviewer and Robert F. Lucas relied on materials assembled in a somewhat ad-hoc fashion from colleagues and personal resources when presenting a course on parallel scientific computing at the University of California, Berkeley, a few years ago. Thus it is indeed

  1. 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.

  2. Theoretical and technological building blocks for an innovation accelerator

    NASA Astrophysics Data System (ADS)

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

    2012-11-01

    Modern science is a main driver of technological innovation. The efficiency of the scientific system is of key importance to ensure the competitiveness of a nation or region. However, the scientific system that we use today was devised centuries ago and is inadequate for our current ICT-based society: the peer review system encourages conservatism, journal publications are monolithic and slow, data is often not available to other scientists, and the independent validation of results is limited. The resulting scientific process is hence slow and sloppy. Building on the Innovation Accelerator paper by Helbing and Balietti [1], this paper takes the initial global vision and reviews the theoretical and technological building blocks that can be used for implementing an innovation (in first place: science) accelerator platform driven by re-imagining the science system. The envisioned platform would rest on four pillars: (i) Redesign the incentive scheme to reduce behavior such as conservatism, herding and hyping; (ii) Advance scientific publications by breaking up the monolithic paper unit and introducing other building blocks such as data, tools, experiment workflows, resources; (iii) Use machine readable semantics for publications, debate structures, provenance etc. in order to include the computer as a partner in the scientific process, and (iv) Build an online platform for collaboration, including a network of trust and reputation among the different types of stakeholders in the scientific system: scientists, educators, funding agencies, policy makers, students and industrial innovators among others. Any such improvements to the scientific system must support the entire scientific process (unlike current tools that chop up the scientific process into disconnected pieces), must facilitate and encourage collaboration and interdisciplinarity (again unlike current tools), must facilitate the inclusion of intelligent computing in the scientific process, must facilitate

  3. Convergence acceleration of the Proteus computer code with multigrid methods

    NASA Technical Reports Server (NTRS)

    Demuren, A. O.; Ibraheem, S. O.

    1992-01-01

    Presented here is the first part of a study to implement convergence acceleration techniques based on the multigrid concept in the Proteus computer code. A review is given of previous studies on the implementation of multigrid methods in computer codes for compressible flow analysis. Also presented is a detailed stability analysis of upwind and central-difference based numerical schemes for solving the Euler and Navier-Stokes equations. Results are given of a convergence study of the Proteus code on computational grids of different sizes. The results presented here form the foundation for the implementation of multigrid methods in the Proteus code.

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

    PubMed Central

    2012-01-01

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

  5. Convergence acceleration of the Proteus computer code with multigrid methods

    NASA Technical Reports Server (NTRS)

    Demuren, A. O.; Ibraheem, S. O.

    1995-01-01

    This report presents the results of a study to implement convergence acceleration techniques based on the multigrid concept in the two-dimensional and three-dimensional versions of the Proteus computer code. The first section presents a review of the relevant literature on the implementation of the multigrid methods in computer codes for compressible flow analysis. The next two sections present detailed stability analysis of numerical schemes for solving the Euler and Navier-Stokes equations, based on conventional von Neumann analysis and the bi-grid analysis, respectively. The next section presents details of the computational method used in the Proteus computer code. Finally, the multigrid implementation and applications to several two-dimensional and three-dimensional test problems are presented. The results of the present study show that the multigrid method always leads to a reduction in the number of iterations (or time steps) required for convergence. However, there is an overhead associated with the use of multigrid acceleration. The overhead is higher in 2-D problems than in 3-D problems, thus overall multigrid savings in CPU time are in general better in the latter. Savings of about 40-50 percent are typical in 3-D problems, but they are about 20-30 percent in large 2-D problems. The present multigrid method is applicable to steady-state problems and is therefore ineffective in problems with inherently unstable solutions.

  6. Predicting future discoveries from current scientific literature.

    PubMed

    Petrič, Ingrid; Cestnik, Bojan

    2014-01-01

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

  7. A coarse-grid projection method for accelerating incompressible flow computations

    NASA Astrophysics Data System (ADS)

    San, Omer; Staples, Anne

    2011-11-01

    We present a coarse-grid projection (CGP) algorithm for accelerating incompressible flow computations, which is applicable to methods involving Poisson equations as incompressibility constraints. CGP methodology is a modular approach that facilitates data transfer with simple interpolations and uses black-box solvers for the Poisson and advection-diffusion equations in the flow solver. Here, we investigate a particular CGP method for the vorticity-stream function formulation that uses the full weighting operation for mapping from fine to coarse grids, the third-order Runge-Kutta method for time stepping, and finite differences for the spatial discretization. After solving the Poisson equation on a coarsened grid, bilinear interpolation is used to obtain the fine data for consequent time stepping on the full grid. We compute several benchmark flows: the Taylor-Green vortex, a vortex pair merging, a double shear layer, decaying turbulence and the Taylor-Green vortex on a distorted grid. In all cases we use either FFT-based or V-cycle multigrid linear-cost Poisson solvers. Reducing the number of degrees of freedom of the Poisson solver by powers of two accelerates these computations while, for the first level of coarsening, retaining the same level of accuracy in the fine resolution vorticity field.

  8. 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.

  9. The Observation of Bahasa Indonesia Official Computer Terms Implementation in Scientific Publication

    NASA Astrophysics Data System (ADS)

    Gunawan, D.; Amalia, A.; Lydia, M. S.; Muthaqin, M. I.

    2018-03-01

    The government of the Republic of Indonesia had issued a regulation to substitute computer terms in foreign language that have been used earlier into official computer terms in Bahasa Indonesia. This regulation was stipulated in Presidential Decree No. 2 of 2001 concerning the introduction of official computer terms in Bahasa Indonesia (known as Senarai Padanan Istilah/SPI). After sixteen years, people of Indonesia, particularly for academics, should have implemented the official computer terms in their official publications. This observation is conducted to discover the implementation of official computer terms usage in scientific publications which are written in Bahasa Indonesia. The data source used in this observation are the publications by the academics, particularly in computer science field. The method used in the observation is divided into four stages. The first stage is metadata harvesting by using Open Archive Initiative - Protocol for Metadata Harvesting (OAI-PMH). Second, converting the harvested document (in pdf format) to plain text. The third stage is text-preprocessing as the preparation of string matching. Then the final stage is searching the official computer terms based on 629 SPI terms by using Boyer-Moore algorithm. We observed that there are 240,781 foreign computer terms in 1,156 scientific publications from six universities. This result shows that the foreign computer terms are still widely used by the academics.

  10. OPENING REMARKS: Scientific Discovery through Advanced Computing

    NASA Astrophysics Data System (ADS)

    Strayer, Michael

    2006-01-01

    Good morning. Welcome to SciDAC 2006 and Denver. I share greetings from the new Undersecretary for Energy, Ray Orbach. Five years ago SciDAC was launched as an experiment in computational science. The goal was to form partnerships among science applications, computer scientists, and applied mathematicians to take advantage of the potential of emerging terascale computers. This experiment has been a resounding success. SciDAC has emerged as a powerful concept for addressing some of the biggest challenges facing our world. As significant as these successes were, I believe there is also significance in the teams that achieved them. In addition to their scientific aims these teams have advanced the overall field of computational science and set the stage for even larger accomplishments as we look ahead to SciDAC-2. I am sure that many of you are expecting to hear about the results of our current solicitation for SciDAC-2. I’m afraid we are not quite ready to make that announcement. Decisions are still being made and we will announce the results later this summer. Nearly 250 unique proposals were received and evaluated, involving literally thousands of researchers, postdocs, and students. These collectively requested more than five times our expected budget. This response is a testament to the success of SciDAC in the community. In SciDAC-2 our budget has been increased to about 70 million for FY 2007 and our partnerships have expanded to include the Environment and National Security missions of the Department. The National Science Foundation has also joined as a partner. These new partnerships are expected to expand the application space of SciDAC, and broaden the impact and visibility of the program. We have, with our recent solicitation, expanded to turbulence, computational biology, and groundwater reactive modeling and simulation. We are currently talking with the Department’s applied energy programs about risk assessment, optimization of complex systems - such

  11. Building Cognition: The Construction of Computational Representations for Scientific Discovery.

    PubMed

    Chandrasekharan, Sanjay; Nersessian, Nancy J

    2015-11-01

    Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that led to a remarkable discovery in basic bioscience. Accounting for such discoveries requires a distributed cognition (DC) analysis, as DC focuses on the roles played by external representations in cognitive processes. However, DC analyses by and large have not examined scientific discovery, and they mostly focus on memory offloading, particularly how the use of existing external representations changes the nature of cognitive tasks. In contrast, we study discovery processes and argue that discoveries emerge from the processes of building the computational representation. The building process integrates manipulations in imagination and in the representation, creating a coupled cognitive system of model and modeler, where the model is incorporated into the modeler's imagination. This account extends DC significantly, and we present some of the theoretical and application implications of this extended account. Copyright © 2014 Cognitive Science Society, Inc.

  12. Enabling large-scale viscoelastic calculations via neural network acceleration

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

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

    ERIC Educational Resources Information Center

    Weiss, Charles J.

    2017-01-01

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

  14. Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

    NASA Astrophysics Data System (ADS)

    Pallant, Amy; Lee, Hee-Sun

    2015-04-01

    Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students ( N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation tasks with three increasingly complex dynamic climate models. Each scientific argumentation task consisted of four parts: multiple-choice claim, openended explanation, five-point Likert scale uncertainty rating, and open-ended uncertainty rationale. We coded 1,294 scientific arguments in terms of a claim's consistency with current scientific consensus, whether explanations were model based or knowledge based and categorized the sources of uncertainty (personal vs. scientific). We used chi-square and ANOVA tests to identify significant patterns. Results indicate that (1) a majority of students incorporated models as evidence to support their claims, (2) most students used model output results shown on graphs to confirm their claim rather than to explain simulated molecular processes, (3) students' dependence on model results and their uncertainty rating diminished as the dynamic climate models became more and more complex, (4) some students' misconceptions interfered with observing and interpreting model results or simulated processes, and (5) students' uncertainty sources reflected more frequently on their assessment of personal knowledge or abilities related to the tasks than on their critical examination of scientific evidence resulting from models. These findings have implications for teaching and research related to the integration of scientific argumentation and modeling practices to address complex Earth systems.

  15. Scientific Computing Strategic Plan for the Idaho National Laboratory

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

    Whiting, Eric Todd

    Scientific computing is a critical foundation of modern science. Without innovations in the field of computational science, the essential missions of the Department of Energy (DOE) would go unrealized. Taking a leadership role in such innovations is Idaho National Laboratory’s (INL’s) challenge and charge, and is central to INL’s ongoing success. Computing is an essential part of INL’s future. DOE science and technology missions rely firmly on computing capabilities in various forms. Modeling and simulation, fueled by innovations in computational science and validated through experiment, are a critical foundation of science and engineering. Big data analytics from an increasing numbermore » of widely varied sources is opening new windows of insight and discovery. Computing is a critical tool in education, science, engineering, and experiments. Advanced computing capabilities in the form of people, tools, computers, and facilities, will position INL competitively to deliver results and solutions on important national science and engineering challenges. A computing strategy must include much more than simply computers. The foundational enabling component of computing at many DOE national laboratories is the combination of a showcase like data center facility coupled with a very capable supercomputer. In addition, network connectivity, disk storage systems, and visualization hardware are critical and generally tightly coupled to the computer system and co located in the same facility. The existence of these resources in a single data center facility opens the doors to many opportunities that would not otherwise be possible.« less

  16. Ultrasound window-modulated compounding Nakagami imaging: Resolution improvement and computational acceleration for liver characterization.

    PubMed

    Ma, Hsiang-Yang; Lin, Ying-Hsiu; Wang, Chiao-Yin; Chen, Chiung-Nien; Ho, Ming-Chih; Tsui, Po-Hsiang

    2016-08-01

    Ultrasound Nakagami imaging is an attractive method for visualizing changes in envelope statistics. Window-modulated compounding (WMC) Nakagami imaging was reported to improve image smoothness. The sliding window technique is typically used for constructing ultrasound parametric and Nakagami images. Using a large window overlap ratio may improve the WMC Nakagami image resolution but reduces computational efficiency. Therefore, the objectives of this study include: (i) exploring the effects of the window overlap ratio on the resolution and smoothness of WMC Nakagami images; (ii) proposing a fast algorithm that is based on the convolution operator (FACO) to accelerate WMC Nakagami imaging. Computer simulations and preliminary clinical tests on liver fibrosis samples (n=48) were performed to validate the FACO-based WMC Nakagami imaging. The results demonstrated that the width of the autocorrelation function and the parameter distribution of the WMC Nakagami image reduce with the increase in the window overlap ratio. One-pixel shifting (i.e., sliding the window on the image data in steps of one pixel for parametric imaging) as the maximum overlap ratio significantly improves the WMC Nakagami image quality. Concurrently, the proposed FACO method combined with a computational platform that optimizes the matrix computation can accelerate WMC Nakagami imaging, allowing the detection of liver fibrosis-induced changes in envelope statistics. FACO-accelerated WMC Nakagami imaging is a new-generation Nakagami imaging technique with an improved image quality and fast computation. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

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

    Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

    The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less

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

    PubMed Central

    Filipovic, Nenad D.

    2017-01-01

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

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

    PubMed

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

    2017-01-01

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

  20. Quantum computational complexity, Einstein's equations and accelerated expansion of the Universe

    NASA Astrophysics Data System (ADS)

    Ge, Xian-Hui; Wang, Bin

    2018-02-01

    We study the relation between quantum computational complexity and general relativity. The quantum computational complexity is proposed to be quantified by the shortest length of geodesic quantum curves. We examine the complexity/volume duality in a geodesic causal ball in the framework of Fermi normal coordinates and derive the full non-linear Einstein equation. Using insights from the complexity/action duality, we argue that the accelerated expansion of the universe could be driven by the quantum complexity and free from coincidence and fine-tunning problems.

  1. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

    PubMed

    Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

    2016-04-07

    With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  2. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

    PubMed Central

    Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

    2016-01-01

    With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate. PMID:27070606

  3. Computational study of radiation doses at UNLV accelerator facility

    NASA Astrophysics Data System (ADS)

    Hodges, Matthew; Barzilov, Alexander; Chen, Yi-Tung; Lowe, Daniel

    2017-09-01

    A Varian K15 electron linear accelerator (linac) has been considered for installation at University of Nevada, Las Vegas (UNLV). Before experiments can be performed, it is necessary to evaluate the photon and neutron spectra as generated by the linac, as well as the resulting dose rates within the accelerator facility. A computational study using MCNPX was performed to characterize the source terms for the bremsstrahlung converter. The 15 MeV electron beam available in the linac is above the photoneutron threshold energy for several materials in the linac assembly, and as a result, neutrons must be accounted for. The angular and energy distributions for bremsstrahlung flux generated by the interaction of the 15 MeV electron beam with the linac target were determined. This source term was used in conjunction with the K15 collimators to determine the dose rates within the facility.

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

  5. Extraordinary Tools for Extraordinary Science: The Impact ofSciDAC on Accelerator Science&Technology

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

    Ryne, Robert D.

    2006-08-10

    Particle accelerators are among the most complex and versatile instruments of scientific exploration. They have enabled remarkable scientific discoveries and important technological advances that span all programs within the DOE Office of Science (DOE/SC). The importance of accelerators to the DOE/SC mission is evident from an examination of the DOE document, ''Facilities for the Future of Science: A Twenty-Year Outlook''. Of the 28 facilities listed, 13 involve accelerators. Thanks to SciDAC, a powerful suite of parallel simulation tools has been developed that represent a paradigm shift in computational accelerator science. Simulations that used to take weeks or more now takemore » hours, and simulations that were once thought impossible are now performed routinely. These codes have been applied to many important projects of DOE/SC including existing facilities (the Tevatron complex, the Relativistic Heavy Ion Collider), facilities under construction (the Large Hadron Collider, the Spallation Neutron Source, the Linac Coherent Light Source), and to future facilities (the International Linear Collider, the Rare Isotope Accelerator). The new codes have also been used to explore innovative approaches to charged particle acceleration. These approaches, based on the extremely intense fields that can be present in lasers and plasmas, may one day provide a path to the outermost reaches of the energy frontier. Furthermore, they could lead to compact, high-gradient accelerators that would have huge consequences for US science and technology, industry, and medicine. In this talk I will describe the new accelerator modeling capabilities developed under SciDAC, the essential role of multi-disciplinary collaboration with applied mathematicians, computer scientists, and other IT experts in developing these capabilities, and provide examples of how the codes have been used to support DOE/SC accelerator projects.« less

  6. Integrating multiple scientific computing needs via a Private Cloud infrastructure

    NASA Astrophysics Data System (ADS)

    Bagnasco, S.; Berzano, D.; Brunetti, R.; Lusso, S.; Vallero, S.

    2014-06-01

    In a typical scientific computing centre, diverse applications coexist and share a single physical infrastructure. An underlying Private Cloud facility eases the management and maintenance of heterogeneous use cases such as multipurpose or application-specific batch farms, Grid sites catering to different communities, parallel interactive data analysis facilities and others. It allows to dynamically and efficiently allocate resources to any application and to tailor the virtual machines according to the applications' requirements. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques; for example, rolling updates can be performed easily and minimizing the downtime. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 site and a dynamically expandable PROOF-based Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The Private Cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem (used in two different configurations for worker- and service-class hypervisors) and the OpenWRT Linux distribution (used for network virtualization). A future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and by using mainstream contextualization tools like CloudInit.

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

    ERIC Educational Resources Information Center

    Adams, Stephen T.

    2004-01-01

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

  8. Compiler-based code generation and autotuning for geometric multigrid on GPU-accelerated supercomputers

    DOE PAGES

    Basu, Protonu; Williams, Samuel; Van Straalen, Brian; ...

    2017-04-05

    GPUs, with their high bandwidths and computational capabilities are an increasingly popular target for scientific computing. Unfortunately, to date, harnessing the power of the GPU has required use of a GPU-specific programming model like CUDA, OpenCL, or OpenACC. Thus, in order to deliver portability across CPU-based and GPU-accelerated supercomputers, programmers are forced to write and maintain two versions of their applications or frameworks. In this paper, we explore the use of a compiler-based autotuning framework based on CUDA-CHiLL to deliver not only portability, but also performance portability across CPU- and GPU-accelerated platforms for the geometric multigrid linear solvers found inmore » many scientific applications. We also show that with autotuning we can attain near Roofline (a performance bound for a computation and target architecture) performance across the key operations in the miniGMG benchmark for both CPU- and GPU-based architectures as well as for a multiple stencil discretizations and smoothers. We show that our technology is readily interoperable with MPI resulting in performance at scale equal to that obtained via hand-optimized MPI+CUDA implementation.« less

  9. Compiler-based code generation and autotuning for geometric multigrid on GPU-accelerated supercomputers

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

    Basu, Protonu; Williams, Samuel; Van Straalen, Brian

    GPUs, with their high bandwidths and computational capabilities are an increasingly popular target for scientific computing. Unfortunately, to date, harnessing the power of the GPU has required use of a GPU-specific programming model like CUDA, OpenCL, or OpenACC. Thus, in order to deliver portability across CPU-based and GPU-accelerated supercomputers, programmers are forced to write and maintain two versions of their applications or frameworks. In this paper, we explore the use of a compiler-based autotuning framework based on CUDA-CHiLL to deliver not only portability, but also performance portability across CPU- and GPU-accelerated platforms for the geometric multigrid linear solvers found inmore » many scientific applications. We also show that with autotuning we can attain near Roofline (a performance bound for a computation and target architecture) performance across the key operations in the miniGMG benchmark for both CPU- and GPU-based architectures as well as for a multiple stencil discretizations and smoothers. We show that our technology is readily interoperable with MPI resulting in performance at scale equal to that obtained via hand-optimized MPI+CUDA implementation.« less

  10. DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges

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

    Lucas, Robert; Ang, James; Bergman, Keren

    2014-02-10

    Exascale computing systems are essential for the scientific fields that will transform the 21st century global economy, including energy, biotechnology, nanotechnology, and materials science. Progress in these fields is predicated on the ability to perform advanced scientific and engineering simulations, and analyze the deluge of data. On July 29, 2013, ASCAC was charged by Patricia Dehmer, the Acting Director of the Office of Science, to assemble a subcommittee to provide advice on exascale computing. This subcommittee was directed to return a list of no more than ten technical approaches (hardware and software) that will enable the development of a systemmore » that achieves the Department's goals for exascale computing. Numerous reports over the past few years have documented the technical challenges and the non¬-viability of simply scaling existing computer designs to reach exascale. The technical challenges revolve around energy consumption, memory performance, resilience, extreme concurrency, and big data. Drawing from these reports and more recent experience, this ASCAC subcommittee has identified the top ten computing technology advancements that are critical to making a capable, economically viable, exascale system.« less

  11. 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.

  12. Can Accelerators Accelerate Learning?

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-12-01

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

  15. Accelerating Technology Development through Integrated Computation and Experimentation

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

    Shekhawat, Dushyant; Srivastava, Rameshwar D.; Ciferno, Jared

    2013-08-15

    This special section of Energy & Fuels comprises a selection of papers presented at the topical conference “Accelerating Technology Development through Integrated Computation and Experimentation”, sponsored and organized by the United States Department of Energy’s National Energy Technology Laboratory (NETL) as part of the 2012 American Institute of Chemical Engineers (AIChE) Annual Meeting held in Pittsburgh, PA, Oct 28-Nov 2, 2012. That topical conference focused on the latest research and development efforts in five main areas related to fossil energy, with each area focusing on the utilization of both experimental and computational approaches: (1) gas separations (membranes, sorbents, and solventsmore » for CO{sub 2}, H{sub 2}, and O{sub 2} production), (2) CO{sub 2} utilization (enhanced oil recovery, chemical production, mineralization, etc.), (3) carbon sequestration (flow in natural systems), (4) advanced power cycles (oxy-combustion, chemical looping, gasification, etc.), and (5) fuel processing (H{sub 2} production for fuel cells).« less

  16. Space and Earth Sciences, Computer Systems, and Scientific Data Analysis Support, Volume 1

    NASA Technical Reports Server (NTRS)

    Estes, Ronald H. (Editor)

    1993-01-01

    This Final Progress Report covers the specific technical activities of Hughes STX Corporation for the last contract triannual period of 1 June through 30 Sep. 1993, in support of assigned task activities at Goddard Space Flight Center (GSFC). It also provides a brief summary of work throughout the contract period of performance on each active task. Technical activity is presented in Volume 1, while financial and level-of-effort data is presented in Volume 2. Technical support was provided to all Division and Laboratories of Goddard's Space Sciences and Earth Sciences Directorates. Types of support include: scientific programming, systems programming, computer management, mission planning, scientific investigation, data analysis, data processing, data base creation and maintenance, instrumentation development, and management services. Mission and instruments supported include: ROSAT, Astro-D, BBXRT, XTE, AXAF, GRO, COBE, WIND, UIT, SMM, STIS, HEIDI, DE, URAP, CRRES, Voyagers, ISEE, San Marco, LAGEOS, TOPEX/Poseidon, Pioneer-Venus, Galileo, Cassini, Nimbus-7/TOMS, Meteor-3/TOMS, FIFE, BOREAS, TRMM, AVHRR, and Landsat. Accomplishments include: development of computing programs for mission science and data analysis, supercomputer applications support, computer network support, computational upgrades for data archival and analysis centers, end-to-end management for mission data flow, scientific modeling and results in the fields of space and Earth physics, planning and design of GSFC VO DAAC and VO IMS, fabrication, assembly, and testing of mission instrumentation, and design of mission operations center.

  17. Extraordinary tools for extraordinary science: the impact of SciDAC on accelerator science and technology

    NASA Astrophysics Data System (ADS)

    Ryne, Robert D.

    2006-09-01

    Particle accelerators are among the most complex and versatile instruments of scientific exploration. They have enabled remarkable scientific discoveries and important technological advances that span all programs within the DOE Office of Science (DOE/SC). The importance of accelerators to the DOE/SC mission is evident from an examination of the DOE document, ''Facilities for the Future of Science: A Twenty-Year Outlook.'' Of the 28 facilities listed, 13 involve accelerators. Thanks to SciDAC, a powerful suite of parallel simulation tools has been developed that represent a paradigm shift in computational accelerator science. Simulations that used to take weeks or more now take hours, and simulations that were once thought impossible are now performed routinely. These codes have been applied to many important projects of DOE/SC including existing facilities (the Tevatron complex, the Relativistic Heavy Ion Collider), facilities under construction (the Large Hadron Collider, the Spallation Neutron Source, the Linac Coherent Light Source), and to future facilities (the International Linear Collider, the Rare Isotope Accelerator). The new codes have also been used to explore innovative approaches to charged particle acceleration. These approaches, based on the extremely intense fields that can be present in lasers and plasmas, may one day provide a path to the outermost reaches of the energy frontier. Furthermore, they could lead to compact, high-gradient accelerators that would have huge consequences for US science and technology, industry, and medicine. In this talk I will describe the new accelerator modeling capabilities developed under SciDAC, the essential role of multi-disciplinary collaboration with applied mathematicians, computer scientists, and other IT experts in developing these capabilities, and provide examples of how the codes have been used to support DOE/SC accelerator projects.

  18. Recent Scientific Evidence and Technical Developments in Cardiovascular Computed Tomography.

    PubMed

    Marcus, Roy; Ruff, Christer; Burgstahler, Christof; Notohamiprodjo, Mike; Nikolaou, Konstantin; Geisler, Tobias; Schroeder, Stephen; Bamberg, Fabian

    2016-05-01

    In recent years, coronary computed tomography angiography has become an increasingly safe and noninvasive modality for the evaluation of the anatomical structure of the coronary artery tree with diagnostic benefits especially in patients with a low-to-intermediate pretest probability of disease. Currently, increasing evidence from large randomized diagnostic trials is accumulating on the diagnostic impact of computed tomography angiography for the management of patients with acute and stable chest pain syndrome. At the same time, technical advances have substantially reduced adverse effects and limiting factors, such as radiation exposure, the amount of iodinated contrast agent, and scanning time, rendering the technique appropriate for broader clinical applications. In this work, we review the latest developments in computed tomography technology and describe the scientific evidence on the use of cardiac computed tomography angiography to evaluate patients with acute and stable chest pain syndrome. Copyright © 2016 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

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

    NASA Technical Reports Server (NTRS)

    Lichtenstein, J. H.

    1975-01-01

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

  20. Real-time dose computation: GPU-accelerated source modeling and superposition/convolution

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

    Jacques, Robert; Wong, John; Taylor, Russell

    Purpose: To accelerate dose calculation to interactive rates using highly parallel graphics processing units (GPUs). Methods: The authors have extended their prior work in GPU-accelerated superposition/convolution with a modern dual-source model and have enhanced performance. The primary source algorithm supports both focused leaf ends and asymmetric rounded leaf ends. The extra-focal algorithm uses a discretized, isotropic area source and models multileaf collimator leaf height effects. The spectral and attenuation effects of static beam modifiers were integrated into each source's spectral function. The authors introduce the concepts of arc superposition and delta superposition. Arc superposition utilizes separate angular sampling for themore » total energy released per unit mass (TERMA) and superposition computations to increase accuracy and performance. Delta superposition allows single beamlet changes to be computed efficiently. The authors extended their concept of multi-resolution superposition to include kernel tilting. Multi-resolution superposition approximates solid angle ray-tracing, improving performance and scalability with a minor loss in accuracy. Superposition/convolution was implemented using the inverse cumulative-cumulative kernel and exact radiological path ray-tracing. The accuracy analyses were performed using multiple kernel ray samplings, both with and without kernel tilting and multi-resolution superposition. Results: Source model performance was <9 ms (data dependent) for a high resolution (400{sup 2}) field using an NVIDIA (Santa Clara, CA) GeForce GTX 280. Computation of the physically correct multispectral TERMA attenuation was improved by a material centric approach, which increased performance by over 80%. Superposition performance was improved by {approx}24% to 0.058 and 0.94 s for 64{sup 3} and 128{sup 3} water phantoms; a speed-up of 101-144x over the highly optimized Pinnacle{sup 3} (Philips, Madison, WI) implementation

  1. Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

    NASA Astrophysics Data System (ADS)

    Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt; Larson, Krista; Sfiligoi, Igor; Rynge, Mats

    2014-06-01

    Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared over the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by "Big Data" will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.

  2. Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

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

    Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt

    Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared overmore » the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by 'Big Data' will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.« less

  3. Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

    ERIC Educational Resources Information Center

    Hulshof, Casper D.; de Jong, Ton

    2006-01-01

    Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

  4. GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

    PubMed Central

    Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal

    2016-01-01

    Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300

  5. GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

    PubMed

    Fang, Ye; Ding, Yun; Feinstein, Wei P; Koppelman, David M; Moreno, Juana; Jarrell, Mark; Ramanujam, J; Brylinski, Michal

    2016-01-01

    Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

  6. Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction.

    PubMed

    Huang, Hsuan-Ming; Hsiao, Ing-Tsung

    2017-01-01

    Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

  7. Multiple-grid convergence acceleration of viscous and inviscid flow computations

    NASA Technical Reports Server (NTRS)

    Johnson, G. M.

    1983-01-01

    A multiple-grid algorithm for use in efficiently obtaining steady solution to the Euler and Navier-Stokes equations is presented. The convergence of a simple, explicit fine-grid solution procedure is accelerated on a sequence of successively coarser grids by a coarse-grid information propagation method which rapidly eliminates transients from the computational domain. This use of multiple-gridding to increase the convergence rate results in substantially reduced work requirements for the numerical solution of a wide range of flow problems. Computational results are presented for subsonic and transonic inviscid flows and for laminar and turbulent, attached and separated, subsonic viscous flows. Work reduction factors as large as eight, in comparison to the basic fine-grid algorithm, were obtained. Possibilities for further performance improvement are discussed.

  8. Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data

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

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

    2009-10-19

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

  9. InSAR Scientific Computing Environment - The Home Stretch

    NASA Astrophysics Data System (ADS)

    Rosen, P. A.; Gurrola, E. M.; Sacco, G.; Zebker, H. A.

    2011-12-01

    The Interferometric Synthetic Aperture Radar (InSAR) Scientific Computing Environment (ISCE) is a software development effort in its third and final year within the NASA Advanced Information Systems and Technology program. The ISCE is a new computing environment for geodetic image processing for InSAR sensors enabling scientists to reduce measurements directly from radar satellites to new geophysical products with relative ease. The environment can serve as the core of a centralized processing center to bring Level-0 raw radar data up to Level-3 data products, but is adaptable to alternative processing approaches for science users interested in new and different ways to exploit mission data. Upcoming international SAR missions will deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystem. The InSAR Scientific Computing Environment has the functionality to become a key element in processing data from NASA's proposed DESDynI mission into higher level data products, supporting a new class of analyses that take advantage of the long time and large spatial scales of these new data. At the core of ISCE is a new set of efficient and accurate InSAR algorithms. These algorithms are placed into an object-oriented, flexible, extensible software package that is informed by modern programming methods, including rigorous componentization of processing codes, abstraction and generalization of data models. The environment is designed to easily allow user contributions, enabling an open source community to extend the framework into the indefinite future. ISCE supports data from nearly all of the available satellite platforms, including ERS, EnviSAT, Radarsat-1, Radarsat-2, ALOS, TerraSAR-X, and Cosmo-SkyMed. The code applies a number of parallelization techniques and sensible approximations for speed. It is configured to work on modern linux-based computers with gcc compilers and python

  10. Java Performance for Scientific Applications on LLNL Computer Systems

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

    Kapfer, C; Wissink, A

    2002-05-10

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

  11. A call for virtual experiments: accelerating the scientific process.

    PubMed

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

    2015-01-01

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

  12. Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

    NASA Astrophysics Data System (ADS)

    Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Muzaffar, Shahzad

    2015-05-01

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).

  13. Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

    PubMed Central

    Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

    2016-01-01

    Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

  14. Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

    PubMed

    Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

    2016-01-01

    Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

  15. Teaching scientific thinking skills: Students and computers coaching each other

    NASA Astrophysics Data System (ADS)

    Reif, Frederick; Scott, Lisa A.

    1999-09-01

    Our attempts to improve physics instruction have led us to analyze thought processes needed to apply scientific principles to problems—and to recognize that reliable performance requires the basic cognitive functions of deciding, implementing, and assessing. Using a reciprocal-teaching strategy to teach such thought processes explicitly, we have developed computer programs called PALs (P_ersonal A_ssistants for L_earning) in which computers and students alternately coach each other. These computer-implemented tutorials make it practically feasible to provide students with individual guidance and feedback ordinarily unavailable in most courses. We constructed PALs specifically designed to teach the application of Newton's laws. In a comparative experimental study these computer tutorials were found to be nearly as effective as individual tutoring by expert teachers—and considerably more effective than the instruction provided in a well-taught physics class. Furthermore, almost all of the students using the PALs perceived them as very helpful to their learning. These results suggest that the proposed instructional approach could fruitfully be extended to improve instruction in various practically realistic contexts.

  16. Acceleration of Radiance for Lighting Simulation by Using Parallel Computing with OpenCL

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

    Zuo, Wangda; McNeil, Andrew; Wetter, Michael

    2011-09-06

    We report on the acceleration of annual daylighting simulations for fenestration systems in the Radiance ray-tracing program. The algorithm was optimized to reduce both the redundant data input/output operations and the floating-point operations. To further accelerate the simulation speed, the calculation for matrix multiplications was implemented using parallel computing on a graphics processing unit. We used OpenCL, which is a cross-platform parallel programming language. Numerical experiments show that the combination of the above measures can speed up the annual daylighting simulations 101.7 times or 28.6 times when the sky vector has 146 or 2306 elements, respectively.

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

    NASA Astrophysics Data System (ADS)

    Faerber, Christian

    2017-10-01

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

  18. Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity

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

    Jin, Yier

    As technology advances, computer systems are subject to increasingly sophisticated cyber-attacks that compromise both their security and integrity. High performance computing platforms used in commercial and scientific applications involving sensitive, or even classified data, are frequently targeted by powerful adversaries. This situation is made worse by a lack of fundamental security solutions that both perform efficiently and are effective at preventing threats. Current security solutions fail to address the threat landscape and ensure the integrity of sensitive data. As challenges rise, both private and public sectors will require robust technologies to protect its computing infrastructure. The research outcomes from thismore » project try to address all these challenges. For example, we present LAZARUS, a novel technique to harden kernel Address Space Layout Randomization (KASLR) against paging-based side-channel attacks. In particular, our scheme allows for fine-grained protection of the virtual memory mappings that implement the randomization. We demonstrate the effectiveness of our approach by hardening a recent Linux kernel with LAZARUS, mitigating all of the previously presented side-channel attacks on KASLR. Our extensive evaluation shows that LAZARUS incurs only 0.943% overhead for standard benchmarks, and is therefore highly practical. We also introduced HA2lloc, a hardware-assisted allocator that is capable of leveraging an extended memory management unit to detect memory errors in the heap. We also perform testing using HA2lloc in a simulation environment and find that the approach is capable of preventing common memory vulnerabilities.« less

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

    ERIC Educational Resources Information Center

    Halbauer, Siegfried

    1976-01-01

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

  20. Computational Simulations and the Scientific Method

    NASA Technical Reports Server (NTRS)

    Kleb, Bil; Wood, Bill

    2005-01-01

    As scientific simulation software becomes more complicated, the scientific-software implementor's need for component tests from new model developers becomes more crucial. The community's ability to follow the basic premise of the Scientific Method requires independently repeatable experiments, and model innovators are in the best position to create these test fixtures. Scientific software developers also need to quickly judge the value of the new model, i.e., its cost-to-benefit ratio in terms of gains provided by the new model and implementation risks such as cost, time, and quality. This paper asks two questions. The first is whether other scientific software developers would find published component tests useful, and the second is whether model innovators think publishing test fixtures is a feasible approach.

  1. Heterogeneous high throughput scientific computing with APM X-Gene and Intel Xeon Phi

    DOE PAGES

    Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; ...

    2015-05-22

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. As a result, we report our experience on software porting, performance and energy efficiency and evaluatemore » the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).« less

  2. USSR and Eastern Europe Scientific Abstracts, Cybernetics, Computers, and Automation Technology, Number 27

    DTIC Science & Technology

    1977-05-10

    apply this method of forecast- ing in the solution of all major scientific-technical problems of the na- tional economy. Citing the slow...the future, however, computers will "mature" and learn to recognize patterns in what amounts to a much more complex language—the language of visual...images. Photoelectronic tracking devices or "eyes" will allow the computer to take in information in a much more complex form and to perform opera

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

    ERIC Educational Resources Information Center

    Nagasinghe, Iranga

    2010-01-01

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

  4. Accelerator Science: Circular vs. Linear

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

    Lincoln, Don

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

  5. Acceleration of color computer-generated hologram from three-dimensional scenes with texture and depth information

    NASA Astrophysics Data System (ADS)

    Shimobaba, Tomoyoshi; Kakue, Takashi; Ito, Tomoyoshi

    2014-06-01

    We propose acceleration of color computer-generated holograms (CGHs) from three-dimensional (3D) scenes that are expressed as texture (RGB) and depth (D) images. These images are obtained by 3D graphics libraries and RGB-D cameras: for example, OpenGL and Kinect, respectively. We can regard them as two-dimensional (2D) cross-sectional images along the depth direction. The generation of CGHs from the 2D cross-sectional images requires multiple diffraction calculations. If we use convolution-based diffraction such as the angular spectrum method, the diffraction calculation takes a long time and requires large memory usage because the convolution diffraction calculation requires the expansion of the 2D cross-sectional images to avoid the wraparound noise. In this paper, we first describe the acceleration of the diffraction calculation using "Band-limited double-step Fresnel diffraction," which does not require the expansion. Next, we describe color CGH acceleration using color space conversion. In general, color CGHs are generated on RGB color space; however, we need to repeat the same calculation for each color component, so that the computational burden of the color CGH generation increases three-fold, compared with monochrome CGH generation. We can reduce the computational burden by using YCbCr color space because the 2D cross-sectional images on YCbCr color space can be down-sampled without the impairing of the image quality.

  6. Cooperative high-performance storage in the accelerated strategic computing initiative

    NASA Technical Reports Server (NTRS)

    Gary, Mark; Howard, Barry; Louis, Steve; Minuzzo, Kim; Seager, Mark

    1996-01-01

    The use and acceptance of new high-performance, parallel computing platforms will be impeded by the absence of an infrastructure capable of supporting orders-of-magnitude improvement in hierarchical storage and high-speed I/O (Input/Output). The distribution of these high-performance platforms and supporting infrastructures across a wide-area network further compounds this problem. We describe an architectural design and phased implementation plan for a distributed, Cooperative Storage Environment (CSE) to achieve the necessary performance, user transparency, site autonomy, communication, and security features needed to support the Accelerated Strategic Computing Initiative (ASCI). ASCI is a Department of Energy (DOE) program attempting to apply terascale platforms and Problem-Solving Environments (PSEs) toward real-world computational modeling and simulation problems. The ASCI mission must be carried out through a unified, multilaboratory effort, and will require highly secure, efficient access to vast amounts of data. The CSE provides a logically simple, geographically distributed, storage infrastructure of semi-autonomous cooperating sites to meet the strategic ASCI PSE goal of highperformance data storage and access at the user desktop.

  7. Accelerator Science: Circular vs. Linear

    ScienceCinema

    Lincoln, Don

    2018-06-12

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

  8. Position Paper: Applying Machine Learning to Software Analysis to Achieve Trusted, Repeatable Scientific Computing

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

    Prowell, Stacy J; Symons, Christopher T

    2015-01-01

    Producing trusted results from high-performance codes is essential for policy and has significant economic impact. We propose combining rigorous analytical methods with machine learning techniques to achieve the goal of repeatable, trustworthy scientific computing.

  9. Accelerator Based Tools of Stockpile Stewardship

    NASA Astrophysics Data System (ADS)

    Seestrom, Susan

    2017-01-01

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

  10. Accelerated computer generated holography using sparse bases in the STFT domain.

    PubMed

    Blinder, David; Schelkens, Peter

    2018-01-22

    Computer-generated holography at high resolutions is a computationally intensive task. Efficient algorithms are needed to generate holograms at acceptable speeds, especially for real-time and interactive applications such as holographic displays. We propose a novel technique to generate holograms using a sparse basis representation in the short-time Fourier space combined with a wavefront-recording plane placed in the middle of the 3D object. By computing the point spread functions in the transform domain, we update only a small subset of the precomputed largest-magnitude coefficients to significantly accelerate the algorithm over conventional look-up table methods. We implement the algorithm on a GPU, and report a speedup factor of over 30. We show that this transform is superior over wavelet-based approaches, and show quantitative and qualitative improvements over the state-of-the-art WASABI method; we report accuracy gains of 2dB PSNR, as well improved view preservation.

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  12. Opportunities for Computational Discovery in Basic Energy Sciences

    NASA Astrophysics Data System (ADS)

    Pederson, Mark

    2011-03-01

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

  13. Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  14. The nature of the (visualization) game: Challenges and opportunities from computational geophysics

    NASA Astrophysics Data System (ADS)

    Kellogg, L. H.

    2016-12-01

    As the geosciences enters the era of big data, modeling and visualization become increasingly vital tools for discovery, understanding, education, and communication. Here, we focus on modeling and visualization of the structure and dynamics of the Earth's surface and interior. The past decade has seen accelerated data acquisition, including higher resolution imaging and modeling of Earth's deep interior, complex models of geodynamics, and high resolution topographic imaging of the changing surface, with an associated acceleration of computational modeling through better scientific software, increased computing capability, and the use of innovative methods of scientific visualization. The role of modeling is to describe a system, answer scientific questions, and test hypotheses; the term "model" encompasses mathematical models, computational models, physical models, conceptual models, statistical models, and visual models of a structure or process. These different uses of the term require thoughtful communication to avoid confusion. Scientific visualization is integral to every aspect of modeling. Not merely a means of communicating results, the best uses of visualization enable scientists to interact with their data, revealing the characteristics of the data and models to enable better interpretation and inform the direction of future investigation. Innovative immersive technologies like virtual reality, augmented reality, and remote collaboration techniques, are being adapted more widely and are a magnet for students. Time-varying or transient phenomena are especially challenging to model and to visualize; researchers and students may need to investigate the role of initial conditions in driving phenomena, while nonlinearities in the governing equations of many Earth systems make the computations and resulting visualization especially challenging. Training students how to use, design, build, and interpret scientific modeling and visualization tools prepares them

  15. GPU-accelerated Lattice Boltzmann method for anatomical extraction in patient-specific computational hemodynamics

    NASA Astrophysics Data System (ADS)

    Yu, H.; Wang, Z.; Zhang, C.; Chen, N.; Zhao, Y.; Sawchuk, A. P.; Dalsing, M. C.; Teague, S. D.; Cheng, Y.

    2014-11-01

    Existing research of patient-specific computational hemodynamics (PSCH) heavily relies on software for anatomical extraction of blood arteries. Data reconstruction and mesh generation have to be done using existing commercial software due to the gap between medical image processing and CFD, which increases computation burden and introduces inaccuracy during data transformation thus limits the medical applications of PSCH. We use lattice Boltzmann method (LBM) to solve the level-set equation over an Eulerian distance field and implicitly and dynamically segment the artery surfaces from radiological CT/MRI imaging data. The segments seamlessly feed to the LBM based CFD computation of PSCH thus explicit mesh construction and extra data management are avoided. The LBM is ideally suited for GPU (graphic processing unit)-based parallel computing. The parallel acceleration over GPU achieves excellent performance in PSCH computation. An application study will be presented which segments an aortic artery from a chest CT dataset and models PSCH of the segmented artery.

  16. Sign use and cognition in automated scientific discovery: are computers only special kinds of signs?

    NASA Astrophysics Data System (ADS)

    Giza, Piotr

    2018-04-01

    James Fetzer criticizes the computational paradigm, prevailing in cognitive science by questioning, what he takes to be, its most elementary ingredient: that cognition is computation across representations. He argues that if cognition is taken to be a purposive, meaningful, algorithmic problem solving activity, then computers are incapable of cognition. Instead, they appear to be signs of a special kind, that can facilitate computation. He proposes the conception of minds as semiotic systems as an alternative paradigm for understanding mental phenomena, one that seems to overcome the difficulties of computationalism. Now, I argue, that with computer systems dealing with scientific discovery, the matter is not so simple as that. The alleged superiority of humans using signs to stand for something other over computers being merely "physical symbol systems" or "automatic formal systems" is only easy to establish in everyday life, but becomes far from obvious when scientific discovery is at stake. In science, as opposed to everyday life, the meaning of symbols is, apart from very low-level experimental investigations, defined implicitly by the way the symbols are used in explanatory theories or experimental laws relevant to the field, and in consequence, human and machine discoverers are much more on a par. Moreover, the great practical success of the genetic programming method and recent attempts to apply it to automatic generation of cognitive theories seem to show, that computer systems are capable of very efficient problem solving activity in science, which is neither purposive nor meaningful, nor algorithmic. This, I think, undermines Fetzer's argument that computer systems are incapable of cognition because computation across representations is bound to be a purposive, meaningful, algorithmic problem solving activity.

  17. Acceleration Environment of the International Space Station

    NASA Technical Reports Server (NTRS)

    McPherson, Kevin; Kelly, Eric; Keller, Jennifer

    2009-01-01

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

  18. Accelerating phylogenetics computing on the desktop: experiments with executing UPGMA in programmable logic.

    PubMed

    Davis, J P; Akella, S; Waddell, P H

    2004-01-01

    Having greater computational power on the desktop for processing taxa data sets has been a dream of biologists/statisticians involved in phylogenetics data analysis. Many existing algorithms have been highly optimized-one example being Felsenstein's PHYLIP code, written in C, for UPGMA and neighbor joining algorithms. However, the ability to process more than a few tens of taxa in a reasonable amount of time using conventional computers has not yielded a satisfactory speedup in data processing, making it difficult for phylogenetics practitioners to quickly explore data sets-such as might be done from a laptop computer. We discuss the application of custom computing techniques to phylogenetics. In particular, we apply this technology to speed up UPGMA algorithm execution by a factor of a hundred, against that of PHYLIP code running on the same PC. We report on these experiments and discuss how custom computing techniques can be used to not only accelerate phylogenetics algorithm performance on the desktop, but also on larger, high-performance computing engines, thus enabling the high-speed processing of data sets involving thousands of taxa.

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

    ERIC Educational Resources Information Center

    Paisley, William; Butler, Matilda

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

  20. Managing competing elastic Grid and Cloud scientific computing applications using OpenNebula

    NASA Astrophysics Data System (ADS)

    Bagnasco, S.; Berzano, D.; Lusso, S.; Masera, M.; Vallero, S.

    2015-12-01

    Elastic cloud computing applications, i.e. applications that automatically scale according to computing needs, work on the ideal assumption of infinite resources. While large public cloud infrastructures may be a reasonable approximation of this condition, scientific computing centres like WLCG Grid sites usually work in a saturated regime, in which applications compete for scarce resources through queues, priorities and scheduling policies, and keeping a fraction of the computing cores idle to allow for headroom is usually not an option. In our particular environment one of the applications (a WLCG Tier-2 Grid site) is much larger than all the others and cannot autoscale easily. Nevertheless, other smaller applications can benefit of automatic elasticity; the implementation of this property in our infrastructure, based on the OpenNebula cloud stack, will be described and the very first operational experiences with a small number of strategies for timely allocation and release of resources will be discussed.

  1. Bringing Federated Identity to Grid Computing

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

    Teheran, Jeny

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

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

    DOE PAGES

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

    2015-04-16

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

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

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

    Brown, Maxine D.; Leigh, Jason

    2014-02-17

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

  4. Scientific Services on the Cloud

    NASA Astrophysics Data System (ADS)

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

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

  5. Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

    2016-01-01

    In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

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

    PubMed

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

    2012-01-01

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

  7. Accelerated Reader.

    ERIC Educational Resources Information Center

    Education Commission of the States, Denver, CO.

    This paper provides an overview of Accelerated Reader, a system of computerized testing and record-keeping that supplements the regular classroom reading program. Accelerated Reader's primary goal is to increase literature-based reading practice. The program offers a computer-aided reading comprehension and management program intended to motivate…

  8. Investigation of Storage Options for Scientific Computing on Grid and Cloud Facilities

    NASA Astrophysics Data System (ADS)

    Garzoglio, Gabriele

    2012-12-01

    In recent years, several new storage technologies, such as Lustre, Hadoop, OrangeFS, and BlueArc, have emerged. While several groups have run benchmarks to characterize them under a variety of configurations, more work is needed to evaluate these technologies for the use cases of scientific computing on Grid clusters and Cloud facilities. This paper discusses our evaluation of the technologies as deployed on a test bed at FermiCloud, one of the Fermilab infrastructure-as-a-service Cloud facilities. The test bed consists of 4 server-class nodes with 40 TB of disk space and up to 50 virtual machine clients, some running on the storage server nodes themselves. With this configuration, the evaluation compares the performance of some of these technologies when deployed on virtual machines and on “bare metal” nodes. In addition to running standard benchmarks such as IOZone to check the sanity of our installation, we have run I/O intensive tests using physics-analysis applications. This paper presents how the storage solutions perform in a variety of realistic use cases of scientific computing. One interesting difference among the storage systems tested is found in a decrease in total read throughput with increasing number of client processes, which occurs in some implementations but not others.

  9. Investigation of storage options for scientific computing on Grid and Cloud facilities

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

    Garzoglio, Gabriele

    In recent years, several new storage technologies, such as Lustre, Hadoop, OrangeFS, and BlueArc, have emerged. While several groups have run benchmarks to characterize them under a variety of configurations, more work is needed to evaluate these technologies for the use cases of scientific computing on Grid clusters and Cloud facilities. This paper discusses our evaluation of the technologies as deployed on a test bed at FermiCloud, one of the Fermilab infrastructure-as-a-service Cloud facilities. The test bed consists of 4 server-class nodes with 40 TB of disk space and up to 50 virtual machine clients, some running on the storagemore » server nodes themselves. With this configuration, the evaluation compares the performance of some of these technologies when deployed on virtual machines and on bare metal nodes. In addition to running standard benchmarks such as IOZone to check the sanity of our installation, we have run I/O intensive tests using physics-analysis applications. This paper presents how the storage solutions perform in a variety of realistic use cases of scientific computing. One interesting difference among the storage systems tested is found in a decrease in total read throughput with increasing number of client processes, which occurs in some implementations but not others.« less

  10. CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

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

    Miller, David; Agarwal, Deborah A.; Sun, Xin

    2011-09-01

    The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

  11. CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

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

    Miller, D.; Agarwal, D.; Sun, X.

    2011-01-01

    The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

  12. Covariant Uniform Acceleration

    NASA Astrophysics Data System (ADS)

    Friedman, Yaakov; Scarr, Tzvi

    2013-04-01

    We derive a 4D covariant Relativistic Dynamics Equation. This equation canonically extends the 3D relativistic dynamics equation , where F is the 3D force and p = m0γv is the 3D relativistic momentum. The standard 4D equation is only partially covariant. To achieve full Lorentz covariance, we replace the four-force F by a rank 2 antisymmetric tensor acting on the four-velocity. By taking this tensor to be constant, we obtain a covariant definition of uniformly accelerated motion. This solves a problem of Einstein and Planck. We compute explicit solutions for uniformly accelerated motion. The solutions are divided into four Lorentz-invariant types: null, linear, rotational, and general. For null acceleration, the worldline is cubic in the time. Linear acceleration covariantly extends 1D hyperbolic motion, while rotational acceleration covariantly extends pure rotational motion. We use Generalized Fermi-Walker transport to construct a uniformly accelerated family of inertial frames which are instantaneously comoving to a uniformly accelerated observer. We explain the connection between our approach and that of Mashhoon. We show that our solutions of uniformly accelerated motion have constant acceleration in the comoving frame. Assuming the Weak Hypothesis of Locality, we obtain local spacetime transformations from a uniformly accelerated frame K' to an inertial frame K. The spacetime transformations between two uniformly accelerated frames with the same acceleration are Lorentz. We compute the metric at an arbitrary point of a uniformly accelerated frame. We obtain velocity and acceleration transformations from a uniformly accelerated system K' to an inertial frame K. We introduce the 4D velocity, an adaptation of Horwitz and Piron s notion of "off-shell." We derive the general formula for the time dilation between accelerated clocks. We obtain a formula for the angular velocity of a uniformly accelerated object. Every rest point of K' is uniformly accelerated, and

  13. Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

    DTIC Science & Technology

    1987-10-01

    include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

  14. Acceleration of the matrix multiplication of Radiance three phase daylighting simulations with parallel computing on heterogeneous hardware of personal computer

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

    Zuo, Wangda; McNeil, Andrew; Wetter, Michael

    2013-05-23

    Building designers are increasingly relying on complex fenestration systems to reduce energy consumed for lighting and HVAC in low energy buildings. Radiance, a lighting simulation program, has been used to conduct daylighting simulations for complex fenestration systems. Depending on the configurations, the simulation can take hours or even days using a personal computer. This paper describes how to accelerate the matrix multiplication portion of a Radiance three-phase daylight simulation by conducting parallel computing on heterogeneous hardware of a personal computer. The algorithm was optimized and the computational part was implemented in parallel using OpenCL. The speed of new approach wasmore » evaluated using various daylighting simulation cases on a multicore central processing unit and a graphics processing unit. Based on the measurements and analysis of the time usage for the Radiance daylighting simulation, further speedups can be achieved by using fast I/O devices and storing the data in a binary format.« less

  15. Studying Scientific Discovery by Computer Simulation.

    DTIC Science & Technology

    1983-03-30

    Mendel’s laws of inheritance, the law of Gay- Lussac for gaseous reactions, tile law of Dulong and Petit, the derivation of atomic weights by Avogadro...neceseary mid identify by block number) scientific discovery -ittri sic properties physical laws extensive terms data-driven heuristics intensive...terms theory-driven heuristics conservation laws 20. ABSTRACT (Continue on revere. side It necessary and identify by block number) Scientific discovery

  16. A Hybrid Human-Computer Approach to the Extraction of Scientific Facts from the Literature.

    PubMed

    Tchoua, Roselyne B; Chard, Kyle; Audus, Debra; Qin, Jian; de Pablo, Juan; Foster, Ian

    2016-01-01

    A wealth of valuable data is locked within the millions of research articles published each year. Reading and extracting pertinent information from those articles has become an unmanageable task for scientists. This problem hinders scientific progress by making it hard to build on results buried in literature. Moreover, these data are loosely structured, encoded in manuscripts of various formats, embedded in different content types, and are, in general, not machine accessible. We present a hybrid human-computer solution for semi-automatically extracting scientific facts from literature. This solution combines an automated discovery, download, and extraction phase with a semi-expert crowd assembled from students to extract specific scientific facts. To evaluate our approach we apply it to a challenging molecular engineering scenario, extraction of a polymer property: the Flory-Huggins interaction parameter. We demonstrate useful contributions to a comprehensive database of polymer properties.

  17. Explicit integration with GPU acceleration for large kinetic networks

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

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

    2015-12-01

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

  18. Explicit integration with GPU acceleration for large kinetic networks

    DOE PAGES

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

    2015-09-15

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

  19. LANDSAT-D accelerated payload correction subsystem output computer compatible tape format

    NASA Technical Reports Server (NTRS)

    1982-01-01

    The NASA GSFC LANDSAT-D Ground Segment (GS) is developing an Accelerated Payload Correction Subsystem (APCS) to provide Thematic Mapper (TM) image correction data to be used outside the GS. This correction data is computed from a subset of the TM Payload Correction Data (PCD), which is downlinked from the spacecraft in a 32 Kbps data stream, and mirror scan correction data (MSCD), which is extracted from the wideband video data. This correction data is generated in the GS Thematic Mapper Mission Management Facility (MMF-T), and is recorded on a 9-track 1600 bit per inch computer compatible tape (CCT). This CCT is known as a APCS Output CCT (AOT). The AOT follows standardized corrections with respect to data formats, record construction and record identification. Applicable documents are delineated; common conventions which are used in further defining the structure, format and content of the AOT are defined; and the structure and content of the AOT are described.

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

    PubMed Central

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

    2016-01-01

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

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

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

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

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

  2. Advanced Scientific Computing Research Network Requirements: ASCR Network Requirements Review Final Report

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

    Bacon, Charles; Bell, Greg; Canon, Shane

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SCmore » organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.« less

  3. Instruction-Level Characterization of Scientific Computing Applications Using Hardware Performance Counters

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

    Luo, Y.; Cameron, K.W.

    1998-11-24

    Workload characterization has been proven an essential tool to architecture design and performance evaluation in both scientific and commercial computing areas. Traditional workload characterization techniques include FLOPS rate, cache miss ratios, CPI (cycles per instruction or IPC, instructions per cycle) etc. With the complexity of sophisticated modern superscalar microprocessors, these traditional characterization techniques are not powerful enough to pinpoint the performance bottleneck of an application on a specific microprocessor. They are also incapable of immediately demonstrating the potential performance benefit of any architectural or functional improvement in a new processor design. To solve these problems, many people rely on simulators,more » which have substantial constraints especially on large-scale scientific computing applications. This paper presents a new technique of characterizing applications at the instruction level using hardware performance counters. It has the advantage of collecting instruction-level characteristics in a few runs virtually without overhead or slowdown. A variety of instruction counts can be utilized to calculate some average abstract workload parameters corresponding to microprocessor pipelines or functional units. Based on the microprocessor architectural constraints and these calculated abstract parameters, the architectural performance bottleneck for a specific application can be estimated. In particular, the analysis results can provide some insight to the problem that only a small percentage of processor peak performance can be achieved even for many very cache-friendly codes. Meanwhile, the bottleneck estimation can provide suggestions about viable architectural/functional improvement for certain workloads. Eventually, these abstract parameters can lead to the creation of an analytical microprocessor pipeline model and memory hierarchy model.« less

  4. An Analysis on the Effect of Computer Self-Efficacy over Scientific Research Self-Efficacy and Information Literacy Self-Efficacy

    ERIC Educational Resources Information Center

    Tuncer, Murat

    2013-01-01

    Present research investigates reciprocal relations amidst computer self-efficacy, scientific research and information literacy self-efficacy. Research findings have demonstrated that according to standardized regression coefficients, computer self-efficacy has a positive effect on information literacy self-efficacy. Likewise it has been detected…

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

    NASA Astrophysics Data System (ADS)

    Brædstrup, Christian; Egholm, David

    2013-04-01

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

  6. DB90: A Fortran Callable Relational Database Routine for Scientific and Engineering Computer Programs

    NASA Technical Reports Server (NTRS)

    Wrenn, Gregory A.

    2005-01-01

    This report describes a database routine called DB90 which is intended for use with scientific and engineering computer programs. The software is written in the Fortran 90/95 programming language standard with file input and output routines written in the C programming language. These routines should be completely portable to any computing platform and operating system that has Fortran 90/95 and C compilers. DB90 allows a program to supply relation names and up to 5 integer key values to uniquely identify each record of each relation. This permits the user to select records or retrieve data in any desired order.

  7. Scientific Visualization, Seeing the Unseeable

    ScienceCinema

    LBNL

    2017-12-09

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

  8. A coarse-grid-projection acceleration method for finite-element incompressible flow computations

    NASA Astrophysics Data System (ADS)

    Kashefi, Ali; Staples, Anne; FiN Lab Team

    2015-11-01

    Coarse grid projection (CGP) methodology provides a framework for accelerating computations by performing some part of the computation on a coarsened grid. We apply the CGP to pressure projection methods for finite element-based incompressible flow simulations. Based on it, the predicted velocity field data is restricted to a coarsened grid, the pressure is determined by solving the Poisson equation on the coarse grid, and the resulting data are prolonged to the preset fine grid. The contributions of the CGP method to the pressure correction technique are twofold: first, it substantially lessens the computational cost devoted to the Poisson equation, which is the most time-consuming part of the simulation process. Second, it preserves the accuracy of the velocity field. The velocity and pressure spaces are approximated by Galerkin spectral element using piecewise linear basis functions. A restriction operator is designed so that fine data are directly injected into the coarse grid. The Laplacian and divergence matrices are driven by taking inner products of coarse grid shape functions. Linear interpolation is implemented to construct a prolongation operator. A study of the data accuracy and the CPU time for the CGP-based versus non-CGP computations is presented. Laboratory for Fluid Dynamics in Nature.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

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

    2015-06-01

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

  11. A data management system for engineering and scientific computing

    NASA Technical Reports Server (NTRS)

    Elliot, L.; Kunii, H. S.; Browne, J. C.

    1978-01-01

    Data elements and relationship definition capabilities for this data management system are explicitly tailored to the needs of engineering and scientific computing. System design was based upon studies of data management problems currently being handled through explicit programming. The system-defined data element types include real scalar numbers, vectors, arrays and special classes of arrays such as sparse arrays and triangular arrays. The data model is hierarchical (tree structured). Multiple views of data are provided at two levels. Subschemas provide multiple structural views of the total data base and multiple mappings for individual record types are supported through the use of a REDEFINES capability. The data definition language and the data manipulation language are designed as extensions to FORTRAN. Examples of the coding of real problems taken from existing practice in the data definition language and the data manipulation language are given.

  12. Accelerated Application Development: The ORNL Titan Experience

    DOE PAGES

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

    2015-05-09

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

  13. Accelerated application development: The ORNL Titan experience

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

    Joubert, Wayne; Archibald, Rick; Berrill, Mark

    2015-08-01

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

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

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

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

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

  15. Software Innovations Speed Scientific Computing

    NASA Technical Reports Server (NTRS)

    2012-01-01

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

  16. The InSAR Scientific Computing Environment

    NASA Technical Reports Server (NTRS)

    Rosen, Paul A.; Gurrola, Eric; Sacco, Gian Franco; Zebker, Howard

    2012-01-01

    We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms

  17. Using Equation-Free Computation to Accelerate Network-Free Stochastic Simulation of Chemical Kinetics.

    PubMed

    Lin, Yen Ting; Chylek, Lily A; Lemons, Nathan W; Hlavacek, William S

    2018-06-21

    The chemical kinetics of many complex systems can be concisely represented by reaction rules, which can be used to generate reaction events via a kinetic Monte Carlo method that has been termed network-free simulation. Here, we demonstrate accelerated network-free simulation through a novel approach to equation-free computation. In this process, variables are introduced that approximately capture system state. Derivatives of these variables are estimated using short bursts of exact stochastic simulation and finite differencing. The variables are then projected forward in time via a numerical integration scheme, after which a new exact stochastic simulation is initialized and the whole process repeats. The projection step increases efficiency by bypassing the firing of numerous individual reaction events. As we show, the projected variables may be defined as populations of building blocks of chemical species. The maximal number of connected molecules included in these building blocks determines the degree of approximation. Equation-free acceleration of network-free simulation is found to be both accurate and efficient.

  18. Open scientific communication urged

    NASA Astrophysics Data System (ADS)

    Richman, Barbara T.

    In a report released last week the National Academy of Sciences' Panel on Scientific Communication and National Security concluded that the ‘limited and uncertain benefits’ of controls on the dissemination of scientific and technological research are ‘outweighed by the importance of scientific progress, which open communication accelerates, to the overall welfare of the nation.’ The 18-member panel, chaired by Dale R. Corson, president emeritus of Cornell University, was created last spring (Eos, April 20, 1982, p. 241) to examine the delicate balance between open dissemination of scientific and technical information and the U.S. government's desire to protect scientific and technological achievements from being translated into military advantages for our political adversaries.The panel dealt almost exclusively with the relationship between the United States and the Soviet Union but noted that there are ‘clear problems in scientific communication and national security involving Third World countries.’ Further study of this matter is necessary.

  19. The Effects of Inquiry-Based Computer Simulation with Cooperative Learning on Scientific Thinking and Conceptual Understanding of Gas Laws

    ERIC Educational Resources Information Center

    Abdullah, Sopiah; Shariff, Adilah

    2008-01-01

    The purpose of the study was to investigate the effects of inquiry-based computer simulation with heterogeneous-ability cooperative learning (HACL) and inquiry-based computer simulation with friendship cooperative learning (FCL) on (a) scientific reasoning (SR) and (b) conceptual understanding (CU) among Form Four students in Malaysian Smart…

  20. TU-FG-201-04: Computer Vision in Autonomous Quality Assurance of Linear Accelerators

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

    Yu, H; Jenkins, C; Yu, S

    Purpose: Routine quality assurance (QA) of linear accelerators represents a critical and costly element of a radiation oncology center. Recently, a system was developed to autonomously perform routine quality assurance on linear accelerators. The purpose of this work is to extend this system and contribute computer vision techniques for obtaining quantitative measurements for a monthly multi-leaf collimator (MLC) QA test specified by TG-142, namely leaf position accuracy, and demonstrate extensibility for additional routines. Methods: Grayscale images of a picket fence delivery on a radioluminescent phosphor coated phantom are captured using a CMOS camera. Collected images are processed to correct formore » camera distortions, rotation and alignment, reduce noise, and enhance contrast. The location of each MLC leaf is determined through logistic fitting and a priori modeling based on knowledge of the delivered beams. Using the data collected and the criteria from TG-142, a decision is made on whether or not the leaf position accuracy of the MLC passes or fails. Results: The locations of all MLC leaf edges are found for three different picket fence images in a picket fence routine to 0.1mm/1pixel precision. The program to correct for image alignment and determination of leaf positions requires a runtime of 21– 25 seconds for a single picket, and 44 – 46 seconds for a group of three pickets on a standard workstation CPU, 2.2 GHz Intel Core i7. Conclusion: MLC leaf edges were successfully found using techniques in computer vision. With the addition of computer vision techniques to the previously described autonomous QA system, the system is able to quickly perform complete QA routines with minimal human contribution.« less

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

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

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

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

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

    DOE PAGES

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

    2015-12-12

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

  3. Acceleration and Velocity Sensing from Measured Strain

    NASA Technical Reports Server (NTRS)

    Pak, Chan-Gi; Truax, Roger

    2015-01-01

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

  4. QALMA: A computational toolkit for the analysis of quality protocols for medical linear accelerators in radiation therapy

    NASA Astrophysics Data System (ADS)

    Rahman, Md Mushfiqur; Lei, Yu; Kalantzis, Georgios

    2018-01-01

    Quality Assurance (QA) for medical linear accelerator (linac) is one of the primary concerns in external beam radiation Therapy. Continued advancements in clinical accelerators and computer control technology make the QA procedures more complex and time consuming which often, adequate software accompanied with specific phantoms is required. To ameliorate that matter, we introduce QALMA (Quality Assurance for Linac with MATLAB), a MALAB toolkit which aims to simplify the quantitative analysis of QA for linac which includes Star-Shot analysis, Picket Fence test, Winston-Lutz test, Multileaf Collimator (MLC) log file analysis and verification of light & radiation field coincidence test.

  5. Semiempirical Quantum Chemical Calculations Accelerated on a Hybrid Multicore CPU-GPU Computing Platform.

    PubMed

    Wu, Xin; Koslowski, Axel; Thiel, Walter

    2012-07-10

    In this work, we demonstrate that semiempirical quantum chemical calculations can be accelerated significantly by leveraging the graphics processing unit (GPU) as a coprocessor on a hybrid multicore CPU-GPU computing platform. Semiempirical calculations using the MNDO, AM1, PM3, OM1, OM2, and OM3 model Hamiltonians were systematically profiled for three types of test systems (fullerenes, water clusters, and solvated crambin) to identify the most time-consuming sections of the code. The corresponding routines were ported to the GPU and optimized employing both existing library functions and a GPU kernel that carries out a sequence of noniterative Jacobi transformations during pseudodiagonalization. The overall computation times for single-point energy calculations and geometry optimizations of large molecules were reduced by one order of magnitude for all methods, as compared to runs on a single CPU core.

  6. Acceleration technologies for charged particles: an introduction

    NASA Astrophysics Data System (ADS)

    Carter, Richard G.

    2011-01-01

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

  7. The Goal Specificity Effect on Strategy Use and Instructional Efficiency during Computer-Based Scientific Discovery Learning

    ERIC Educational Resources Information Center

    Kunsting, Josef; Wirth, Joachim; Paas, Fred

    2011-01-01

    Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the "effects of goal specificity" (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on "strategy use" and "instructional efficiency". Our empirical findings close an important research gap,…

  8. Computer modeling of test particle acceleration at oblique shocks

    NASA Technical Reports Server (NTRS)

    Decker, Robert B.

    1988-01-01

    The present evaluation of the basic techniques and illustrative results of charged particle-modeling numerical codes suitable for particle acceleration at oblique, fast-mode collisionless shocks emphasizes the treatment of ions as test particles, calculating particle dynamics through numerical integration along exact phase-space orbits. Attention is given to the acceleration of particles at planar, infinitessimally thin shocks, as well as to plasma simulations in which low-energy ions are injected and accelerated at quasi-perpendicular shocks with internal structure.

  9. Highly Productive Application Development with ViennaCL for Accelerators

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    for types from the Eigen library [8] and MTL 4 [9] are provided as well, enabling a seamless transition from single-core CPU to GPU and multi-core CPU computations. Case studies from the numerical solution of PDEs are given and isolated performance benchmarks are discussed. Also, pitfalls in scientific computing with GPUs and accelerators are addressed, allowing for a first evaluation of whether these novel devices can be mapped well to certain applications. References: [1] R. Bordawekar et al., Technical Report, IBM, 2010 [2] ViennaCL library. Online: http://viennacl.sourceforge.net/ [3] K. Rupp et al., GPUScA, 2010 [4] MAGMA library. Online: http://icl.cs.utk.edu/magma/ [5] Cusp library. Online: http://code.google.com/p/cusp-library/ [6] uBLAS library. Online: http://www.boost.org/libs/numeric/ublas/ [7] Boost C++ Libraries. Online: http://www.boost.org/ [8] Eigen library. Online: http://eigen.tuxfamily.org/ [9] MTL 4 Library. Online: http://www.mtl4.org/

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

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

    You, Yang; Fu, Haohuan; Song, Shuaiwen

    2014-07-18

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

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

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

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

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

  12. The OSG Open Facility: an on-ramp for opportunistic scientific computing

    NASA Astrophysics Data System (ADS)

    Jayatilaka, B.; Levshina, T.; Sehgal, C.; Gardner, R.; Rynge, M.; Würthwein, F.

    2017-10-01

    The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource owners and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.

  13. The OSG Open Facility: An On-Ramp for Opportunistic Scientific Computing

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

    Jayatilaka, B.; Levshina, T.; Sehgal, C.

    The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource ownersmore » and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.« less

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

    EPA Pesticide Factsheets

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

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

    NASA Astrophysics Data System (ADS)

    Sourouri, Mohammed; Birger Raknes, Espen

    2017-04-01

    In advanced imaging methods like reverse-time migration (RTM) and full waveform inversion (FWI) the elastic wave equation (EWE) is numerically solved many times to create the seismic image or the elastic parameter model update. Thus, it is essential to optimize the solution time for solving the EWE as this will have a major impact on the total computational cost in running RTM or FWI. From a computational point of view applications implementing EWEs are associated with two major challenges. The first challenge is the amount of memory-bound computations involved, while the second challenge is the execution of such computations over very large datasets. So far, multi-core processors have not been able to tackle these two challenges, which eventually led to the adoption of accelerators such as Graphics Processing Units (GPUs). Compared to conventional CPUs, GPUs are densely populated with many floating-point units and fast memory, a type of architecture that has proven to map well to many scientific computations. Despite its architectural advantages, full-scale adoption of accelerators has yet to materialize. First, accelerators require a significant programming effort imposed by programming models such as CUDA or OpenCL. Second, accelerators come with a limited amount of memory, which also require explicit data transfers between the CPU and the accelerator over the slow PCI bus. The second generation of the Xeon Phi processor based on the Knights Landing (KNL) architecture, promises the computational capabilities of an accelerator but require the same programming effort as traditional multi-core processors. The high computational performance is realized through many integrated cores (number of cores and tiles and memory varies with the model) organized in tiles that are connected via a 2D mesh based interconnect. In contrary to accelerators, KNL is a self-hosted system, meaning explicit data transfers over the PCI bus are no longer required. However, like most

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

    NASA Technical Reports Server (NTRS)

    Biswas, Rupak

    2006-01-01

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

  17. Computational Cosmology at the Bleeding Edge

    NASA Astrophysics Data System (ADS)

    Habib, Salman

    2013-04-01

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

  18. Accelerating Approximate Bayesian Computation with Quantile Regression: application to cosmological redshift distributions

    NASA Astrophysics Data System (ADS)

    Kacprzak, T.; Herbel, J.; Amara, A.; Réfrégier, A.

    2018-02-01

    Approximate Bayesian Computation (ABC) is a method to obtain a posterior distribution without a likelihood function, using simulations and a set of distance metrics. For that reason, it has recently been gaining popularity as an analysis tool in cosmology and astrophysics. Its drawback, however, is a slow convergence rate. We propose a novel method, which we call qABC, to accelerate ABC with Quantile Regression. In this method, we create a model of quantiles of distance measure as a function of input parameters. This model is trained on a small number of simulations and estimates which regions of the prior space are likely to be accepted into the posterior. Other regions are then immediately rejected. This procedure is then repeated as more simulations are available. We apply it to the practical problem of estimation of redshift distribution of cosmological samples, using forward modelling developed in previous work. The qABC method converges to nearly same posterior as the basic ABC. It uses, however, only 20% of the number of simulations compared to basic ABC, achieving a fivefold gain in execution time for our problem. For other problems the acceleration rate may vary; it depends on how close the prior is to the final posterior. We discuss possible improvements and extensions to this method.

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

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

    Higgins, Valerie

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

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

    DOE PAGES

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

    2018-01-31

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

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

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

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

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

  2. Amplify scientific discovery with artificial intelligence

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

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

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

  3. Good enough practices in scientific computing.

    PubMed

    Wilson, Greg; Bryan, Jennifer; Cranston, Karen; Kitzes, Justin; Nederbragt, Lex; Teal, Tracy K

    2017-06-01

    Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing. As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data. Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often don't know where to start. This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010.

  4. PS3 CELL Development for Scientific Computation and Research

    NASA Astrophysics Data System (ADS)

    Christiansen, M.; Sevre, E.; Wang, S. M.; Yuen, D. A.; Liu, S.; Lyness, M. D.; Broten, M.

    2007-12-01

    The Cell processor is one of the most powerful processors on the market, and researchers in the earth sciences may find its parallel architecture to be very useful. A cell processor, with 7 cores, can easily be obtained for experimentation by purchasing a PlayStation 3 (PS3) and installing linux and the IBM SDK. Each core of the PS3 is capable of 25 GFLOPS giving a potential limit of 150 GFLOPS when using all 6 SPUs (synergistic processing units) by using vectorized algorithms. We have used the Cell's computational power to create a program which takes simulated tsunami datasets, parses them, and returns a colorized height field image using ray casting techniques. As expected, the time required to create an image is inversely proportional to the number of SPUs used. We believe that this trend will continue when multiple PS3s are chained using OpenMP functionality and are in the process of researching this. By using the Cell to visualize tsunami data, we have found that its greatest feature is its power. This fact entwines well with the needs of the scientific community where the limiting factor is time. Any algorithm, such as the heat equation, that can be subdivided into multiple parts can take advantage of the PS3 Cell's ability to split the computations across the 6 SPUs reducing required run time by one sixth. Further vectorization of the code can allow for 4 simultanious floating point operations by using the SIMD (single instruction multiple data) capabilities of the SPU increasing efficiency 24 times.

  5. Using Cloud-Computing Applications to Support Collaborative Scientific Inquiry: Examining Pre-Service Teachers' Perceived Barriers to Integration

    ERIC Educational Resources Information Center

    Donna, Joel D.; Miller, Brant G.

    2013-01-01

    Technology plays a crucial role in facilitating collaboration within the scientific community. Cloud-computing applications, such as Google Drive, can be used to model such collaboration and support inquiry within the secondary science classroom. Little is known about pre-service teachers' beliefs related to the envisioned use of collaborative,…

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    DOE PAGES

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

    2017-08-26

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

  8. Computationally efficient methods for modelling laser wakefield acceleration in the blowout regime

    NASA Astrophysics Data System (ADS)

    Cowan, B. M.; Kalmykov, S. Y.; Beck, A.; Davoine, X.; Bunkers, K.; Lifschitz, A. F.; Lefebvre, E.; Bruhwiler, D. L.; Shadwick, B. A.; Umstadter, D. P.; Umstadter

    2012-08-01

    Electron self-injection and acceleration until dephasing in the blowout regime is studied for a set of initial conditions typical of recent experiments with 100-terawatt-class lasers. Two different approaches to computationally efficient, fully explicit, 3D particle-in-cell modelling are examined. First, the Cartesian code vorpal (Nieter, C. and Cary, J. R. 2004 VORPAL: a versatile plasma simulation code. J. Comput. Phys. 196, 538) using a perfect-dispersion electromagnetic solver precisely describes the laser pulse and bubble dynamics, taking advantage of coarser resolution in the propagation direction, with a proportionally larger time step. Using third-order splines for macroparticles helps suppress the sampling noise while keeping the usage of computational resources modest. The second way to reduce the simulation load is using reduced-geometry codes. In our case, the quasi-cylindrical code calder-circ (Lifschitz, A. F. et al. 2009 Particle-in-cell modelling of laser-plasma interaction using Fourier decomposition. J. Comput. Phys. 228(5), 1803-1814) uses decomposition of fields and currents into a set of poloidal modes, while the macroparticles move in the Cartesian 3D space. Cylindrical symmetry of the interaction allows using just two modes, reducing the computational load to roughly that of a planar Cartesian simulation while preserving the 3D nature of the interaction. This significant economy of resources allows using fine resolution in the direction of propagation and a small time step, making numerical dispersion vanishingly small, together with a large number of particles per cell, enabling good particle statistics. Quantitative agreement of two simulations indicates that these are free of numerical artefacts. Both approaches thus retrieve the physically correct evolution of the plasma bubble, recovering the intrinsic connection of electron self-injection to the nonlinear optical evolution of the driver.

  9. From experiment to design -- Fault characterization and detection in parallel computer systems using computational accelerators

    NASA Astrophysics Data System (ADS)

    Yim, Keun Soo

    This dissertation summarizes experimental validation and co-design studies conducted to optimize the fault detection capabilities and overheads in hybrid computer systems (e.g., using CPUs and Graphics Processing Units, or GPUs), and consequently to improve the scalability of parallel computer systems using computational accelerators. The experimental validation studies were conducted to help us understand the failure characteristics of CPU-GPU hybrid computer systems under various types of hardware faults. The main characterization targets were faults that are difficult to detect and/or recover from, e.g., faults that cause long latency failures (Ch. 3), faults in dynamically allocated resources (Ch. 4), faults in GPUs (Ch. 5), faults in MPI programs (Ch. 6), and microarchitecture-level faults with specific timing features (Ch. 7). The co-design studies were based on the characterization results. One of the co-designed systems has a set of source-to-source translators that customize and strategically place error detectors in the source code of target GPU programs (Ch. 5). Another co-designed system uses an extension card to learn the normal behavioral and semantic execution patterns of message-passing processes executing on CPUs, and to detect abnormal behaviors of those parallel processes (Ch. 6). The third co-designed system is a co-processor that has a set of new instructions in order to support software-implemented fault detection techniques (Ch. 7). The work described in this dissertation gains more importance because heterogeneous processors have become an essential component of state-of-the-art supercomputers. GPUs were used in three of the five fastest supercomputers that were operating in 2011. Our work included comprehensive fault characterization studies in CPU-GPU hybrid computers. In CPUs, we monitored the target systems for a long period of time after injecting faults (a temporally comprehensive experiment), and injected faults into various types of

  10. NIH/NSF accelerate biomedical research innovations

    Cancer.gov

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

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

    PubMed Central

    Gokmen, Tayfun; Vlasov, Yurii

    2016-01-01

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

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

    PubMed

    Gokmen, Tayfun; Vlasov, Yurii

    2016-01-01

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

  13. GPU-accelerated computational tool for studying the effectiveness of asteroid disruption techniques

    NASA Astrophysics Data System (ADS)

    Zimmerman, Ben J.; Wie, Bong

    2016-10-01

    This paper presents the development of a new Graphics Processing Unit (GPU) accelerated computational tool for asteroid disruption techniques. Numerical simulations are completed using the high-order spectral difference (SD) method. Due to the compact nature of the SD method, it is well suited for implementation with the GPU architecture, hence solutions are generated at orders of magnitude faster than the Central Processing Unit (CPU) counterpart. A multiphase model integrated with the SD method is introduced, and several asteroid disruption simulations are conducted, including kinetic-energy impactors, multi-kinetic energy impactor systems, and nuclear options. Results illustrate the benefits of using multi-kinetic energy impactor systems when compared to a single impactor system. In addition, the effectiveness of nuclear options is observed.

  14. An Accelerated Recursive Doubling Algorithm for Block Tridiagonal Systems

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

    Seal, Sudip K

    2014-01-01

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

  15. Comparison of Scientific Calipers and Computer-Enabled CT Review for the Measurement of Skull Base and Craniomaxillofacial Dimensions

    PubMed Central

    Citardi, Martin J.; Herrmann, Brian; Hollenbeak, Chris S.; Stack, Brendan C.; Cooper, Margaret; Bucholz, Richard D.

    2001-01-01

    Traditionally, cadaveric studies and plain-film cephalometrics provided information about craniomaxillofacial proportions and measurements; however, advances in computer technology now permit software-based review of computed tomography (CT)-based models. Distances between standardized anatomic points were measured on five dried human skulls with standard scientific calipers (Geneva Gauge, Albany, NY) and through computer workstation (StealthStation 2.6.4, Medtronic Surgical Navigation Technology, Louisville, CO) review of corresponding CT scans. Differences in measurements between the caliper and CT model were not statistically significant for each parameter. Measurements obtained by computer workstation CT review of the cranial skull base are an accurate representation of actual bony anatomy. Such information has important implications for surgical planning and clinical research. ImagesFigure 1Figure 2Figure 3 PMID:17167599

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

    PubMed

    Tian, Xinzhi

    2017-11-30

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

  17. Checkpointing for a hybrid computing node

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

    Cher, Chen-Yong

    2016-03-08

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

  18. Validation of GPU-accelerated superposition-convolution dose computations for the Small Animal Radiation Research Platform.

    PubMed

    Cho, Nathan; Tsiamas, Panagiotis; Velarde, Esteban; Tryggestad, Erik; Jacques, Robert; Berbeco, Ross; McNutt, Todd; Kazanzides, Peter; Wong, John

    2018-05-01

    The Small Animal Radiation Research Platform (SARRP) has been developed for conformal microirradiation with on-board cone beam CT (CBCT) guidance. The graphics processing unit (GPU)-accelerated Superposition-Convolution (SC) method for dose computation has been integrated into the treatment planning system (TPS) for SARRP. This paper describes the validation of the SC method for the kilovoltage energy by comparing with EBT2 film measurements and Monte Carlo (MC) simulations. MC data were simulated by EGSnrc code with 3 × 10 8 -1.5 × 10 9 histories, while 21 photon energy bins were used to model the 220 kVp x-rays in the SC method. Various types of phantoms including plastic water, cork, graphite, and aluminum were used to encompass the range of densities of mouse organs. For the comparison, percentage depth dose (PDD) of SC, MC, and film measurements were analyzed. Cross beam (x,y) dosimetric profiles of SC and film measurements are also presented. Correction factors (CFz) to convert SC to MC dose-to-medium are derived from the SC and MC simulations in homogeneous phantoms of aluminum and graphite to improve the estimation. The SC method produces dose values that are within 5% of film measurements and MC simulations in the flat regions of the profile. The dose is less accurate at the edges, due to factors such as geometric uncertainties of film placement and difference in dose calculation grids. The GPU-accelerated Superposition-Convolution dose computation method was successfully validated with EBT2 film measurements and MC calculations. The SC method offers much faster computation speed than MC and provides calculations of both dose-to-water in medium and dose-to-medium in medium. © 2018 American Association of Physicists in Medicine.

  19. The Centre of High-Performance Scientific Computing, Geoverbund, ABC/J - Geosciences enabled by HPSC

    NASA Astrophysics Data System (ADS)

    Kollet, Stefan; Görgen, Klaus; Vereecken, Harry; Gasper, Fabian; Hendricks-Franssen, Harrie-Jan; Keune, Jessica; Kulkarni, Ketan; Kurtz, Wolfgang; Sharples, Wendy; Shrestha, Prabhakar; Simmer, Clemens; Sulis, Mauro; Vanderborght, Jan

    2016-04-01

    The Centre of High-Performance Scientific Computing (HPSC TerrSys) was founded 2011 to establish a centre of competence in high-performance scientific computing in terrestrial systems and the geosciences enabling fundamental and applied geoscientific research in the Geoverbund ABC/J (geoscientfic research alliance of the Universities of Aachen, Cologne, Bonn and the Research Centre Jülich, Germany). The specific goals of HPSC TerrSys are to achieve relevance at the national and international level in (i) the development and application of HPSC technologies in the geoscientific community; (ii) student education; (iii) HPSC services and support also to the wider geoscientific community; and in (iv) the industry and public sectors via e.g., useful applications and data products. A key feature of HPSC TerrSys is the Simulation Laboratory Terrestrial Systems, which is located at the Jülich Supercomputing Centre (JSC) and provides extensive capabilities with respect to porting, profiling, tuning and performance monitoring of geoscientific software in JSC's supercomputing environment. We will present a summary of success stories of HPSC applications including integrated terrestrial model development, parallel profiling and its application from watersheds to the continent; massively parallel data assimilation using physics-based models and ensemble methods; quasi-operational terrestrial water and energy monitoring; and convection permitting climate simulations over Europe. The success stories stress the need for a formalized education of students in the application of HPSC technologies in future.

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

    PubMed

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

    2016-10-06

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

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

    NASA Astrophysics Data System (ADS)

    Myre, Joseph M.

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

  2. Advanced computations in plasma physics

    NASA Astrophysics Data System (ADS)

    Tang, W. M.

    2002-05-01

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

  3. Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence

    PubMed Central

    Gimeno-Blanes, Francisco J.; Blanco-Velasco, Manuel; Barquero-Pérez, Óscar; García-Alberola, Arcadi; Rojo-Álvarez, José L.

    2016-01-01

    Great effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG) analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limited diagnostic accuracy and to the lack of consensus about the appropriate computational signal processing implementation. This paper addresses a three-fold approach, based on ECG indices, to structure this review on sudden cardiac risk stratification. First, throughout the computational techniques that had been widely proposed for obtaining these indices in technical literature. Second, over the scientific evidence, that although is supported by observational clinical studies, they are not always representative enough. And third, via the limited technology transfer of academy-accepted algorithms, requiring further meditation for future systems. We focus on three families of ECG derived indices which are tackled from the aforementioned viewpoints, namely, heart rate turbulence (HRT), heart rate variability (HRV), and T-wave alternans. In terms of computational algorithms, we still need clearer scientific evidence, standardizing, and benchmarking, siting on advanced algorithms applied over large and representative datasets. New scenarios like electronic health recordings, big data, long-term monitoring, and cloud databases, will eventually open new frameworks to foresee suitable new paradigms in the near future. PMID:27014083

  4. Model-Driven Development for scientific computing. Computations of RHEED intensities for a disordered surface. Part I

    NASA Astrophysics Data System (ADS)

    Daniluk, Andrzej

    2010-03-01

    Scientific computing is the field of study concerned with constructing mathematical models, numerical solution techniques and with using computers to analyse and solve scientific and engineering problems. Model-Driven Development (MDD) has been proposed as a means to support the software development process through the use of a model-centric approach. This paper surveys the core MDD technology that was used to develop an application that allows computation of the RHEED intensities dynamically for a disordered surface. New version program summaryProgram title: RHEED1DProcess Catalogue identifier: ADUY_v4_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADUY_v4_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 31 971 No. of bytes in distributed program, including test data, etc.: 3 039 820 Distribution format: tar.gz Programming language: Embarcadero C++ Builder Computer: Intel Core Duo-based PC Operating system: Windows XP, Vista, 7 RAM: more than 1 GB Classification: 4.3, 7.2, 6.2, 8, 14 Catalogue identifier of previous version: ADUY_v3_0 Journal reference of previous version: Comput. Phys. Comm. 180 (2009) 2394 Does the new version supersede the previous version?: No Nature of problem: An application that implements numerical simulations should be constructed according to the CSFAR rules: clear and well-documented, simple, fast, accurate, and robust. A clearly written, externally and internally documented program is much easier to understand and modify. A simple program is much less prone to error and is more easily modified than one that is complicated. Simplicity and clarity also help make the program flexible. Making the program fast has economic benefits. It also allows flexibility because some of the features that make a program efficient can be traded off for

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

    DOE PAGES

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

    2014-01-01

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

  6. Cancer Diagnosis Epigenomics Scientific Workflow Scheduling in the Cloud Computing Environment Using an Improved PSO Algorithm

    PubMed

    N, Sadhasivam; R, Balamurugan; M, Pandi

    2018-01-27

    Objective: Epigenetic modifications involving DNA methylation and histone statud are responsible for the stable maintenance of cellular phenotypes. Abnormalities may be causally involved in cancer development and therefore could have diagnostic potential. The field of epigenomics refers to all epigenetic modifications implicated in control of gene expression, with a focus on better understanding of human biology in both normal and pathological states. Epigenomics scientific workflow is essentially a data processing pipeline to automate the execution of various genome sequencing operations or tasks. Cloud platform is a popular computing platform for deploying large scale epigenomics scientific workflow. Its dynamic environment provides various resources to scientific users on a pay-per-use billing model. Scheduling epigenomics scientific workflow tasks is a complicated problem in cloud platform. We here focused on application of an improved particle swam optimization (IPSO) algorithm for this purpose. Methods: The IPSO algorithm was applied to find suitable resources and allocate epigenomics tasks so that the total cost was minimized for detection of epigenetic abnormalities of potential application for cancer diagnosis. Result: The results showed that IPSO based task to resource mapping reduced total cost by 6.83 percent as compared to the traditional PSO algorithm. Conclusion: The results for various cancer diagnosis tasks showed that IPSO based task to resource mapping can achieve better costs when compared to PSO based mapping for epigenomics scientific application workflow. Creative Commons Attribution License

  7. Acceleration and Velocity Sensing from Measured Strain

    NASA Technical Reports Server (NTRS)

    Pak, Chan-Gi; Truax, Roger

    2016-01-01

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

  8. Choosing experiments to accelerate collective discovery

    DOE PAGES

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

    2015-11-24

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

  9. The accelerator neutron source for boron neutron capture therapy

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  10. The Operation of a Specialized Scientific Information and Data Analysis Center With Computer Base and Associated Communications Network.

    ERIC Educational Resources Information Center

    Cottrell, William B.; And Others

    The Nuclear Safety Information Center (NSIC) is a highly sophisticated scientific information center operated at Oak Ridge National Laboratory (ORNL) for the U.S. Atomic Energy Commission. Its information file, which consists of both data and bibliographic information, is computer stored and numerous programs have been developed to facilitate the…

  11. Accelerating Dust Storm Simulation by Balancing Task Allocation in Parallel Computing Environment

    NASA Astrophysics Data System (ADS)

    Gui, Z.; Yang, C.; XIA, J.; Huang, Q.; YU, M.

    2013-12-01

    Dust storm has serious negative impacts on environment, human health, and assets. The continuing global climate change has increased the frequency and intensity of dust storm in the past decades. To better understand and predict the distribution, intensity and structure of dust storm, a series of dust storm models have been developed, such as Dust Regional Atmospheric Model (DREAM), the NMM meteorological module (NMM-dust) and Chinese Unified Atmospheric Chemistry Environment for Dust (CUACE/Dust). The developments and applications of these models have contributed significantly to both scientific research and our daily life. However, dust storm simulation is a data and computing intensive process. Normally, a simulation for a single dust storm event may take several days or hours to run. It seriously impacts the timeliness of prediction and potential applications. To speed up the process, high performance computing is widely adopted. By partitioning a large study area into small subdomains according to their geographic location and executing them on different computing nodes in a parallel fashion, the computing performance can be significantly improved. Since spatiotemporal correlations exist in the geophysical process of dust storm simulation, each subdomain allocated to a node need to communicate with other geographically adjacent subdomains to exchange data. Inappropriate allocations may introduce imbalance task loads and unnecessary communications among computing nodes. Therefore, task allocation method is the key factor, which may impact the feasibility of the paralleling. The allocation algorithm needs to carefully leverage the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire system. This presentation introduces two algorithms for such allocation and compares them with evenly distributed allocation method. Specifically, 1) In order to get optimized solutions, a

  12. The NOAA Scientific Computing System Data Assembly Center

    NASA Astrophysics Data System (ADS)

    Suchdeve, K. L.; Smith, S. R.; Van Waes, M.

    2016-02-01

    The Scientific Computing System (SCS) Data Assembly Center (DAC) was established in 2014 by the Office of Marine and Aviation Operations (OMAO) to evaluate the quality of full-resolution (sampling on the order of once per second) data collected by SCS onboard NOAA-operated research vessels. The SCS data are nominally transferred from the vessel to the National Centers for Environmental Information (NCEI) soon after the completion of each cruise and are complimented with detailed cruise metadata from OMAO. The authors will describe tools developed by the SCS DAC to monitor the timeliness of SCS data delivery to NCEI and the completeness of the SCS packages received by NCEI (ensuring the package contains data for all enabled sensors on a given cruise). Feedback to OMAO and NCEI regarding the timeliness and data completeness will be outlined along with challenges encountered by the DAC as it works to develop automated quality assessment of the SCS data packages.Data collected by SCS on NOAA vessels represent a significant investment by the American taxpayer. The mission of the SCS DAC is to ensure that archived SCS data at NCEI are a complete record of the observations made on NOAA research cruises. Archival of complete SCS datasets at NCEI ensures these data are preserved for future generations of scientists, policy makers, and the public.

  13. Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

    DOE PAGES

    Haidar, Azzam; Jagode, Heike; Vaccaro, Phil; ...

    2018-03-22

    The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

  14. Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

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

    Haidar, Azzam; Jagode, Heike; Vaccaro, Phil

    The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

  15. Impact of configuration management system of computer center on support of scientific projects throughout their lifecycle

    NASA Astrophysics Data System (ADS)

    Bogdanov, A. V.; Iuzhanin, N. V.; Zolotarev, V. I.; Ezhakova, T. R.

    2017-12-01

    In this article the problem of scientific projects support throughout their lifecycle in the computer center is considered in every aspect of support. Configuration Management system plays a connecting role in processes related to the provision and support of services of a computer center. In view of strong integration of IT infrastructure components with the use of virtualization, control of infrastructure becomes even more critical to the support of research projects, which means higher requirements for the Configuration Management system. For every aspect of research projects support, the influence of the Configuration Management system is being reviewed and development of the corresponding elements of the system is being described in the present paper.

  16. Particle acceleration, transport and turbulence in cosmic and heliospheric physics

    NASA Technical Reports Server (NTRS)

    Matthaeus, W.

    1992-01-01

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

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

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

    Kostadin, Damevski

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

  18. Advances and challenges in computational plasma science

    NASA Astrophysics Data System (ADS)

    Tang, W. M.

    2005-02-01

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

  19. Accelerator on a Chip

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

    England, Joel

    2014-06-30

    SLAC's Joel England explains how the same fabrication techniques used for silicon computer microchips allowed their team to create the new laser-driven particle accelerator chips. (SLAC Multimedia Communications)

  20. Accelerator on a Chip

    ScienceCinema

    England, Joel

    2018-01-16

    SLAC's Joel England explains how the same fabrication techniques used for silicon computer microchips allowed their team to create the new laser-driven particle accelerator chips. (SLAC Multimedia Communications)

  1. Advanced Computation in Plasma Physics

    NASA Astrophysics Data System (ADS)

    Tang, William

    2001-10-01

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

  2. Accelerated time-of-flight (TOF) PET image reconstruction using TOF bin subsetization and TOF weighting matrix pre-computation.

    PubMed

    Mehranian, Abolfazl; Kotasidis, Fotis; Zaidi, Habib

    2016-02-07

    FDG-PET study also revealed that for the same noise level, a higher contrast recovery can be obtained by increasing the number of TOF subsets. It can be concluded that the proposed TOF weighting matrix pre-computation and subsetization approaches enable to further accelerate and improve the convergence properties of OSEM and MLEM algorithms, thus opening new avenues for accelerated TOF PET image reconstruction.

  3. Accelerated time-of-flight (TOF) PET image reconstruction using TOF bin subsetization and TOF weighting matrix pre-computation

    NASA Astrophysics Data System (ADS)

    Mehranian, Abolfazl; Kotasidis, Fotis; Zaidi, Habib

    2016-02-01

    FDG-PET study also revealed that for the same noise level, a higher contrast recovery can be obtained by increasing the number of TOF subsets. It can be concluded that the proposed TOF weighting matrix pre-computation and subsetization approaches enable to further accelerate and improve the convergence properties of OSEM and MLEM algorithms, thus opening new avenues for accelerated TOF PET image reconstruction.

  4. Acceleration and torque feedback for robotic control - Experimental results

    NASA Technical Reports Server (NTRS)

    Mclnroy, John E.; Saridis, George N.

    1990-01-01

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

  5. 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

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

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

    Brown, W Michael; Yamada, Masako

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

  7. Diagnosis of Acceleration, Reconnection, Turbulence, and Heating

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

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

    PubMed

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

    2017-03-28

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

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

    PubMed Central

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

    2017-01-01

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

  10. Accelerated Adaptive MGS Phase Retrieval

    NASA Technical Reports Server (NTRS)

    Lam, Raymond K.; Ohara, Catherine M.; Green, Joseph J.; Bikkannavar, Siddarayappa A.; Basinger, Scott A.; Redding, David C.; Shi, Fang

    2011-01-01

    The Modified Gerchberg-Saxton (MGS) algorithm is an image-based wavefront-sensing method that can turn any science instrument focal plane into a wavefront sensor. MGS characterizes optical systems by estimating the wavefront errors in the exit pupil using only intensity images of a star or other point source of light. This innovative implementation of MGS significantly accelerates the MGS phase retrieval algorithm by using stream-processing hardware on conventional graphics cards. Stream processing is a relatively new, yet powerful, paradigm to allow parallel processing of certain applications that apply single instructions to multiple data (SIMD). These stream processors are designed specifically to support large-scale parallel computing on a single graphics chip. Computationally intensive algorithms, such as the Fast Fourier Transform (FFT), are particularly well suited for this computing environment. This high-speed version of MGS exploits commercially available hardware to accomplish the same objective in a fraction of the original time. The exploit involves performing matrix calculations in nVidia graphic cards. The graphical processor unit (GPU) is hardware that is specialized for computationally intensive, highly parallel computation. From the software perspective, a parallel programming model is used, called CUDA, to transparently scale multicore parallelism in hardware. This technology gives computationally intensive applications access to the processing power of the nVidia GPUs through a C/C++ programming interface. The AAMGS (Accelerated Adaptive MGS) software takes advantage of these advanced technologies, to accelerate the optical phase error characterization. With a single PC that contains four nVidia GTX-280 graphic cards, the new implementation can process four images simultaneously to produce a JWST (James Webb Space Telescope) wavefront measurement 60 times faster than the previous code.

  11. Report for the Office of Scientific and Technical Information: Population Modeling of the Emergence and Development of Scientific Fields

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

    Bettencourt, L. M. A.; Castillo-Chavez, C.; Kaiser, D.

    2006-10-04

    The accelerated development of digital libraries and archives, in tandem with efficient search engines and the computational ability to retrieve and parse massive amounts of information, are making it possible to quantify the time evolution of scientific literatures. These data are but one piece of the tangible recorded evidence of the processes whereby scientists create and exchange information in their journeys towards the generation of knowledge. As such, these tools provide a proxy with which to study our ability to innovate. Innovation has often been linked with prosperity and growth and, consequently, trying to understand what drives scientific innovation ismore » of extreme interest. Identifying sets of population characteristics, factors, and mechanisms that enable scientific communities to remain at the cutting edge, accelerate their growth, or increase their ability to re-organize around new themes or research topics is therefore of special significance. Yet generating a quantitative understanding of the factors that make scientific fields arise and/or become more or less productive is still in its infancy. This is precisely the type of knowledge most needed for promoting and sustaining innovation. Ideally, the efficient and strategic allocation of resources on the part of funding agencies and corporations would be driven primarily by knowledge of this type. Early steps have been taken toward such a quantitative understanding of scientific innovation. Some have focused on characterizing the broad properties of relevant time series, such as numbers of publications and authors in a given field. Others have focused on the structure and evolution of networks of coauthorship and citation. Together these types of studies provide much needed statistical analyses of the structure and evolution of scientific communities. Despite these efforts, however, crucial elements of prediction have remained elusive. Building on many of these earlier insights, we provide

  12. The future of scientific workflows

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

    Deelman, Ewa; Peterka, Tom; Altintas, Ilkay

    Today’s computational, experimental, and observational sciences rely on computations that involve many related tasks. The success of a scientific mission often hinges on the computer automation of these workflows. In April 2015, the US Department of Energy (DOE) invited a diverse group of domain and computer scientists from national laboratories supported by the Office of Science, the National Nuclear Security Administration, from industry, and from academia to review the workflow requirements of DOE’s science and national security missions, to assess the current state of the art in science workflows, to understand the impact of emerging extreme-scale computing systems on thosemore » workflows, and to develop requirements for automated workflow management in future and existing environments. This article is a summary of the opinions of over 50 leading researchers attending this workshop. We highlight use cases, computing systems, workflow needs and conclude by summarizing the remaining challenges this community sees that inhibit large-scale scientific workflows from becoming a mainstream tool for extreme-scale science.« less

  13. Batched matrix computations on hardware accelerators based on GPUs

    DOE PAGES

    Haidar, Azzam; Dong, Tingxing; Luszczek, Piotr; ...

    2015-02-09

    Scientific applications require solvers that work on many small size problems that are independent from each other. At the same time, the high-end hardware evolves rapidly and becomes ever more throughput-oriented and thus there is an increasing need for an effective approach to develop energy-efficient, high-performance codes for these small matrix problems that we call batched factorizations. The many applications that need this functionality could especially benefit from the use of GPUs, which currently are four to five times more energy efficient than multicore CPUs on important scientific workloads. This study, consequently, describes the development of the most common, one-sidedmore » factorizations, Cholesky, LU, and QR, for a set of small dense matrices. The algorithms we present together with their implementations are, by design, inherently parallel. In particular, our approach is based on representing the process as a sequence of batched BLAS routines that are executed entirely on a GPU. Importantly, this is unlike the LAPACK and the hybrid MAGMA factorization algorithms that work under drastically different assumptions of hardware design and efficiency of execution of the various computational kernels involved in the implementation. Thus, our approach is more efficient than what works for a combination of multicore CPUs and GPUs for the problems sizes of interest of the application use cases. The paradigm where upon a single chip (a GPU or a CPU) factorizes a single problem at a time is not at all efficient in our applications’ context. We illustrate all of these claims through a detailed performance analysis. With the help of profiling and tracing tools, we guide our development of batched factorizations to achieve up to two-fold speedup and three-fold better energy efficiency as compared against our highly optimized batched CPU implementations based on MKL library. Finally, the tested system featured two sockets of Intel Sandy Bridge CPUs and we

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  15. News | Computing

    Science.gov Websites

    Support News Publications Computing for Experiments Computing for Neutrino and Muon Physics Computing for Collider Experiments Computing for Astrophysics Research and Development Accelerator Modeling ComPASS - Impact of Detector Simulation on Particle Physics Collider Experiments Daniel Elvira's paper "Impact

  16. GPU Accelerated Prognostics

    NASA Technical Reports Server (NTRS)

    Gorospe, George E., Jr.; Daigle, Matthew J.; Sankararaman, Shankar; Kulkarni, Chetan S.; Ng, Eley

    2017-01-01

    Prognostic methods enable operators and maintainers to predict the future performance for critical systems. However, these methods can be computationally expensive and may need to be performed each time new information about the system becomes available. In light of these computational requirements, we have investigated the application of graphics processing units (GPUs) as a computational platform for real-time prognostics. Recent advances in GPU technology have reduced cost and increased the computational capability of these highly parallel processing units, making them more attractive for the deployment of prognostic software. We present a survey of model-based prognostic algorithms with considerations for leveraging the parallel architecture of the GPU and a case study of GPU-accelerated battery prognostics with computational performance results.

  17. Program Supports Scientific Visualization

    NASA Technical Reports Server (NTRS)

    Keith, Stephan

    1994-01-01

    Primary purpose of General Visualization System (GVS) computer program is to support scientific visualization of data generated by panel-method computer program PMARC_12 (inventory number ARC-13362) on Silicon Graphics Iris workstation. Enables user to view PMARC geometries and wakes as wire frames or as light shaded objects. GVS is written in C language.

  18. Scientific Application Requirements for Leadership Computing at the Exascale

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

    Ahern, Sean; Alam, Sadaf R; Fahey, Mark R

    2007-12-01

    The Department of Energy s Leadership Computing Facility, located at Oak Ridge National Laboratory s National Center for Computational Sciences, recently polled scientific teams that had large allocations at the center in 2007, asking them to identify computational science requirements for future exascale systems (capable of an exaflop, or 1018 floating point operations per second). These requirements are necessarily speculative, since an exascale system will not be realized until the 2015 2020 timeframe, and are expressed where possible relative to a recent petascale requirements analysis of similar science applications [1]. Our initial findings, which beg further data collection, validation, andmore » analysis, did in fact align with many of our expectations and existing petascale requirements, yet they also contained some surprises, complete with new challenges and opportunities. First and foremost, the breadth and depth of science prospects and benefits on an exascale computing system are striking. Without a doubt, they justify a large investment, even with its inherent risks. The possibilities for return on investment (by any measure) are too large to let us ignore this opportunity. The software opportunities and challenges are enormous. In fact, as one notable computational scientist put it, the scale of questions being asked at the exascale is tremendous and the hardware has gotten way ahead of the software. We are in grave danger of failing because of a software crisis unless concerted investments and coordinating activities are undertaken to reduce and close this hardwaresoftware gap over the next decade. Key to success will be a rigorous requirement for natural mapping of algorithms to hardware in a way that complements (rather than competes with) compilers and runtime systems. The level of abstraction must be raised, and more attention must be paid to functionalities and capabilities that incorporate intent into data structures, are aware of memory

  19. Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing

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

    Xu, Zuwei; Zhao, Haibo, E-mail: klinsmannzhb@163.com; Zheng, Chuguang

    2015-01-15

    This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule providesmore » a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance–rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC

  20. Generation of nanosecond neutron pulses in vacuum accelerating tubes

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  1. Neuromorphic Computing for Temporal Scientific Data Classification

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

    Schuman, Catherine D.; Potok, Thomas E.; Young, Steven

    In this work, we apply a spiking neural network model and an associated memristive neuromorphic implementation to an application in classifying temporal scientific data. We demonstrate that the spiking neural network model achieves comparable results to a previously reported convolutional neural network model, with significantly fewer neurons and synapses required.

  2. An Adiabatic Phase-Matching Accelerator

    DOE PAGES

    Lemery, Francois; Floettmann, Klaus; Piot, Philippe; ...

    2018-05-25

    We present a general concept to accelerate non-relativistic charged particles. Our concept employs an adiabatically-tapered dielectric-lined waveguide which supports accelerating phase velocities for synchronous acceleration. We propose an ansatz for the transient field equations, show it satisfies Maxwell's equations under an adiabatic approximation and find excellent agreement with a finite-difference time-domain computer simulation. The fields were implemented into the particle-tracking program {\\sc astra} and we present beam dynamics results for an accelerating field with a 1-mm-wavelength and peak electric field of 100~MV/m. The numerical simulations indicate that amore » $$\\sim 200$$-keV electron beam can be accelerated to an energy of $$\\sim10$$~MeV over $$\\sim 10$$~cm. The novel scheme is also found to form electron beams with parameters of interest to a wide range of applications including, e.g., future advanced accelerators, and ultra-fast electron diffraction.« less

  3. An Adiabatic Phase-Matching Accelerator

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

    Lemery, Francois; Floettmann, Klaus; Piot, Philippe

    2017-12-22

    We present a general concept to accelerate non-relativistic charged particles. Our concept employs an adiabatically-tapered dielectric-lined waveguide which supports accelerating phase velocities for synchronous acceleration. We propose an ansatz for the transient field equations, show it satisfies Maxwell's equations under an adiabatic approximation and find excellent agreement with a finite-difference time-domain computer simulation. The fields were implemented into the particle-tracking program {\\sc astra} and we present beam dynamics results for an accelerating field with a 1-mm-wavelength and peak electric field of 100~MV/m. The numerical simulations indicate that amore » $$\\sim 200$$-keV electron beam can be accelerated to an energy of $$\\sim10$$~MeV over $$\\sim 10$$~cm. The novel scheme is also found to form electron beams with parameters of interest to a wide range of applications including, e.g., future advanced accelerators, and ultra-fast electron diffraction.« less

  4. [Text mining, a method for computer-assisted analysis of scientific texts, demonstrated by an analysis of author networks].

    PubMed

    Hahn, P; Dullweber, F; Unglaub, F; Spies, C K

    2014-06-01

    Searching for relevant publications is becoming more difficult with the increasing number of scientific articles. Text mining as a specific form of computer-based data analysis may be helpful in this context. Highlighting relations between authors and finding relevant publications concerning a specific subject using text analysis programs are illustrated graphically by 2 performed examples. © Georg Thieme Verlag KG Stuttgart · New York.

  5. A toolbox and a record for scientific model development

    NASA Technical Reports Server (NTRS)

    Ellman, Thomas

    1994-01-01

    Scientific computation can benefit from software tools that facilitate construction of computational models, control the application of models, and aid in revising models to handle new situations. Existing environments for scientific programming provide only limited means of handling these tasks. This paper describes a two pronged approach for handling these tasks: (1) designing a 'Model Development Toolbox' that includes a basic set of model constructing operations; and (2) designing a 'Model Development Record' that is automatically generated during model construction. The record is subsequently exploited by tools that control the application of scientific models and revise models to handle new situations. Our two pronged approach is motivated by our belief that the model development toolbox and record should be highly interdependent. In particular, a suitable model development record can be constructed only when models are developed using a well defined set of operations. We expect this research to facilitate rapid development of new scientific computational models, to help ensure appropriate use of such models and to facilitate sharing of such models among working computational scientists. We are testing this approach by extending SIGMA, and existing knowledge-based scientific software design tool.

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

    ERIC Educational Resources Information Center

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

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

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

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

    De Supinski, B.; Caliga, D.

    2017-09-28

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

  8. Multi-Mode Cavity Accelerator Structure

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

    Jiang, Yong; Hirshfield, Jay Leonard

    2016-11-10

    This project aimed to develop a prototype for a novel accelerator structure comprising coupled cavities that are tuned to support modes with harmonically-related eigenfrequencies, with the goal of reaching an acceleration gradient >200 MeV/m and a breakdown rate <10 -7/pulse/meter. Phase I involved computations, design, and preliminary engineering of a prototype multi-harmonic cavity accelerator structure; plus tests of a bimodal cavity. A computational procedure was used to design an optimized profile for a bimodal cavity with high shunt impedance and low surface fields to maximize the reduction in temperature rise ΔT. This cavity supports the TM010 mode and its 2ndmore » harmonic TM011 mode. Its fundamental frequency is at 12 GHz, to benchmark against the empirical criteria proposed within the worldwide High Gradient collaboration for X-band copper structures; namely, a surface electric field E sur max< 260 MV/m and pulsed surface heating ΔT max< 56 °K. With optimized geometry, amplitude and relative phase of the two modes, reductions are found in surface pulsed heating, modified Poynting vector, and total RF power—as compared with operation at the same acceleration gradient using only the fundamental mode.« less

  9. TOPICAL REVIEW: Advances and challenges in computational plasma science

    NASA Astrophysics Data System (ADS)

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

    2005-02-01

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

  10. Klynac: Compact Linear Accelerator with Integrated Power Supply

    NASA Astrophysics Data System (ADS)

    Malyzhenkov, A. V.

    Accelerators and accelerator-based light sources have a wide range of applications in science, engineering technology and medicine. Today the scientific community is working towards improving the quality of the accelerated beam and its parameters, while trying to develop technology for reducing accelerator size. This work describes a design of a compact linear accelerator (linac) prototype: resonant Klynac device, which is a combined linear accelerator and its power supply - klystron. The intended purpose of a Klynac device is to provide a compact and inexpensive alternative to a conventional 1 to 6 MeV accelerator, which typically requires a separate RF source, accelerator itself and all the associated hardware. Because the Klynac is a single structure, it has the potential to be much less sensitive to temperature variations than a system with separate klystron and linac. We start by introducing a simplified theoretical model for a Klynac device. We then demonstrate how a prototype is designed step-by-step using Particle-In-Cell simulation studies for mono-resonant and bi-resonant structures. Finally, we discuss design options from a stability point of view and required input power as well as behavior of competing modes for the actual built device.

  11. The next scientific revolution.

    PubMed

    Hey, Tony

    2010-11-01

    For decades, computer scientists have tried to teach computers to think like human experts. Until recently, most of those efforts have failed to come close to generating the creative insights and solutions that seem to come naturally to the best researchers, doctors, and engineers. But now, Tony Hey, a VP of Microsoft Research, says we're witnessing the dawn of a new generation of powerful computer tools that can "mash up" vast quantities of data from many sources, analyze them, and help produce revolutionary scientific discoveries. Hey and his colleagues call this new method of scientific exploration "machine learning." At Microsoft, a team has already used it to innovate a method of predicting with impressive accuracy whether a patient with congestive heart failure who is released from the hospital will be readmitted within 30 days. It was developed by directing a computer program to pore through hundreds of thousands of data points on 300,000 patients and "learn" the profiles of patients most likely to be rehospitalized. The economic impact of this prediction tool could be huge: If a hospital understands the likelihood that a patient will "bounce back," it can design programs to keep him stable and save thousands of dollars in health care costs. Similar efforts to uncover important correlations that could lead to scientific breakthroughs are under way in oceanography, conservation, and AIDS research. And in business, deep data exploration has the potential to unearth critical insights about customers, supply chains, advertising effectiveness, and more.

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

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

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

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

  13. Accelerated Reader. What Works Clearinghouse Intervention Report

    ERIC Educational Resources Information Center

    What Works Clearinghouse, 2009

    2009-01-01

    "Accelerated Reader" is a computer-based reading management system designed to complement an existing classroom literacy program for grades pre-K-12. It is designed to increase the amount of time students spend reading independently. Students choose reading-level appropriate books or short stories for which Accelerated Reader tests are…

  14. Energy Innovation Hubs: A Home for Scientific Collaboration

    ScienceCinema

    Chu, Steven

    2017-12-11

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

  15. Evolutionary optimization methods for accelerator design

    NASA Astrophysics Data System (ADS)

    Poklonskiy, Alexey A.

    Many problems from the fields of accelerator physics and beam theory can be formulated as optimization problems and, as such, solved using optimization methods. Despite growing efficiency of the optimization methods, the adoption of modern optimization techniques in these fields is rather limited. Evolutionary Algorithms (EAs) form a relatively new and actively developed optimization methods family. They possess many attractive features such as: ease of the implementation, modest requirements on the objective function, a good tolerance to noise, robustness, and the ability to perform a global search efficiently. In this work we study the application of EAs to problems from accelerator physics and beam theory. We review the most commonly used methods of unconstrained optimization and describe the GATool, evolutionary algorithm and the software package, used in this work, in detail. Then we use a set of test problems to assess its performance in terms of computational resources, quality of the obtained result, and the tradeoff between them. We justify the choice of GATool as a heuristic method to generate cutoff values for the COSY-GO rigorous global optimization package for the COSY Infinity scientific computing package. We design the model of their mutual interaction and demonstrate that the quality of the result obtained by GATool increases as the information about the search domain is refined, which supports the usefulness of this model. We Giscuss GATool's performance on the problems suffering from static and dynamic noise and study useful strategies of GATool parameter tuning for these and other difficult problems. We review the challenges of constrained optimization with EAs and methods commonly used to overcome them. We describe REPA, a new constrained optimization method based on repairing, in exquisite detail, including the properties of its two repairing techniques: REFIND and REPROPT. We assess REPROPT's performance on the standard constrained

  16. Software Accelerates Computing Time for Complex Math

    NASA Technical Reports Server (NTRS)

    2014-01-01

    Ames Research Center awarded Newark, Delaware-based EM Photonics Inc. SBIR funding to utilize graphic processing unit (GPU) technology- traditionally used for computer video games-to develop high-computing software called CULA. The software gives users the ability to run complex algorithms on personal computers with greater speed. As a result of the NASA collaboration, the number of employees at the company has increased 10 percent.

  17. The charged particle accelerators subsystems modeling

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

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

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

    2008-05-04

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

  19. Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU.

    PubMed

    Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

    2013-01-01

    This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis.

  20. Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU

    PubMed Central

    Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

    2013-01-01

    This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis. PMID:23840507

  1. Optimizations of Human Restraint Systems for Short-Period Acceleration

    NASA Technical Reports Server (NTRS)

    Payne, P. R.

    1963-01-01

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

  2. An acceleration framework for synthetic aperture radar algorithms

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  3. Development of hardware accelerator for molecular dynamics simulations: a computation board that calculates nonbonded interactions in cooperation with fast multipole method.

    PubMed

    Amisaki, Takashi; Toyoda, Shinjiro; Miyagawa, Hiroh; Kitamura, Kunihiro

    2003-04-15

    Evaluation of long-range Coulombic interactions still represents a bottleneck in the molecular dynamics (MD) simulations of biological macromolecules. Despite the advent of sophisticated fast algorithms, such as the fast multipole method (FMM), accurate simulations still demand a great amount of computation time due to the accuracy/speed trade-off inherently involved in these algorithms. Unless higher order multipole expansions, which are extremely expensive to evaluate, are employed, a large amount of the execution time is still spent in directly calculating particle-particle interactions within the nearby region of each particle. To reduce this execution time for pair interactions, we developed a computation unit (board), called MD-Engine II, that calculates nonbonded pairwise interactions using a specially designed hardware. Four custom arithmetic-processors and a processor for memory manipulation ("particle processor") are mounted on the computation board. The arithmetic processors are responsible for calculation of the pair interactions. The particle processor plays a central role in realizing efficient cooperation with the FMM. The results of a series of 50-ps MD simulations of a protein-water system (50,764 atoms) indicated that a more stringent setting of accuracy in FMM computation, compared with those previously reported, was required for accurate simulations over long time periods. Such a level of accuracy was efficiently achieved using the cooperative calculations of the FMM and MD-Engine II. On an Alpha 21264 PC, the FMM computation at a moderate but tolerable level of accuracy was accelerated by a factor of 16.0 using three boards. At a high level of accuracy, the cooperative calculation achieved a 22.7-fold acceleration over the corresponding conventional FMM calculation. In the cooperative calculations of the FMM and MD-Engine II, it was possible to achieve more accurate computation at a comparable execution time by incorporating larger nearby

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  6. Utilizing GPUs to Accelerate Turbomachinery CFD Codes

    NASA Technical Reports Server (NTRS)

    MacCalla, Weylin; Kulkarni, Sameer

    2016-01-01

    GPU computing has established itself as a way to accelerate parallel codes in the high performance computing world. This work focuses on speeding up APNASA, a legacy CFD code used at NASA Glenn Research Center, while also drawing conclusions about the nature of GPU computing and the requirements to make GPGPU worthwhile on legacy codes. Rewriting and restructuring of the source code was avoided to limit the introduction of new bugs. The code was profiled and investigated for parallelization potential, then OpenACC directives were used to indicate parallel parts of the code. The use of OpenACC directives was not able to reduce the runtime of APNASA on either the NVIDIA Tesla discrete graphics card, or the AMD accelerated processing unit. Additionally, it was found that in order to justify the use of GPGPU, the amount of parallel work being done within a kernel would have to greatly exceed the work being done by any one portion of the APNASA code. It was determined that in order for an application like APNASA to be accelerated on the GPU, it should not be modular in nature, and the parallel portions of the code must contain a large portion of the code's computation time.

  7. Cloud-based opportunities in scientific computing: insights from processing Suomi National Polar-Orbiting Partnership (S-NPP) Direct Broadcast data

    NASA Astrophysics Data System (ADS)

    Evans, J. D.; Hao, W.; Chettri, S.

    2013-12-01

    The cloud is proving to be a uniquely promising platform for scientific computing. Our experience with processing satellite data using Amazon Web Services highlights several opportunities for enhanced performance, flexibility, and cost effectiveness in the cloud relative to traditional computing -- for example: - Direct readout from a polar-orbiting satellite such as the Suomi National Polar-Orbiting Partnership (S-NPP) requires bursts of processing a few times a day, separated by quiet periods when the satellite is out of receiving range. In the cloud, by starting and stopping virtual machines in minutes, we can marshal significant computing resources quickly when needed, but not pay for them when not needed. To take advantage of this capability, we are automating a data-driven approach to the management of cloud computing resources, in which new data availability triggers the creation of new virtual machines (of variable size and processing power) which last only until the processing workflow is complete. - 'Spot instances' are virtual machines that run as long as one's asking price is higher than the provider's variable spot price. Spot instances can greatly reduce the cost of computing -- for software systems that are engineered to withstand unpredictable interruptions in service (as occurs when a spot price exceeds the asking price). We are implementing an approach to workflow management that allows data processing workflows to resume with minimal delays after temporary spot price spikes. This will allow systems to take full advantage of variably-priced 'utility computing.' - Thanks to virtual machine images, we can easily launch multiple, identical machines differentiated only by 'user data' containing individualized instructions (e.g., to fetch particular datasets or to perform certain workflows or algorithms) This is particularly useful when (as is the case with S-NPP data) we need to launch many very similar machines to process an unpredictable number of

  8. Enabling a Scientific Cloud Marketplace: VGL (Invited)

    NASA Astrophysics Data System (ADS)

    Fraser, R.; Woodcock, R.; Wyborn, L. A.; Vote, J.; Rankine, T.; Cox, S. J.

    2013-12-01

    The Virtual Geophysics Laboratory (VGL) provides a flexible, web based environment where researchers can browse data and use a variety of scientific software packaged into tool kits that run in the Cloud. Both data and tool kits are published by multiple researchers and registered with the VGL infrastructure forming a data and application marketplace. The VGL provides the basic work flow of Discovery and Access to the disparate data sources and a Library for tool kits and scripting to drive the scientific codes. Computation is then performed on the Research or Commercial Clouds. Provenance information is collected throughout the work flow and can be published alongside the results allowing for experiment comparison and sharing with other researchers. VGL's "mix and match" approach to data, computational resources and scientific codes, enables a dynamic approach to scientific collaboration. VGL allows scientists to publish their specific contribution, be it data, code, compute or work flow, knowing the VGL framework will provide other components needed for a complete application. Other scientists can choose the pieces that suit them best to assemble an experiment. The coarse grain workflow of the VGL framework combined with the flexibility of the scripting library and computational toolkits allows for significant customisation and sharing amongst the community. The VGL utilises the cloud computational and storage resources from the Australian academic research cloud provided by the NeCTAR initiative and a large variety of data accessible from national and state agencies via the Spatial Information Services Stack (SISS - http://siss.auscope.org). VGL v1.2 screenshot - http://vgl.auscope.org

  9. GPU Accelerated Vector Median Filter

    NASA Technical Reports Server (NTRS)

    Aras, Rifat; Shen, Yuzhong

    2011-01-01

    Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

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

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

    Wu, Jerry; Wu, Kesheng

    2011-04-18

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

  11. Multithreaded transactions in scientific computing. The Growth06_v2 program

    NASA Astrophysics Data System (ADS)

    Daniluk, Andrzej

    2009-07-01

    efficient than the previous ones [3]. Summary of revisions:The design pattern (See Fig. 2 of Ref. [3]) has been modified according to the scheme shown on Fig. 1. A graphical user interface (GUI) for the program has been reconstructed. Fig. 2 presents a hybrid diagram of a GUI that shows how onscreen objects connect to use cases. The program has been compiled with English/USA regional and language options. Note: The figures mentioned above are contained in the program distribution file. Unusual features: The program is distributed in the form of source project GROWTH06_v2.dpr with associated files, and should be compiled using Borland Delphi compilers versions 6 or latter (including Borland Developer Studio 2006 and Code Gear compilers for Delphi). Additional comments: Two figures are included in the program distribution file. These are captioned Static classes model for Transaction design pattern. A model of a window that shows how onscreen objects connect to use cases. Running time: The typical running time is machine and user-parameters dependent. References: [1] A. Daniluk, Comput. Phys. Comm. 170 (2005) 265. [2] W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling, Numerical Recipes in Pascal: The Art of Scientific Computing, first ed., Cambridge University Press, 1989. [3] M. Brzuszek, A. Daniluk, Comput. Phys. Comm. 175 (2006) 678.

  12. Analysis of Movement Acceleration of Down's Syndrome Teenagers Playing Computer Games.

    PubMed

    Carrogi-Vianna, Daniela; Lopes, Paulo Batista; Cymrot, Raquel; Hengles Almeida, Jefferson Jesus; Yazaki, Marcos Lomonaco; Blascovi-Assis, Silvana Maria

    2017-12-01

    This study aimed to evaluate movement acceleration characteristics in adolescents with Down syndrome (DS) and typical development (TD), while playing bowling and golf videogames on the Nintendo ® Wii™. The sample comprised 21 adolescents diagnosed with DS and 33 with TD of both sexes, between 10 and 14 years of age. The arm swing accelerations of the dominant upper limb were collected as measures during the bowling and the golf games. The first valid measurement, verified by the software readings, recorded at the start of each of the games, was used in the analysis. In the bowling game, the groups presented significant statistical differences, with the maximum (M) peaks of acceleration for the Male Control Group (MCG) (M = 70.37) and Female Control Group (FCG) (M = 70.51) when compared with Male Down Syndrome Group (MDSG) (M = 45.33) and Female Down Syndrome Group (FDSG) (M = 37.24). In the golf game the groups also presented significant statistical differences, the only difference being that the maximum peaks of acceleration for both male groups were superior compared with the female groups, MCG (M = 74.80) and FCG (M = 56.80), as well as in MDSG (M = 45.12) and in FDSG (M = 30.52). It was possible to use accelerometry to evaluate the movement acceleration characteristics of teenagers diagnosed with DS during virtual bowling and golf games played on the Nintendo Wii console.

  13. Application of Plasma Waveguides to High Energy Accelerators

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

    Milchberg, Howard M

    2013-03-30

    The eventual success of laser-plasma based acceleration schemes for high-energy particle physics will require the focusing and stable guiding of short intense laser pulses in reproducible plasma channels. For this goal to be realized, many scientific issues need to be addressed. These issues include an understanding of the basic physics of, and an exploration of various schemes for, plasma channel formation. In addition, the coupling of intense laser pulses to these channels and the stable propagation of pulses in the channels require study. Finally, new theoretical and computational tools need to be developed to aid in the design and analysismore » of experiments and future accelerators. Here we propose a 3-year renewal of our combined theoretical and experimental program on the applications of plasma waveguides to high-energy accelerators. During the past grant period we have made a number of significant advances in the science of laser-plasma based acceleration. We pioneered the development of clustered gases as a new highly efficient medium for plasma channel formation. Our contributions here include theoretical and experimental studies of the physics of cluster ionization, heating, explosion, and channel formation. We have demonstrated for the first time the generation of and guiding in a corrugated plasma waveguide. The fine structure demonstrated in these guides is only possible with cluster jet heating by lasers. The corrugated guide is a slow wave structure operable at arbitrarily high laser intensities, allowing direct laser acceleration, a process we have explored in detail with simulations. The development of these guides opens the possibility of direct laser acceleration, a true miniature analogue of the SLAC RF-based accelerator. Our theoretical studies during this period have also contributed to the further development of the simulation codes, Wake and QuickPIC, which can be used for both laser driven and beam driven plasma based acceleration

  14. Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization.

    PubMed

    Huang, Hsuan-Ming; Hsiao, Ing-Tsung

    2016-01-01

    In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate.

  15. Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization

    PubMed Central

    Huang, Hsuan-Ming; Hsiao, Ing-Tsung

    2016-01-01

    In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate. PMID:27073853

  16. The Four Lives of a Nuclear Accelerator

    NASA Astrophysics Data System (ADS)

    Wiescher, Michael

    2017-06-01

    Electrostatic accelerators have emerged as a major tool in research and industry in the second half of the twentieth century. In particular in low energy nuclear physics they have been essential for addressing a number of critical research questions from nuclear structure to nuclear astrophysics. This article describes this development on the example of a single machine which has been used for nearly sixty years at the forefront of scientific research in nuclear physics. The article summarizes the concept of electrostatic accelerators and outlines how this accelerator developed from a bare support function to an independent research tool that has been utilized in different research environments and institutions and now looks forward to a new life as part of the experiment CASPAR at the 4,850" level of the Sanford Underground Research Facility.

  17. Bulk Acceleration of Electrons in Solar Flares?

    NASA Astrophysics Data System (ADS)

    Holman, Gordon D.

    2014-06-01

    In two recent papers it has been argued that RHESSI observations of two coronal “above-the-loop-top” hard X-ray sources, together with EUV observations, show that ALL the electrons in the source volumes must have been accelerated. I will briefly review these papers and show that the interpretation most consistent with the combined flare observations is multi-thermal, with hot, thermal plasma in the “above-the-loop-top” sources and only a fraction, albeit a substantial fraction, of the electrons accelerated. Thus, there is no credible scientific evidence for bulk acceleration of electrons in flares. Differential emission measure (DEM) models deduced from SDO/AIA and RHESSI data, including the inversion of the AIA data to determine DEM, will be discussed as part of this analysis.

  18. Investigations into dual-grating THz-driven accelerators

    NASA Astrophysics Data System (ADS)

    Wei, Y.; Ischebeck, R.; Dehler, M.; Ferrari, E.; Hiller, N.; Jamison, S.; Xia, G.; Hanahoe, K.; Li, Y.; Smith, J. D. A.; Welsch, C. P.

    2018-01-01

    Advanced acceleration technologies are receiving considerable interest in order to miniaturize future particle accelerators. One such technology is the dual-grating dielectric structures, which can support accelerating fields one to two orders of magnitude higher than the metal RF cavities in conventional accelerators. This opens up the possibility of enabling high accelerating gradients of up to several GV/m. This paper investigates numerically a quartz dual-grating structure which is driven by THz pulses to accelerate electrons. Geometry optimizations are carried out to achieve the trade-offs between accelerating gradient and vacuum channel gap. A realistic electron bunch available from the future Compact Linear Accelerator for Research and Applications (CLARA) is loaded into an optimized 100-period dual-grating structure for a detailed wakefield study. A THz pulse is then employed to interact with this CLARA bunch in the optimized structure. The computed beam quality is analyzed in terms of emittance, energy spread and loaded accelerating gradient. The simulations show that an accelerating gradient of 348 ± 12 MV/m with an emittance growth of 3.0% can be obtained.

  19. Acceleration of low order finite element computation with GPUs (Invited)

    NASA Astrophysics Data System (ADS)

    Knepley, M. G.

    2010-12-01

    Considerable effort has been focused on the acceleration using GPUs of high order spectral element methods and discontinuous Galerkin finite element methods. However, these methods are not universally applicable, and much of the existing FEM software base employs low order methods. In this talk, we present a formulation of FEM, using the PETSc framework from ANL, which is amenable to GPU acceleration even at very low order. In addition, using the FEniCS system for FEM, we show that the relevant kernels can be automatically generated and optimized using a symbolic manipulation system.

  20. Using Interactive Computer to Communicate Scientific Information.

    ERIC Educational Resources Information Center

    Selnow, Gary W.

    1988-01-01

    Asks whether the computer is another channel of communication, if its interactive qualities make it an information source, or if it is an undefined hybrid. Concludes that computers are neither the medium nor the source but will in the future provide the possibility of a sophisticated interaction between human intelligence and artificial…

  1. GPU-accelerated adjoint algorithmic differentiation

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  2. GPU-Accelerated Adjoint Algorithmic Differentiation

    PubMed Central

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

    2015-01-01

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

  3. GPU-Accelerated Adjoint Algorithmic Differentiation.

    PubMed

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

    2016-03-01

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

  4. Accelerating Vaccine Formulation Development Using Design of Experiment Stability Studies.

    PubMed

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

    2016-10-01

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

  5. Considerations on the Use of Custom Accelerators for Big Data Analytics

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

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

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

  6. Numerical Nuclear Second Derivatives on a Computing Grid: Enabling and Accelerating Frequency Calculations on Complex Molecular Systems.

    PubMed

    Yang, Tzuhsiung; Berry, John F

    2018-06-04

    The computation of nuclear second derivatives of energy, or the nuclear Hessian, is an essential routine in quantum chemical investigations of ground and transition states, thermodynamic calculations, and molecular vibrations. Analytic nuclear Hessian computations require the resolution of costly coupled-perturbed self-consistent field (CP-SCF) equations, while numerical differentiation of analytic first derivatives has an unfavorable 6 N ( N = number of atoms) prefactor. Herein, we present a new method in which grid computing is used to accelerate and/or enable the evaluation of the nuclear Hessian via numerical differentiation: NUMFREQ@Grid. Nuclear Hessians were successfully evaluated by NUMFREQ@Grid at the DFT level as well as using RIJCOSX-ZORA-MP2 or RIJCOSX-ZORA-B2PLYP for a set of linear polyacenes with systematically increasing size. For the larger members of this group, NUMFREQ@Grid was found to outperform the wall clock time of analytic Hessian evaluation; at the MP2 or B2LYP levels, these Hessians cannot even be evaluated analytically. We also evaluated a 156-atom catalytically relevant open-shell transition metal complex and found that NUMFREQ@Grid is faster (7.7 times shorter wall clock time) and less demanding (4.4 times less memory requirement) than an analytic Hessian. Capitalizing on the capabilities of parallel grid computing, NUMFREQ@Grid can outperform analytic methods in terms of wall time, memory requirements, and treatable system size. The NUMFREQ@Grid method presented herein demonstrates how grid computing can be used to facilitate embarrassingly parallel computational procedures and is a pioneer for future implementations.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  8. Nanoinformatics: developing new computing applications for nanomedicine

    PubMed Central

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

    2012-01-01

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

  9. File-System Workload on a Scientific Multiprocessor

    NASA Technical Reports Server (NTRS)

    Kotz, David; Nieuwejaar, Nils

    1995-01-01

    Many scientific applications have intense computational and I/O requirements. Although multiprocessors have permitted astounding increases in computational performance, the formidable I/O needs of these applications cannot be met by current multiprocessors a their I/O subsystems. To prevent I/O subsystems from forever bottlenecking multiprocessors and limiting the range of feasible applications, new I/O subsystems must be designed. The successful design of computer systems (both hardware and software) depends on a thorough understanding of their intended use. A system designer optimizes the policies and mechanisms for the cases expected to most common in the user's workload. In the case of multiprocessor file systems, however, designers have been forced to build file systems based only on speculation about how they would be used, extrapolating from file-system characterizations of general-purpose workloads on uniprocessor and distributed systems or scientific workloads on vector supercomputers (see sidebar on related work). To help these system designers, in June 1993 we began the Charisma Project, so named because the project sought to characterize 1/0 in scientific multiprocessor applications from a variety of production parallel computing platforms and sites. The Charisma project is unique in recording individual read and write requests-in live, multiprogramming, parallel workloads (rather than from selected or nonparallel applications). In this article, we present the first results from the project: a characterization of the file-system workload an iPSC/860 multiprocessor running production, parallel scientific applications at NASA's Ames Research Center.

  10. Synchronous acceleration with tapered dielectric-lined waveguides

    NASA Astrophysics Data System (ADS)

    Lemery, F.; Floettmann, K.; Piot, P.; Kärtner, F. X.; Aßmann, R.

    2018-05-01

    We present a general concept to accelerate nonrelativistic charged particles. Our concept employs an adiabatically-tapered dielectric-lined waveguide which supports accelerating phase velocities for synchronous acceleration. We propose an ansatz for the transient field equations, show it satisfies Maxwell's equations under an adiabatic approximation and find excellent agreement with a finite-difference time-domain computer simulation. The fields were implemented into the particle-tracking program astra and we present beam dynamics results for an accelerating field with a 1-mm-wavelength and peak electric field of 100 MV /m . Numerical simulations indicate that a ˜200 -keV electron beam can be accelerated to an energy of ˜10 MeV over ˜10 cm with parameters of interest to a wide range of applications including, e.g., future advanced accelerators, and ultra-fast electron diffraction.

  11. Highly parallel computation

    NASA Technical Reports Server (NTRS)

    Denning, Peter J.; Tichy, Walter F.

    1990-01-01

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

  12. New project to support scientific collaboration electronically

    NASA Astrophysics Data System (ADS)

    Clauer, C. R.; Rasmussen, C. E.; Niciejewski, R. J.; Killeen, T. L.; Kelly, J. D.; Zambre, Y.; Rosenberg, T. J.; Stauning, P.; Friis-Christensen, E.; Mende, S. B.; Weymouth, T. E.; Prakash, A.; McDaniel, S. E.; Olson, G. M.; Finholt, T. A.; Atkins, D. E.

    A new multidisciplinary effort is linking research in the upper atmospheric and space, computer, and behavioral sciences to develop a prototype electronic environment for conducting team science worldwide. A real-world electronic collaboration testbed has been established to support scientific work centered around the experimental operations being conducted with instruments from the Sondrestrom Upper Atmospheric Research Facility in Kangerlussuaq, Greenland. Such group computing environments will become an important component of the National Information Infrastructure initiative, which is envisioned as the high-performance communications infrastructure to support national scientific research.

  13. Anderson Acceleration for Fixed-Point Iterations

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

    Walker, Homer F.

    The purpose of this grant was to support research on acceleration methods for fixed-point iterations, with applications to computational frameworks and simulation problems that are of interest to DOE.

  14. Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers.

    PubMed

    Sochat, Vanessa V; Prybol, Cameron J; Kurtzer, Gregory M

    2017-01-01

    Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub's primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers.

  15. Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers

    PubMed Central

    Prybol, Cameron J.; Kurtzer, Gregory M.

    2017-01-01

    Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub’s primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers. PMID:29186161

  16. Strategic Reading, Ontologies, and the Future of Scientific Publishing

    NASA Astrophysics Data System (ADS)

    Renear, Allen H.; Palmer, Carole L.

    2009-08-01

    The revolution in scientific publishing that has been promised since the 1980s is about to take place. Scientists have always read strategically, working with many articles simultaneously to search, filter, scan, link, annotate, and analyze fragments of content. An observed recent increase in strategic reading in the online environment will soon be further intensified by two current trends: (i) the widespread use of digital indexing, retrieval, and navigation resources and (ii) the emergence within many scientific disciplines of interoperable ontologies. Accelerated and enhanced by reading tools that take advantage of ontologies, reading practices will become even more rapid and indirect, transforming the ways in which scientists engage the literature and shaping the evolution of scientific publishing.

  17. An "Elective Replacement" Approach to Providing Extra Help in Math: The Talent Development Middle Schools' Computer- and Team-Assisted Mathematics Acceleration (CATAMA) Program.

    ERIC Educational Resources Information Center

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

    1999-01-01

    Two studies evaluated the Computer- and Team-Assisted Mathematics Acceleration course (CATAMA) in Talent Development Middle Schools. The first study compared growth in math achievement for 96 seventh-graders (48 of whom participated in CATAMA and 48 of whom did not); the second study gathered data from interviews with, and observations of, CATAMA…

  18. Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU

    NASA Astrophysics Data System (ADS)

    Doulgerakis, Matthaios; Eggebrecht, Adam; Wojtkiewicz, Stanislaw; Culver, Joseph; Dehghani, Hamid

    2017-12-01

    Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ˜600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ˜0.25 s/excitation source.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  20. The need for scientific software engineering in the pharmaceutical industry

    NASA Astrophysics Data System (ADS)

    Luty, Brock; Rose, Peter W.

    2017-03-01

    Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

  1. The need for scientific software engineering in the pharmaceutical industry.

    PubMed

    Luty, Brock; Rose, Peter W

    2017-03-01

    Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

  2. Computation of linear acceleration through an internal model in the macaque cerebellum

    PubMed Central

    Laurens, Jean; Meng, Hui; Angelaki, Dora E.

    2013-01-01

    A combination of theory and behavioral findings has supported a role for internal models in the resolution of sensory ambiguities and sensorimotor processing. Although the cerebellum has been proposed as a candidate for implementation of internal models, concrete evidence from neural responses is lacking. Here we exploit un-natural motion stimuli, which induce incorrect self-motion perception and eye movements, to explore the neural correlates of an internal model proposed to compensate for Einstein’s equivalence principle and generate neural estimates of linear acceleration and gravity. We show that caudal cerebellar vermis Purkinje cells and cerebellar nuclei neurons selective for actual linear acceleration also encode erroneous linear acceleration, as expected from the internal model hypothesis, even when no actual linear acceleration occurs. These findings provide strong evidence that the cerebellum might be involved in the implementation of internal models that mimic physical principles to interpret sensory signals, as previously hypothesized by theorists. PMID:24077562

  3. Visual Language for the Expression of Scientific Concepts

    ERIC Educational Resources Information Center

    Zender, Mike; Crutcher, Keith A.

    2007-01-01

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

  4. Ion acceleration in a plasma focus

    NASA Technical Reports Server (NTRS)

    Gary, S. P.

    1974-01-01

    The electric and magnetic fields associated with anomalous diffusion to the axis of a linear plasma discharge are used to compute representative ion trajectories. Substantial axial acceleration of the ions is demonstrated.

  5. Hackathons as a means of accelerating scientific discoveries and knowledge transfer.

    PubMed

    Ghouila, Amel; Siwo, Geoffrey Henry; Entfellner, Jean-Baka Domelevo; Panji, Sumir; Button-Simons, Katrina A; Davis, Sage Zenon; Fadlelmola, Faisal M; Ferdig, Michael T; Mulder, Nicola

    2018-05-01

    Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions. © 2018 Ghouila et al.; Published by Cold Spring Harbor Laboratory Press.

  6. Accelerated Profile HMM Searches

    PubMed Central

    Eddy, Sean R.

    2011-01-01

    Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the “multiple segment Viterbi” (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call “sparse rescaling”. These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches. PMID:22039361

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

    DTIC Science & Technology

    2006-11-01

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

  8. Beam breakup in an advanced linear induction accelerator

    DOE PAGES

    Ekdahl, Carl August; Coleman, Joshua Eugene; McCuistian, Brian Trent

    2016-07-01

    Two linear induction accelerators (LIAs) have been in operation for a number of years at the Los Alamos Dual Axis Radiographic Hydrodynamic Test (DARHT) facility. A new multipulse LIA is being developed. We have computationally investigated the beam breakup (BBU) instability in this advanced LIA. In particular, we have explored the consequences of the choice of beam injector energy and the grouping of LIA cells. We find that within the limited range of options presently under consideration for the LIA architecture, there is little adverse effect on the BBU growth. The computational tool that we used for this investigation wasmore » the beam dynamics code linear accelerator model for DARHT (LAMDA). In conclusion, to confirm that LAMDA was appropriate for this task, we first validated it through comparisons with the experimental BBU data acquired on the DARHT accelerators.« less

  9. Idea Paper: The Lifecycle of Software for Scientific Simulations

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

    Dubey, Anshu; McInnes, Lois C.

    The software lifecycle is a well researched topic that has produced many models to meet the needs of different types of software projects. However, one class of projects, software development for scientific computing, has received relatively little attention from lifecycle researchers. In particular, software for end-to-end computations for obtaining scientific results has received few lifecycle proposals and no formalization of a development model. An examination of development approaches employed by the teams implementing large multicomponent codes reveals a great deal of similarity in their strategies. This idea paper formalizes these related approaches into a lifecycle model for end-to-end scientific applicationmore » software, featuring loose coupling between submodels for development of infrastructure and scientific capability. We also invite input from stakeholders to converge on a model that captures the complexity of this development processes and provides needed lifecycle guidance to the scientific software community.« less

  10. Emphasizing history in communicating scientific debates

    NASA Astrophysics Data System (ADS)

    Sherwood, S. C.

    2010-12-01

    Communication to the public of the reality of anthropogenic climate change has been less successful than many expect. The scientists themselves, the media, special interest groups, or the complexity of modern society are often blamed. However a look at past scientific paradigm shifts, in particular the Copernican revolution and the discovery of relativity, shows close parallels with the modern situation. Common aspects include the gradual formation of a scientific consensus in advance of the public; a politically partisan backlash against the new theory that, paradoxically, occurs after the arrival of conclusive supporting evidence; the prevalence of convincing but invalid pseudo-scientific counterarguments; the general failure of "debates" to increase public acceptance of the scientists' position; and, in the case of the heliocentric solar system, a very long time scale to final public acceptance (> 100 years). Greater emphasis on the lessons from such historical parallels, and on the success so far of consensus predictions of global warming made up to and including the first IPCC report in 1990, might be one useful way of enhancing the public's trust in science and scientists and thereby accelerate acceptance of uncomfortable scientific findings.

  11. Summary Scientific Performance of EUCLID Detector Prototypes

    NASA Technical Reports Server (NTRS)

    Rauscher, Bernard J.

    2011-01-01

    NASA and the European Space Agency (ESA) plan to partner to build the EUCLID mission. EUCLID is a mission concept for studying the Dark Energy that is hypothesized to account for the accelerating cosmic expansion. For the past year, NASA has been building detector prototypes at Teledyne Imaging Sensors. This talk will summarize the measured scientific performance of these detector prototypes for astrophysical and cosmological applications.

  12. Constructing Scientific Applications from Heterogeneous Resources

    NASA Technical Reports Server (NTRS)

    Schichting, Richard D.

    1995-01-01

    A new model for high-performance scientific applications in which such applications are implemented as heterogeneous distributed programs or, equivalently, meta-computations, is investigated. The specific focus of this grant was a collaborative effort with researchers at NASA and the University of Toledo to test and improve Schooner, a software interconnection system, and to explore the benefits of increased user interaction with existing scientific applications.

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

    PubMed

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

    2016-04-01

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

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

    PubMed

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

    2017-11-16

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

  15. Synchronous acceleration with tapered dielectric-lined waveguides

    DOE PAGES

    Lemery, Francois; Floettmann, Klaus; Piot, Philippe; ...

    2018-05-25

    Here, we present a general concept to accelerate non-relativistic charged particles. Our concept employs an adiabatically-tapered dielectric-lined waveguide which supports accelerating phase velocities for synchronous acceleration. We propose an ansatz for the transient field equations, show it satisfies Maxwell's equations under an adiabatic approximation and find excellent agreement with a finite-difference time-domain computer simulation. The fields were implemented into the particle-tracking program {\\sc astra} and we present beam dynamics results for an accelerating field with a 1-mm-wavelength and peak electric field of 100~MV/m. The numerical simulations indicate that amore » $$\\sim 200$$-keV electron beam can be accelerated to an energy of $$\\sim10$$~MeV over $$\\sim 10$$~cm. The novel scheme is also found to form electron beams with parameters of interest to a wide range of applications including, e.g., future advanced accelerators, and ultra-fast electron diffraction.« less

  16. DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

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

    Gerber, Richard; Allcock, William; Beggio, Chris

    2014-10-17

    U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at themore » DOE national laboratories. The report contains findings from that review.« less

  17. Computer applications in scientific balloon quality control

    NASA Astrophysics Data System (ADS)

    Seely, Loren G.; Smith, Michael S.

    Seal defects and seal tensile strength are primary determinants of product quality in scientific balloon manufacturing; they therefore require a unit of quality measure. The availability of inexpensive and powerful data-processing tools can serve as the basis of a quality-trends-discerning analysis of products. The results of one such analysis are presently given in graphic form for use on the production floor. Software descriptions and their sample outputs are presented, together with a summary of overall and long-term effects of these methods on product quality.

  18. Basic mathematical function libraries for scientific computation

    NASA Technical Reports Server (NTRS)

    Galant, David C.

    1989-01-01

    Ada packages implementing selected mathematical functions for the support of scientific and engineering applications were written. The packages provide the Ada programmer with the mathematical function support found in the languages Pascal and FORTRAN as well as an extended precision arithmetic and a complete complex arithmetic. The algorithms used are fully described and analyzed. Implementation assumes that the Ada type FLOAT objects fully conform to the IEEE 754-1985 standard for single binary floating-point arithmetic, and that INTEGER objects are 32-bit entities. Codes for the Ada packages are included as appendixes.

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

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

    Loew, Gregory

    2008-12-16

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

  20. Research | Computational Science | NREL

    Science.gov Websites

    Research Research NREL's computational science experts use advanced high-performance computing (HPC technologies, thereby accelerating the transformation of our nation's energy system. Enabling High-Impact Research NREL's computational science capabilities enable high-impact research. Some recent examples

  1. The scaling issue: scientific opportunities

    NASA Astrophysics Data System (ADS)

    Orbach, Raymond L.

    2009-07-01

    A brief history of the Leadership Computing Facility (LCF) initiative is presented, along with the importance of SciDAC to the initiative. The initiative led to the initiation of the Innovative and Novel Computational Impact on Theory and Experiment program (INCITE), open to all researchers in the US and abroad, and based solely on scientific merit through peer review, awarding sizeable allocations (typically millions of processor-hours per project). The development of the nation's LCFs has enabled available INCITE processor-hours to double roughly every eight months since its inception in 2004. The 'top ten' LCF accomplishments in 2009 illustrate the breadth of the scientific program, while the 75 million processor hours allocated to American business since 2006 highlight INCITE contributions to US competitiveness. The extrapolation of INCITE processor hours into the future brings new possibilities for many 'classic' scaling problems. Complex systems and atomic displacements to cracks are but two examples. However, even with increasing computational speeds, the development of theory, numerical representations, algorithms, and efficient implementation are required for substantial success, exhibiting the crucial role that SciDAC will play.

  2. 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

  3. Analysis of Scientific Attitude, Computer Anxiety, Educational Internet Use, Problematic Internet Use, and Academic Achievement of Middle School Students According to Demographic Variables

    ERIC Educational Resources Information Center

    Bekmezci, Mehmet; Celik, Ismail; Sahin, Ismail; Kiray, Ahmet; Akturk, Ahmet Oguz

    2015-01-01

    In this research, students' scientific attitude, computer anxiety, educational use of the Internet, academic achievement, and problematic use of the Internet are analyzed based on different variables (gender, parents' educational level and daily access to the Internet). The research group involves 361 students from two middle schools which are…

  4. Scientific Library Offers New Training Options | Poster

    Cancer.gov

    The Scientific Library is expanding its current training opportunities by offering webinars, allowing employees to take advantage of trainings from the comfort of their own offices. Due to the nature of their work, some employees find it inconvenient to attend in-person training classes; others simply prefer to use their own computers. The Scientific Library has been

  5. 77 FR 12823 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-02

    ... Exascale ARRA projects--Magellan final report, Advanced Networking update Status from Computer Science COV Early Career technical talks Summary of Applied Math and Computer Science Workshops ASCR's new SBIR..., Office of Science. ACTION: Notice of Open Meeting. SUMMARY: This notice announces a meeting of the...

  6. Educating and Training Accelerator Scientists and Technologists for Tomorrow

    NASA Astrophysics Data System (ADS)

    Barletta, William; Chattopadhyay, Swapan; Seryi, Andrei

    2012-01-01

    Accelerator science and technology is inherently an integrative discipline that combines aspects of physics, computational science, electrical and mechanical engineering. As few universities offer full academic programs, the education of accelerator physicists and engineers for the future has primarily relied on a combination of on-the-job training supplemented with intensive courses at regional accelerator schools. This article describes the approaches being used to satisfy the educational curiosity of a growing number of interested physicists and engineers.

  7. Educating and Training Accelerator Scientists and Technologists for Tomorrow

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

    Barletta, William A.; Chattopadhyay, Swapan; Seryi, Andrei

    2012-07-01

    Accelerator science and technology is inherently an integrative discipline that combines aspects of physics, computational science, electrical and mechanical engineering. As few universities offer full academic programs, the education of accelerator physicists and engineers for the future has primarily relied on a combination of on-the-job training supplemented with intense courses at regional accelerator schools. This paper describes the approaches being used to satisfy the educational interests of a growing number of interested physicists and engineers.

  8. 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.

  9. Towards Robot Scientists for autonomous scientific discovery

    PubMed Central

    2010-01-01

    We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist. PMID:20119518

  10. Towards Robot Scientists for autonomous scientific discovery.

    PubMed

    Sparkes, Andrew; Aubrey, Wayne; Byrne, Emma; Clare, Amanda; Khan, Muhammed N; Liakata, Maria; Markham, Magdalena; Rowland, Jem; Soldatova, Larisa N; Whelan, Kenneth E; Young, Michael; King, Ross D

    2010-01-04

    We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist.

  11. Evolution of the Virtualized HPC Infrastructure of Novosibirsk Scientific Center

    NASA Astrophysics Data System (ADS)

    Adakin, A.; Anisenkov, A.; Belov, S.; Chubarov, D.; Kalyuzhny, V.; Kaplin, V.; Korol, A.; Kuchin, N.; Lomakin, S.; Nikultsev, V.; Skovpen, K.; Sukharev, A.; Zaytsev, A.

    2012-12-01

    Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies, and Institute of Computational Mathematics and Mathematical Geophysics (ICM&MG). Since each institute has specific requirements on the architecture of computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for a particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM&MG), and a Grid Computing Facility of BINP. A dedicated optical network with the initial bandwidth of 10 Gb/s connecting these three facilities was built in order to make it possible to share the computing resources among the research communities, thus increasing the efficiency of operating the existing computing facilities and offering a common platform for building the computing infrastructure for future scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technology based on XEN and KVM platforms. This contribution gives a thorough review of the present status and future development prospects for the NSC virtualized computing infrastructure and the experience gained while using it for running production data analysis jobs related to HEP experiments being carried out at BINP, especially the KEDR detector experiment at the VEPP-4M electron-positron collider.

  12. Laser-driven ion acceleration: methods, challenges and prospects

    NASA Astrophysics Data System (ADS)

    Badziak, J.

    2018-01-01

    The recent development of laser technology has resulted in the construction of short-pulse lasers capable of generating fs light pulses with PW powers and intensities exceeding 1021 W/cm2, and has laid the basis for the multi-PW lasers, just being built in Europe, that will produce fs pulses of ultra-relativistic intensities ~ 1023 - 1024 W/cm2. The interaction of such an intense laser pulse with a dense target can result in the generation of collimated beams of ions of multi-MeV to GeV energies of sub-ps time durations and of extremely high beam intensities and ion fluencies, barely attainable with conventional RF-driven accelerators. Ion beams with such unique features have the potential for application in various fields of scientific research as well as in medical and technological developments. This paper provides a brief review of state-of-the art in laser-driven ion acceleration, with a focus on basic ion acceleration mechanisms and the production of ultra-intense ion beams. The challenges facing laser-driven ion acceleration studies, in particular those connected with potential applications of laser-accelerated ion beams, are also discussed.

  13. Real-time orthorectification by FPGA-based hardware acceleration

    NASA Astrophysics Data System (ADS)

    Kuo, David; Gordon, Don

    2010-10-01

    Orthorectification that corrects the perspective distortion of remote sensing imagery, providing accurate geolocation and ease of correlation to other images is a valuable first-step in image processing for information extraction. However, the large amount of metadata and the floating-point matrix transformations required to operate on each pixel make this a computation and I/O (Input/Output) intensive process. As result much imagery is either left unprocessed or loses timesensitive value in the long processing cycle. However, the computation on each pixel can be reduced substantially by using computational results of the neighboring pixels and accelerated by special pipelined hardware architecture in one to two orders of magnitude. A specialized coprocessor that is implemented inside an FPGA (Field Programmable Gate Array) chip and surrounded by vendorsupported hardware IP (Intellectual Property) shares the computation workload with CPU through PCI-Express interface. The ultimate speed of one pixel per clock (125 MHz) is achieved by the pipelined systolic array architecture. The optimal partition between software and hardware, the timing profile among image I/O and computation, and the highly automated GUI (Graphical User Interface) that fully exploits this speed increase to maximize overall image production throughput will also be discussed. The software that runs on a workstation with the acceleration hardware orthorectifies 16 Megapixels per second, which is 16 times faster than without the hardware. It turns the production time from months to days. A real-life successful story of an imaging satellite company that adopted such workstations for their orthorectified imagery production will be presented. The potential candidacy of the image processing computation that can be accelerated more efficiently by the same approach will also be analyzed.

  14. Virtual Environments in Scientific Visualization

    NASA Technical Reports Server (NTRS)

    Bryson, Steve; Lisinski, T. A. (Technical Monitor)

    1994-01-01

    Virtual environment technology is a new way of approaching the interface between computers and humans. Emphasizing display and user control that conforms to the user's natural ways of perceiving and thinking about space, virtual environment technologies enhance the ability to perceive and interact with computer generated graphic information. This enhancement potentially has a major effect on the field of scientific visualization. Current examples of this technology include the Virtual Windtunnel being developed at NASA Ames Research Center. Other major institutions such as the National Center for Supercomputing Applications and SRI International are also exploring this technology. This talk will be describe several implementations of virtual environments for use in scientific visualization. Examples include the visualization of unsteady fluid flows (the virtual windtunnel), the visualization of geodesics in curved spacetime, surface manipulation, and examples developed at various laboratories.

  15. Exploring prospective secondary science teachers' understandings of scientific inquiry and Mendelian genetics concepts using computer simulation

    NASA Astrophysics Data System (ADS)

    Cakir, Mustafa

    The primary objective of this case study was to examine prospective secondary science teachers' developing understanding of scientific inquiry and Mendelian genetics. A computer simulation of basic Mendelian inheritance processes (Catlab) was used in combination with small-group discussions and other instructional scaffolds to enhance prospective science teachers' understandings. The theoretical background for this research is derived from a social constructivist perspective. Structuring scientific inquiry as investigation to develop explanations presents meaningful context for the enhancement of inquiry abilities and understanding of the science content. The context of the study was a teaching and learning course focused on inquiry and technology. Twelve prospective science teachers participated in this study. Multiple data sources included pre- and post-module questionnaires of participants' view of scientific inquiry, pre-posttests of understandings of Mendelian concepts, inquiry project reports, class presentations, process videotapes of participants interacting with the simulation, and semi-structured interviews. Seven selected prospective science teachers participated in in-depth interviews. Findings suggest that while studying important concepts in science, carefully designed inquiry experiences can help prospective science teachers to develop an understanding about the types of questions scientists in that field ask, the methodological and epistemological issues that constrain their pursuit of answers to those questions, and the ways in which they construct and share their explanations. Key findings included prospective teachers' initial limited abilities to create evidence-based arguments, their hesitancy to include inquiry in their future teaching, and the impact of collaboration on thinking. Prior to this experience the prospective teachers held uninformed views of scientific inquiry. After the module, participants demonstrated extended expertise in

  16. Chaotic dynamics in accelerator physics

    NASA Astrophysics Data System (ADS)

    Cary, J. R.

    1992-11-01

    Substantial progress was made in several areas of accelerator dynamics. We have completed a design of an FEL wiggler with adiabatic trapping and detrapping sections to develop an understanding of longitudinal adiabatic dynamics and to create efficiency enhancements for recirculating free-electron lasers. We developed a computer code for analyzing the critical KAM tori that binds the dynamic aperture in circular machines. Studies of modes that arise due to the interaction of coating beams with a narrow-spectrum impedance have begun. During this research educational and research ties with the accelerator community at large have been strengthened.

  17. Organization of the 17th Advanced Accelerator Concepts (AAC16) Workshop by the IEEE. Final Scientific/Technical Report On AWARD NO. DE-SC0015635

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

    Sutter, David F.

    The 2016 Workshop on Advanced Accelerator Concepts (AAC) was held at the Gaylord Hotel and Conference Center, National Harbor, Maryland, from July 31 through August 5, 2016. This workshop was the seventeenth in a biennial series that began at Los Alamos National Laboratory in 1982 with a workshop on laser acceleration of particles (see AIP Conf. Proc. 91). AAC16 was organized under the sponsorship of the IEEE Council on Superconductivity with financial support from the U. S. Department of Energy Office of High Energy Physics and the National Science Foundation. The scope of the AAC Workshop has grown since 1982more » to encompass a broad range of topics related to advancing accelerator science and technology beyond its current scientific and technical limits and is now an internationally acknowledged forum for interdisciplinary discussions on advanced accelerator and beam physics/technology concepts covering the widest possible range of applications. The Workshop continued the trend of growing worldwide participation, attracting world wide participation. The Workshop had a total of 256 attendees comprising (including the U.S.) representatives from 11 countries representing 65 different institutions. Each day’s schedule began with plenary sessions covering broad, cross disciplinary interests or general tutorial topics as selected by the Program Committee, followed by a break out into more narrowly focused working groups. The Workshop was organized into eight Working Groups each with a published statement of topical focus, scope of discussion and goals. A summary of the Working Group activities and conclusions is included in the American Institute of Physics’ (AIP) Conference Proceedings now available as an on line open source document. It has been a long tradition of the AAC workshops to encourage strong student participation. This is accomplished in part by subsidizing student attendance, done for this work shop by using funds from the DOE and National

  18. Scientific guidelines for preservation of samples collected from Mars

    NASA Technical Reports Server (NTRS)

    Gooding, James L. (Editor)

    1990-01-01

    The maximum scientific value of Martian geologic and atmospheric samples is retained when the samples are preserved in the conditions that applied prior to their collection. Any sample degradation equates to loss of information. Based on detailed review of pertinent scientific literature, and advice from experts in planetary sample analysis, number values are recommended for key parameters in the environmental control of collected samples with respect to material contamination, temperature, head-space gas pressure, ionizing radiation, magnetic fields, and acceleration/shock. Parametric values recommended for the most sensitive geologic samples should also be adequate to preserve any biogenic compounds or exobiological relics.

  19. Ice-sheet modelling accelerated by graphics cards

    NASA Astrophysics Data System (ADS)

    Brædstrup, Christian Fredborg; Damsgaard, Anders; Egholm, David Lundbek

    2014-11-01

    Studies of glaciers and ice sheets have increased the demand for high performance numerical ice flow models over the past decades. When exploring the highly non-linear dynamics of fast flowing glaciers and ice streams, or when coupling multiple flow processes for ice, water, and sediment, researchers are often forced to use super-computing clusters. As an alternative to conventional high-performance computing hardware, the Graphical Processing Unit (GPU) is capable of massively parallel computing while retaining a compact design and low cost. In this study, we present a strategy for accelerating a higher-order ice flow model using a GPU. By applying the newest GPU hardware, we achieve up to 180× speedup compared to a similar but serial CPU implementation. Our results suggest that GPU acceleration is a competitive option for ice-flow modelling when compared to CPU-optimised algorithms parallelised by the OpenMP or Message Passing Interface (MPI) protocols.

  20. Deep learning for computational chemistry

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

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

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

  1. Computer Diagnostics.

    ERIC Educational Resources Information Center

    Tondow, Murray

    The report deals with the influence of computer technology on education, particularly guidance. The need for computers is a result of increasing complexity which is defined as: (1) an exponential increase of information; (2) an exponential increase in dissemination capabilities; and (3) an accelerating curve of change. Listed are five functions of…

  2. CAD/CAM and scientific data management at Dassault

    NASA Technical Reports Server (NTRS)

    Bohn, P.

    1984-01-01

    The history of CAD/CAM and scientific data management at Dassault are presented. Emphasis is put on the targets of the now commercially available software CATIA. The links with scientific computations such as aerodynamics and structural analysis are presented. Comments are made on the principles followed within the company. The consequences of the approximative nature of scientific data are examined. Consequence of the new history function is mainly its protection against copy or alteration. Future plans at Dassault for scientific data appear to be in opposite directions compared to some general tendencies.

  3. A toolbox and record for scientific models

    NASA Technical Reports Server (NTRS)

    Ellman, Thomas

    1994-01-01

    Computational science presents a host of challenges for the field of knowledge-based software design. Scientific computation models are difficult to construct. Models constructed by one scientist are easily misapplied by other scientists to problems for which they are not well-suited. Finally, models constructed by one scientist are difficult for others to modify or extend to handle new types of problems. Construction of scientific models actually involves much more than the mechanics of building a single computational model. In the course of developing a model, a scientist will often test a candidate model against experimental data or against a priori expectations. Test results often lead to revisions of the model and a consequent need for additional testing. During a single model development session, a scientist typically examines a whole series of alternative models, each using different simplifying assumptions or modeling techniques. A useful scientific software design tool must support these aspects of the model development process as well. In particular, it should propose and carry out tests of candidate models. It should analyze test results and identify models and parts of models that must be changed. It should determine what types of changes can potentially cure a given negative test result. It should organize candidate models, test data, and test results into a coherent record of the development process. Finally, it should exploit the development record for two purposes: (1) automatically determining the applicability of a scientific model to a given problem; (2) supporting revision of a scientific model to handle a new type of problem. Existing knowledge-based software design tools must be extended in order to provide these facilities.

  4. Teaching Electromagnetism to High-School Students Using Particle Accelerators

    ERIC Educational Resources Information Center

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

    2006-01-01

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

  5. Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU.

    PubMed

    Doulgerakis, Matthaios; Eggebrecht, Adam; Wojtkiewicz, Stanislaw; Culver, Joseph; Dehghani, Hamid

    2017-12-01

    Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25  s/excitation source. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

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

    ScienceCinema

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

    2018-05-07

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

  7. GPU-Accelerated Voxelwise Hepatic Perfusion Quantification

    PubMed Central

    Wang, H; Cao, Y

    2012-01-01

    Voxelwise quantification of hepatic perfusion parameters from dynamic contrast enhanced (DCE) imaging greatly contributes to assessment of liver function in response to radiation therapy. However, the efficiency of the estimation of hepatic perfusion parameters voxel-by-voxel in the whole liver using a dual-input single-compartment model requires substantial improvement for routine clinical applications. In this paper, we utilize the parallel computation power of a graphics processing unit (GPU) to accelerate the computation, while maintaining the same accuracy as the conventional method. Using CUDA-GPU, the hepatic perfusion computations over multiple voxels are run across the GPU blocks concurrently but independently. At each voxel, non-linear least squares fitting the time series of the liver DCE data to the compartmental model is distributed to multiple threads in a block, and the computations of different time points are performed simultaneously and synchronically. An efficient fast Fourier transform in a block is also developed for the convolution computation in the model. The GPU computations of the voxel-by-voxel hepatic perfusion images are compared with ones by the CPU using the simulated DCE data and the experimental DCE MR images from patients. The computation speed is improved by 30 times using a NVIDIA Tesla C2050 GPU compared to a 2.67 GHz Intel Xeon CPU processor. To obtain liver perfusion maps with 626400 voxels in a patient’s liver, it takes 0.9 min with the GPU-accelerated voxelwise computation, compared to 110 min with the CPU, while both methods result in perfusion parameters differences less than 10−6. The method will be useful for generating liver perfusion images in clinical settings. PMID:22892645

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  9. Artificial intelligence support for scientific model-building

    NASA Technical Reports Server (NTRS)

    Keller, Richard M.

    1992-01-01

    Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

  10. An Imagination Effect in Learning from Scientific Text

    ERIC Educational Resources Information Center

    Leopold, Claudia; Mayer, Richard E.

    2015-01-01

    Asking students to imagine the spatial arrangement of the elements in a scientific text constitutes a learning strategy intended to foster deep processing of the instructional material. Two experiments investigated the effects of mental imagery prompts on learning from scientific text. Students read a computer-based text on the human respiratory…

  11. A link between occupant and vehicle accelerations during common driving tasks.

    PubMed

    Mathias, Anne C; Shibata, Peggy A; Sprague, James K

    2014-01-01

    When evaluating occupant motions during driving tasks, it is desirable to have a well-established correlation between vehicle and occupant accelerations. Therefore, this study demonstrated a methodology to quantify accelerations experienced by the driver of a passenger vehicle and compare them to associated vehicle motions. Acceleration levels were measured at the seat and the driver’s head, cervical spine, and lumbar spine during six non-collision driving tasks. Tasks included mounting a 127 mm (5 in) -high curb, crossing railroad tracks, driving on a rough road, braking heavily from 13.4 m/s (30 mph), having a 89 mm (3.5 in)-diameter roller sequentially pass under two tires, and dropping one tire from a 171-mm (6.75 in) height. The driver experienced peak resultant accelerations of similar magnitudes across all trials. Peak body accelerations were less than 1.2 g, including 0.82 g lumbar acceleration during heavy braking and 0.88 g head acceleration during the curb mount. These preliminary measurements are comparable to or lower than accelerations experienced during non-driving activities such as sitting quickly. This study contributes to the scientific understanding of accelerations experienced by vehicle occupants and demonstrates the potential to relate vehicle and occupant accelerations during common driving activities that do not involve collisions.

  12. plasmaFoam: An OpenFOAM framework for computational plasma physics and chemistry

    NASA Astrophysics Data System (ADS)

    Venkattraman, Ayyaswamy; Verma, Abhishek Kumar

    2016-09-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  14. Environmentalists and the Computer.

    ERIC Educational Resources Information Center

    Baron, Robert C.

    1982-01-01

    Review characteristics, applications, and limitations of computers, including word processing, data/record keeping, scientific and industrial, and educational applications. Discusses misuse of computers and role of computers in environmental management. (JN)

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

    ERIC Educational Resources Information Center

    Chauncey, Depew M.

    1988-01-01

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

  16. GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  17. 77 FR 11139 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-24

    ...: Center for Scientific Review Special Emphasis Panel; ``Genetics and Epigenetics of Disease.'' Date: March... Scientific Review Special Emphasis Panel; Small Business: Cell, Computational, and Molecular Biology. Date...

  18. Harnessing the crowd to accelerate molecular medicine research.

    PubMed

    Smith, Robert J; Merchant, Raina M

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Eisenbach, Markus

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

  20. [Earth Science Technology Office's Computational Technologies Project

    NASA Technical Reports Server (NTRS)

    Fischer, James (Technical Monitor); Merkey, Phillip

    2005-01-01

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

  1. NOTE: Acceleration of Monte Carlo-based scatter compensation for cardiac SPECT

    NASA Astrophysics Data System (ADS)

    Sohlberg, A.; Watabe, H.; Iida, H.

    2008-07-01

    Single proton emission computed tomography (SPECT) images are degraded by photon scatter making scatter compensation essential for accurate reconstruction. Reconstruction-based scatter compensation with Monte Carlo (MC) modelling of scatter shows promise for accurate scatter correction, but it is normally hampered by long computation times. The aim of this work was to accelerate the MC-based scatter compensation using coarse grid and intermittent scatter modelling. The acceleration methods were compared to un-accelerated implementation using MC-simulated projection data of the mathematical cardiac torso (MCAT) phantom modelling 99mTc uptake and clinical myocardial perfusion studies. The results showed that when combined the acceleration methods reduced the reconstruction time for 10 ordered subset expectation maximization (OS-EM) iterations from 56 to 11 min without a significant reduction in image quality indicating that the coarse grid and intermittent scatter modelling are suitable for MC-based scatter compensation in cardiac SPECT.

  2. galario: Gpu Accelerated Library for Analyzing Radio Interferometer Observations

    NASA Astrophysics Data System (ADS)

    Tazzari, Marco; Beaujean, Frederik; Testi, Leonardo

    2017-10-01

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

  3. Applications of artificial intelligence to scientific research

    NASA Technical Reports Server (NTRS)

    Prince, Mary Ellen

    1986-01-01

    Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

  4. 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.

  5. Implementation of a Curriculum-Integrated Computer Game for Introducing Scientific Argumentation

    NASA Astrophysics Data System (ADS)

    Wallon, Robert C.; Jasti, Chandana; Lauren, Hillary Z. G.; Hug, Barbara

    2017-11-01

    Argumentation has been emphasized in recent US science education reform efforts (NGSS Lead States 2013; NRC 2012), and while existing studies have investigated approaches to introducing and supporting argumentation (e.g., McNeill and Krajcik in Journal of Research in Science Teaching, 45(1), 53-78, 2008; Kang et al. in Science Education, 98(4), 674-704, 2014), few studies have investigated how game-based approaches may be used to introduce argumentation to students. In this paper, we report findings from a design-based study of a teacher's use of a computer game intended to introduce the claim, evidence, reasoning (CER) framework (McNeill and Krajcik 2012) for scientific argumentation. We studied the implementation of the game over two iterations of development in a high school biology teacher's classes. The results of this study include aspects of enactment of the activities and student argument scores. We found the teacher used the game in aspects of explicit instruction of argumentation during both iterations, although the ways in which the game was used differed. Also, students' scores in the second iteration were significantly higher than the first iteration. These findings support the notion that students can learn argumentation through a game, especially when used in conjunction with explicit instruction and support in student materials. These findings also highlight the importance of analyzing classroom implementation in studies of game-based learning.

  6. EDITORIAL: Laser and Plasma Accelerators Workshop, Kardamyli, Greece, 2009 Laser and Plasma Accelerators Workshop, Kardamyli, Greece, 2009

    NASA Astrophysics Data System (ADS)

    Bingham, Bob; Muggli, Patric

    2011-01-01

    The Laser and Plasma Accelerators Workshop 2009 was part of a very successful series of international workshops which were conceived at the 1985 Laser Acceleration of Particles Workshop in Malibu, California. Since its inception, the workshop has been held in Asia and in Europe (Kardamyli, Kyoto, Presqu'ile de Giens, Portovenere, Taipei and the Azores). The purpose of the workshops is to bring together the most recent results in laser wakefield acceleration, plasma wakefield acceleration, laser-driven ion acceleration, and radiation generation produced by plasma-based accelerator beams. The 2009 workshop was held on 22-26 June in Kardamyli, Greece, and brought together over 80 participants. (http://cfp.ist.utl.pt/lpaw09/). The workshop involved five main themes: • Laser plasma electron acceleration (experiment/theory/simulation) • Computational methods • Plasma wakefield acceleration (experiment/theory/simulation) • Laser-driven ion acceleration • Radiation generation and application. All of these themes are covered in this special issue of Plasma Physics and Controlled Fusion. The topic and application of plasma accelerators is one of the success stories in plasma physics, with laser wakefield acceleration of mono-energetic electrons to GeV energies, of ions to hundreds of MeV, and electron-beam-driven wakefield acceleration to 85 GeV. The accelerating electric field in the wake is of the order 1 GeV cm-1, or an accelerating gradient 1000 times greater than in conventional accelerators, possibly leading to an accelerator 1000 times smaller (and much more affordable) for the same energy. At the same time, the electron beams generated by laser wakefield accelerators have very good emittance with a correspondingly good energy spread of about a few percent. They also have the unique feature in being ultra-short in the femtosecond scale. This makes them attractive for a variety of applications, ranging from material science to ultra-fast time

  7. Computational Science in Armenia (Invited Talk)

    NASA Astrophysics Data System (ADS)

    Marandjian, H.; Shoukourian, Yu.

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

  8. Measuring scientific reasoning through behavioral analysis in a computer-based problem solving exercise

    NASA Astrophysics Data System (ADS)

    Mead, C.; Horodyskyj, L.; Buxner, S.; Semken, S. C.; Anbar, A. D.

    2016-12-01

    Developing scientific reasoning skills is a common learning objective for general-education science courses. However, effective assessments for such skills typically involve open-ended questions or tasks, which must be hand-scored and may not be usable online. Using computer-based learning environments, reasoning can be assessed automatically by analyzing student actions within the learning environment. We describe such an assessment under development and present pilot results. In our content-neutral instrument, students solve a problem by collecting and interpreting data in a logical, systematic manner. We then infer reasoning skill automatically based on student actions. Specifically, students investigate why Earth has seasons, a scientifically simple but commonly misunderstood topic. Students are given three possible explanations and asked to select a set of locations on a world map from which to collect temperature data. They then explain how the data support or refute each explanation. The best approaches will use locations in both the Northern and Southern hemispheres to argue that the contrasting seasonality of the hemispheres supports only the correct explanation. We administered a pilot version to students at the beginning of an online, introductory science course (n = 223) as an optional extra credit exercise. We were able to categorize students' data collection decisions as more and less logically sound. Students who choose the most logical measurement locations earned higher course grades, but not significantly higher. This result is encouraging, but not definitive. In the future, we will clarify our results in two ways. First, we plan to incorporate more open-ended interactions into the assessment to improve the resolving power of this tool. Second, to avoid relying on course grades, we will independently measure reasoning skill with one of the existing hand-scored assessments (e.g., Critical Thinking Assessment Test) to cross-validate our new

  9. Acceleration of discrete stochastic biochemical simulation using GPGPU.

    PubMed

    Sumiyoshi, Kei; Hirata, Kazuki; Hiroi, Noriko; Funahashi, Akira

    2015-01-01

    For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130.

  10. Acceleration of discrete stochastic biochemical simulation using GPGPU

    PubMed Central

    Sumiyoshi, Kei; Hirata, Kazuki; Hiroi, Noriko; Funahashi, Akira

    2015-01-01

    For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130. PMID:25762936

  11. Brookhaven National Laboratory's Accelerator Test Facility: research highlights and plans

    NASA Astrophysics Data System (ADS)

    Pogorelsky, I. V.; Ben-Zvi, I.

    2014-08-01

    The Accelerator Test Facility (ATF) at Brookhaven National Laboratory has served as a user facility for accelerator science for over a quarter of a century. In fulfilling this mission, the ATF offers the unique combination of a high-brightness 80 MeV electron beam that is synchronized to a 1 TW picosecond CO2 laser. We unveil herein our plan to considerably expand the ATF's floor space with an upgrade of the electron beam's energy to 300 MeV and the CO2 laser's peak power to 100 TW. This upgrade will propel the ATF even further to the forefront of research on advanced accelerators and radiation sources, supporting the most innovative ideas in this field. We discuss emerging opportunities for scientific breakthroughs, including the following: plasma wakefield acceleration studies in research directions already active at the ATF; laser wakefield acceleration (LWFA), where the longer laser wavelengths are expected to engender a proportional increase in the beam's charge while our linac will assure, for the first time, the opportunity to undertake detailed studies of seeding and staging of the LWFA; proton acceleration to the 100-200 MeV level, which is essential for medical applications; and others.

  12. Atwood's Machine: Experiments in an Accelerating Frame.

    ERIC Educational Resources Information Center

    Chee, Chia Teck; Hong, Chia Yee

    1999-01-01

    Experiments in an accelerating frame are hard to perform. Illustrates how simple computer software allows sufficiently rapid and accurate measurements to be made on an arrangement of weights and pulleys known as Atwood's machine. (Author/CCM)

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

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

    Negele, John W.

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

  14. 160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA)

    PubMed Central

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

    2007-01-01

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

  15. 160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA).

    PubMed

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

    2007-06-07

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

  16. Deep learning for computational chemistry.

    PubMed

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

    2017-06-15

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

  17. XML Based Scientific Data Management Facility

    NASA Technical Reports Server (NTRS)

    Mehrotra, Piyush; Zubair, M.; Ziebartt, John (Technical Monitor)

    2001-01-01

    The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of HTML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

  18. XML Based Scientific Data Management Facility

    NASA Technical Reports Server (NTRS)

    Mehrotra, P.; Zubair, M.; Bushnell, Dennis M. (Technical Monitor)

    2002-01-01

    The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of XML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management ,facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

  19. Electrical Engineering in Los Alamos Neutron Science Center Accelerator

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

    Silva, Michael James

    The field of electrical engineering plays a significant role in particle accelerator design and operations. Los Alamos National Laboratories LANSCE facility utilizes the electrical energy concepts of power distribution, plasma generation, radio frequency energy, electrostatic acceleration, signals and diagnostics. The culmination of these fields produces a machine of incredible potential with uses such as isotope production, neutron spallation, neutron imaging and particle analysis. The key isotope produced in LANSCE isotope production facility is Strontium-82 which is utilized for medical uses such as cancer treatment and positron emission tomography also known as PET scans. Neutron spallation is one of the verymore » few methods used to produce neutrons for scientific research the other methods are natural decay of transuranic elements from nuclear reactors. Accelerator produce neutrons by accelerating charged particles into neutron dense elements such as tungsten imparting a neutral particle with kinetic energy, this has the benefit of producing a large number of neutrons as well as minimizing the waste generated. Utilizing the accelerator scientist can gain an understanding of how various particles behave and interact with matter to better understand the natural laws of physics and the universe around us.« less

  20. The role of dedicated data computing centers in the age of cloud computing

    NASA Astrophysics Data System (ADS)

    Caramarcu, Costin; Hollowell, Christopher; Strecker-Kellogg, William; Wong, Antonio; Zaytsev, Alexandr

    2017-10-01

    Brookhaven National Laboratory (BNL) anticipates significant growth in scientific programs with large computing and data storage needs in the near future and has recently reorganized support for scientific computing to meet these needs. A key component is the enhanced role of the RHIC-ATLAS Computing Facility (RACF) in support of high-throughput and high-performance computing (HTC and HPC) at BNL. This presentation discusses the evolving role of the RACF at BNL, in light of its growing portfolio of responsibilities and its increasing integration with cloud (academic and for-profit) computing activities. We also discuss BNL’s plan to build a new computing center to support the new responsibilities of the RACF and present a summary of the cost benefit analysis done, including the types of computing activities that benefit most from a local data center vs. cloud computing. This analysis is partly based on an updated cost comparison of Amazon EC2 computing services and the RACF, which was originally conducted in 2012.

  1. Facilitating Preschoolers' Scientific Knowledge Construction via Computer Games Regarding Light and Shadow: The Effect of the Prediction-Observation-Explanation (POE) Strategy

    NASA Astrophysics Data System (ADS)

    Hsu, Chung-Yuan; Tsai, Chin-Chung; Liang, Jyh-Chong

    2011-10-01

    Educational researchers have suggested that computer games have a profound influence on students' motivation, knowledge construction, and learning performance, but little empirical research has targeted preschoolers. Thus, the purpose of the present study was to investigate the effects of implementing a computer game that integrates the prediction-observation-explanation (POE) strategy (White and Gunstone in Probing understanding. Routledge, New York, 1992) on facilitating preschoolers' acquisition of scientific concepts regarding light and shadow. The children's alternative conceptions were explored as well. Fifty participants were randomly assigned into either an experimental group that played a computer game integrating the POE model or a control group that played a non-POE computer game. By assessing the students' conceptual understanding through interviews, this study revealed that the students in the experimental group significantly outperformed their counterparts in the concepts regarding "shadow formation in daylight" and "shadow orientation." However, children in both groups, after playing the games, still expressed some alternative conceptions such as "Shadows always appear behind a person" and "Shadows should be on the same side as the sun."

  2. Computational Science: A Research Methodology for the 21st Century

    NASA Astrophysics Data System (ADS)

    Orbach, Raymond L.

    2004-03-01

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

  3. 77 FR 59200 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-26

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

  4. 78 FR 66018 - Center for Scientific Review; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-04

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

  5. Scientific Reasoning across Different Domains.

    ERIC Educational Resources Information Center

    Glaser, Robert; And Others

    This study seeks to establish which scientific reasoning skills are primarily domain-general and which appear to be domain-specific. The subjects, 12 university undergraduates, each participated in self-directed experimentation with three different content domains. The experimentation contexts were computer-based laboratories in d.c. circuits…

  6. Evolution of computational chemistry, the "launch pad" to scientific computational models: The early days from a personal account, the present status from the TACC-2012 congress, and eventual future applications from the global simulation approach

    NASA Astrophysics Data System (ADS)

    Clementi, Enrico

    2012-06-01

    This is the introductory chapter to the AIP Proceedings volume "Theory and Applications of Computational Chemistry: The First Decade of the Second Millennium" where we discuss the evolution of "computational chemistry". Very early variational computational chemistry developments are reported in Sections 1 to 7, and 11, 12 by recalling some of the computational chemistry contributions by the author and his collaborators (from late 1950 to mid 1990); perturbation techniques are not considered in this already extended work. Present day's computational chemistry is partly considered in Sections 8 to 10 where more recent studies by the author and his collaborators are discussed, including the Hartree-Fock-Heitler-London method; a more general discussion on present day computational chemistry is presented in Section 14. The following chapters of this AIP volume provide a view of modern computational chemistry. Future computational chemistry developments can be extrapolated from the chapters of this AIP volume; further, in Sections 13 and 15 present an overall analysis on computational chemistry, obtained from the Global Simulation approach, by considering the evolution of scientific knowledge confronted with the opportunities offered by modern computers.

  7. Graduate Student Program in Materials and Engineering Research and Development for Future Accelerators

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

    Spentzouris, Linda

    The objective of the proposal was to develop graduate student training in materials and engineering research relevant to the development of particle accelerators. Many components used in today's accelerators or storage rings are at the limit of performance. The path forward in many cases requires the development of new materials or fabrication techniques, or a novel engineering approach. Often, accelerator-based laboratories find it difficult to get top-level engineers or materials experts with the motivation to work on these problems. The three years of funding provided by this grant was used to support development of accelerator components through a multidisciplinary approachmore » that cut across the disciplinary boundaries of accelerator physics, materials science, and surface chemistry. The following results were achieved: (1) significant scientific results on fabrication of novel photocathodes, (2) application of surface science and superconducting materials expertise to accelerator problems through faculty involvement, (3) development of instrumentation for fabrication and characterization of materials for accelerator components, (4) student involvement with problems at the interface of material science and accelerator physics.« less

  8. Defining Computational Thinking for Mathematics and Science Classrooms

    ERIC Educational Resources Information Center

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

    2016-01-01

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

  9. Implementing an Affordable High-Performance Computing for Teaching-Oriented Computer Science Curriculum

    ERIC Educational Resources Information Center

    Abuzaghleh, Omar; Goldschmidt, Kathleen; Elleithy, Yasser; Lee, Jeongkyu

    2013-01-01

    With the advances in computing power, high-performance computing (HPC) platforms have had an impact on not only scientific research in advanced organizations but also computer science curriculum in the educational community. For example, multicore programming and parallel systems are highly desired courses in the computer science major. However,…

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

    NASA Technical Reports Server (NTRS)

    Teren, F.

    1977-01-01

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

  11. A heuristic evaluation of long-term global sea level acceleration

    NASA Astrophysics Data System (ADS)

    Spada, Giorgio; Olivieri, Marco; Galassi, Gaia

    2015-05-01

    In view of the scientific and social implications, the global mean sea level rise (GMSLR) and its possible causes and future trend have been a challenge for so long. For the twentieth century, reconstructions generally indicate a rate of GMSLR in the range of 1.5 to 2.0 mm yr-1. However, the existence of nonlinear trends is still debated, and current estimates of the secular acceleration are subject to ample uncertainties. Here we use various GMSLR estimates published on scholarly journals since the 1940s for a heuristic assessment of global sea level acceleration. The approach, alternative to sea level reconstructions, is based on simple statistical methods and exploits the principles of meta-analysis. Our results point to a global sea level acceleration of 0.54 ± 0.27 mm/yr/century (1σ) between 1898 and 1975. This supports independent estimates and suggests that a sea level acceleration since the early 1900s is more likely than currently believed.

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

    PubMed Central

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

    2013-01-01

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

  13. A novel electron accelerator for MRI-Linac radiotherapy.

    PubMed

    Whelan, Brendan; Gierman, Stephen; Holloway, Lois; Schmerge, John; Keall, Paul; Fahrig, Rebecca

    2016-03-01

    MRI guided radiotherapy is a rapidly growing field; however, current electron accelerators are not designed to operate in the magnetic fringe fields of MRI scanners. As such, current MRI-Linac systems require magnetic shielding, which can degrade MR image quality and limit system flexibility. The purpose of this work was to develop and test a novel medical electron accelerator concept which is inherently robust to operation within magnetic fields for in-line MRI-Linac systems. Computational simulations were utilized to model the accelerator, including the thermionic emission process, the electromagnetic fields within the accelerating structure, and resulting particle trajectories through these fields. The spatial and energy characteristics of the electron beam were quantified at the accelerator target and compared to published data for conventional accelerators. The model was then coupled to the fields from a simulated 1 T superconducting magnet and solved for cathode to isocenter distances between 1.0 and 2.4 m; the impact on the electron beam was quantified. For the zero field solution, the average current at the target was 146.3 mA, with a median energy of 5.8 MeV (interquartile spread of 0.1 MeV), and a spot size diameter of 1.5 mm full-width-tenth-maximum. Such an electron beam is suitable for therapy, comparing favorably to published data for conventional systems. The simulated accelerator showed increased robustness to operation in in-line magnetic fields, with a maximum current loss of 3% compared to 85% for a conventional system in the same magnetic fields. Computational simulations suggest that replacing conventional DC electron sources with a RF based source could be used to develop medical electron accelerators which are robust to operation in in-line magnetic fields. This would enable the development of MRI-Linac systems with no magnetic shielding around the Linac and reduce the requirements for optimization of magnetic fringe field, simplify design of

  14. A novel electron accelerator for MRI-Linac radiotherapy

    PubMed Central

    Whelan, Brendan; Gierman, Stephen; Holloway, Lois; Schmerge, John; Keall, Paul; Fahrig, Rebecca

    2016-01-01

    Purpose: MRI guided radiotherapy is a rapidly growing field; however, current electron accelerators are not designed to operate in the magnetic fringe fields of MRI scanners. As such, current MRI-Linac systems require magnetic shielding, which can degrade MR image quality and limit system flexibility. The purpose of this work was to develop and test a novel medical electron accelerator concept which is inherently robust to operation within magnetic fields for in-line MRI-Linac systems. Methods: Computational simulations were utilized to model the accelerator, including the thermionic emission process, the electromagnetic fields within the accelerating structure, and resulting particle trajectories through these fields. The spatial and energy characteristics of the electron beam were quantified at the accelerator target and compared to published data for conventional accelerators. The model was then coupled to the fields from a simulated 1 T superconducting magnet and solved for cathode to isocenter distances between 1.0 and 2.4 m; the impact on the electron beam was quantified. Results: For the zero field solution, the average current at the target was 146.3 mA, with a median energy of 5.8 MeV (interquartile spread of 0.1 MeV), and a spot size diameter of 1.5 mm full-width-tenth-maximum. Such an electron beam is suitable for therapy, comparing favorably to published data for conventional systems. The simulated accelerator showed increased robustness to operation in in-line magnetic fields, with a maximum current loss of 3% compared to 85% for a conventional system in the same magnetic fields. Conclusions: Computational simulations suggest that replacing conventional DC electron sources with a RF based source could be used to develop medical electron accelerators which are robust to operation in in-line magnetic fields. This would enable the development of MRI-Linac systems with no magnetic shielding around the Linac and reduce the requirements for optimization of

  15. GPU accelerated manifold correction method for spinning compact binaries

    NASA Astrophysics Data System (ADS)

    Ran, Chong-xi; Liu, Song; Zhong, Shuang-ying

    2018-04-01

    The graphics processing unit (GPU) acceleration of the manifold correction algorithm based on the compute unified device architecture (CUDA) technology is designed to simulate the dynamic evolution of the Post-Newtonian (PN) Hamiltonian formulation of spinning compact binaries. The feasibility and the efficiency of parallel computation on GPU have been confirmed by various numerical experiments. The numerical comparisons show that the accuracy on GPU execution of manifold corrections method has a good agreement with the execution of codes on merely central processing unit (CPU-based) method. The acceleration ability when the codes are implemented on GPU can increase enormously through the use of shared memory and register optimization techniques without additional hardware costs, implying that the speedup is nearly 13 times as compared with the codes executed on CPU for phase space scan (including 314 × 314 orbits). In addition, GPU-accelerated manifold correction method is used to numerically study how dynamics are affected by the spin-induced quadrupole-monopole interaction for black hole binary system.

  16. Cloud computing approaches to accelerate drug discovery value chain.

    PubMed

    Garg, Vibhav; Arora, Suchir; Gupta, Chitra

    2011-12-01

    Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

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

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

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

    2014-08-28

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

  18. 76 FR 63311 - Center for Scientific Review Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-12

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

  19. Accurate and efficient spin integration for particle accelerators

    DOE PAGES

    Abell, Dan T.; Meiser, Dominic; Ranjbar, Vahid H.; ...

    2015-02-01

    Accurate spin tracking is a valuable tool for understanding spin dynamics in particle accelerators and can help improve the performance of an accelerator. In this paper, we present a detailed discussion of the integrators in the spin tracking code GPUSPINTRACK. We have implemented orbital integrators based on drift-kick, bend-kick, and matrix-kick splits. On top of the orbital integrators, we have implemented various integrators for the spin motion. These integrators use quaternions and Romberg quadratures to accelerate both the computation and the convergence of spin rotations.We evaluate their performance and accuracy in quantitative detail for individual elements as well as formore » the entire RHIC lattice. We exploit the inherently data-parallel nature of spin tracking to accelerate our algorithms on graphics processing units.« less

  20. Graphics Processing Unit Acceleration of Gyrokinetic Turbulence Simulations

    NASA Astrophysics Data System (ADS)

    Hause, Benjamin; Parker, Scott

    2012-10-01

    We find a substantial increase in on-node performance using Graphics Processing Unit (GPU) acceleration in gyrokinetic delta-f particle-in-cell simulation. Optimization is performed on a two-dimensional slab gyrokinetic particle simulation using the Portland Group Fortran compiler with the GPU accelerator compiler directives. We have implemented the GPU acceleration on a Core I7 gaming PC with a NVIDIA GTX 580 GPU. We find comparable, or better, acceleration relative to the NERSC DIRAC cluster with the NVIDIA Tesla C2050 computing processor. The Tesla C 2050 is about 2.6 times more expensive than the GTX 580 gaming GPU. Optimization strategies and comparisons between DIRAC and the gaming PC will be presented. We will also discuss progress on optimizing the comprehensive three dimensional general geometry GEM code.

  1. Computer modeling of photodegradation

    NASA Technical Reports Server (NTRS)

    Guillet, J.

    1986-01-01

    A computer program to simulate the photodegradation of materials exposed to terrestrial weathering environments is being developed. Input parameters would include the solar spectrum, the daily levels and variations of temperature and relative humidity, and materials such as EVA. A brief description of the program, its operating principles, and how it works was initially described. After that, the presentation focuses on the recent work of simulating aging in a normal, terrestrial day-night cycle. This is significant, as almost all accelerated aging schemes maintain a constant light illumination without a dark cycle, and this may be a critical factor not included in acceleration aging schemes. For outdoor aging, the computer model is indicating that the night dark cycle has a dramatic influence on the chemistry of photothermal degradation, and hints that a dark cycle may be needed in an accelerated aging scheme.

  2. Accelerated spike resampling for accurate multiple testing controls.

    PubMed

    Harrison, Matthew T

    2013-02-01

    Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

  3. Major Depressive Disorder and Bipolar Disorder Predispose Youth to Accelerated Atherosclerosis and Early Cardiovascular Disease: A Scientific Statement From the American Heart Association.

    PubMed

    Goldstein, Benjamin I; Carnethon, Mercedes R; Matthews, Karen A; McIntyre, Roger S; Miller, Gregory E; Raghuveer, Geetha; Stoney, Catherine M; Wasiak, Hank; McCrindle, Brian W

    2015-09-08

    In the 2011 "Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents," several medical conditions among youth were identified that predispose to accelerated atherosclerosis and early cardiovascular disease (CVD), and risk stratification and management strategies for youth with these conditions were elaborated. Major depressive disorder (MDD) and bipolar disorder (BD) among youth satisfy the criteria set for, and therefore merit inclusion among, Expert Panel tier II moderate-risk conditions. The combined prevalence of MDD and BD among adolescents in the United States is ≈10%, at least 10 times greater than the prevalence of the existing moderate-risk conditions combined. The high prevalence of MDD and BD underscores the importance of positioning these diseases alongside other pediatric diseases previously identified as moderate risk for CVD. The overall objective of this statement is to increase awareness and recognition of MDD and BD among youth as moderate-risk conditions for early CVD. To achieve this objective, the primary specific aims of this statement are to (1) summarize evidence that MDD and BD are tier II moderate-risk conditions associated with accelerated atherosclerosis and early CVD and (2) position MDD and BD as tier II moderate-risk conditions that require the application of risk stratification and management strategies in accordance with Expert Panel recommendations. In this scientific statement, there is an integration of the various factors that putatively underlie the association of MDD and BD with CVD, including pathophysiological mechanisms, traditional CVD risk factors, behavioral and environmental factors, and psychiatric medications. © 2015 American Heart Association, Inc.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

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

    DOEpatents

    Schach Von Wittenau, Alexis E.

    2003-01-01

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

  6. Numerical ‘health check’ for scientific codes: the CADNA approach

    NASA Astrophysics Data System (ADS)

    Scott, N. S.; Jézéquel, F.; Denis, C.; Chesneaux, J.-M.

    2007-04-01

    Scientific computation has unavoidable approximations built into its very fabric. One important source of error that is difficult to detect and control is round-off error propagation which originates from the use of finite precision arithmetic. We propose that there is a need to perform regular numerical 'health checks' on scientific codes in order to detect the cancerous effect of round-off error propagation. This is particularly important in scientific codes that are built on legacy software. We advocate the use of the CADNA library as a suitable numerical screening tool. We present a case study to illustrate the practical use of CADNA in scientific codes that are of interest to the Computer Physics Communications readership. In doing so we hope to stimulate a greater awareness of round-off error propagation and present a practical means by which it can be analyzed and managed.

  7. Applications of laser wakefield accelerator-based light sources

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

    Albert, Felicie; Thomas, Alec G. R.

    Laser-wakefield accelerators (LWFAs) were proposed more than three decades ago, and while they promise to deliver compact, high energy particle accelerators, they will also provide the scientific community with novel light sources. In a LWFA, where an intense laser pulse focused onto a plasma forms an electromagnetic wave in its wake, electrons can be trapped and are now routinely accelerated to GeV energies. From terahertz radiation to gamma-rays, this article reviews light sources from relativistic electrons produced by LWFAs, and discusses their potential applications. Betatron motion, Compton scattering and undulators respectively produce x-rays or gamma-rays by oscillating relativistic electrons inmore » the wakefield behind the laser pulse, a counter-propagating laser field, or a magnetic undulator. Other LWFA-based light sources include bremsstrahlung and terahertz radiation. Here, we first evaluate the performance of each of these light sources, and compare them with more conventional approaches, including radio frequency accelerators or other laser-driven sources. We have then identified applications, which we discuss in details, in a broad range of fields: medical and biological applications, military, defense and industrial applications, and condensed matter and high energy density science.« less

  8. Applications of laser wakefield accelerator-based light sources

    DOE PAGES

    Albert, Felicie; Thomas, Alec G. R.

    2016-10-01

    Laser-wakefield accelerators (LWFAs) were proposed more than three decades ago, and while they promise to deliver compact, high energy particle accelerators, they will also provide the scientific community with novel light sources. In a LWFA, where an intense laser pulse focused onto a plasma forms an electromagnetic wave in its wake, electrons can be trapped and are now routinely accelerated to GeV energies. From terahertz radiation to gamma-rays, this article reviews light sources from relativistic electrons produced by LWFAs, and discusses their potential applications. Betatron motion, Compton scattering and undulators respectively produce x-rays or gamma-rays by oscillating relativistic electrons inmore » the wakefield behind the laser pulse, a counter-propagating laser field, or a magnetic undulator. Other LWFA-based light sources include bremsstrahlung and terahertz radiation. Here, we first evaluate the performance of each of these light sources, and compare them with more conventional approaches, including radio frequency accelerators or other laser-driven sources. We have then identified applications, which we discuss in details, in a broad range of fields: medical and biological applications, military, defense and industrial applications, and condensed matter and high energy density science.« less

  9. Architectural requirements for the Red Storm computing system.

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

    Camp, William J.; Tomkins, James Lee

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

  10. Accelerated Compressed Sensing Based CT Image Reconstruction.

    PubMed

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  11. Accelerated Compressed Sensing Based CT Image Reconstruction

    PubMed Central

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R.; Paul, Narinder S.; Cobbold, Richard S. C.

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization. PMID:26167200

  12. Accelerating execution of the integrated TIGER series Monte Carlo radiation transport codes

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

    Smith, L.M.; Hochstedler, R.D.

    1997-02-01

    Execution of the integrated TIGER series (ITS) of coupled electron/photon Monte Carlo radiation transport codes has been accelerated by modifying the FORTRAN source code for more efficient computation. Each member code of ITS was benchmarked and profiled with a specific test case that directed the acceleration effort toward the most computationally intensive subroutines. Techniques for accelerating these subroutines included replacing linear search algorithms with binary versions, replacing the pseudo-random number generator, reducing program memory allocation, and proofing the input files for geometrical redundancies. All techniques produced identical or statistically similar results to the original code. Final benchmark timing of themore » accelerated code resulted in speed-up factors of 2.00 for TIGER (the one-dimensional slab geometry code), 1.74 for CYLTRAN (the two-dimensional cylindrical geometry code), and 1.90 for ACCEPT (the arbitrary three-dimensional geometry code).« less

  13. Using Accelerated Reader with ESL Students.

    ERIC Educational Resources Information Center

    Hamilton, Betty

    1997-01-01

    Describes the use of Accelerated Reader, a computer program that instantly provides scored tests on a variety of books read by high school ESL (English as a Second Language) students as free voluntary reading. Topics include reading improvement programs, including writing assignments; and changes in students' reading habits. (LRW)

  14. Alzforum and SWAN: the present and future of scientific web communities.

    PubMed

    Clark, Tim; Kinoshita, June

    2007-05-01

    Scientists drove the early development of the World Wide Web, primarily as a means for rapid communication, document sharing and data access. They have been far slower to adopt the web as a medium for building research communities. Yet, web-based communities hold great potential for accelerating the pace of scientific research. In this article, we will describe the 10-year experience of the Alzheimer Research Forum ('Alzforum'), a unique example of a thriving scientific web community, and explain the features that contributed to its success. We will then outline the SWAN (Semantic Web Applications in Neuromedicine) project, in which Alzforum curators are collaborating with informatics researchers to develop novel approaches that will enable communities to share richly contextualized information about scientific data, claims and hypotheses.

  15. Accelerating Innovation: How Nuclear Physics Benefits Us All

    DOE R&D Accomplishments Database

    2011-01-01

    Innovation has been accelerated by nuclear physics in the areas of improving our health; making the world safer; electricity, environment, archaeology; better computers; contributions to industry; and training the next generation of innovators.

  16. FPGA-accelerated adaptive optics wavefront control

    NASA Astrophysics Data System (ADS)

    Mauch, S.; Reger, J.; Reinlein, C.; Appelfelder, M.; Goy, M.; Beckert, E.; Tünnermann, A.

    2014-03-01

    The speed of real-time adaptive optical systems is primarily restricted by the data processing hardware and computational aspects. Furthermore, the application of mirror layouts with increasing numbers of actuators reduces the bandwidth (speed) of the system and, thus, the number of applicable control algorithms. This burden turns out a key-impediment for deformable mirrors with continuous mirror surface and highly coupled actuator influence functions. In this regard, specialized hardware is necessary for high performance real-time control applications. Our approach to overcome this challenge is an adaptive optics system based on a Shack-Hartmann wavefront sensor (SHWFS) with a CameraLink interface. The data processing is based on a high performance Intel Core i7 Quadcore hard real-time Linux system. Employing a Xilinx Kintex-7 FPGA, an own developed PCie card is outlined in order to accelerate the analysis of a Shack-Hartmann Wavefront Sensor. A recently developed real-time capable spot detection algorithm evaluates the wavefront. The main features of the presented system are the reduction of latency and the acceleration of computation For example, matrix multiplications which in general are of complexity O(n3 are accelerated by using the DSP48 slices of the field-programmable gate array (FPGA) as well as a novel hardware implementation of the SHWFS algorithm. Further benefits are the Streaming SIMD Extensions (SSE) which intensively use the parallelization capability of the processor for further reducing the latency and increasing the bandwidth of the closed-loop. Due to this approach, up to 64 actuators of a deformable mirror can be handled and controlled without noticeable restriction from computational burdens.

  17. Acceleration modules in linear induction accelerators

    NASA Astrophysics Data System (ADS)

    Wang, Shao-Heng; Deng, Jian-Jun

    2014-05-01

    The Linear Induction Accelerator (LIA) is a unique type of accelerator that is capable of accelerating kilo-Ampere charged particle current to tens of MeV energy. The present development of LIA in MHz bursting mode and the successful application into a synchrotron have broadened LIA's usage scope. Although the transformer model is widely used to explain the acceleration mechanism of LIAs, it is not appropriate to consider the induction electric field as the field which accelerates charged particles for many modern LIAs. We have examined the transition of the magnetic cores' functions during the LIA acceleration modules' evolution, distinguished transformer type and transmission line type LIA acceleration modules, and re-considered several related issues based on transmission line type LIA acceleration module. This clarified understanding should help in the further development and design of LIA acceleration modules.

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

    NASA Technical Reports Server (NTRS)

    Sutliff, Thomas J.

    1999-01-01

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

  19. Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.

    ERIC Educational Resources Information Center

    Russell, Daniel M.; Pirolli, Peter

    Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…

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

    PubMed

    Reggia, James A

    2013-08-01

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

  1. Multicore Challenges and Benefits for High Performance Scientific Computing

    DOE PAGES

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

    2008-01-01

    Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexitymore » of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.« less

  2. Scientific computations section monthly report, November 1993

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

    Buckner, M.R.

    1993-12-30

    This progress report from the Savannah River Technology Center contains abstracts from papers from the computational modeling, applied statistics, applied physics, experimental thermal hydraulics, and packaging and transportation groups. Specific topics covered include: engineering modeling and process simulation, criticality methods and analysis, plutonium disposition.

  3. Choosing order of operations to accelerate strip structure analysis in parameter range

    NASA Astrophysics Data System (ADS)

    Kuksenko, S. P.; Akhunov, R. R.; Gazizov, T. R.

    2018-05-01

    The paper considers the issue of using iteration methods in solving the sequence of linear algebraic systems obtained in quasistatic analysis of strip structures with the method of moments. Using the analysis of 4 strip structures, the authors have proved that additional acceleration (up to 2.21 times) of the iterative process can be obtained during the process of solving linear systems repeatedly by means of choosing a proper order of operations and a preconditioner. The obtained results can be used to accelerate the process of computer-aided design of various strip structures. The choice of the order of operations to accelerate the process is quite simple, universal and could be used not only for strip structure analysis but also for a wide range of computational problems.

  4. Combining Diffusive Shock Acceleration with Acceleration by Contracting and Reconnecting Small-scale Flux Ropes at Heliospheric Shocks

    NASA Astrophysics Data System (ADS)

    le Roux, J. A.; Zank, G. P.; Webb, G. M.; Khabarova, O. V.

    2016-08-01

    Computational and observational evidence is accruing that heliospheric shocks, as emitters of vorticity, can produce downstream magnetic flux ropes and filaments. This led Zank et al. to investigate a new paradigm whereby energetic particle acceleration near shocks is a combination of diffusive shock acceleration (DSA) with downstream acceleration by many small-scale contracting and reconnecting (merging) flux ropes. Using a model where flux-rope acceleration involves a first-order Fermi mechanism due to the mean compression of numerous contracting flux ropes, Zank et al. provide theoretical support for observations that power-law spectra of energetic particles downstream of heliospheric shocks can be harder than predicted by DSA theory and that energetic particle intensities should peak behind shocks instead of at shocks as predicted by DSA theory. In this paper, a more extended formalism of kinetic transport theory developed by le Roux et al. is used to further explore this paradigm. We describe how second-order Fermi acceleration, related to the variance in the electromagnetic fields produced by downstream small-scale flux-rope dynamics, modifies the standard DSA model. The results show that (I) this approach can qualitatively reproduce observations of particle intensities peaking behind the shock, thus providing further support for the new paradigm, and (II) stochastic acceleration by compressible flux ropes tends to be more efficient than incompressible flux ropes behind shocks in modifying the DSA spectrum of energetic particles.

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

    NASA Astrophysics Data System (ADS)

    Esler, Kenneth

    2011-03-01

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

  6. 2011 Computation Directorate Annual Report

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

    Crawford, D L

    2012-04-11

    /ASC accelerated the development of simulation capabilities necessary to ensure confidence in the nuclear stockpile-far exceeding what might have been achieved in the absence of a focused initiative. While stockpile stewardship research pushed LLNL scientists to develop new computer codes, better simulation methods, and improved visualization technologies, this work also stimulated the exploration of HPC applications beyond the standard sponsor base. As LLNL advances to a petascale platform and pursues exascale computing (1,000 times faster than Sequoia), ASC will be paramount to achieving predictive simulation and uncertainty quantification. Predictive simulation and quantifying the uncertainty of numerical predictions where little-to-no data exists demands exascale computing and represents an expanding area of scientific research important not only to nuclear weapons, but to nuclear attribution, nuclear reactor design, and understanding global climate issues, among other fields. Aside from these lofty goals and challenges, computing at LLNL is anything but 'business as usual.' International competition in supercomputing is nothing new, but the HPC community is now operating in an expanded, more aggressive climate of global competitiveness. More countries understand how science and technology research and development are inextricably linked to economic prosperity, and they are aggressively pursuing ways to integrate HPC technologies into their native industrial and consumer products. In the interest of the nation's economic security and the science and technology that underpins it, LLNL is expanding its portfolio and forging new collaborations. We must ensure that HPC remains an asymmetric engine of innovation for the Laboratory and for the U.S. and, in doing so, protect our research and development dynamism and the prosperity it makes possible. One untapped area of opportunity LLNL is pursuing is to help U.S. industry understand how supercomputing can benefit their business

  7. Torque-based optimal acceleration control for electric vehicle

    NASA Astrophysics Data System (ADS)

    Lu, Dongbin; Ouyang, Minggao

    2014-03-01

    The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle(EV) has not been reported. In this paper, the permanent magnet synchronous motor(PMSM) is controlled by the field oriented control(FOC) method and the electric drive system for the EV(including the PMSM, the inverter and the battery) is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming(DP). This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.

  8. Scientific Assistant Virtual Laboratory (SAVL)

    NASA Astrophysics Data System (ADS)

    Alaghband, Gita; Fardi, Hamid; Gnabasik, David

    2007-03-01

    The Scientific Assistant Virtual Laboratory (SAVL) is a scientific discovery environment, an interactive simulated virtual laboratory, for learning physics and mathematics. The purpose of this computer-assisted intervention is to improve middle and high school student interest, insight and scores in physics and mathematics. SAVL develops scientific and mathematical imagination in a visual, symbolic, and experimental simulation environment. It directly addresses the issues of scientific and technological competency by providing critical thinking training through integrated modules. This on-going research provides a virtual laboratory environment in which the student directs the building of the experiment rather than observing a packaged simulation. SAVL: * Engages the persistent interest of young minds in physics and math by visually linking simulation objects and events with mathematical relations. * Teaches integrated concepts by the hands-on exploration and focused visualization of classic physics experiments within software. * Systematically and uniformly assesses and scores students by their ability to answer their own questions within the context of a Master Question Network. We will demonstrate how the Master Question Network uses polymorphic interfaces and C# lambda expressions to manage simulation objects.

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

    PubMed

    Kim, Lok-Won

    2018-05-01

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

  10. Experimental realization of underdense plasma photocathode wakefield acceleration at FACET

    NASA Astrophysics Data System (ADS)

    Scherkl, Paul

    2017-10-01

    Novel electron beam sources from compact plasma accelerator concepts currently mature into the driving technology for next generation high-energy physics and light source facilities. Particularly electron beams of ultra-high brightness could pave the way for major advances for both scientific and commercial applications, but their generation remains tremendously challenging. The presentation outlines the experimental demonstration of the world's first bright electron beam source from spatiotemporally synchronized laser pulses injecting electrons into particle-driven plasma wakefields at FACET. Two distinctive types of operation - laser-triggered density downramp injection (``Plasma Torch'') and underdense plasma photocathode acceleration (``Trojan Horse'') - and their intermediate transitions are characterized and contrasted. Extensive particle-in-cell simulations substantiate the presentation of experimental results. In combination with novel techniques to minimize the beam energy spread, the acceleration scheme presented here promises ultra-high beam quality and brightness.

  11. Acceleration of GPU-based Krylov solvers via data transfer reduction

    DOE PAGES

    Anzt, Hartwig; Tomov, Stanimire; Luszczek, Piotr; ...

    2015-04-08

    Krylov subspace iterative solvers are often the method of choice when solving large sparse linear systems. At the same time, hardware accelerators such as graphics processing units continue to offer significant floating point performance gains for matrix and vector computations through easy-to-use libraries of computational kernels. However, as these libraries are usually composed of a well optimized but limited set of linear algebra operations, applications that use them often fail to reduce certain data communications, and hence fail to leverage the full potential of the accelerator. In this study, we target the acceleration of Krylov subspace iterative methods for graphicsmore » processing units, and in particular the Biconjugate Gradient Stabilized solver that significant improvement can be achieved by reformulating the method to reduce data-communications through application-specific kernels instead of using the generic BLAS kernels, e.g. as provided by NVIDIA’s cuBLAS library, and by designing a graphics processing unit specific sparse matrix-vector product kernel that is able to more efficiently use the graphics processing unit’s computing power. Furthermore, we derive a model estimating the performance improvement, and use experimental data to validate the expected runtime savings. Finally, considering that the derived implementation achieves significantly higher performance, we assert that similar optimizations addressing algorithm structure, as well as sparse matrix-vector, are crucial for the subsequent development of high-performance graphics processing units accelerated Krylov subspace iterative methods.« less

  12. Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale.

    PubMed

    Huang, Muhuan; Wu, Di; Yu, Cody Hao; Fang, Zhenman; Interlandi, Matteo; Condie, Tyson; Cong, Jason

    2016-10-01

    With the end of CPU core scaling due to dark silicon limitations, customized accelerators on FPGAs have gained increased attention in modern datacenters due to their lower power, high performance and energy efficiency. Evidenced by Microsoft's FPGA deployment in its Bing search engine and Intel's 16.7 billion acquisition of Altera, integrating FPGAs into datacenters is considered one of the most promising approaches to sustain future datacenter growth. However, it is quite challenging for existing big data computing systems-like Apache Spark and Hadoop-to access the performance and energy benefits of FPGA accelerators. In this paper we design and implement Blaze to provide programming and runtime support for enabling easy and efficient deployments of FPGA accelerators in datacenters. In particular, Blaze abstracts FPGA accelerators as a service (FaaS) and provides a set of clean programming APIs for big data processing applications to easily utilize those accelerators. Our Blaze runtime implements an FaaS framework to efficiently share FPGA accelerators among multiple heterogeneous threads on a single node, and extends Hadoop YARN with accelerator-centric scheduling to efficiently share them among multiple computing tasks in the cluster. Experimental results using four representative big data applications demonstrate that Blaze greatly reduces the programming efforts to access FPGA accelerators in systems like Apache Spark and YARN, and improves the system throughput by 1.7 × to 3× (and energy efficiency by 1.5× to 2.7×) compared to a conventional CPU-only cluster.

  13. Toward Scientific Numerical Modeling

    NASA Technical Reports Server (NTRS)

    Kleb, Bil

    2007-01-01

    Ultimately, scientific numerical models need quantified output uncertainties so that modeling can evolve to better match reality. Documenting model input uncertainties and verifying that numerical models are translated into code correctly, however, are necessary first steps toward that goal. Without known input parameter uncertainties, model sensitivities are all one can determine, and without code verification, output uncertainties are simply not reliable. To address these two shortcomings, two proposals are offered: (1) an unobtrusive mechanism to document input parameter uncertainties in situ and (2) an adaptation of the Scientific Method to numerical model development and deployment. Because these two steps require changes in the computational simulation community to bear fruit, they are presented in terms of the Beckhard-Harris-Gleicher change model.

  14. High throughput computing: a solution for scientific analysis

    USGS Publications Warehouse

    O'Donnell, M.

    2011-01-01

    handle job failures due to hardware, software, or network interruptions (obviating the need to manually resubmit the job after each stoppage); be affordable; and most importantly, allow us to complete very large, complex analyses that otherwise would not even be possible. In short, we envisioned a job-management system that would take advantage of unused FORT CPUs within a local area network (LAN) to effectively distribute and run highly complex analytical processes. What we found was a solution that uses High Throughput Computing (HTC) and High Performance Computing (HPC) systems to do exactly that (Figure 1).

  15. Accelerating Advanced MRI Reconstructions on GPUs

    PubMed Central

    Stone, S.S.; Haldar, J.P.; Tsao, S.C.; Hwu, W.-m.W.; Sutton, B.P.; Liang, Z.-P.

    2008-01-01

    Computational acceleration on graphics processing units (GPUs) can make advanced magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings, thereby improving the quality of MR images across a broad spectrum of applications. This paper describes the acceleration of such an algorithm on NVIDIA’s Quadro FX 5600. The reconstruction of a 3D image with 1283 voxels achieves up to 180 GFLOPS and requires just over one minute on the Quadro, while reconstruction on a quad-core CPU is twenty-one times slower. Furthermore, relative to the true image, the error exhibited by the advanced reconstruction is only 12%, while conventional reconstruction techniques incur error of 42%. PMID:21796230

  16. Accelerating Advanced MRI Reconstructions on GPUs.

    PubMed

    Stone, S S; Haldar, J P; Tsao, S C; Hwu, W-M W; Sutton, B P; Liang, Z-P

    2008-10-01

    Computational acceleration on graphics processing units (GPUs) can make advanced magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings, thereby improving the quality of MR images across a broad spectrum of applications. This paper describes the acceleration of such an algorithm on NVIDIA's Quadro FX 5600. The reconstruction of a 3D image with 128(3) voxels achieves up to 180 GFLOPS and requires just over one minute on the Quadro, while reconstruction on a quad-core CPU is twenty-one times slower. Furthermore, relative to the true image, the error exhibited by the advanced reconstruction is only 12%, while conventional reconstruction techniques incur error of 42%.

  17. Final Scientific Report: A Scalable Development Environment for Peta-Scale Computing

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

    Karbach, Carsten; Frings, Wolfgang

    2013-02-22

    This document is the final scientific report of the project DE-SC000120 (A scalable Development Environment for Peta-Scale Computing). The objective of this project is the extension of the Parallel Tools Platform (PTP) for applying it to peta-scale systems. PTP is an integrated development environment for parallel applications. It comprises code analysis, performance tuning, parallel debugging and system monitoring. The contribution of the Juelich Supercomputing Centre (JSC) aims to provide a scalable solution for system monitoring of supercomputers. This includes the development of a new communication protocol for exchanging status data between the target remote system and the client running PTP.more » The communication has to work for high latency. PTP needs to be implemented robustly and should hide the complexity of the supercomputer's architecture in order to provide a transparent access to various remote systems via a uniform user interface. This simplifies the porting of applications to different systems, because PTP functions as abstraction layer between parallel application developer and compute resources. The common requirement for all PTP components is that they have to interact with the remote supercomputer. E.g. applications are built remotely and performance tools are attached to job submissions and their output data resides on the remote system. Status data has to be collected by evaluating outputs of the remote job scheduler and the parallel debugger needs to control an application executed on the supercomputer. The challenge is to provide this functionality for peta-scale systems in real-time. The client server architecture of the established monitoring application LLview, developed by the JSC, can be applied to PTP's system monitoring. LLview provides a well-arranged overview of the supercomputer's current status. A set of statistics, a list of running and queued jobs as well as a node display mapping running jobs to their compute resources form

  18. Object-oriented design for accelerator control

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

    Stok, P.D.V. van der; Berk, F. van den; Deckers, R.

    1994-02-01

    An object-oriented design for the distributed computer control system of the accelerator ring EUTERPE is presented. Because of the experimental nature of the ring, flexibility is of the utmost importance. The object-oriented principles have contributed considerably to the flexibility of the design incorporating multiple views, multi-level access and distributed surveillance.

  19. Energy Innovation Hubs: A Home for Scientific Collaboration

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

    Chu, Steven

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

  20. Data mining techniques for scientific computing: Application to asymptotic paraxial approximations to model ultrarelativistic particles

    NASA Astrophysics Data System (ADS)

    Assous, Franck; Chaskalovic, Joël

    2011-06-01

    We propose a new approach that consists in using data mining techniques for scientific computing. Indeed, data mining has proved to be efficient in other contexts which deal with huge data like in biology, medicine, marketing, advertising and communications. Our aim, here, is to deal with the important problem of the exploitation of the results produced by any numerical method. Indeed, more and more data are created today by numerical simulations. Thus, it seems necessary to look at efficient tools to analyze them. In this work, we focus our presentation to a test case dedicated to an asymptotic paraxial approximation to model ultrarelativistic particles. Our method directly deals with numerical results of simulations and try to understand what each order of the asymptotic expansion brings to the simulation results over what could be obtained by other lower-order or less accurate means. This new heuristic approach offers new potential applications to treat numerical solutions to mathematical models.