Science.gov

Sample records for parallel scientific computing

  1. 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.

  2. 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.

  3. Parallel hypergraph partitioning for scientific computing.

    SciTech Connect

    Heaphy, Robert; Devine, Karen Dragon; Catalyurek, Umit; Bisseling, Robert; Hendrickson, Bruce Alan; Boman, Erik Gunnar

    2005-07-01

    Graph partitioning is often used for load balancing in parallel computing, but it is known that hypergraph partitioning has several advantages. First, hypergraphs more accurately model communication volume, and second, they are more expressive and can better represent nonsymmetric problems. Hypergraph partitioning is particularly suited to parallel sparse matrix-vector multiplication, a common kernel in scientific computing. We present a parallel software package for hypergraph (and sparse matrix) partitioning developed at Sandia National Labs. The algorithm is a variation on multilevel partitioning. Our parallel implementation is novel in that it uses a two-dimensional data distribution among processors. We present empirical results that show our parallel implementation achieves good speedup on several large problems (up to 33 million nonzeros) with up to 64 processors on a Linux cluster.

  4. 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.

  5. Advances in Domain Mapping of Massively Parallel Scientific Computations

    SciTech Connect

    Leland, Robert W.; Hendrickson, Bruce A.

    2015-10-01

    One of the most important concerns in parallel computing is the proper distribution of workload across processors. For most scientific applications on massively parallel machines, the best approach to this distribution is to employ data parallelism; that is, to break the datastructures supporting a computation into pieces and then to assign those pieces to different processors. Collectively, these partitioning and assignment tasks comprise the domain mapping problem.

  6. On combining computational differentiation and toolkits for parallel scientific computing.

    SciTech Connect

    Bischof, C. H.; Buecker, H. M.; Hovland, P. D.

    2000-06-08

    Automatic differentiation is a powerful technique for evaluating derivatives of functions given in the form of a high-level programming language such as Fortran, C, or C++. The program is treated as a potentially very long sequence of elementary statements to which the chain rule of differential calculus is applied over and over again. Combining automatic differentiation and the organizational structure of toolkits for parallel scientific computing provides a mechanism for evaluating derivatives by exploiting mathematical insight on a higher level. In these toolkits, algorithmic structures such as BLAS-like operations, linear and nonlinear solvers, or integrators for ordinary differential equations can be identified by their standardized interfaces and recognized as high-level mathematical objects rather than as a sequence of elementary statements. In this note, the differentiation of a linear solver with respect to some parameter vector is taken as an example. Mathematical insight is used to reformulate this problem into the solution of multiple linear systems that share the same coefficient matrix but differ in their right-hand sides. The experiments reported here use ADIC, a tool for the automatic differentiation of C programs, and PETSC, an object-oriented toolkit for the parallel solution of scientific problems modeled by partial differential equations.

  7. Lattice gauge theory on the Intel parallel scientific computer

    NASA Astrophysics Data System (ADS)

    Gottlieb, Steven

    1990-08-01

    Intel Scientific Computers (ISC) has just started producing its third general of parallel computer, the iPSC/860. Based on the i860 chip that has a peak performance of 80 Mflops and with a current maximum of 128 nodes, this computer should achieve speeds in excess of those obtainable on conventional vector supercomputers. The hardware, software and computing techniques appropriate for lattice gauge theory calculations are described. The differences between a staggered fermion conjugate gradient program written under CANOPY and for the iPSC are detailed.

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

    SciTech Connect

    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 large 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 refreshing to see

  9. SIAM Conference on Parallel Processing for Scientific Computing - March 12-14, 2008

    SciTech Connect

    Kolata, William G.

    2008-09-08

    The themes of the 2008 conference included, but were not limited to: Programming languages, models, and compilation techniques; The transition to ubiquitous multicore/manycore processors; Scientific computing on special-purpose processors (Cell, GPUs, etc.); Architecture-aware algorithms; From scalable algorithms to scalable software; Tools for software development and performance evaluation; Global perspectives on HPC; Parallel computing in industry; Distributed/grid computing; Fault tolerance; Parallel visualization and large scale data management; and The future of parallel architectures.

  10. Parallel computing works

    SciTech Connect

    Not Available

    1991-10-23

    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 many 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.

  11. Eighth SIAM conference on parallel processing for scientific computing: Final program and abstracts

    SciTech Connect

    1997-12-31

    This SIAM conference is the premier forum for developments in parallel numerical algorithms, a field that has seen very lively and fruitful developments over the past decade, and whose health is still robust. Themes for this conference were: combinatorial optimization; data-parallel languages; large-scale parallel applications; message-passing; molecular modeling; parallel I/O; parallel libraries; parallel software tools; parallel compilers; particle simulations; problem-solving environments; and sparse matrix computations.

  12. MiniGhost : a miniapp for exploring boundary exchange strategies using stencil computations in scientific parallel computing.

    SciTech Connect

    Barrett, Richard Frederick; Heroux, Michael Allen; Vaughan, Courtenay Thomas

    2012-04-01

    A broad range of scientific computation involves the use of difference stencils. In a parallel computing environment, this computation is typically implemented by decomposing the spacial domain, inducing a 'halo exchange' of process-owned boundary data. This approach adheres to the Bulk Synchronous Parallel (BSP) model. Because commonly available architectures provide strong inter-node bandwidth relative to latency costs, many codes 'bulk up' these messages by aggregating data into a message as a means of reducing the number of messages. A renewed focus on non-traditional architectures and architecture features provides new opportunities for exploring alternatives to this programming approach. In this report we describe miniGhost, a 'miniapp' designed for exploration of the capabilities of current as well as emerging and future architectures within the context of these sorts of applications. MiniGhost joins the suite of miniapps developed as part of the Mantevo project.

  13. Highly parallel computation

    NASA Technical Reports Server (NTRS)

    Denning, Peter J.; Tichy, Walter F.

    1990-01-01

    Among the highly parallel computing architectures required for advanced scientific computation, those designated 'MIMD' and 'SIMD' have yielded the best results to date. The present development status evaluation of such architectures shown neither to have attained a decisive advantage in most near-homogeneous problems' treatment; in the cases of problems involving numerous dissimilar parts, however, such currently speculative architectures as 'neural networks' or 'data flow' machines may be entailed. Data flow computers are the most practical form of MIMD fine-grained parallel computers yet conceived; they automatically solve the problem of assigning virtual processors to the real processors in the machine.

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  15. Research in parallel computing

    NASA Technical Reports Server (NTRS)

    Ortega, James M.; Henderson, Charles

    1994-01-01

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

  16. Parallel and Distributed Computing.

    DTIC Science & Technology

    1986-12-12

    program was devoted to parallel and distributed computing . Support for this part of the program was obtained from the present Army contract and a...Umesh Vazirani. A workshop on parallel and distributed computing was held from May 19 to May 23, 1986 and drew 141 participants. Keywords: Mathematical programming; Protocols; Randomized algorithms. (Author)

  17. Improving scalability with loop transformations and message aggregation in parallel object-oriented frameworks for scientific computing

    SciTech Connect

    Bassetti, F.; Davis, K.; Quinlan, D.

    1998-09-01

    Application codes reliably achieve performance far less than the advertised capabilities of existing architectures, and this problem is worsening with increasingly-parallel machines. For large-scale numerical applications, stencil operations often impose the great part of the computational cost, and the primary sources of inefficiency are the costs of message passing and poor cache utilization. This paper proposes and demonstrates optimizations for stencil and stencil-like computations for both serial and parallel environments that ameliorate these sources of inefficiency. Achieving scalability, they believe, requires both algorithm design and compile-time support. The optimizations they present are automatable because the stencil-like computations are implemented at a high level of abstraction using object-oriented parallel array class libraries. These optimizations, which are beyond the capabilities of today compilers, may be performed automatically by a preprocessor such as the one they are currently developing.

  18. Merlin - Massively parallel heterogeneous computing

    NASA Technical Reports Server (NTRS)

    Wittie, Larry; Maples, Creve

    1989-01-01

    Hardware and software for Merlin, a new kind of massively parallel computing system, are described. Eight computers are linked as a 300-MIPS prototype to develop system software for a larger Merlin network with 16 to 64 nodes, totaling 600 to 3000 MIPS. These working prototypes help refine a mapped reflective memory technique that offers a new, very general way of linking many types of computer to form supercomputers. Processors share data selectively and rapidly on a word-by-word basis. Fast firmware virtual circuits are reconfigured to match topological needs of individual application programs. Merlin's low-latency memory-sharing interfaces solve many problems in the design of high-performance computing systems. The Merlin prototypes are intended to run parallel programs for scientific applications and to determine hardware and software needs for a future Teraflops Merlin network.

  19. Visualizing Parallel Computer System Performance

    NASA Technical Reports Server (NTRS)

    Malony, Allen D.; Reed, Daniel A.

    1988-01-01

    Parallel computer systems are among the most complex of man's creations, making satisfactory performance characterization difficult. Despite this complexity, there are strong, indeed, almost irresistible, incentives to quantify parallel system performance using a single metric. The fallacy lies in succumbing to such temptations. A complete performance characterization requires not only an analysis of the system's constituent levels, it also requires both static and dynamic characterizations. Static or average behavior analysis may mask transients that dramatically alter system performance. Although the human visual system is remarkedly adept at interpreting and identifying anomalies in false color data, the importance of dynamic, visual scientific data presentation has only recently been recognized Large, complex parallel system pose equally vexing performance interpretation problems. Data from hardware and software performance monitors must be presented in ways that emphasize important events while eluding irrelevant details. Design approaches and tools for performance visualization are the subject of this paper.

  20. Parallel Computing in SCALE

    SciTech Connect

    DeHart, Mark D; Williams, Mark L; Bowman, Stephen M

    2010-01-01

    The SCALE computational architecture has remained basically the same since its inception 30 years ago, although constituent modules and capabilities have changed significantly. This SCALE concept was intended to provide a framework whereby independent codes can be linked to provide a more comprehensive capability than possible with the individual programs - allowing flexibility to address a wide variety of applications. However, the current system was designed originally for mainframe computers with a single CPU and with significantly less memory than today's personal computers. It has been recognized that the present SCALE computation system could be restructured to take advantage of modern hardware and software capabilities, while retaining many of the modular features of the present system. Preliminary work is being done to define specifications and capabilities for a more advanced computational architecture. This paper describes the state of current SCALE development activities and plans for future development. With the release of SCALE 6.1 in 2010, a new phase of evolutionary development will be available to SCALE users within the TRITON and NEWT modules. The SCALE (Standardized Computer Analyses for Licensing Evaluation) code system developed by Oak Ridge National Laboratory (ORNL) provides a comprehensive and integrated package of codes and nuclear data for a wide range of applications in criticality safety, reactor physics, shielding, isotopic depletion and decay, and sensitivity/uncertainty (S/U) analysis. Over the last three years, since the release of version 5.1 in 2006, several important new codes have been introduced within SCALE, and significant advances applied to existing codes. Many of these new features became available with the release of SCALE 6.0 in early 2009. However, beginning with SCALE 6.1, a first generation of parallel computing is being introduced. In addition to near-term improvements, a plan for longer term SCALE enhancement

  1. Massively parallel processor computer

    NASA Technical Reports Server (NTRS)

    Fung, L. W. (Inventor)

    1983-01-01

    An apparatus for processing multidimensional data with strong spatial characteristics, such as raw image data, characterized by a large number of parallel data streams in an ordered array is described. It comprises a large number (e.g., 16,384 in a 128 x 128 array) of parallel processing elements operating simultaneously and independently on single bit slices of a corresponding array of incoming data streams under control of a single set of instructions. Each of the processing elements comprises a bidirectional data bus in communication with a register for storing single bit slices together with a random access memory unit and associated circuitry, including a binary counter/shift register device, for performing logical and arithmetical computations on the bit slices, and an I/O unit for interfacing the bidirectional data bus with the data stream source. The massively parallel processor architecture enables very high speed processing of large amounts of ordered parallel data, including spatial translation by shifting or sliding of bits vertically or horizontally to neighboring processing elements.

  2. Parallel distributed computing using Python

    NASA Astrophysics Data System (ADS)

    Dalcin, Lisandro D.; Paz, Rodrigo R.; Kler, Pablo A.; Cosimo, Alejandro

    2011-09-01

    This work presents two software components aimed to relieve the costs of accessing high-performance parallel computing resources within a Python programming environment: MPI for Python and PETSc for Python. MPI for Python is a general-purpose Python package that provides bindings for the Message Passing Interface (MPI) standard using any back-end MPI implementation. Its facilities allow parallel Python programs to easily exploit multiple processors using the message passing paradigm. PETSc for Python provides access to the Portable, Extensible Toolkit for Scientific Computation (PETSc) libraries. Its facilities allow sequential and parallel Python applications to exploit state of the art algorithms and data structures readily available in PETSc for the solution of large-scale problems in science and engineering. MPI for Python and PETSc for Python are fully integrated to PETSc-FEM, an MPI and PETSc based parallel, multiphysics, finite elements code developed at CIMEC laboratory. This software infrastructure supports research activities related to simulation of fluid flows with applications ranging from the design of microfluidic devices for biochemical analysis to modeling of large-scale stream/aquifer interactions.

  3. Parallel Computational Protein Design

    PubMed Central

    Zhou, Yichao; Donald, Bruce R.; Zeng, Jianyang

    2016-01-01

    Computational structure-based protein design (CSPD) is an important problem in computational biology, which aims to design or improve a prescribed protein function based on a protein structure template. It provides a practical tool for real-world protein engineering applications. A popular CSPD method that guarantees to find the global minimum energy solution (GMEC) is to combine both dead-end elimination (DEE) and A* tree search algorithms. However, in this framework, the A* search algorithm can run in exponential time in the worst case, which may become the computation bottleneck of large-scale computational protein design process. To address this issue, we extend and add a new module to the OSPREY program that was previously developed in the Donald lab [1] to implement a GPU-based massively parallel A* algorithm for improving protein design pipeline. By exploiting the modern GPU computational framework and optimizing the computation of the heuristic function for A* search, our new program, called gOSPREY, can provide up to four orders of magnitude speedups in large protein design cases with a small memory overhead comparing to the traditional A* search algorithm implementation, while still guaranteeing the optimality. In addition, gOSPREY can be configured to run in a bounded-memory mode to tackle the problems in which the conformation space is too large and the global optimal solution cannot be computed previously. Furthermore, the GPU-based A* algorithm implemented in the gOSPREY program can be combined with the state-of-the-art rotamer pruning algorithms such as iMinDEE [2] and DEEPer [3] to also consider continuous backbone and side-chain flexibility. PMID:27914056

  4. Scientific Grid computing.

    PubMed

    Coveney, Peter V

    2005-08-15

    We introduce a definition of Grid computing which is adhered to throughout this Theme Issue. We compare the evolution of the World Wide Web with current aspirations for Grid computing and indicate areas that need further research and development before a generally usable Grid infrastructure becomes available. We discuss work that has been done in order to make scientific Grid computing a viable proposition, including the building of Grids, middleware developments, computational steering and visualization. We review science that has been enabled by contemporary computational Grids, and associated progress made through the widening availability of high performance computing.

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

    NASA Astrophysics Data System (ADS)

    Decyk, Viktor K.; Dauger, Dean E.

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

  6. Introduction to Parallel Computing

    DTIC Science & Technology

    1992-05-01

    Topology C, Ada, C++, Data-parallel FORTRAN, 2D mesh of node boards, each node FORTRAN-90 (late 1992) board has 1 application processor Devopment Tools ...parallel machines become the wave of the present, tools are increasingly needed to assist programmers in creating parallel tasks and coordinating...their activities. Linda was designed to be such a tool . Linda was designed with three important goals in mind: to be portable, efficient, and easy to use

  7. Computers in Scientific Instrumentation.

    DTIC Science & Technology

    1982-01-13

    The CPU bus Attachment. In the first applications or d 4ata are connected to the central ues parallel digital lines for data an computers to...simple function se- Mg on ae results of its previous opera- designing instruments that can provide hotios by being directly labeled for the ties. In...that the signal from the sensor is with an operating system is powerful , that might be found in appropriately pro- interpretable to give the sought- for

  8. Accelerating Scientific Computations using FPGAs

    NASA Astrophysics Data System (ADS)

    Pell, O.; Atasu, K.; Mencer, O.

    Field Programmable Gate Arrays (FPGAs) are semiconductor devices that contain a grid of programmable cells, which the user configures to implement any digital circuit of up to a few million gates. Modern FPGAs allow the user to reconfigure these circuits many times each second, making FPGAs fully programmable and general purpose. Recent FPGA technology provides sufficient resources to tackle scientific applications on large-scale parallel systems. As a case study, we implement the Fast Fourier Transform [1] in a flexible floating point implementation. We utilize A Stream Compiler [2] (ASC) which combines C++ syntax with flexible floating point support by providing a 'HWfloat' data-type. The resulting FFT can be targeted to a variety of FPGA platforms in FFTW-style, though not yet completely automatically. The resulting FFT circuit can be adapted to the particular resources available on the system. The optimal implementation of an FFT accelerator depends on the length and dimensionality of the FFT, the available FPGA area, the available hard DSP blocks, the FPGA board architecture, and the precision and range of the application [3]. Software-style object-orientated abstractions allow us to pursue an accelerated pace of development by maximizing re-use of design patterns. ASC allows a few core hardware descriptions to generate hundreds of different circuit variants to meet particular speed, area and precision goals. The key to achieving maximum acceleration of FFT computation is to match memory and compute bandwidths so that maximum use is made of computational resources. Modern FPGAs contain up to hundreds of independent SRAM banks to store intermediate results, providing ample scope for optimizing memory parallelism. At 175Mhz, one of Maxeler's Radix-4 FFT cores computes 4x as many 1024pt FFTs per second as a dual Pentium-IV Xeon machine running FFTW. Eight such parallel cores fit onto the largest FPGA in the Xilinx Virtex-4 family, providing a 32x speed-up over

  9. Parallel Architecture For Robotics Computation

    NASA Technical Reports Server (NTRS)

    Fijany, Amir; Bejczy, Antal K.

    1990-01-01

    Universal Real-Time Robotic Controller and Simulator (URRCS) is highly parallel computing architecture for control and simulation of robot motion. Result of extensive algorithmic study of different kinematic and dynamic computational problems arising in control and simulation of robot motion. Study led to development of class of efficient parallel algorithms for these problems. Represents algorithmically specialized architecture, in sense capable of exploiting common properties of this class of parallel algorithms. System with both MIMD and SIMD capabilities. Regarded as processor attached to bus of external host processor, as part of bus memory.

  10. Parallel computing in atmospheric chemistry models

    SciTech Connect

    Rotman, D.

    1996-02-01

    Studies of atmospheric chemistry are of high scientific interest, involve computations that are complex and intense, and require enormous amounts of I/O. Current supercomputer computational capabilities are limiting the studies of stratospheric and tropospheric chemistry and will certainly not be able to handle the upcoming coupled chemistry/climate models. To enable such calculations, the authors have developed a computing framework that allows computations on a wide range of computational platforms, including massively parallel machines. Because of the fast paced changes in this field, the modeling framework and scientific modules have been developed to be highly portable and efficient. Here, the authors present the important features of the framework and focus on the atmospheric chemistry module, named IMPACT, and its capabilities. Applications of IMPACT to aircraft studies will be presented.

  11. Computational electromagnetics and parallel dense matrix computations

    SciTech Connect

    Forsman, K.; Kettunen, L.; Gropp, W.; Levine, D.

    1995-06-01

    We present computational results using CORAL, a parallel, three-dimensional, nonlinear magnetostatic code based on a volume integral equation formulation. A key feature of CORAL is the ability to solve, in parallel, the large, dense systems of linear equations that are inherent in the use of integral equation methods. Using the Chameleon and PSLES libraries ensures portability and access to the latest linear algebra solution technology.

  12. Computational electromagnetics and parallel dense matrix computations

    SciTech Connect

    Forsman, K.; Kettunen, L.; Gropp, W.

    1995-12-01

    We present computational results using CORAL, a parallel, three-dimensional, nonlinear magnetostatic code based on a volume integral equation formulation. A key feature of CORAL is the ability to solve, in parallel, the large, dense systems of linear equations that are inherent in the use of integral equation methods. Using the Chameleon and PSLES libraries ensures portability and access to the latest linear algebra solution technology.

  13. The science of computing - Parallel computation

    NASA Technical Reports Server (NTRS)

    Denning, P. J.

    1985-01-01

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

  14. Parallel Tensor Compression for Large-Scale Scientific Data.

    SciTech Connect

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

    2015-10-01

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

  15. 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.

  16. High Performance Parallel Computational Nanotechnology

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

    At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to

  17. ASP: a parallel computing technology

    NASA Astrophysics Data System (ADS)

    Lea, R. M.

    1990-09-01

    ASP modules constitute the basis of a parallel computing technology platform for the rapid development of a broad range of numeric and symbolic information processing systems. Based on off-the-shelf general-purpose hardware and software modules ASP technology is intended to increase productivity in the development (and competitiveness in the marketing) of cost-effective low-MIMD/high-SIMD Massively Parallel Processor (MPPs). The paper discusses ASP module philosophy and demonstrates how ASP modules can satisfy the market algorithmic architectural and engineering requirements of such MPPs. In particular two specific ASP modules based on VLSI and WSI technologies are studied as case examples of ASP technology the latter reporting 1 TOPS/fl3 1 GOPS/W and 1 MOPS/$ as ball-park figures-of-merit of cost-effectiveness.

  18. Parallel Computing for Brain Simulation.

    PubMed

    Pastur-Romay, L A; Porto-Pazos, A B; Cedrón, F; Pazos, A

    2016-11-04

    The human brain is the most complex system in the known universe, but it is the most unknown system. It allows the human beings to possess extraordinary capacities. However, we don´t understand yet how and why most of these capacities are produced. For decades, it have been tried that the computers reproduces these capacities. On one hand, to help understanding the nervous system. On the other hand, to process the data in a more efficient way than before. It is intended to make the computers process the information like the brain does it. The important technological developments and the big multidisciplinary projects have allowed create the first simulation with a number of neurons similar to the human brain neurons number. This paper presents an update review about the main research projects that are trying of simulate and/or emulate the human brain. They employ different types of computational models using parallel computing: digital models, analog models and hybrid models. This review includes the actual applications of these works and also the future trends. We have reviewed some works that look for a step forward in Neuroscience and other ones that look for a breakthrough in Computer Science (neuromorphic hardware, machine learning techniques). We summarize the most outstanding characteristics of them and present the latest advances and future plans. In addition, this review remarks the importance of considering not only neurons: the computational models of the brain should include glial cells, given the proven importance of the astrocytes in the information processing.

  19. Trajectory optimization using parallel shooting method on parallel computer

    SciTech Connect

    Wirthman, D.J.; Park, S.Y.; Vadali, S.R.

    1995-03-01

    The efficiency of a parallel shooting method on a parallel computer for solving a variety of optimal control guidance problems is studied. Several examples are considered to demonstrate that a speedup of nearly 7 to 1 is achieved with the use of 16 processors. It is suggested that further improvements in performance can be achieved by parallelizing in the state domain. 10 refs.

  20. Parallel Pascal - An extended Pascal for parallel computers

    NASA Technical Reports Server (NTRS)

    Reeves, A. P.

    1984-01-01

    Parallel Pascal is an extended version of the conventional serial Pascal programming language which includes a convenient syntax for specifying array operations. It is upward compatible with standard Pascal and involves only a small number of carefully chosen new features. Parallel Pascal was developed to reduce the semantic gap between standard Pascal and a large range of highly parallel computers. Two important design goals of Parallel Pascal were efficiency and portability. Portability is particularly difficult to achieve since different parallel computers frequently have very different capabilities.

  1. Parallel computing in enterprise modeling.

    SciTech Connect

    Goldsby, Michael E.; Armstrong, Robert C.; Shneider, Max S.; Vanderveen, Keith; Ray, Jaideep; Heath, Zach; Allan, Benjamin A.

    2008-08-01

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

  2. Parallel Environment for Quantum Computing

    NASA Astrophysics Data System (ADS)

    Tabakin, Frank; Diaz, Bruno Julia

    2009-03-01

    To facilitate numerical study of noise and decoherence in QC algorithms,and of the efficacy of error correction schemes, we have developed a Fortran 90 quantum computer simulator with parallel processing capabilities. It permits rapid evaluation of quantum algorithms for a large number of qubits and for various ``noise'' scenarios. State vectors are distributed over many processors, to employ a large number of qubits. Parallel processing is implemented by the Message-Passing Interface protocol. A description of how to spread the wave function components over many processors, along with how to efficiently describe the action of general one- and two-qubit operators on these state vectors will be delineated.Grover's search and Shor's factoring algorithms with noise will be discussed as examples. A major feature of this work is that concurrent versions of the algorithms can be evaluated with each version subject to diverse noise effects, corresponding to solving a stochastic Schrodinger equation. The density matrix for the ensemble of such noise cases is constructed using parallel distribution methods to evaluate its associated entropy. Applications of this powerful tool is made to delineate the stability and correction of QC processes using Hamiltonian based dynamics.

  3. Exploring HPCS Languages in Scientific Computing

    SciTech Connect

    Barrett, Richard F; Alam, Sadaf R; de Almeida, Valmor F; Bernholdt, David E; Elwasif, Wael R; Kuehn, Jeffery A; Poole, Stephen W; Shet, Aniruddha G

    2008-01-01

    As computers scale up dramatically to tens and hundreds of thousands of cores, develop deeper computational and memory hierarchies, and increased heterogeneity, developers of scientific software are increasingly challenged to express complex parallel simulations effectively and efficiently. In this paper, we explore the three languages developed under the DARPA High-Productivity Computing Systems (HPCS) program to help address these concerns: Chapel, Fortress, and X10. These languages provide a variety of features not found in currently popular HPC programming environments and make it easier to express powerful computational constructs, leading to new ways of thinking about parallel programming. Though the languages and their implementations are not yet mature enough for a comprehensive evaluation, we discuss some of the important features, and provide examples of how they can be used in scientific computing. We believe that these characteristics will be important to the future of high-performance scientific computing, whether the ultimate language of choice is one of the HPCS languages or something else.

  4. An Expert Assistant for Computer Aided Parallelization

    NASA Technical Reports Server (NTRS)

    Jost, Gabriele; Chun, Robert; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit

    2004-01-01

    The prototype implementation of an expert system was developed to assist the user in the computer aided parallelization process. The system interfaces to tools for automatic parallelization and performance analysis. By fusing static program structure information and dynamic performance analysis data the expert system can help the user to filter, correlate, and interpret the data gathered by the existing tools. Sections of the code that show poor performance and require further attention are rapidly identified and suggestions for improvements are presented to the user. In this paper we describe the components of the expert system and discuss its interface to the existing tools. We present a case study to demonstrate the successful use in full scale scientific applications.

  5. 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…

  6. Accelerating Scientific Discovery Through Computation and Visualization

    PubMed Central

    Sims, James S.; Hagedorn, John G.; Ketcham, Peter M.; Satterfield, Steven G.; Griffin, Terence J.; George, William L.; Fowler, Howland A.; am Ende, Barbara A.; Hung, Howard K.; Bohn, Robert B.; Koontz, John E.; Martys, Nicos S.; Bouldin, Charles E.; Warren, James A.; Feder, David L.; Clark, Charles W.; Filla, B. James; Devaney, Judith E.

    2000-01-01

    The rate of scientific discovery can be accelerated through computation and visualization. This acceleration results from the synergy of expertise, computing tools, and hardware for enabling high-performance computation, information science, and visualization that is provided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the research scientists. In the context of this discussion, high performance refers to capabilities beyond the current state of the art in desktop computing. To be effective in this arena, a team comprising a critical mass of talent, parallel computing techniques, visualization algorithms, advanced visualization hardware, and a recurring investment is required to stay beyond the desktop capabilities. This article describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing and visualization to accelerate condensate modeling, (2) fluid flow in porous materials and in other complex geometries, (3) flows in suspensions, (4) x-ray absorption, (5) dielectric breakdown modeling, and (6) dendritic growth in alloys. PMID:27551642

  7. Accelerating Scientific Discovery Through Computation and Visualization.

    PubMed

    Sims, J S; Hagedorn, J G; Ketcham, P M; Satterfield, S G; Griffin, T J; George, W L; Fowler, H A; Am Ende, B A; Hung, H K; Bohn, R B; Koontz, J E; Martys, N S; Bouldin, C E; Warren, J A; Feder, D L; Clark, C W; Filla, B J; Devaney, J E

    2000-01-01

    The rate of scientific discovery can be accelerated through computation and visualization. This acceleration results from the synergy of expertise, computing tools, and hardware for enabling high-performance computation, information science, and visualization that is provided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the research scientists. In the context of this discussion, high performance refers to capabilities beyond the current state of the art in desktop computing. To be effective in this arena, a team comprising a critical mass of talent, parallel computing techniques, visualization algorithms, advanced visualization hardware, and a recurring investment is required to stay beyond the desktop capabilities. This article describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing and visualization to accelerate condensate modeling, (2) fluid flow in porous materials and in other complex geometries, (3) flows in suspensions, (4) x-ray absorption, (5) dielectric breakdown modeling, and (6) dendritic growth in alloys.

  8. Parallel Computing Using Web Servers and "Servlets".

    ERIC Educational Resources Information Center

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

    2000-01-01

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

  9. Broadcasting a message in a parallel computer

    DOEpatents

    Berg, Jeremy E.; Faraj, Ahmad A.

    2011-08-02

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

  10. Enabling Computational Technologies for Terascale Scientific Simulations

    SciTech Connect

    Ashby, S.F.

    2000-08-24

    We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulations on massively parallel processors (MPPs). Our research in multigrid-based linear solvers and adaptive mesh refinement enables Laboratory programs to use MPPs to explore important physical phenomena. For example, our research aids stockpile stewardship by making practical detailed 3D simulations of radiation transport. The need to solve large linear systems arises in many applications, including radiation transport, structural dynamics, combustion, and flow in porous media. These systems result from discretizations of partial differential equations on computational meshes. Our first research objective is to develop multigrid preconditioned iterative methods for such problems and to demonstrate their scalability on MPPs. Scalability describes how total computational work grows with problem size; it measures how effectively additional resources can help solve increasingly larger problems. Many factors contribute to scalability: computer architecture, parallel implementation, and choice of algorithm. Scalable algorithms have been shown to decrease simulation times by several orders of magnitude.

  11. File-access characteristics of parallel scientific workloads

    NASA Technical Reports Server (NTRS)

    Nieuwejaar, Nils; Kotz, David; Purakayastha, Apratim; Best, Michael; Ellis, Carla Schlatter

    1995-01-01

    Phenomenal improvements in the computational performance of multiprocessors have not been matched by comparable gains in I/O system performance. This imbalance has resulted in I/O becoming a significant bottleneck for many scientific applications. One key to overcoming this bottleneck is improving the performance of parallel file systems. The design of a high-performance parallel file system requires a comprehensive understanding of the expected workload. Unfortunately, until recently, no general workload studies of parallel file systems have been conducted. The goal of the CHARISMA project was to remedy this problem by characterizing the behavior of several production workloads, on different machines, at the level of individual reads and writes. The first set of results from the CHARISMA project describe the workloads observed on an Intel iPSC/860 and a Thinking Machines CM-5. This paper is intended to compare and contrast these two workloads for an understanding of their essential similarities and differences, isolating common trends and platform-dependent variances. Using this comparison, we are able to gain more insight into the general principles that should guide parallel file-system design.

  12. Scientific Computing on the Grid

    SciTech Connect

    Allen, Gabrielle; Seidel, Edward; Shalf, John

    2001-12-12

    Computer simulations are becoming increasingly important as the only means for studying and interpreting the complex processes of nature. Yet the scope and accuracy of these simulations are severely limited by available computational power, even using today's most powerful supercomputers. As we endeavor to simulate the true complexity of nature, we will require much larger scale calculations than are possible at present. Such dynamic and large scale applications will require computational grids and grids require development of new latency tolerant algorithms, and sophisticated code frameworks like Cactus to carry out more complex and high fidelity simulations with a massive degree of parallelism.

  13. 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.

  14. Implementing clips on a parallel computer

    NASA Technical Reports Server (NTRS)

    Riley, Gary

    1987-01-01

    The C language integrated production system (CLIPS) is a forward chaining rule based language to provide training and delivery for expert systems. Conceptually, rule based languages have great potential for benefiting from the inherent parallelism of the algorithms that they employ. During each cycle of execution, a knowledge base of information is compared against a set of rules to determine if any rules are applicable. Parallelism also can be employed for use with multiple cooperating expert systems. To investigate the potential benefits of using a parallel computer to speed up the comparison of facts to rules in expert systems, a parallel version of CLIPS was developed for the FLEX/32, a large grain parallel computer. The FLEX implementation takes a macroscopic approach in achieving parallelism by splitting whole sets of rules among several processors rather than by splitting the components of an individual rule among processors. The parallel CLIPS prototype demonstrates the potential advantages of integrating expert system tools with parallel computers.

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

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  16. Template based parallel checkpointing in a massively parallel computer system

    DOEpatents

    Archer, Charles Jens; Inglett, Todd Alan

    2009-01-13

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

  17. Parallel computations and control of adaptive structures

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  18. Heisenberg: Paralleling Scientific and Historical Methods

    NASA Astrophysics Data System (ADS)

    Cofield, Calla

    2007-04-01

    Werner Heisenberg is an important historical subject within the physics community partly because his actions as a human being are discussed nearly as often as his work as a physicist. But does the scientific community establish it's historical ideas with the same methods and standards as it's scientific conclusions? I interviewed Heisenberg's son, Jochen Heisenberg, a professor of physics at UNH. Despite a great amount of literature on Werner Heisenberg, only one historian has interviewed Jochen about his father and few have interviewed Werner's wife. Nature is mysterious and unpredictable, but it doesn't lie or distort like humans, and we believe it can give ``honest'' results. But are we keeping the same standards with history that we do with science? Are we holding historians to these standards and if not, is it up to scientists to not only be keepers of scientific understanding, but historical understanding as well? Shouldn't we record history by using the scientific method, by weighing the best sources of data differently than the less reliable, and are we right to be as stubborn about changing our views on history as we are about changing our views on nature?

  19. The BLAZE language - A parallel language for scientific programming

    NASA Technical Reports Server (NTRS)

    Mehrotra, Piyush; Van Rosendale, John

    1987-01-01

    A Pascal-like scientific programming language, BLAZE, is described. BLAZE contains array arithmetic, forall loops, and APL-style accumulation operators, which allow natural expression of fine grained parallelism. It also employs an applicative or functional procedure invocation mechanism, which makes it easy for compilers to extract coarse grained parallelism using machine specific program restructuring. Thus BLAZE should allow one to achieve highly parallel execution on multiprocessor architectures, while still providing the user with conceptually sequential control flow. A central goal in the design of BLAZE is portability across a broad range of parallel architectures. The multiple levels of parallelism present in BLAZE code, in principle, allow a compiler to extract the types of parallelism appropriate for the given architecture while neglecting the remainder. The features of BLAZE are described and it is shown how this language would be used in typical scientific programming.

  20. The BLAZE language: A parallel language for scientific programming

    NASA Technical Reports Server (NTRS)

    Mehrotra, P.; Vanrosendale, J.

    1985-01-01

    A Pascal-like scientific programming language, Blaze, is described. Blaze contains array arithmetic, forall loops, and APL-style accumulation operators, which allow natural expression of fine grained parallelism. It also employs an applicative or functional procedure invocation mechanism, which makes it easy for compilers to extract coarse grained parallelism using machine specific program restructuring. Thus Blaze should allow one to achieve highly parallel execution on multiprocessor architectures, while still providing the user with onceptually sequential control flow. A central goal in the design of Blaze is portability across a broad range of parallel architectures. The multiple levels of parallelism present in Blaze code, in principle, allow a compiler to extract the types of parallelism appropriate for the given architecture while neglecting the remainder. The features of Blaze are described and shows how this language would be used in typical scientific programming.

  1. Molecular dynamics on hypercube parallel computers

    NASA Astrophysics Data System (ADS)

    Smith, W.

    1991-03-01

    The implementation of molecular dynamics on parallel computers is described, with particular reference to hypercube computers. Three particular algorithms are described: replicated data (RD); systolic loop (SLS-G), and parallelised link-cells (PLC), all of which have good load balancing. The performance characteristics of each algorithm and the factors affecting their scaling properties are discussed. The article is pedagogic in intent, to introduce a novice to the main aspects of parallel computing in molecular dynamics.

  2. Parallel and Distributed Computing Combinatorial Algorithms

    DTIC Science & Technology

    1993-10-01

    FUPNDKC %2,•, PARALLEL AND DISTRIBUTED COMPUTING COMBINATORIAL ALGORITHMS 6. AUTHOR(S) 2304/DS F49620-92-J-0125 DR. LEIGHTON 7 PERFORMING ORGANIZATION NAME...on several problems involving parallel and distributed computing and combinatorial optimization. This research is reported in the numerous papers that...network decom- position. In Proceedings of the Eleventh Annual ACM Symposium on Principles of Distributed Computing , August 1992. [15] B. Awerbuch, B

  3. A Parallel Computational Fluid Dynamics Unstructured Grid Generator

    DTIC Science & Technology

    1993-12-01

    Vol 11. 953-961. Philadelphia: SIAM, 1993. Holey, J. Andrew and Oscar H. Ibarra . "Triangulation, Veronoi Diagram, and Convex Hull in k-Space on Mesh...rIdhner, Rainald, Jose Camberos, and Marshall Merriam. "Parallel Unstructured Grid Generation," in Unstructured Scientific Computation on Scalable

  4. Collectively loading an application in a parallel computer

    SciTech Connect

    Aho, Michael E.; Attinella, John E.; Gooding, Thomas M.; Miller, Samuel J.; Mundy, Michael B.

    2016-01-05

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

  5. Charon Message-Passing Toolkit for Scientific Computations

    NASA Technical Reports Server (NTRS)

    VanderWijngarrt, Rob F.; Saini, Subhash (Technical Monitor)

    1998-01-01

    The Charon toolkit for piecemeal development of high-efficiency parallel programs for scientific computing is described. The portable toolkit, callable from C and Fortran, provides flexible domain decompositions and high-level distributed constructs for easy translation of serial legacy code or design to distributed environments. Gradual tuning can subsequently be applied to obtain high performance, possibly by using explicit message passing. Charon also features general structured communications that support stencil-based computations with complex recurrences. Through the separation of partitioning and distribution, the toolkit can also be used for blocking of uni-processor code, and for debugging of parallel algorithms on serial machines. An elaborate review of recent parallelization aids is presented to highlight the need for a toolkit like Charon. Some performance results of parallelizing the NAS Parallel Benchmark SP program using Charon are given, showing good scalability. Some performance results of parallelizing the NAS Parallel Benchmark SP program using Charon are given, showing good scalability.

  6. Parallel Algorithms for Computer Vision.

    DTIC Science & Technology

    1987-01-01

    73 755 P fiu.LEL ALORITHMS FOR CO PUTER VISIO (U) /MASSACHUSETTS INST OF TECH CRMORIDGE T P00010 ET AL.JAN 8? ETL-0456 DACA7-05-C-8IIO m 7E F/0 1...regularization principles, such as edge detection, stereo , motion, surface interpolation and shape from shading. The basic members of class I are convolution...them in collabo- ration with Thinking Machines Corporation): * Parallel convolution * Zero-crossing detection * Stereo -matching * Surface reconstruction

  7. Parallel Algorithms for Computer Vision.

    DTIC Science & Technology

    1989-01-01

    demonstrated the Vision Machine system processing images and recognizing objects through the inte- gration of several visual cues. The first version of the...achievements. n 2.1 The Vision Machine The overall organization of tie Vision Machine systeliis ased. o parallel processing of tie images by independent...smoothed and made dense by exploiting known constraints within each process (for example., that disparity is smooth). This is the stage of approximation

  8. Parallel computation with the spectral element method

    SciTech Connect

    Ma, Hong

    1995-12-01

    Spectral element models for the shallow water equations and the Navier-Stokes equations have been successfully implemented on a data parallel supercomputer, the Connection Machine model CM-5. The nonstaggered grid formulations for both models are described, which are shown to be especially efficient in data parallel computing environment.

  9. Parallel Computing Strategies for Irregular Algorithms

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  10. Parallel unstructured grid generation for computational aerosciences

    NASA Technical Reports Server (NTRS)

    Shephard, Mark S.

    1993-01-01

    The objective of this research project is to develop efficient parallel automatic grid generation procedures for use in computational aerosciences. This effort is focused on a parallel version of the Finite Octree grid generator. Progress made during the first six months is reported.

  11. Massively Parallel Computing: A Sandia Perspective

    SciTech Connect

    Dosanjh, Sudip S.; Greenberg, David S.; Hendrickson, Bruce; Heroux, Michael A.; Plimpton, Steve J.; Tomkins, James L.; Womble, David E.

    1999-05-06

    The computing power available to scientists and engineers has increased dramatically in the past decade, due in part to progress in making massively parallel computing practical and available. The expectation for these machines has been great. The reality is that progress has been slower than expected. Nevertheless, massively parallel computing is beginning to realize its potential for enabling significant break-throughs in science and engineering. This paper provides a perspective on the state of the field, colored by the authors' experiences using large scale parallel machines at Sandia National Laboratories. We address trends in hardware, system software and algorithms, and we also offer our view of the forces shaping the parallel computing industry.

  12. Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges

    NASA Technical Reports Server (NTRS)

    Djomehri, Mohammad Jahed; Biswas, R.; VanderWijngaart, R.; Yarrow, M.

    2000-01-01

    This paper describes several results of parallel and distributed computing using a large scale production flow solver program. A coarse grained parallelization based on clustering of discretization grids combined with partitioning of large grids for load balancing is presented. An assessment is given of its performance on distributed and distributed-shared memory platforms using large scale scientific problems. An experiment with this solver, adapted to a Wide Area Network execution environment is presented. We also give a comparative performance assessment of computation and communication times on both the tightly and loosely-coupled machines.

  13. Fast combinatorial optimization with parallel digital computers.

    PubMed

    Kakeya, H; Okabe, Y

    2000-01-01

    This paper presents an algorithm which realizes fast search for the solutions of combinatorial optimization problems with parallel digital computers.With the standard weight matrices designed for combinatorial optimization, many iterations are required before convergence to a quasioptimal solution even when many digital processors can be used in parallel. By removing the components of the eingenvectors with eminent negative eigenvalues of the weight matrix, the proposed algorithm avoids oscillation and realizes energy reduction under synchronous discrete dynamics, which enables parallel digital computers to obtain quasi-optimal solutions with much less time than the conventional algorithm.

  14. IPython: components for interactive and parallel computing across disciplines. (Invited)

    NASA Astrophysics Data System (ADS)

    Perez, F.; Bussonnier, M.; Frederic, J. D.; Froehle, B. M.; Granger, B. E.; Ivanov, P.; Kluyver, T.; Patterson, E.; Ragan-Kelley, B.; Sailer, Z.

    2013-12-01

    Scientific computing is an inherently exploratory activity that requires constantly cycling between code, data and results, each time adjusting the computations as new insights and questions arise. To support such a workflow, good interactive environments are critical. The IPython project (http://ipython.org) provides a rich architecture for interactive computing with: 1. Terminal-based and graphical interactive consoles. 2. A web-based Notebook system with support for code, text, mathematical expressions, inline plots and other rich media. 3. Easy to use, high performance tools for parallel computing. Despite its roots in Python, the IPython architecture is designed in a language-agnostic way to facilitate interactive computing in any language. This allows users to mix Python with Julia, R, Octave, Ruby, Perl, Bash and more, as well as to develop native clients in other languages that reuse the IPython clients. In this talk, I will show how IPython supports all stages in the lifecycle of a scientific idea: 1. Individual exploration. 2. Collaborative development. 3. Production runs with parallel resources. 4. Publication. 5. Education. In particular, the IPython Notebook provides an environment for "literate computing" with a tight integration of narrative and computation (including parallel computing). These Notebooks are stored in a JSON-based document format that provides an "executable paper": notebooks can be version controlled, exported to HTML or PDF for publication, and used for teaching.

  15. Adaptive Explicitly Parallel Instruction Computing

    DTIC Science & Technology

    2000-12-16

    1993. [17] James F. Blinn. Jim Blinn’s corner: Fugue for MMX. IEEE Computer Graphics and Applications, 17(2):88– 93, March/April 1997. Makes several...processors. IEEE Transactions on Computers, C-29(4):308–316, April 1980. [22] Doug Burger and James R. Goodman. Guest editors introduction: Billion...sequencing and scheduling: A survey. Ann. Discrete Mathematics, 5:287–326, 1979. [58] C. Ebeling D. C. Green and P. Franklin . RaPiD – reconfigurable

  16. Computer-Aided Parallelizer and Optimizer

    NASA Technical Reports Server (NTRS)

    Jin, Haoqiang

    2011-01-01

    The Computer-Aided Parallelizer and Optimizer (CAPO) automates the insertion of compiler directives (see figure) to facilitate parallel processing on Shared Memory Parallel (SMP) machines. While CAPO currently is integrated seamlessly into CAPTools (developed at the University of Greenwich, now marketed as ParaWise), CAPO was independently developed at Ames Research Center as one of the components for the Legacy Code Modernization (LCM) project. The current version takes serial FORTRAN programs, performs interprocedural data dependence analysis, and generates OpenMP directives. Due to the widely supported OpenMP standard, the generated OpenMP codes have the potential to run on a wide range of SMP machines. CAPO relies on accurate interprocedural data dependence information currently provided by CAPTools. Compiler directives are generated through identification of parallel loops in the outermost level, construction of parallel regions around parallel loops and optimization of parallel regions, and insertion of directives with automatic identification of private, reduction, induction, and shared variables. Attempts also have been made to identify potential pipeline parallelism (implemented with point-to-point synchronization). Although directives are generated automatically, user interaction with the tool is still important for producing good parallel codes. A comprehensive graphical user interface is included for users to interact with the parallelization process.

  17. Graph Partitioning Models for Parallel Computing

    SciTech Connect

    Hendrickson, B.; Kolda, T.G.

    1999-03-02

    Calculations can naturally be described as graphs in which vertices represent computation and edges reflect data dependencies. By partitioning the vertices of a graph, the calculation can be divided among processors of a parallel computer. However, the standard methodology for graph partitioning minimizes the wrong metric and lacks expressibility. We survey several recently proposed alternatives and discuss their relative merits.

  18. Fast Parallel Computation Of Manipulator Inverse Dynamics

    NASA Technical Reports Server (NTRS)

    Fijany, Amir; Bejczy, Antal K.

    1991-01-01

    Method for fast parallel computation of inverse dynamics problem, essential for real-time dynamic control and simulation of robot manipulators, undergoing development. Enables exploitation of high degree of parallelism and, achievement of significant computational efficiency, while minimizing various communication and synchronization overheads as well as complexity of required computer architecture. Universal real-time robotic controller and simulator (URRCS) consists of internal host processor and several SIMD processors with ring topology. Architecture modular and expandable: more SIMD processors added to match size of problem. Operate asynchronously and in MIMD fashion.

  19. Locating hardware faults in a parallel computer

    DOEpatents

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

    2010-04-13

    Locating hardware faults in a parallel computer, including defining within a tree network of the parallel computer two or more sets of non-overlapping test levels of compute nodes of the network that together include all the data communications links of the network, each non-overlapping test level comprising two or more adjacent tiers of the tree; defining test cells within each non-overlapping test level, each test cell comprising a subtree of the tree including a subtree root compute node and all descendant compute nodes of the subtree root compute node within a non-overlapping test level; performing, separately on each set of non-overlapping test levels, an uplink test on all test cells in a set of non-overlapping test levels; and performing, separately from the uplink tests and separately on each set of non-overlapping test levels, a downlink test on all test cells in a set of non-overlapping test levels.

  20. Internode data communications in a parallel computer

    DOEpatents

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

    2014-02-11

    Internode data communications in a parallel computer that includes compute nodes that each include main memory and a messaging unit, the messaging unit including computer memory and coupling compute nodes for data communications, in which, for each compute node at compute node boot time: a messaging unit allocates, in the messaging unit's computer memory, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; receives, prior to initialization of a particular process on the compute node, a data communications message intended for the particular process; and stores the data communications message in the message buffer associated with the particular process. Upon initialization of the particular process, the process establishes a messaging buffer in main memory of the compute node and copies the data communications message from the message buffer of the messaging unit into the message buffer of main memory.

  1. Internode data communications in a parallel computer

    DOEpatents

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

    2013-09-03

    Internode data communications in a parallel computer that includes compute nodes that each include main memory and a messaging unit, the messaging unit including computer memory and coupling compute nodes for data communications, in which, for each compute node at compute node boot time: a messaging unit allocates, in the messaging unit's computer memory, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; receives, prior to initialization of a particular process on the compute node, a data communications message intended for the particular process; and stores the data communications message in the message buffer associated with the particular process. Upon initialization of the particular process, the process establishes a messaging buffer in main memory of the compute node and copies the data communications message from the message buffer of the messaging unit into the message buffer of main memory.

  2. Link failure detection in a parallel computer

    DOEpatents

    Archer, Charles J.; Blocksome, Michael A.; Megerian, Mark G.; Smith, Brian E.

    2010-11-09

    Methods, apparatus, and products are disclosed for link failure detection in a parallel computer including compute nodes connected in a rectangular mesh network, each pair of adjacent compute nodes in the rectangular mesh network connected together using a pair of links, that includes: assigning each compute node to either a first group or a second group such that adjacent compute nodes in the rectangular mesh network are assigned to different groups; sending, by each of the compute nodes assigned to the first group, a first test message to each adjacent compute node assigned to the second group; determining, by each of the compute nodes assigned to the second group, whether the first test message was received from each adjacent compute node assigned to the first group; and notifying a user, by each of the compute nodes assigned to the second group, whether the first test message was received.

  3. Fast Parallel Computation Of Multibody Dynamics

    NASA Technical Reports Server (NTRS)

    Fijany, Amir; Kwan, Gregory L.; Bagherzadeh, Nader

    1996-01-01

    Constraint-force algorithm fast, efficient, parallel-computation algorithm for solving forward dynamics problem of multibody system like robot arm or vehicle. Solves problem in minimum time proportional to log(N) by use of optimal number of processors proportional to N, where N is number of dynamical degrees of freedom: in this sense, constraint-force algorithm both time-optimal and processor-optimal parallel-processing algorithm.

  4. Parallel computer methods for eigenvalue extraction

    NASA Technical Reports Server (NTRS)

    Akl, Fred

    1988-01-01

    A new numerical algorithm for the solution of large-order eigenproblems typically encountered in linear elastic finite element systems is presented. The architecture of parallel processing is used in the algorithm to achieve increased speed and efficiency of calculations. The algorithm is based on the frontal technique for the solution of linear simultaneous equations and the modified subspace eigenanalysis method for the solution of the eigenproblem. The advantages of this new algorithm in parallel computer architecture are discussed.

  5. Toward a science of parallel computation

    SciTech Connect

    Worlton, W.J.

    1986-01-01

    The evolution of parallel processing over the past several decades can be viewed as the development of a new scientific discipline. Parallel processing has been, and is, undergoing the same evolutionary stages that are common to the development of scientific disciplines in general: exploration, focusing, and maturity. That parallel processing is not yet a science can readily be appreciated by its lack of some of the characteristics typical of mature sciences, such as prescriptive terminology, comprehensive taxonomies, and authoritative fundamental principles. A great deal of outstanding work has been done and the field is experiencing the beginnings of its ''focusing'' phase, i.e., support is being concentrated in a set of the more promising approaches selected from among the larger set of exploratory projects. However, the possible set of parallel-processing concepts is so extensive that exploratory work will probably continue for one or two more decades. In the meantime, the growing maturity of the field will be reflected in the increasing clarity and precision of the terminology, the development of systematic classification of the domain of discourse, the development of basic principles, and the growing number of commercial products that are the outcome of the research and development projects on which support is being focused. In this paper we develop some generalizations of taxonomies and use basic principles to draw conclusions about the extensibility of parallel processor architectures. 7 refs., 5 figs., 2 tabs.

  6. Parallel processing for computer vision and display

    SciTech Connect

    Dew, P.M. . Dept. of Computer Studies); Earnshaw, R.A. ); Heywood, T.R. )

    1989-01-01

    The widespread availability of high performance computers has led to an increased awareness of the importance of visualization techniques particularly in engineering and science. However, many visualization tasks involve processing large amounts of data or manipulating complex computer models of 3D objects. For example, in the field of computer aided engineering it is often necessary to display an edit solid object (see Plate 1) which can take many minutes even on the fastest serial processors. Another example of a computationally intensive problem, this time from computer vision, is the recognition of objects in a 3D scene from a stereo image pair. To perform visualization tasks of this type in real and reasonable time it is necessary to exploit the advances in parallel processing that have taken place over the last decade. This book uniquely provides a collection of papers from leading visualization researchers with a common interest in the application and exploitation of parallel processing techniques.

  7. Wing-Body Aeroelasticity on Parallel Computers

    NASA Technical Reports Server (NTRS)

    Guruswamy, Guru P.; Byun, Chansup

    1996-01-01

    This article presents a procedure for computing the aeroelasticity of wing-body configurations on multiple-instruction, multiple-data parallel computers. In this procedure, fluids are modeled using Euler equations discretized by a finite difference method, and structures are modeled using finite element equations. The procedure is designed in such a way that each discipline can be developed and maintained independently by using a domain decomposition approach. A parallel integration scheme is used to compute aeroelastic responses by solving the coupled fluid and structural equations concurrently while keeping modularity of each discipline. The present procedure is validated by computing the aeroelastic response of a wing and comparing with experiment. Aeroelastic computations are illustrated for a high speed civil transport type wing-body configuration.

  8. Interfacing Computer Aided Parallelization and Performance Analysis

    NASA Technical Reports Server (NTRS)

    Jost, Gabriele; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit; Biegel, Bryan A. (Technical Monitor)

    2003-01-01

    When porting sequential applications to parallel computer architectures, the program developer will typically go through several cycles of source code optimization and performance analysis. We have started a project to develop an environment where the user can jointly navigate through program structure and performance data information in order to make efficient optimization decisions. In a prototype implementation we have interfaced the CAPO computer aided parallelization tool with the Paraver performance analysis tool. We describe both tools and their interface and give an example for how the interface helps within the program development cycle of a benchmark code.

  9. Charon Message-Passing Toolkit for Scientific Computations

    NASA Technical Reports Server (NTRS)

    VanderWijngaart, Rob F.; Saini, Subhash (Technical Monitor)

    1998-01-01

    The Charon toolkit for piecemeal development of high-efficiency parallel programs for scientific computing is described. The portable toolkit, callable from C and Fortran, provides flexible domain decompositions and high-level distributed constructs for easy translation of serial legacy code or design to distributed environments. Gradual tuning can subsequently be applied to obtain high performance, possibly by using explicit message passing. Charon also features general structured communications that support stencil-based computations with complex recurrences. Through the separation of partitioning and distribution, the toolkit can also be used for blocking of uni-processor code, and for debugging of parallel algorithms on serial machines. An elaborate review of recent parallelization aids is presented to highlight the need for a toolkit like Charon. Some performance results of parallelizing the NAS Parallel Benchmark SP program using Charon are given, showing good scalability.

  10. Highly parallel computer architecture for robotic computation

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

    In a computer having a large number of single instruction multiple data (SIMD) processors, each of the SIMD processors has two sets of three individual processor elements controlled by a master control unit and interconnected among a plurality of register file units where data is stored. The register files input and output data in synchronism with a minor cycle clock under control of two slave control units controlling the register file units connected to respective ones of the two sets of processor elements. Depending upon which ones of the register file units are enabled to store or transmit data during a particular minor clock cycle, the processor elements within an SIMD processor are connected in rings or in pipeline arrays, and may exchange data with the internal bus or with neighboring SIMD processors through interface units controlled by respective ones of the two slave control units.

  11. Tpetra, and the use of generic programming in scientific computing

    SciTech Connect

    Baker, Christopher G; Heroux, Dr. Michael A

    2012-01-01

    We present Tpetra, a Trilinos package for parallel linear algebra primitives implementing the Petra object model. We describe Tpetra s design, based on generic programming via C++ templated types and template metaprogramming. We discuss some benefits of this approach in the context of scientific computing, with illustrations consisting of code and notable empirical results.

  12. Impact of Parallel Computing on Large Scale Aeroelastic Computations

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    Aeroelasticity is computationally one of the most intensive fields in aerospace engineering. Though over the last three decades the computational speed of supercomputers have substantially increased, they are still inadequate for large scale aeroelastic computations using high fidelity flow and structural equations. In addition to reaching a saturation in computational speed because of changes in economics, computer manufactures are stopping the manufacturing of mainframe type supercomputers. This has led computational aeroelasticians to face the gigantic task of finding alternate approaches for fulfilling their needs. The alternate path to over come speed and availability limitations of mainframe type supercomputers is to use parallel computers. During this decade several different architectures have evolved. In FY92 the US Government started the High Performance Computing and Communication (HPCC) program. As a participant in this program NASA developed several parallel computational tools for aeroelastic applications. This talk describes the impact of those application tools on high fidelity based multidisciplinary analysis.

  13. Parallel Object-Oriented Computation Applied to a Finite Element Problem

    NASA Technical Reports Server (NTRS)

    Weissman, Jon B.; Grimshaw, Andrew S.; Ferraro, Robert

    1993-01-01

    The conventional wisdom in the scientific computing community is that the best way to solve large-scale numerically intensive scientific problems on today's parallel MIMD computers is to use Fortran or C programmed in a data-parallel style using low-level message-passing primitives. This approach inevitably leads to nonportable codes, extensive development time, and restricts parallel programming to the domain of the expert programmer. We believe that these problems are not inherent to parallel computing but are the result of the tools used. We will show that comparable performance can be achieved with little effort if better tools that present higher level abstractions are used.

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

    DOEpatents

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

    2014-02-11

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

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

    DOEpatents

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

    2014-08-12

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

  16. Computing association probabilities using parallel Boltzmann machines.

    PubMed

    Iltis, R A; Ting, P Y

    1993-01-01

    A new computational method is presented for solving the data association problem using parallel Boltzmann machines. It is shown that the association probabilities can be computed with arbitrarily small errors if a sufficient number of parallel Boltzmann machines are available. The probability beta(i)(j) that the i th measurement emanated from the jth target can be obtained simply by observing the relative frequency with which neuron v(i,j) in a two-dimensional network is on throughout the layers. Some simple tracking examples comparing the performance of the Boltzmann algorithm to the exact data association solution and with the performance of an alternative parallel method using the Hopfield neural network are also presented.

  17. FastQuery: A Parallel Indexing System for Scientific Data

    SciTech Connect

    Chou, Jerry; Wu, Kesheng; Prabhat,

    2011-07-29

    Modern scientific datasets present numerous data management and analysis challenges. State-of-the- art index and query technologies such as FastBit can significantly improve accesses to these datasets by augmenting the user data with indexes and other secondary information. However, a challenge is that the indexes assume the relational data model but the scientific data generally follows the array data model. To match the two data models, we design a generic mapping mechanism and implement an efficient input and output interface for reading and writing the data and their corresponding indexes. To take advantage of the emerging many-core architectures, we also develop a parallel strategy for indexing using threading technology. This approach complements our on-going MPI-based parallelization efforts. We demonstrate the flexibility of our software by applying it to two of the most commonly used scientific data formats, HDF5 and NetCDF. We present two case studies using data from a particle accelerator model and a global climate model. We also conducted a detailed performance study using these scientific datasets. The results show that FastQuery speeds up the query time by a factor of 2.5x to 50x, and it reduces the indexing time by a factor of 16 on 24 cores.

  18. Unsteady flow simulation on a parallel computer

    NASA Astrophysics Data System (ADS)

    Faden, M.; Pokorny, S.; Engel, K.

    For the simulation of the flow through compressor stages, an interactive flow simulation system is set up on an MIMD-type parallel computer. An explicit scheme is used in order to resolve the time-dependent interaction between the blades. The 2D Navier-Stokes equations are transformed into their general moving coordinates. The parallelization of the solver is based on the idea of domain decomposition. Results are presented for a problem of fixed size (4096 grid nodes for the Hakkinen case).

  19. Scientific Computation of Optimal Statistical Estimators

    DTIC Science & Technology

    2015-07-13

    AFRL-AFOSR-VA-TR-2015-0276 Scientific Computation of Optimal Statistical Estimators Houman Owhadi CALIFORNIA INSTITUTE OF TECHNOLOGY 1200 E...CALIFORNIA BLDV PASADENA, CA 91125 07/13/2015 Final Report DISTRIBUTION A: Distribution approved for public release. AF Office Of Scientific Research (AFOSR...From - To) 8/1/12 - 7/31/15 4. TITLE AND SUBTITLE Scientific Computation of Optimal Statistical Estimators 5a. CONTRACT NUMBER FA9550-12-1-0389 5b

  20. Intranode data communications in a parallel computer

    DOEpatents

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

    2013-07-23

    Intranode data communications in a parallel computer that includes compute nodes configured to execute processes, where the data communications include: allocating, upon initialization of a first process of a compute node, a region of shared memory; establishing, by the first process, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; sending, to a second process on the same compute node, a data communications message without determining whether the second process has been initialized, including storing the data communications message in the message buffer of the second process; and upon initialization of the second process: retrieving, by the second process, a pointer to the second process's message buffer; and retrieving, by the second process from the second process's message buffer in dependence upon the pointer, the data communications message sent by the first process.

  1. Intranode data communications in a parallel computer

    DOEpatents

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

    2014-01-07

    Intranode data communications in a parallel computer that includes compute nodes configured to execute processes, where the data communications include: allocating, upon initialization of a first process of a computer node, a region of shared memory; establishing, by the first process, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; sending, to a second process on the same compute node, a data communications message without determining whether the second process has been initialized, including storing the data communications message in the message buffer of the second process; and upon initialization of the second process: retrieving, by the second process, a pointer to the second process's message buffer; and retrieving, by the second process from the second process's message buffer in dependence upon the pointer, the data communications message sent by the first process.

  2. Libraries and Development Environments for Monte Carlo Simulations of Lattice Gauge Theories on Parallel Computers

    NASA Astrophysics Data System (ADS)

    Decker, K. M.; Jayewardena, C.; Rehmann, R.

    We describe the library lgtlib, and lgttool, the corresponding development environment for Monte Carlo simulations of lattice gauge theory on multiprocessor vector computers with shared memory. We explain why distributed memory parallel processor (DMPP) architectures are particularly appealing for compute-intensive scientific applications, and introduce the design of a general application and program development environment system for scientific applications on DMPP architectures.

  3. Synchronizing compute node time bases in a parallel computer

    DOEpatents

    Chen, Dong; Faraj, Daniel A; Gooding, Thomas M; Heidelberger, Philip

    2014-12-30

    Synchronizing time bases in a parallel computer that includes compute nodes organized for data communications in a tree network, where one compute node is designated as a root, and, for each compute node: calculating data transmission latency from the root to the compute node; configuring a thread as a pulse waiter; initializing a wakeup unit; and performing a local barrier operation; upon each node completing the local barrier operation, entering, by all compute nodes, a global barrier operation; upon all nodes entering the global barrier operation, sending, to all the compute nodes, a pulse signal; and for each compute node upon receiving the pulse signal: waking, by the wakeup unit, the pulse waiter; setting a time base for the compute node equal to the data transmission latency between the root node and the compute node; and exiting the global barrier operation.

  4. Synchronizing compute node time bases in a parallel computer

    DOEpatents

    Chen, Dong; Faraj, Daniel A; Gooding, Thomas M; Heidelberger, Philip

    2015-01-27

    Synchronizing time bases in a parallel computer that includes compute nodes organized for data communications in a tree network, where one compute node is designated as a root, and, for each compute node: calculating data transmission latency from the root to the compute node; configuring a thread as a pulse waiter; initializing a wakeup unit; and performing a local barrier operation; upon each node completing the local barrier operation, entering, by all compute nodes, a global barrier operation; upon all nodes entering the global barrier operation, sending, to all the compute nodes, a pulse signal; and for each compute node upon receiving the pulse signal: waking, by the wakeup unit, the pulse waiter; setting a time base for the compute node equal to the data transmission latency between the root node and the compute node; and exiting the global barrier operation.

  5. Opportunities in computational mechanics: Advances in parallel computing

    SciTech Connect

    Lesar, R.A.

    1999-02-01

    In this paper, the authors will discuss recent advances in computing power and the prospects for using these new capabilities for studying plasticity and failure. They will first review the new capabilities made available with parallel computing. They will discuss how these machines perform and how well their architecture might work on materials issues. Finally, they will give some estimates on the size of problems possible using these computers.

  6. Parallel Computation of the Regional Ocean Modeling System (ROMS)

    SciTech Connect

    Wang, P; Song, Y T; Chao, Y; Zhang, H

    2005-04-05

    The Regional Ocean Modeling System (ROMS) is a regional ocean general circulation modeling system solving the free surface, hydrostatic, primitive equations over varying topography. It is free software distributed world-wide for studying both complex coastal ocean problems and the basin-to-global scale ocean circulation. The original ROMS code could only be run on shared-memory systems. With the increasing need to simulate larger model domains with finer resolutions and on a variety of computer platforms, there is a need in the ocean-modeling community to have a ROMS code that can be run on any parallel computer ranging from 10 to hundreds of processors. Recently, we have explored parallelization for ROMS using the MPI programming model. In this paper, an efficient parallelization strategy for such a large-scale scientific software package, based on an existing shared-memory computing model, is presented. In addition, scientific applications and data-performance issues on a couple of SGI systems, including Columbia, the world's third-fastest supercomputer, are discussed.

  7. A design methodology for portable software on parallel computers

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  8. Efficient Parallel Engineering Computing on Linux Workstations

    NASA Technical Reports Server (NTRS)

    Lou, John Z.

    2010-01-01

    A C software module has been developed that creates lightweight processes (LWPs) dynamically to achieve parallel computing performance in a variety of engineering simulation and analysis applications to support NASA and DoD project tasks. The required interface between the module and the application it supports is simple, minimal and almost completely transparent to the user applications, and it can achieve nearly ideal computing speed-up on multi-CPU engineering workstations of all operating system platforms. The module can be integrated into an existing application (C, C++, Fortran and others) either as part of a compiled module or as a dynamically linked library (DLL).

  9. Seismic imaging on massively parallel computers

    SciTech Connect

    Ober, C.C.; Oldfield, R.A.; Womble, D.E.; Mosher, C.C.

    1997-07-01

    A key to reducing the risks and costs associated with oil and gas exploration is the fast, accurate imaging of complex geologies, such as salt domes in the Gulf of Mexico and overthrust regions in US onshore regions. Pre-stack depth migration generally yields the most accurate images, and one approach to this is to solve the scalar-wave equation using finite differences. Current industry computational capabilities are insufficient for the application of finite-difference, 3-D, prestack, depth-migration algorithms. High performance computers and state-of-the-art algorithms and software are required to meet this need. As part of an ongoing ACTI project funded by the US Department of Energy, the authors have developed a finite-difference, 3-D prestack, depth-migration code for massively parallel computer systems. The goal of this work is to demonstrate that massively parallel computers (thousands of processors) can be used efficiently for seismic imaging, and that sufficient computing power exists (or soon will exist) to make finite-difference, prestack, depth migration practical for oil and gas exploration.

  10. Parallel architectures for computing cyclic convolutions

    NASA Technical Reports Server (NTRS)

    Yeh, C.-S.; Reed, I. S.; Truong, T. K.

    1983-01-01

    In the paper two parallel architectural structures are developed to compute one-dimensional cyclic convolutions. The first structure is based on the Chinese remainder theorem and Kung's pipelined array. The second structure is a direct mapping from the mathematical definition of a cyclic convolution to a computational architecture. To compute a d-point cyclic convolution the first structure needs d/2 inner product cells, while the second structure and Kung's linear array require d cells. However, to compute a cyclic convolution, the second structure requires less time than both the first structure and Kung's linear array. Another application of the second structure is to multiply a Toeplitz matrix by a vector. A table is listed to compare these two structures and Kung's linear array. Both structures are simple and regular and are therefore suitable for VLSI implementation.

  11. Scientific computing environment for the 1980s

    NASA Technical Reports Server (NTRS)

    Bailey, F. R.

    1986-01-01

    An emerging scientific computing environment in which computers are used not only to solve large-scale models, but are also integrated into the daily activities of scientists and engineers, is discussed. The requirements of the scientific user in this environment are reviewed, and the hardware environment is described, including supercomputers, work stations, mass storage, and communications. Significant increases in memory capacity to keep pace with performance increases, the introduction of powerful graphics displays into the work station, and networking to integrate many computers are stressed. The emerging system software environment is considered, including the operating systems, communications software, and languages. New scientific user tools and utilities that will become available are described.

  12. Parallelized reliability estimation of reconfigurable computer networks

    NASA Technical Reports Server (NTRS)

    Nicol, David M.; Das, Subhendu; Palumbo, Dan

    1990-01-01

    A parallelized system, ASSURE, for computing the reliability of embedded avionics flight control systems which are able to reconfigure themselves in the event of failure is described. ASSURE accepts a grammar that describes a reliability semi-Markov state-space. From this it creates a parallel program that simultaneously generates and analyzes the state-space, placing upper and lower bounds on the probability of system failure. ASSURE is implemented on a 32-node Intel iPSC/860, and has achieved high processor efficiencies on real problems. Through a combination of improved algorithms, exploitation of parallelism, and use of an advanced microprocessor architecture, ASSURE has reduced the execution time on substantial problems by a factor of one thousand over previous workstation implementations. Furthermore, ASSURE's parallel execution rate on the iPSC/860 is an order of magnitude faster than its serial execution rate on a Cray-2 supercomputer. While dynamic load balancing is necessary for ASSURE's good performance, it is needed only infrequently; the particular method of load balancing used does not substantially affect performance.

  13. Parallel Computational Environment for Substructure Optimization

    NASA Technical Reports Server (NTRS)

    Gendy, Atef S.; Patnaik, Surya N.; Hopkins, Dale A.; Berke, Laszlo

    1995-01-01

    Design optimization of large structural systems can be attempted through a substructure strategy when convergence difficulties are encountered. When this strategy is used, the large structure is divided into several smaller substructures and a subproblem is defined for each substructure. The solution of the large optimization problem can be obtained iteratively through repeated solutions of the modest subproblems. Substructure strategies, in sequential as well as in parallel computational modes on a Cray YMP multiprocessor computer, have been incorporated in the optimization test bed CometBoards. CometBoards is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for Design of Structures. Three issues, intensive computation, convergence of the iterative process, and analytically superior optimum, were addressed in the implementation of substructure optimization into CometBoards. Coupling between subproblems as well as local and global constraint grouping are essential for convergence of the iterative process. The substructure strategy can produce an analytically superior optimum different from what can be obtained by regular optimization. For the problems solved, substructure optimization in a parallel computational mode made effective use of all assigned processors.

  14. Dynamic file-access characteristics of a production parallel scientific workload

    NASA Technical Reports Server (NTRS)

    Kotz, David; Nieuwejaar, Nils

    1994-01-01

    Multiprocessors have permitted astounding increases in computational performance, but many cannot meet the intense I/O requirements of some scientific applications. An important component of any solution to this I/O bottleneck is a parallel file system that can provide high-bandwidth access to tremendous amounts of data in parallel to hundreds or thousands of processors. Most successful systems are based on a solid understanding of the expected workload, but thus far there have been no comprehensive workload characterizations of multiprocessor file systems. This paper presents the results of a three week tracing study in which all file-related activity on a massively parallel computer was recorded. Our instrumentation differs from previous efforts in that it collects information about every I/O request and about the mix of jobs running in a production environment. We also present the results of a trace-driven caching simulation and recommendations for designers of multiprocessor file systems.

  15. An improved spectral graph partitioning algorithm for mapping parallel computations

    SciTech Connect

    Hendrickson, B.; Leland, R.

    1992-09-01

    Efficient use of a distributed memory parallel computer requires that the computational load be balanced across processors in a way that minimizes interprocessor communication. We present a new domain mapping algorithm that extends recent work in which ideas from spectral graph theory have been applied to this problem. Our generalization of spectral graph bisection involves a novel use of multiple eigenvectors to allow for division of a computation into four or eight parts at each stage of a recursive decomposition. The resulting method is suitable for scientific computations like irregular finite elements or differences performed on hypercube or mesh architecture machines. Experimental results confirm that the new method provides better decompositions arrived at more economically and robustly than with previous spectral methods. We have also improved upon the known spectral lower bound for graph bisection.

  16. Computational chaos in massively parallel neural networks

    NASA Technical Reports Server (NTRS)

    Barhen, Jacob; Gulati, Sandeep

    1989-01-01

    A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.

  17. Electromagnetic physics models for parallel computing architectures

    SciTech Connect

    Amadio, G.; Ananya, A.; Apostolakis, J.; Aurora, A.; Bandieramonte, M.; Bhattacharyya, A.; Bianchini, C.; Brun, R.; Canal, P.; Carminati, F.; Duhem, L.; Elvira, D.; Gheata, A.; Gheata, M.; Goulas, I.; Iope, R.; Jun, S. Y.; Lima, G.; Mohanty, A.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.; Zhang, Y.

    2016-11-21

    The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.

  18. Computation and parallel implementation for early vision

    NASA Technical Reports Server (NTRS)

    Gualtieri, J. Anthony

    1990-01-01

    The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.

  19. Electromagnetic physics models for parallel computing architectures

    DOE PAGES

    Amadio, G.; Ananya, A.; Apostolakis, J.; ...

    2016-11-21

    The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part ofmore » the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.« less

  20. Electromagnetic Physics Models for Parallel Computing Architectures

    NASA Astrophysics Data System (ADS)

    Amadio, G.; Ananya, A.; Apostolakis, J.; Aurora, A.; Bandieramonte, M.; Bhattacharyya, A.; Bianchini, C.; Brun, R.; Canal, P.; Carminati, F.; Duhem, L.; Elvira, D.; Gheata, A.; Gheata, M.; Goulas, I.; Iope, R.; Jun, S. Y.; Lima, G.; Mohanty, A.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.; Zhang, Y.

    2016-10-01

    The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Results of preliminary performance evaluation and physics validation are presented as well.

  1. Parallel computing techniques for rotorcraft aerodynamics

    NASA Astrophysics Data System (ADS)

    Ekici, Kivanc

    The modification of unsteady three-dimensional Navier-Stokes codes for application on massively parallel and distributed computing environments is investigated. The Euler/Navier-Stokes code TURNS (Transonic Unsteady Rotor Navier-Stokes) was chosen as a test bed because of its wide use by universities and industry. For the efficient implementation of TURNS on parallel computing systems, two algorithmic changes are developed. First, main modifications to the implicit operator, Lower-Upper Symmetric Gauss Seidel (LU-SGS) originally used in TURNS, is performed. Second, application of an inexact Newton method, coupled with a Krylov subspace iterative method (Newton-Krylov method) is carried out. Both techniques have been tried previously for the Euler equations mode of the code. In this work, we have extended the methods to the Navier-Stokes mode. Several new implicit operators were tried because of convergence problems of traditional operators with the high cell aspect ratio (CAR) grids needed for viscous calculations on structured grids. Promising results for both Euler and Navier-Stokes cases are presented for these operators. For the efficient implementation of Newton-Krylov methods to the Navier-Stokes mode of TURNS, efficient preconditioners must be used. The parallel implicit operators used in the previous step are employed as preconditioners and the results are compared. The Message Passing Interface (MPI) protocol has been used because of its portability to various parallel architectures. It should be noted that the proposed methodology is general and can be applied to several other CFD codes (e.g. OVERFLOW).

  2. Parallel algorithm for computing points on a computation front hyperplane

    NASA Astrophysics Data System (ADS)

    Krasnov, M. M.

    2015-01-01

    A parallel algorithm for computing points on a computation front hyperplane is described. This task arises in the computation of a quantity defined on a multidimensional rectangular domain. Three-dimensional domains are usually discussed, but the material is given in the general form when the number of measurements is at least two. When the values of a quantity at different points are internally independent (which is frequently the case), the corresponding computations are independent as well and can be performed in parallel. However, if there are internal dependences (as, for example, in the Gauss-Seidel method for systems of linear equations), then the order of scanning points of the domain is an important issue. A conventional approach in this case is to form a computation front hyperplane (a usual plane in the three-dimensional case and a line in the two-dimensional case) that moves linearly across the domain at a certain angle. At every step in the course of motion of this hyperplane, its intersection points with the domain can be treated independently and, hence, in parallel, but the steps themselves are executed sequentially. At different steps, the intersection of the hyperplane with the entire domain can have a rather complex geometry and the search for all points of the domain lying on the hyperplane at a given step is a nontrivial problem. This problem (i.e., the computation of the coordinates of points lying in the intersection of the domain with the hyperplane at a given step in the course of hyperplane motion) is addressed below. The computations over the points of the hyperplane can be executed in parallel.

  3. Hypercluster - Parallel processing for computational mechanics

    NASA Technical Reports Server (NTRS)

    Blech, Richard A.

    1988-01-01

    An account is given of the development status, performance capabilities and implications for further development of NASA-Lewis' testbed 'hypercluster' parallel computer network, in which multiple processors communicate through a shared memory. Processors have local as well as shared memory; the hypercluster is expanded in the same manner as the hypercube, with processor clusters replacing the normal single processor node. The NASA-Lewis machine has three nodes with a vector personality and one node with a scalar personality. Each of the vector nodes uses four board-level vector processors, while the scalar node uses four general-purpose microcomputer boards.

  4. A Component Architecture for High-Performance Scientific Computing

    SciTech Connect

    Bernholdt, D E; Allan, B A; Armstrong, R; Bertrand, F; Chiu, K; Dahlgren, T L; Damevski, K; Elwasif, W R; Epperly, T W; Govindaraju, M; Katz, D S; Kohl, J A; Krishnan, M; Kumfert, G; Larson, J W; Lefantzi, S; Lewis, M J; Malony, A D; McInnes, L C; Nieplocha, J; Norris, B; Parker, S G; Ray, J; Shende, S; Windus, T L; Zhou, S

    2004-12-14

    The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and to move toward a plug-and-play environment for high-performance computing. In the scientific computing context, component models also promote collaboration using independently developed software, thereby allowing particular individuals or groups to focus on the aspects of greatest interest to them. The CCA supports parallel and distributed computing as well as local high-performance connections between components in a language-independent manner. The design places minimal requirements on components and thus facilitates the integration of existing code into the CCA environment. The CCA model imposes minimal overhead to minimize the impact on application performance. The focus on high performance distinguishes the CCA from most other component models. The CCA is being applied within an increasing range of disciplines, including combustion research, global climate simulation, and computational chemistry.

  5. A Component Architecture for High-Performance Scientific Computing

    SciTech Connect

    Bernholdt, David E; Allan, Benjamin A; Armstrong, Robert C; Bertrand, Felipe; Chiu, Kenneth; Dahlgren, Tamara L; Damevski, Kostadin; Elwasif, Wael R; Epperly, Thomas G; Govindaraju, Madhusudhan; Katz, Daniel S; Kohl, James A; Krishnan, Manoj Kumar; Kumfert, Gary K; Larson, J Walter; Lefantzi, Sophia; Lewis, Michael J; Malony, Allen D; McInnes, Lois C; Nieplocha, Jarek; Norris, Boyana; Parker, Steven G; Ray, Jaideep; Shende, Sameer; Windus, Theresa L; Zhou, Shujia

    2006-07-03

    The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and to move toward a plug-and-play environment for high-performance computing. In the scientific computing context, component models also promote collaboration using independently developed software, thereby allowing particular individuals or groups to focus on the aspects of greatest interest to them. The CCA supports parallel and distributed computing as well as local high-performance connections between components in a language-independent manner. The design places minimal requirements on components and thus facilitates the integration of existing code into the CCA environment. The CCA model imposes minimal overhead to minimize the impact on application performance. The focus on high performance distinguishes the CCA from most other component models. The CCA is being applied within an increasing range of disciplines, including combustion research, global climate simulation, and computational chemistry.

  6. Optimized data communications in a parallel computer

    SciTech Connect

    Faraj, Daniel A.

    2014-08-19

    A parallel computer includes nodes that include a network adapter that couples the node in a point-to-point network and supports communications in opposite directions of each dimension. Optimized communications include: receiving, by a network adapter of a receiving compute node, a packet--from a source direction--that specifies a destination node and deposit hints. Each hint is associated with a direction within which the packet is to be deposited. If a hint indicates the packet to be deposited in the opposite direction: the adapter delivers the packet to an application on the receiving node; forwards the packet to a next node in the opposite direction if the receiving node is not the destination; and forwards the packet to a node in a direction of a subsequent dimension if the hints indicate that the packet is to be deposited in the direction of the subsequent dimension.

  7. Optimized data communications in a parallel computer

    SciTech Connect

    Faraj, Daniel A

    2014-10-21

    A parallel computer includes nodes that include a network adapter that couples the node in a point-to-point network and supports communications in opposite directions of each dimension. Optimized communications include: receiving, by a network adapter of a receiving compute node, a packet--from a source direction--that specifies a destination node and deposit hints. Each hint is associated with a direction within which the packet is to be deposited. If a hint indicates the packet to be deposited in the opposite direction: the adapter delivers the packet to an application on the receiving node; forwards the packet to a next node in the opposite direction if the receiving node is not the destination; and forwards the packet to a node in a direction of a subsequent dimension if the hints indicate that the packet is to be deposited in the direction of the subsequent dimension.

  8. CFD Research, Parallel Computation and Aerodynamic Optimization

    NASA Technical Reports Server (NTRS)

    Ryan, James S.

    1995-01-01

    During the last five years, CFD has matured substantially. Pure CFD research remains to be done, but much of the focus has shifted to integration of CFD into the design process. The work under these cooperative agreements reflects this trend. The recent work, and work which is planned, is designed to enhance the competitiveness of the US aerospace industry. CFD and optimization approaches are being developed and tested, so that the industry can better choose which methods to adopt in their design processes. The range of computer architectures has been dramatically broadened, as the assumption that only huge vector supercomputers could be useful has faded. Today, researchers and industry can trade off time, cost, and availability, choosing vector supercomputers, scalable parallel architectures, networked workstations, or heterogenous combinations of these to complete required computations efficiently.

  9. Parallel Proximity Detection for Computer Simulations

    NASA Technical Reports Server (NTRS)

    Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)

    1998-01-01

    The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are included by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

  10. Parallel Proximity Detection for Computer Simulation

    NASA Technical Reports Server (NTRS)

    Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)

    1997-01-01

    The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are includes by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

  11. Accelerating Scientific Discovery Through Computation and Visualization II

    PubMed Central

    Sims, James S.; George, William L.; Satterfield, Steven G.; Hung, Howard K.; Hagedorn, John G.; Ketcham, Peter M.; Griffin, Terence J.; Hagstrom, Stanley A.; Franiatte, Julien C.; Bryant, Garnett W.; Jaskólski, W.; Martys, Nicos S.; Bouldin, Charles E.; Simmons, Vernon; Nicolas, Oliver P.; Warren, James A.; am Ende, Barbara A.; Koontz, John E.; Filla, B. James; Pourprix, Vital G.; Copley, Stefanie R.; Bohn, Robert B.; Peskin, Adele P.; Parker, Yolanda M.; Devaney, Judith E.

    2002-01-01

    This is the second in a series of articles describing a wide variety of projects at NIST that synergistically combine physical science and information science. It describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate research. The examples include scientific collaborations in the following areas: (1) High Precision Energies for few electron atomic systems, (2) Flows of suspensions, (3) X-ray absorption, (4) Molecular dynamics of fluids, (5) Nanostructures, (6) Dendritic growth in alloys, (7) Screen saver science, (8) genetic programming. PMID:27446728

  12. Final Report: Super Instruction Architecture for Scalable Parallel Computations

    SciTech Connect

    Sanders, Beverly Ann; Bartlett, Rodney; Deumens, Erik

    2013-12-23

    The most advanced methods for reliable and accurate computation of the electronic structure of molecular and nano systems are the coupled-cluster techniques. These high-accuracy methods help us to understand, for example, how biological enzymes operate and contribute to the design of new organic explosives. The ACES III software provides a modern, high-performance implementation of these methods optimized for high performance parallel computer systems, ranging from small clusters typical in individual research groups, through larger clusters available in campus and regional computer centers, all the way to high-end petascale systems at national labs, including exploiting GPUs if available. This project enhanced the ACESIII software package and used it to study interesting scientific problems.

  13. Techniques and Tools for Performance Tuning of Parallel and Distributed Scientific Applications

    NASA Technical Reports Server (NTRS)

    Sarukkai, Sekhar R.; VanderWijngaart, Rob F.; Castagnera, Karen (Technical Monitor)

    1994-01-01

    Performance degradation in scientific computing on parallel and distributed computer systems can be caused by numerous factors. In this half-day tutorial we explain what are the important methodological issues involved in obtaining codes that have good performance potential. Then we discuss what are the possible obstacles in realizing that potential on contemporary hardware platforms, and give an overview of the software tools currently available for identifying the performance bottlenecks. Finally, some realistic examples are used to illustrate the actual use and utility of such tools.

  14. A Computational Fluid Dynamics Algorithm on a Massively Parallel Computer

    NASA Technical Reports Server (NTRS)

    Jespersen, Dennis C.; Levit, Creon

    1989-01-01

    The discipline of computational fluid dynamics is demanding ever-increasing computational power to deal with complex fluid flow problems. We investigate the performance of a finite-difference computational fluid dynamics algorithm on a massively parallel computer, the Connection Machine. Of special interest is an implicit time-stepping algorithm; to obtain maximum performance from the Connection Machine, it is necessary to use a nonstandard algorithm to solve the linear systems that arise in the implicit algorithm. We find that the Connection Machine ran achieve very high computation rates on both explicit and implicit algorithms. The performance of the Connection Machine puts it in the same class as today's most powerful conventional supercomputers.

  15. Simple, parallel virtual machines for extreme computations

    NASA Astrophysics Data System (ADS)

    Chokoufe Nejad, Bijan; Ohl, Thorsten; Reuter, Jürgen

    2015-11-01

    We introduce a virtual machine (VM) written in a numerically fast language like Fortran or C for evaluating very large expressions. We discuss the general concept of how to perform computations in terms of a VM and present specifically a VM that is able to compute tree-level cross sections for any number of external legs, given the corresponding byte-code from the optimal matrix element generator, O'MEGA. Furthermore, this approach allows to formulate the parallel computation of a single phase space point in a simple and obvious way. We analyze hereby the scaling behavior with multiple threads as well as the benefits and drawbacks that are introduced with this method. Our implementation of a VM can run faster than the corresponding native, compiled code for certain processes and compilers, especially for very high multiplicities, and has in general runtimes in the same order of magnitude. By avoiding the tedious compile and link steps, which may fail for source code files of gigabyte sizes, new processes or complex higher order corrections that are currently out of reach could be evaluated with a VM given enough computing power.

  16. Swift : fast, reliable, loosely coupled parallel computation.

    SciTech Connect

    Zhao, Y.; Hategan, M.; Clifford, B.; Foster, I.; von Laszewski, G.; Nefedova, V.; Raicu, I.; Stef-Praun, T.; Wilde, M.; Mathematics and Computer Science; Univ. of Chicago

    2007-01-01

    A common pattern in scientific computing involves the execution of many tasks that are coupled only in the sense that the output of one may be passed as input to one or more others - for example, as a file, or via a Web Services invocation. While such 'loosely coupled' computations can involve large amounts of computation and communication, the concerns of the programmer tend to be different than in traditional high performance computing, being focused on management issues relating to the large numbers of datasets and tasks (and often, the complexities inherent in 'messy' data organizations) rather than the optimization of interprocessor communication. To address these concerns, we have developed Swift, a system that combines a novel scripting language called SwiftScript with a powerful runtime system based on CoG Karajan and Falkon to allow for the concise specification, and reliable and efficient execution, of large loosely coupled computations. Swift adopts and adapts ideas first explored in the GriPhyN virtual data system, improving on that system in many regards. We describe the SwiftScript language and its use of XDTM to describe the logical structure of complex file system structures. We also present the Swift system and its use of CoG Karajan, Falkon, and Globus services to dispatch and manage the execution of many tasks in different execution environments. We summarize application experiences and detail performance experiments that quantify the cost of Swift operations.

  17. Research initiatives for plug-and-play scientific computing.

    SciTech Connect

    McInnes, L. C.; Dahlgren, T.; Nieplocha, J.; Bernholdt, D.; Allan, B.; Armstrong, R.; Chavarria, D.; Elwasif, W.; Gorton, I.; Krishan, M.; Malony, A.; Norris, B.; Ray, J.; Shende, S.; Mathematics and Computer Science; LLNL; PNNL; ORNL; SNL; Univ. of Oregon

    2007-01-01

    This paper introduces three component technology initiatives within the SciDAC Center for Technology for Advanced Scientific Component Software (TASCS) that address ever-increasing productivity challenges in creating, managing, and applying simulation software to scientific discovery. By leveraging the Common Component Architecture (CCA), a new component standard for high-performance scientific computing, these initiatives tackle difficulties at different but related levels in the development of component-based scientific software: (1) deploying applications on massively parallel and heterogeneous architectures, (2) investigating new approaches to the runtime enforcement of behavioral semantics, and (3) developing tools to facilitate dynamic composition, substitution, and reconfiguration of component implementations and parameters, so that application scientists can explore tradeoffs among factors such as accuracy, reliability, and performance.

  18. Research initiatives for plug-and-play scientific computing

    NASA Astrophysics Data System (ADS)

    Curfman McInnes, Lois; Dahlgren, Tamara; Nieplocha, Jarek; Bernholdt, David; Allan, Ben; Armstrong, Rob; Chavarria, Daniel; Elwasif, Wael; Gorton, Ian; Kenny, Joe; Krishan, Manoj; Malony, Allen; Norris, Boyana; Ray, Jaideep; Shende, Sameer

    2007-07-01

    This paper introduces three component technology initiatives within the SciDAC Center for Technology for Advanced Scientific Component Software (TASCS) that address ever-increasing productivity challenges in creating, managing, and applying simulation software to scientific discovery. By leveraging the Common Component Architecture (CCA), a new component standard for high-performance scientific computing, these initiatives tackle difficulties at different but related levels in the development of component-based scientific software: (1) deploying applications on massively parallel and heterogeneous architectures, (2) investigating new approaches to the runtime enforcement of behavioral semantics, and (3) developing tools to facilitate dynamic composition, substitution, and reconfiguration of component implementations and parameters, so that application scientists can explore tradeoffs among factors such as accuracy, reliability, and performance.

  19. Accelerating Scientific Discovery Through Computation and Visualization III. Tight-Binding Wave Functions for Quantum Dots.

    PubMed

    Sims, James S; George, William L; Griffin, Terence J; Hagedorn, John G; Hung, Howard K; Kelso, John T; Olano, Marc; Peskin, Adele P; Satterfield, Steven G; Terrill, Judith Devaney; Bryant, Garnett W; Diaz, Jose G

    2008-01-01

    This is the third in a series of articles that describe, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate scientific discovery. In this article we focus on the use of high performance computing and visualization for simulations of nanotechnology.

  20. Evaluation of leading scalar and vector architectures for scientific computations

    SciTech Connect

    Simon, Horst D.; Oliker, Leonid; Canning, Andrew; Carter, Jonathan; Ethier, Stephane; Shalf, John

    2004-04-20

    The growing gap between sustained and peak performance for scientific applications is a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to reduce this gap for many computational science codes and deliver a substantial increase in computing capabilities. This project examines the performance of the cacheless vector Earth Simulator (ES) and compares it to superscalar cache-based IBM Power3 system. Results demonstrate that the ES is significantly faster than the Power3 architecture, highlighting the tremendous potential advantage of the ES for numerical simulation. However, vectorization of a particle-in-cell application (GTC) greatly increased the memory footprint preventing loop-level parallelism and limiting scalability potential.

  1. QCMPI: A parallel environment for quantum computing

    NASA Astrophysics Data System (ADS)

    Tabakin, Frank; Juliá-Díaz, Bruno

    2009-06-01

    QCMPI is a quantum computer (QC) simulation package written in Fortran 90 with parallel processing capabilities. It is an accessible research tool that permits rapid evaluation of quantum algorithms for a large number of qubits and for various "noise" scenarios. The prime motivation for developing QCMPI is to facilitate numerical examination of not only how QC algorithms work, but also to include noise, decoherence, and attenuation effects and to evaluate the efficacy of error correction schemes. The present work builds on an earlier Mathematica code QDENSITY, which is mainly a pedagogic tool. In that earlier work, although the density matrix formulation was featured, the description using state vectors was also provided. In QCMPI, the stress is on state vectors, in order to employ a large number of qubits. The parallel processing feature is implemented by using the Message-Passing Interface (MPI) protocol. A description of how to spread the wave function components over many processors is provided, along with how to efficiently describe the action of general one- and two-qubit operators on these state vectors. These operators include the standard Pauli, Hadamard, CNOT and CPHASE gates and also Quantum Fourier transformation. These operators make up the actions needed in QC. Codes for Grover's search and Shor's factoring algorithms are provided as examples. A major feature of this work is that concurrent versions of the algorithms can be evaluated with each version subject to alternate noise effects, which corresponds to the idea of solving a stochastic Schrödinger equation. The density matrix for the ensemble of such noise cases is constructed using parallel distribution methods to evaluate its eigenvalues and associated entropy. Potential applications of this powerful tool include studies of the stability and correction of QC processes using Hamiltonian based dynamics. Program summaryProgram title: QCMPI Catalogue identifier: AECS_v1_0 Program summary URL

  2. Broadcasting a message in a parallel computer

    DOEpatents

    Archer, Charles J; Faraj, Daniel A

    2014-11-18

    Methods, systems, and products are disclosed for broadcasting a message in a parallel computer that includes: transmitting, by the logical root to all of the nodes directly connected to the logical root, a message; and for each node except the logical root: receiving the message; if that node is the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received; if that node received the message from a parent node and if that node is not a leaf node, then transmitting the message to all of the child nodes; and if that node received the message from a child node and if that node is not the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received and transmitting the message to the parent node.

  3. Broadcasting a message in a parallel computer

    DOEpatents

    Archer, Charles J; Faraj, Ahmad A

    2013-04-16

    Methods, systems, and products are disclosed for broadcasting a message in a parallel computer that includes: transmitting, by the logical root to all of the nodes directly connected to the logical root, a message; and for each node except the logical root: receiving the message; if that node is the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received; if that node received the message from a parent node and if that node is not a leaf node, then transmitting the message to all of the child nodes; and if that node received the message from a child node and if that node is not the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received and transmitting the message to the parent node.

  4. CFD research, parallel computation and aerodynamic optimization

    NASA Technical Reports Server (NTRS)

    Ryan, James S.

    1995-01-01

    Over five years of research in Computational Fluid Dynamics and its applications are covered in this report. Using CFD as an established tool, aerodynamic optimization on parallel architectures is explored. The objective of this work is to provide better tools to vehicle designers. Submarine design requires accurate force and moment calculations in flow with thick boundary layers and large separated vortices. Low noise production is critical, so flow into the propulsor region must be predicted accurately. The High Speed Civil Transport (HSCT) has been the subject of recent work. This vehicle is to be a passenger vehicle with the capability of cutting overseas flight times by more than half. A successful design must surpass the performance of comparable planes. Fuel economy, other operational costs, environmental impact, and range must all be improved substantially. For all these reasons, improved design tools are required, and these tools must eventually integrate optimization, external aerodynamics, propulsion, structures, heat transfer and other disciplines.

  5. Broadcasting collective operation contributions throughout a parallel computer

    DOEpatents

    Faraj, Ahmad [Rochester, MN

    2012-02-21

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

  6. Scientific data analysis on data-parallel platforms.

    SciTech Connect

    Ulmer, Craig D.; Bayer, Gregory W.; Choe, Yung Ryn; Roe, Diana C.

    2010-09-01

    As scientific computing users migrate to petaflop platforms that promise to generate multi-terabyte datasets, there is a growing need in the community to be able to embed sophisticated analysis algorithms in the computing platforms' storage systems. Data Warehouse Appliances (DWAs) are attractive for this work, due to their ability to store and process massive datasets efficiently. While DWAs have been utilized effectively in data-mining and informatics applications, they remain largely unproven in scientific workloads. In this paper we present our experiences in adapting two mesh analysis algorithms to function on five different DWA architectures: two Netezza database appliances, an XtremeData dbX database, a LexisNexis DAS, and multiple Hadoop MapReduce clusters. The main contribution of this work is insight into the differences between these DWAs from a user's perspective. In addition, we present performance measurements for ten DWA systems to help understand the impact of different architectural trade-offs in these systems.

  7. Application Specific Performance Technology for Productive Parallel Computing

    SciTech Connect

    Malony, Allen D.; Shende, Sameer

    2008-09-30

    Our accomplishments over the last three years of the DOE project Application- Specific Performance Technology for Productive Parallel Computing (DOE Agreement: DE-FG02-05ER25680) are described below. The project will have met all of its objectives by the time of its completion at the end of September, 2008. Two extensive yearly progress reports were produced in in March 2006 and 2007 and were previously submitted to the DOE Office of Advanced Scientific Computing Research (OASCR). Following an overview of the objectives of the project, we summarize for each of the project areas the achievements in the first two years, and then describe in some more detail the project accomplishments this past year. At the end, we discuss the relationship of the proposed renewal application to the work done on the current project.

  8. Intel Woodcrest: An Evaluation for Scientific Computing

    SciTech Connect

    Roth, Philip C; Vetter, Jeffrey S

    2007-01-01

    Intel recently began shipping its Xeon 5100 series processors, formerly known by their 'Woodcrest' code name. To evaluate the suitability of the Woodcrest processor for high-end scientific computing, we obtained access to a Woodcrest-based system at Intel and measured its performance first using computation and memory micro-benchmarks, followed by full applications from the areas of climate modeling and molecular dynamics. For computational benchmarks, the Woodcrest showed excellent performance compared to a test system that uses Opteron processors from Advanced Micro Devices (AMD), though its performance advantage for full applications was less definitive. Nevertheless, our evaluation suggests the Woodcrest to be a compelling foundation for future leadership class systems for scientific computing.

  9. 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.

  10. SCE: Grid Environment for Scientific Computing

    NASA Astrophysics Data System (ADS)

    Xiao, Haili; Wu, Hong; Chi, Xuebin

    Over the last few years Grid computing has evolved into an innovating technology and gotten increased commercial adoption. However, existing Grids do not have enough users as for sustainable development in the long term. This paper proposes several suggestions to this problem on the basis of long-term experience and careful analysis. The Scientific Computing Environment (SCE) in the Chinese Academy of Sciences is introduced as a completely new model and a feasible solution to this problem.

  11. Parallel reservoir computing using optical amplifiers.

    PubMed

    Vandoorne, Kristof; Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Bienstman, Peter

    2011-09-01

    Reservoir computing (RC), a computational paradigm inspired on neural systems, has become increasingly popular in recent years for solving a variety of complex recognition and classification problems. Thus far, most implementations have been software-based, limiting their speed and power efficiency. Integrated photonics offers the potential for a fast, power efficient and massively parallel hardware implementation. We have previously proposed a network of coupled semiconductor optical amplifiers as an interesting test case for such a hardware implementation. In this paper, we investigate the important design parameters and the consequences of process variations through simulations. We use an isolated word recognition task with babble noise to evaluate the performance of the photonic reservoirs with respect to traditional software reservoir implementations, which are based on leaky hyperbolic tangent functions. Our results show that the use of coherent light in a well-tuned reservoir architecture offers significant performance benefits. The most important design parameters are the delay and the phase shift in the system's physical connections. With optimized values for these parameters, coherent semiconductor optical amplifier (SOA) reservoirs can achieve better results than traditional simulated reservoirs. We also show that process variations hardly degrade the performance, but amplifier noise can be detrimental. This effect must therefore be taken into account when designing SOA-based RC implementations.

  12. Parallel CE/SE Computations via Domain Decomposition

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  13. A Scientific Cloud Computing Platform for Condensed Matter Physics

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

    Scientific Cloud Computing (SCC) makes possible calculations with high performance computational tools, without the need to purchase or maintain sophisticated hardware and software. We have recently developed an interface dubbed SC2IT that controls on-demand virtual Linux clusters within the Amazon EC2 cloud platform. Using this interface we have developed a more advanced, user-friendly SCC Platform configured especially for condensed matter calculations. This platform contains a GUI, based on a new Java version of SC2IT, that permits calculations of various materials properties. The cloud platform includes Virtual Machines preconfigured for parallel calculations and several precompiled and optimized materials science codes for electronic structure and x-ray and electron spectroscopy. Consequently this SCC makes state-of-the-art condensed matter calculations easy to access for general users. Proof-of-principle performance benchmarks show excellent parallelization and communication performance. Supported by NSF grant OCI-1048052

  14. A Simple Physical Optics Algorithm Perfect for Parallel Computing Architecture

    NASA Technical Reports Server (NTRS)

    Imbriale, W. A.; Cwik, T.

    1994-01-01

    A reflector antenna computer program based upon a simple discreet approximation of the radiation integral has proven to be extremely easy to adapt to the parallel computing architecture of the modest number of large-gain computing elements such as are used in the Intel iPSC and Touchstone Delta parallel machines.

  15. CFD Optimization on Network-Based Parallel Computer System

    NASA Technical Reports Server (NTRS)

    Cheung, Samson H.; Holst, Terry L. (Technical Monitor)

    1994-01-01

    Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advance computational fluid dynamics codes, which is computationally expensive in mainframe supercomputer. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computer on a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package has been applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.

  16. Parallel CFD design on network-based computer

    NASA Technical Reports Server (NTRS)

    Cheung, Samson

    1995-01-01

    Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advanced computational fluid dynamics codes, which can be computationally expensive on mainframe supercomputers. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computing environment utilizing a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package is applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.

  17. 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

  18. Scientific Computing Kernels on the Cell Processor

    SciTech Connect

    Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine

    2007-04-04

    The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

  19. Knowledge-Based Parallel Performance Technology for Scientific Application Competitiveness Final Report

    SciTech Connect

    Malony, Allen D; Shende, Sameer

    2011-08-15

    The primary goal of the University of Oregon's DOE "œcompetitiveness" project was to create performance technology that embodies and supports knowledge of performance data, analysis, and diagnosis in parallel performance problem solving. The target of our development activities was the TAU Performance System and the technology accomplishments reported in this and prior reports have all been incorporated in the TAU open software distribution. In addition, the project has been committed to maintaining strong interactions with the DOE SciDAC Performance Engineering Research Institute (PERI) and Center for Technology for Advanced Scientific Component Software (TASCS). This collaboration has proved valuable for translation of our knowledge-based performance techniques to parallel application development and performance engineering practice. Our outreach has also extended to the DOE Advanced CompuTational Software (ACTS) collection and project. Throughout the project we have participated in the PERI and TASCS meetings, as well as the ACTS annual workshops.

  20. Performance Evaluation in Network-Based Parallel Computing

    NASA Technical Reports Server (NTRS)

    Dezhgosha, Kamyar

    1996-01-01

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

  1. Review of parallel computing methods and tools for FPGA technology

    NASA Astrophysics Data System (ADS)

    Cieszewski, Radosław; Linczuk, Maciej; Pozniak, Krzysztof; Romaniuk, Ryszard

    2013-10-01

    Parallel computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated using parallel computing techniques. Specialized parallel computer architectures are used for accelerating speci c tasks. High-Energy Physics Experiments measuring systems often use FPGAs for ne-grained computation. FPGA combines many bene ts of both software and ASIC implementations. Like software, the mapped circuit is exible, and can be recon gured over the lifetime of the system. FPGAs 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. Creating parallel programs implemented in FPGAs is not trivial. This paper presents existing methods and tools for ne-grained computation implemented in FPGA using Behavioral Description and High Level Programming Languages.

  2. Numerical recipes, The art of scientific computing

    SciTech Connect

    Press, W.H.; Flannery, B.P.; Teukolsky, S.; Vetterling, W.T.

    1986-01-01

    Seventeen chapter are divided into 130 sections provide a self-contained treatment that derives, critically discusses, and actually implements over 200 of the most important numerical algorithms for scientific work. Each algorithm is presented both in FORTRAN and Pascal, with the source programs printed in the book itself. The scope of Numerical Recipes ranges from standard areas of numerical analysis (linear algebra, differential equations, roots) through subjects useful to signal processing (Fourier methods, filtering), data analysis (least squares, robust fitting, statistical functions), simulation (random deviates and Monte Carlo). The routines themselves are available for a wide variety of different computers, from personal computers to mainframes, and are largely portable among different machines.

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

    DOEpatents

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

    2013-11-12

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

  4. Access and visualization using clusters and other parallel computers

    NASA Technical Reports Server (NTRS)

    Katz, D. S.; Bergou, A.; Berriman, B.; Block, G.; Collier, J.; Curkendall, D.; Good, J.; Husman, L.; Jacob, J.; Laity, A.; Li, P.; Miller, C.; Plesea, L.; Prince, T.; Siegel, H.; Williams, R.

    2003-01-01

    JPL's Parallel Applications Technologies Group has been exploring the issues of data access and visualization of very large data sets over the past 10 years. this work has used a number of types of parallel computers, and today includes the use of commodity clusters. This talk will highlight some of the applications and tools we have developed, including how they use parallel computing resources, and specifically how we are using modern clusters.

  5. Parallel In Situ Indexing for Data-intensive Computing

    SciTech Connect

    Kim, Jinoh; Abbasi, Hasan; Chacon, Luis; Docan, Ciprian; Klasky, Scott; Liu, Qing; Podhorszki, Norbert; Shoshani, Arie; Wu, Kesheng

    2011-09-09

    As computing power increases exponentially, vast amount of data is created by many scientific re- search activities. However, the bandwidth for storing the data to disks and reading the data from disks has been improving at a much slower pace. These two trends produce an ever-widening data access gap. Our work brings together two distinct technologies to address this data access issue: indexing and in situ processing. From decades of database research literature, we know that indexing is an effective way to address the data access issue, particularly for accessing relatively small fraction of data records. As data sets increase in sizes, more and more analysts need to use selective data access, which makes indexing an even more important for improving data access. The challenge is that most implementations of in- dexing technology are embedded in large database management systems (DBMS), but most scientific datasets are not managed by any DBMS. In this work, we choose to include indexes with the scientific data instead of requiring the data to be loaded into a DBMS. We use compressed bitmap indexes from the FastBit software which are known to be highly effective for query-intensive workloads common to scientific data analysis. To use the indexes, we need to build them first. The index building procedure needs to access the whole data set and may also require a significant amount of compute time. In this work, we adapt the in situ processing technology to generate the indexes, thus removing the need of read- ing data from disks and to build indexes in parallel. The in situ data processing system used is ADIOS, a middleware for high-performance I/O. Our experimental results show that the indexes can improve the data access time up to 200 times depending on the fraction of data selected, and using in situ data processing system can effectively reduce the time needed to create the indexes, up to 10 times with our in situ technique when using identical parallel settings.

  6. 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

  7. Parallel image computation in clusters with task-distributor.

    PubMed

    Baun, Christian

    2016-01-01

    Distributed systems, especially clusters, can be used to execute ray tracing tasks in parallel for speeding up the image computation. Because ray tracing is a computational expensive and memory consuming task, ray tracing can also be used to benchmark clusters. This paper introduces task-distributor, a free software solution for the parallel execution of ray tracing tasks in distributed systems. The ray tracing solution used for this work is the Persistence Of Vision Raytracer (POV-Ray). Task-distributor does not require any modification of the POV-Ray source code or the installation of an additional message passing library like the Message Passing Interface or Parallel Virtual Machine to allow parallel image computation, in contrast to various other projects. By analyzing the runtime of the sequential and parallel program parts of task-distributor, it becomes clear how the problem size and available hardware resources influence the scaling of the parallel application.

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

    DOEpatents

    Gooding, Thomas M.

    2016-08-09

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

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

    DOEpatents

    Gooding, Thomas M.

    2016-09-13

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

  10. Development of Message Passing Routines for High Performance Parallel Computations

    NASA Technical Reports Server (NTRS)

    Summers, Edward K.

    2004-01-01

    Computational Fluid Dynamics (CFD) calculations require a great deal of computing power for completing the detailed computations involved. In an effort shorten the time it takes to complete such calculations they are implemented on a parallel computer. In the case of a parallel computer some sort of message passing structure must be used to communicate between the computers because, unlike a single machine, each computer in a parallel computing cluster does not have access to all the data or run all the parts of the total program. Thus, message passing is used to divide up the data and send instructions to each machine. The nature of my work this summer involves programming the "message passing" aspect of the parallel computer. I am working on modifying an existing program, which was written with OpenMP, and does not use a multi-machine parallel computing structure, to work with Message Passing Interface (MPI) routines. The actual code is being written in the FORTRAN 90 programming language. My goal is to write a parameterized message passing structure that could be used for a variety of individual applications and implement it on Silicon Graphics Incorporated s (SGI) IRIX operating system. With this new parameterized structure engineers would be able to speed up computations for a wide variety of purposes without having to use larger and more expensive computing equipment from another division or another NASA center.

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

    DOEpatents

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

    2014-02-11

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

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

    DOEpatents

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

    2013-10-29

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

  13. Parallel, distributed and GPU computing technologies in single-particle electron microscopy

    PubMed Central

    Schmeisser, Martin; Heisen, Burkhard C.; Luettich, Mario; Busche, Boris; Hauer, Florian; Koske, Tobias; Knauber, Karl-Heinz; Stark, Holger

    2009-01-01

    Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today’s technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined. PMID:19564686

  14. AVES: A Computer Cluster System approach for INTEGRAL Scientific Analysis

    NASA Astrophysics Data System (ADS)

    Federici, M.; Martino, B. L.; Natalucci, L.; Umbertini, P.

    The AVES computing system, based on an "Cluster" architecture is a fully integrated, low cost computing facility dedicated to the archiving and analysis of the INTEGRAL data. AVES is a modular system that uses the software resource manager (SLURM) and allows almost unlimited expandibility (65,536 nodes and hundreds of thousands of processors); actually is composed by 30 Personal Computers with Quad-Cores CPU able to reach the computing power of 300 Giga Flops (300x10{9} Floating point Operations Per Second), with 120 GB of RAM and 7.5 Tera Bytes (TB) of storage memory in UFS configuration plus 6 TB for users area. AVES was designed and built to solve growing problems raised from the analysis of the large data amount accumulated by the INTEGRAL mission (actually about 9 TB) and due to increase every year. The used analysis software is the OSA package, distributed by the ISDC in Geneva. This is a very complex package consisting of dozens of programs that can not be converted to parallel computing. To overcome this limitation we developed a series of programs to distribute the workload analysis on the various nodes making AVES automatically divide the analysis in N jobs sent to N cores. This solution thus produces a result similar to that obtained by the parallel computing configuration. In support of this we have developed tools that allow a flexible use of the scientific software and quality control of on-line data storing. The AVES software package is constituted by about 50 specific programs. Thus the whole computing time, compared to that provided by a Personal Computer with single processor, has been enhanced up to a factor 70.

  15. A scalable parallel black oil simulator on distributed memory parallel computers

    NASA Astrophysics Data System (ADS)

    Wang, Kun; Liu, Hui; Chen, Zhangxin

    2015-11-01

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

  16. Algorithms for parallel and vector computations

    NASA Technical Reports Server (NTRS)

    Ortega, James M.

    1995-01-01

    This is a final report on work performed under NASA grant NAG-1-1112-FOP during the period March, 1990 through February 1995. Four major topics are covered: (1) solution of nonlinear poisson-type equations; (2) parallel reduced system conjugate gradient method; (3) orderings for conjugate gradient preconditioners, and (4) SOR as a preconditioner.

  17. Dynamic traffic assignment on parallel computers

    SciTech Connect

    Nagel, K.; Frye, R.; Jakob, R.; Rickert, M.; Stretz, P.

    1998-12-01

    The authors describe part of the current framework of the TRANSIMS traffic research project at the Los Alamos National Laboratory. It includes parallel implementations of a route planner and a microscopic traffic simulation model. They present performance figures and results of an offline load-balancing scheme used in one of the iterative re-planning runs required for dynamic route assignment.

  18. Research on Web-based Scientific Computing Legacy Application Sharing

    NASA Astrophysics Data System (ADS)

    Zhang, Yong; Cui, Bin-Ge

    With the development of Internet technology, A legion of scientific computing legacy programs with rich domain knowledge and expertise were distributed across various disciplines. As the program implementations or interfaces and so on, scientific computing legacy programs can not be shared through the Internet. This paper proposes a method of packaging scientific computing legacy programs into DLL(Dynamic Link Library), and packaging them into Web services through the C# reflection, making the scientific computing legacy programs successfully share on the Internet.

  19. Parallel algorithms and architecture for computation of manipulator forward dynamics

    NASA Technical Reports Server (NTRS)

    Fijany, Amir; Bejczy, Antal K.

    1989-01-01

    Parallel computation of manipulator forward dynamics is investigated. Considering three classes of algorithms for the solution of the problem, that is, the O(n), the O(n exp 2), and the O(n exp 3) algorithms, parallelism in the problem is analyzed. It is shown that the problem belongs to the class of NC and that the time and processors bounds are of O(log2/2n) and O(n exp 4), respectively. However, the fastest stable parallel algorithms achieve the computation time of O(n) and can be derived by parallelization of the O(n exp 3) serial algorithms. Parallel computation of the O(n exp 3) algorithms requires the development of parallel algorithms for a set of fundamentally different problems, that is, the Newton-Euler formulation, the computation of the inertia matrix, decomposition of the symmetric, positive definite matrix, and the solution of triangular systems. Parallel algorithms for this set of problems are developed which can be efficiently implemented on a unique architecture, a triangular array of n(n+2)/2 processors with a simple nearest-neighbor interconnection. This architecture is particularly suitable for VLSI and WSI implementations. The developed parallel algorithm, compared to the best serial O(n) algorithm, achieves an asymptotic speedup of more than two orders-of-magnitude in the computation the forward dynamics.

  20. Large scale scientific computing - future directions

    NASA Astrophysics Data System (ADS)

    Patterson, G. S.

    1982-06-01

    Every new generation of scientific computers has opened up new areas of science for exploration through the use of more realistic numerical models or the ability to process ever larger amounts of data. Concomitantly, scientists, because of the success of past models and the wide range of physical phenomena left unexplored, have pressed computer designers to strive for the maximum performance that current technology will permit. This encompasses not only increased processor speed, but also substantial improvements in processor memory, I/O bandwidth, secondary storage and facilities to augment the scientist's ability both to program and to understand the results of a computation. Over the past decade, performance improvements for scientific calculations have come from algoeithm development and a major change in the underlying architecture of the hardware, not from significantly faster circuitry. It appears that this trend will continue for another decade. A future archetectural change for improved performance will most likely be multiple processors coupled together in some fashion. Because the demand for a significantly more powerful computer system comes from users with single large applications, it is essential that an application be efficiently partitionable over a set of processors; otherwise, a multiprocessor system will not be effective. This paper explores some of the constraints on multiple processor architecture posed by these large applications. In particular, the trade-offs between large numbers of slow processors and small numbers of fast processors is examined. Strategies for partitioning range from partitioning at the language statement level (in-the-small) and at the program module level (in-the-large). Some examples of partitioning in-the-large are given and a strategy for efficiently executing a partitioned program is explored.

  1. Massively parallel computing at Sandia and its application to national defense

    SciTech Connect

    Dosanjh, S.S.

    1991-01-01

    Two years ago, researchers at Sandia National Laboratories showed that a massively parallel computer with 1024 processors could solve scientific problems more than 1000 times faster than a single processor. Since then, interest in massively parallel processing has increased dramatically. This review paper discusses some of the applications of this emerging technology to important problems at Sandia. Particular attention is given here to the impact of massively parallel systems on applications related to national defense. New concepts in heterogenous programming and load balancing for MIMD computers are drastically increasing synthetic aperture radar (SAR) and SDI modeling capabilities. Also, researchers are showing that the current generation of massively parallel MIMD and SIMD computers are highly competitive with a CRAY on hydrodynamic and structural mechanics codes that are optimized for vector processors. 9 refs., 5 figs., 1 tab.

  2. Performance issues for engineering analysis on MIMD parallel computers

    SciTech Connect

    Fang, H.E.; Vaughan, C.T.; Gardner, D.R.

    1994-08-01

    We discuss how engineering analysts can obtain greater computational resolution in a more timely manner from applications codes running on MIMD parallel computers. Both processor speed and memory capacity are important to achieving better performance than a serial vector supercomputer. To obtain good performance, a parallel applications code must be scalable. In addition, the aspect ratios of the subdomains in the decomposition of the simulation domain onto the parallel computer should be of order 1. We demonstrate these conclusions using simulations conducted with the PCTH shock wave physics code running on a Cray Y-MP, a 1024-node nCUBE 2, and an 1840-node Paragon.

  3. 75 FR 64720 - DOE/Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-20

    .../Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy, Office of Science. ACTION: Notice of open meeting. SUMMARY: This notice announces a meeting of the Advanced Scientific Computing... Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building; U. S. Department...

  4. 75 FR 9887 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-04

    ... Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy, Office of Science. ACTION: Notice of open meeting. SUMMARY: This notice announces a meeting of the Advanced Scientific Computing... Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building; U.S. Department...

  5. 78 FR 6087 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-29

    ... Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy, Office of Science. ACTION: Notice of open meeting. SUMMARY: This notice announces a meeting of the Advanced Scientific Computing..., Office of Advanced Scientific Computing Research; SC-21/Germantown Building; U. S. Department of...

  6. 75 FR 43518 - Advanced Scientific Computing Advisory Committee; Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-26

    ... Advanced Scientific Computing Advisory Committee; Meeting AGENCY: Office of Science, DOE. ACTION: Notice of open meeting. SUMMARY: This notice announces a meeting of the Advanced Scientific Computing Advisory..., Office of Advanced Scientific Computing Research; SC-21/Germantown Building; U. S. Department of...

  7. 75 FR 57742 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-22

    ... Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy, Office of Science. ACTION... 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;...

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

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-13

    ... Advanced Scientific Computing Advisory Committee Charter Renewal AGENCY: Department of Energy, Office of... Administration, notice is hereby given that the Advanced Scientific Computing Advisory Committee will be renewed... concerning the Advanced Scientific Computing program in response only to charges from the Director of...

  9. 76 FR 9765 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-22

    ... Advanced Scientific Computing Advisory Committee AGENCY: Office of Science, Department of Energy. ACTION: Notice of open meeting. SUMMARY: This notice announces a meeting of the Advanced Scientific Computing..., Office of Advanced Scientific Computing Research, SC-21/Germantown Building, U.S. Department of...

  10. 77 FR 45345 - DOE/Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-31

    .../Advanced Scientific Computing Advisory Committee AGENCY: Office of Science, Department of Energy. ACTION: Notice of open meeting. SUMMARY: This notice announces a meeting of the Advanced Scientific Computing... Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building; U.S. Department...

  11. 78 FR 41046 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-09

    ... Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy, Office of Science. ACTION... hereby given that the Advanced Scientific Computing Advisory Committee will be renewed for a two-year... (DOE), on the Advanced Scientific Computing Research Program managed by the Office of...

  12. Mathematical model partitioning and packing for parallel computer calculation

    NASA Technical Reports Server (NTRS)

    Arpasi, Dale J.; Milner, Edward J.

    1986-01-01

    This paper deals with the development of multiprocessor simulations from a serial set of ordinary differential equations describing a physical system. The identification of computational parallelism within the model equations is discussed. A technique is presented for identifying this parallelism and for partitioning the equations for parallel solution on a multiprocessor. Next, an algorithm which packs the equations into a minimum number of processors is described. The results of applying the packing algorithm to a turboshaft engine model are presented.

  13. Java Performance for Scientific Applications on LLNL Computer Systems

    SciTech Connect

    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 of 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.

  14. Super and parallel computers and their impact on civil engineering

    SciTech Connect

    Kamat, M.P.

    1986-01-01

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

  15. Research in Parallel Algorithms and Software for Computational Aerosciences

    NASA Technical Reports Server (NTRS)

    Domel, Neal D.

    1996-01-01

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

  16. Research in Parallel Algorithms and Software for Computational Aerosciences

    NASA Technical Reports Server (NTRS)

    Domel, Neal D.

    1996-01-01

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

  17. QCD on the Massively Parallel Computer AP1000

    NASA Astrophysics Data System (ADS)

    Akemi, K.; Fujisaki, M.; Okuda, M.; Tago, Y.; Hashimoto, T.; Hioki, S.; Miyamura, O.; Takaishi, T.; Nakamura, A.; de Forcrand, Ph.; Hege, C.; Stamatescu, I. O.

    We present the QCD-TARO program of calculations which uses the parallel computer AP1000 of Fujitsu. We discuss the results on scaling, correlation times and hadronic spectrum, some aspects of the implementation and the future prospects.

  18. Fluid dynamics parallel computer development at NASA Langley Research Center

    NASA Technical Reports Server (NTRS)

    Townsend, James C.; Zang, Thomas A.; Dwoyer, Douglas L.

    1987-01-01

    To accomplish more detailed simulations of highly complex flows, such as the transition to turbulence, fluid dynamics research requires computers much more powerful than any available today. Only parallel processing on multiple-processor computers offers hope for achieving the required effective speeds. Looking ahead to the use of these machines, the fluid dynamicist faces three issues: algorithm development for near-term parallel computers, architecture development for future computer power increases, and assessment of possible advantages of special purpose designs. Two projects at NASA Langley address these issues. Software development and algorithm exploration is being done on the FLEX/32 Parallel Processing Research Computer. New architecture features are being explored in the special purpose hardware design of the Navier-Stokes Computer. These projects are complementary and are producing promising results.

  19. 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.

  20. A Testbed of Parallel Kernels for Computer Science Research

    SciTech Connect

    Bailey, David; Demmel, James; Ibrahim, Khaled; Kaiser, Alex; Koniges, Alice; Madduri, Kamesh; Shalf, John; Strohmaier, Erich; Williams, Samuel

    2010-04-30

    For several decades, computer scientists have sought guidance on how to evolve architectures, languages, and programming models for optimal performance, efficiency, and productivity. Unfortunately, this guidance is most often taken from the existing software/hardware ecosystem. Architects attempt to provide micro-architectural solutions to improve performance on fixed binaries. Researchers tweak compilers to improve code generation for existing architectures and implementations, and they may invent new programming models for fixed processor and memory architectures and computational algorithms. In today's rapidly evolving world of on-chip parallelism, these isolated and iterative improvements to performance may miss superior solutions in the same way gradient descent optimization techniques may get stuck in local minima. In an initial study, we have developed an alternate approach that, rather than starting with an existing hardware/software solution laced with hidden assumptions, defines the computational problems of interest and invites architects, researchers and programmers to implement novel hardware/ software co-designed solutions. Our work builds on the previous ideas of computational dwarfs, motifs, and parallel patterns by selecting a representative set of essential problems for which we provide: An algorithmic description; scalable problem definition; illustrative reference implementations; verification schemes. For simplicity, we focus initially on the computational problems of interest to the scientific computing community but proclaim the methodology (and perhaps a subset of the problems) as applicable to other communities. We intend to broaden the coverage of this problem space through stronger community involvement. Previous work has established a broad categorization of numerical methods of interest to the scientific computing, in the spirit of the NAS Benchmarks, which pioneered the basic idea of a 'pencil and paper benchmark' in the 1990s. The

  1. The Design and Evaluation of "CAPTools"--A Computer Aided Parallelization Toolkit

    NASA Technical Reports Server (NTRS)

    Yan, Jerry; Frumkin, Michael; Hribar, Michelle; Jin, Haoqiang; Waheed, Abdul; Johnson, Steve; Cross, Jark; Evans, Emyr; Ierotheou, Constantinos; Leggett, Pete; Saini, Subhash (Technical Monitor)

    1998-01-01

    Writing applications for high performance computers is a challenging task. Although writing code by hand still offers the best performance, it is extremely costly and often not very portable. The Computer Aided Parallelization Tools (CAPTools) are a toolkit designed to help automate the mapping of sequential FORTRAN scientific applications onto multiprocessors. CAPTools consists of the following major components: an inter-procedural dependence analysis module that incorporates user knowledge; a 'self-propagating' data partitioning module driven via user guidance; an execution control mask generation and optimization module for the user to fine tune parallel processing of individual partitions; a program transformation/restructuring facility for source code clean up and optimization; a set of browsers through which the user interacts with CAPTools at each stage of the parallelization process; and a code generator supporting multiple programming paradigms on various multiprocessors. Besides describing the rationale behind the architecture of CAPTools, the parallelization process is illustrated via case studies involving structured and unstructured meshes. The programming process and the performance of the generated parallel programs are compared against other programming alternatives based on the NAS Parallel Benchmarks, ARC3D and other scientific applications. Based on these results, a discussion on the feasibility of constructing architectural independent parallel applications is presented.

  2. Serial multiplier arrays for parallel computation

    NASA Technical Reports Server (NTRS)

    Winters, Kel

    1990-01-01

    Arrays of systolic serial-parallel multiplier elements are proposed as an alternative to conventional SIMD mesh serial adder arrays for applications that are multiplication intensive and require few stored operands. The design and operation of a number of multiplier and array configurations featuring locality of connection, modularity, and regularity of structure are discussed. A design methodology combining top-down and bottom-up techniques is described to facilitate development of custom high-performance CMOS multiplier element arrays as well as rapid synthesis of simulation models and semicustom prototype CMOS components. Finally, a differential version of NORA dynamic circuits requiring a single-phase uncomplemented clock signal introduced for this application.

  3. Use of parallel computing in mass processing of laser data

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  4. Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  5. Routing Application for Parallel computatIon of Discharge

    NASA Astrophysics Data System (ADS)

    David, C. H.; Maidment, D. R.; Yang, Z.

    2008-12-01

    Today, meteorological models can predict storm events and climate patterns, but there are few models that connect atmospheric models to the hydraulics of rivers. Such a model is necessary to advance the prediction of events such as floods or droughts. Furthermore, the increasingly available Geographic Information System-based hydrographic datasets offer ways to use actual mapped river for routing. Such GIS-based datasets include NHDPlus at the continental-scale [USEPA and USGS, 2007]and HydroSHEDS at the global- scale [Lehner, et al., 2006]. The objective of ongoing work is to develop RAPID (Routing Application for Parallel computatIon of Discharge), a large-scale river routing model that: - has physical representation of river flow - allows for coupling with both land surface models and groundwater models. In particular enabling bi-directional exchanges between rivers and aquifers through a computation of water volume and flow on a reach-to-reach basis - has some specific treatment for man-made infrastructures and anthropogenic actions (dams, pumping) - benefits from the latest scientific computing developments (supercomputing facilities and high performance parallel computing libraries) - will benefit from the increasingly available Geographic Information System hydrographic databases. RAPID has already been tested over France through a ten-year coupling with SIM-France [Habets, et al., 2008, using a river network made of 24,264 river reaches. RAPID has been adapted to run on the Lonestar supercomputer (http://www.tacc.utexas.edu/resources/hpcsystems/) and to allow the use of the NHDPlus dataset. RAPID is now being tested with the 74,615 river reaches of the entire Texas Gulf. This type of innovative model has strong implications for the future of hydrology. Such a tool can help improve the understanding of the effect of climate change on water resources as well as provide information on how many gages are needed and where are they needed the most. More broadly

  6. History Matching in Parallel Computational Environments

    SciTech Connect

    Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Sharad Yadav

    2004-08-31

    In the probabilistic approach for history matching, the information from the dynamic data is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, fluid properties, well configuration, flow constrains on wells etc. This implies probabilistic approach should then update different regions of the reservoir in different ways. This necessitates delineation of multiple reservoir domains in order to increase the accuracy of the approach. The research focuses on a probabilistic approach to integrate dynamic data that ensures consistency between reservoir models developed from one stage to the next. The algorithm relies on efficient parameterization of the dynamic data integration problem and permits rapid assessment of the updated reservoir model at each stage. The report also outlines various domain decomposition schemes from the perspective of increasing the accuracy of probabilistic approach of history matching. Research progress in three important areas of the project are discussed: {lg_bullet}Validation and testing the probabilistic approach to incorporating production data in reservoir models. {lg_bullet}Development of a robust scheme for identifying reservoir regions that will result in a more robust parameterization of the history matching process. {lg_bullet}Testing commercial simulators for parallel capability and development of a parallel algorithm for history matching.

  7. Access and visualization using clusters and other parallel computers

    NASA Technical Reports Server (NTRS)

    Katz, Daniel S.; Bergou, Attila; Berriman, Bruce; Block, Gary; Collier, Jim; Curkendall, Dave; Good, John; Husman, Laura; Jacob, Joe; Laity, Anastasia; Li, Peggy; Miller, Craig; Plesea, Lucian; Prince, Tom; Siegel, Herb; Williams, Roy

    2003-01-01

    JPL's Parallel Applications Technologies Group has been exploring the issues of data access and visualization of very large data sets over the past 10 or so years. this work has used a number of types of parallel computers, and today includes the use of commodity clusters. This talk will highlight some of the applications and tools we have developed, including how they use parallel computing resources, and specifically how we are using modern clusters. Our applications focus on NASA's needs; thus our data sets are usually related to Earth and Space Science, including data delivered from instruments in space, and data produced by telescopes on the ground.

  8. Partitioning problems in parallel, pipelined and distributed computing

    NASA Technical Reports Server (NTRS)

    Bokhari, S.

    1985-01-01

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

  9. Partitioning problems in parallel, pipelined, and distributed computing

    NASA Technical Reports Server (NTRS)

    Bokhari, Shahid H.

    1988-01-01

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

  10. 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

  11. Parallel Computation of the Topology of Level Sets

    SciTech Connect

    Pascucci, V; Cole-McLaughlin, K

    2004-12-16

    This paper introduces two efficient algorithms that compute the Contour Tree of a 3D scalar field F and its augmented version with the Betti numbers of each isosurface. The Contour Tree is a fundamental data structure in scientific visualization that is used to preprocess the domain mesh to allow optimal computation of isosurfaces with minimal overhead storage. The Contour Tree can also be used to build user interfaces reporting the complete topological characterization of a scalar field, as shown in Figure 1. Data exploration time is reduced since the user understands the evolution of level set components with changing isovalue. The Augmented Contour Tree provides even more accurate information segmenting the range space of the scalar field in portion of invariant topology. The exploration time for a single isosurface is also improved since its genus is known in advance. Our first new algorithm augments any given Contour Tree with the Betti numbers of all possible corresponding isocontours in linear time with the size of the tree. Moreover we show how to extend the scheme introduced in [3] with the Betti number computation without increasing its complexity. Thus, we improve on the time complexity from our previous approach [10] from O(m log m) to O(n log n + m), where m is the number of cells and n is the number of vertices in the domain of F. Our second contribution is a new divide-and-conquer algorithm that computes the Augmented Contour Tree with improved efficiency. The approach computes the output Contour Tree by merging two intermediate Contour Trees and is independent of the interpolant. In this way we confine any knowledge regarding a specific interpolant to an independent function that computes the tree for a single cell. We have implemented this function for the trilinear interpolant and plan to replace it with higher order interpolants when needed. The time complexity is O(n + t log n), where t is the number of critical points of F. For the first time

  12. Performing a global barrier operation in a parallel computer

    DOEpatents

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

    2014-12-09

    Executing computing tasks on a parallel computer that includes compute nodes coupled for data communications, where each compute node executes tasks, with one task on each compute node designated as a master task, including: for each task on each compute node until all master tasks have joined a global barrier: determining whether the task is a master task; if the task is not a master task, joining a single local barrier; if the task is a master task, joining the global barrier and the single local barrier only after all other tasks on the compute node have joined the single local barrier.

  13. Models and Measurements of Parallelism for a Distributed Computer System.

    DTIC Science & Technology

    1982-01-01

    that parallel execution of the processes comprising an application program will defray U the overhead costs of distributed computing . This...of Different Approaches to Distributed Computing ", Proceedings of the Ist International Conference on Distributed Comput er Systems, Huntsville, AL...Oct. 1-5, 1979), pp. 222-232. [20] Liskov, B., "Primitives for Distributed Computing ", Froceedings of the 7--th Symposium on Operating System

  14. Parallel structures in human and computer memory

    NASA Technical Reports Server (NTRS)

    Kanerva, P.

    1986-01-01

    If one thinks of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library. One recognizes a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. A computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do is constructed. Such a memory is remarkably similiar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. It is concluded that the frame problem of artificial intelligence could be solved by the use of such a memory if one were able to encode information about the world properly.

  15. Misleading Performance Claims in Parallel Computations

    SciTech Connect

    Bailey, David H.

    2009-05-29

    In a previous humorous note entitled 'Twelve Ways to Fool the Masses,' I outlined twelve common ways in which performance figures for technical computer systems can be distorted. In this paper and accompanying conference talk, I give a reprise of these twelve 'methods' and give some actual examples that have appeared in peer-reviewed literature in years past. I then propose guidelines for reporting performance, the adoption of which would raise the level of professionalism and reduce the level of confusion, not only in the world of device simulation but also in the larger arena of technical computing.

  16. Scientific development of a massively parallel ocean climate model. Progress report for 1992--1993 and Continuing request for 1993--1994 to CHAMMP (Computer Hardware, Advanced Mathematics, and Model Physics)

    SciTech Connect

    Semtner, A.J. Jr.; Chervin, R.M.

    1993-05-01

    During the second year of CHAMMP funding to the principal investigators, progress has been made in the proposed areas of research, as follows: investigation of the physics of the thermohaline circulation; examination of resolution effects on ocean general circulation; and development of a massively parallel ocean climate model.

  17. 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

  18. Scientific Writing & the Scientific Method: Parallel "Hourglass" Structure in Form & Content

    ERIC Educational Resources Information Center

    Schulte, Bruce A.

    2003-01-01

    The writing of a scientific article offers a sharp divergence from the standard essay paper familiar to most students from English class. Supporting documentation is embedded in the scientific prose, not footnoted along the bottom of each page. Instructing students in the art of scientific writing can be truly challenging. After years of…

  19. Animated computer graphics models of space and earth sciences data generated via the massively parallel processor

    NASA Technical Reports Server (NTRS)

    Treinish, Lloyd A.; Gough, Michael L.; Wildenhain, W. David

    1987-01-01

    The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.

  20. Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

    NASA Technical Reports Server (NTRS)

    Sun, Xian-He

    1997-01-01

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

  1. Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation.

    DTIC Science & Technology

    1986-03-01

    P36-844. **VAX is a trademark of Digital Equipment Corporation . ..- ’. 100 *e .................................................... Paper 2L Parallel...ming, Computzng Surveyv, 9, March, pp. 29-59. U .nix is a trademark AI Bell Lajboratories. ... VAX is a trademark of Digital Equipment Corporation ...parallelism will not reduce the processor communicatio s response time. Thus, there are associated costs and limitations (•) Amount of memory

  2. A Lanczos eigenvalue method on a parallel computer

    NASA Technical Reports Server (NTRS)

    Bostic, Susan W.; Fulton, Robert E.

    1987-01-01

    Eigenvalue analyses of complex structures is a computationally intensive task which can benefit significantly from new and impending parallel computers. This study reports on a parallel computer implementation of the Lanczos method for free vibration analysis. The approach used here subdivides the major Lanczos calculation tasks into subtasks and introduces parallelism down to the subtask levels such as matrix decomposition and forward/backward substitution. The method was implemented on a commercial parallel computer and results were obtained for a long flexible space structure. While parallel computing efficiency for the Lanczos method was good for a moderate number of processors for the test problem, the greatest reduction in time was realized for the decomposition of the stiffness matrix, a calculation which took 70 percent of the time in the sequential program and which took 25 percent of the time on eight processors. For a sample calculation of the twenty lowest frequencies of a 486 degree of freedom problem, the total sequential computing time was reduced by almost a factor of ten using 16 processors.

  3. Identifying failure in a tree network of a parallel computer

    DOEpatents

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

    2010-08-24

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

  4. Institute for Scientific Computing Research Fiscal Year 2002 Annual Report

    SciTech Connect

    Keyes, D E; McGraw, J R; Bodtker, L K

    2003-03-11

    The Institute for Scientific Computing Research (ISCR) at Lawrence Livermore National Laboratory is jointly administered by the Computing Applications and Research Department (CAR) and the University Relations Program (URP), and this joint relationship expresses its mission. An extensively externally networked ISCR cost-effectively expands the level and scope of national computational science expertise available to the Laboratory through CAR. The URP, with its infrastructure for managing six institutes and numerous educational programs at LLNL, assumes much of the logistical burden that is unavoidable in bridging the Laboratory's internal computational research environment with that of the academic community. As large-scale simulations on the parallel platforms of DOE's Advanced Simulation and Computing (ASCI) become increasingly important to the overall mission of LLNL, the role of the ISCR expands in importance, accordingly. Relying primarily on non-permanent staffing, the ISCR complements Laboratory research in areas of the computer and information sciences that are needed at the frontier of Laboratory missions. The ISCR strives to be the ''eyes and ears'' of the Laboratory in the computer and information sciences, in keeping the Laboratory aware of and connected to important external advances. It also attempts to be ''feet and hands, in carrying those advances into the Laboratory and incorporating them into practice. In addition to conducting research, the ISCR provides continuing education opportunities to Laboratory personnel, in the form of on-site workshops taught by experts on novel software or hardware technologies. The ISCR also seeks to influence the research community external to the Laboratory to pursue Laboratory-related interests and to train the workforce that will be required by the Laboratory. Part of the performance of this function is interpreting to the external community appropriate (unclassified) aspects of the Laboratory's own contributions

  5. Parallel Computing by Xeroxing on Transparencies

    NASA Astrophysics Data System (ADS)

    Head, Tom

    We illustrate a procedure for solving instances of the Boolean satisfiability (SAT) problem by xeroxing onto transparent plastic sheets. Suppose that m clauses are given in which n variables occur and that the longest clause contains k literals. The associated instance of the SAT problem can be solved by using a xerox machine to form only n+2k+m successive transparencies. The applicability of this linear time algorithm is limited, of course, by the increase in the information density on the transparencies when n is large. This same scheme of computation can be carried out by using photographic or other optical processes. This work has been developed as an alternate implementation of procedures previously developed in the context of aqueous (DNA) computing.

  6. Nonlinear hierarchical substructural parallelism and computer architecture

    NASA Technical Reports Server (NTRS)

    Padovan, Joe

    1989-01-01

    Computer architecture is investigated in conjunction with the algorithmic structures of nonlinear finite-element analysis. To help set the stage for this goal, the development is undertaken by considering the wide-ranging needs associated with the analysis of rolling tires which possess the full range of kinematic, material and boundary condition induced nonlinearity in addition to gross and local cord-matrix material properties.

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

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  8. A microeconomic scheduler for parallel computers

    NASA Technical Reports Server (NTRS)

    Stoica, Ion; Abdel-Wahab, Hussein; Pothen, Alex

    1995-01-01

    We describe a scheduler based on the microeconomic paradigm for scheduling on-line a set of parallel jobs in a multiprocessor system. In addition to the classical objectives of increasing the system throughput and reducing the response time, we consider fairness in allocating system resources among the users, and providing the user with control over the relative performances of his jobs. We associate with every user a savings account in which he receives money at a constant rate. When a user wants to run a job, he creates an expense account for that job to which he transfers money from his savings account. The job uses the funds in its expense account to obtain the system resources it needs for execution. The share of the system resources allocated to the user is directly related to the rate at which the user receives money; the rate at which the user transfers money into a job expense account controls the job's performance. We prove that starvation is not possible in our model. Simulation results show that our scheduler improves both system and user performances in comparison with two different variable partitioning policies. It is also shown to be effective in guaranteeing fairness and providing control over the performance of jobs.

  9. Methods for operating parallel computing systems employing sequenced communications

    DOEpatents

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

    1999-08-10

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

  10. Methods for operating parallel computing systems employing sequenced communications

    DOEpatents

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

    1999-01-01

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

  11. Numerical characterization of nonlinear dynamical systems using parallel computing: The role of GPUS approach

    NASA Astrophysics Data System (ADS)

    Fazanaro, Filipe I.; Soriano, Diogo C.; Suyama, Ricardo; Madrid, Marconi K.; Oliveira, José Raimundo de; Muñoz, Ignacio Bravo; Attux, Romis

    2016-08-01

    The characterization of nonlinear dynamical systems and their attractors in terms of invariant measures, basins of attractions and the structure of their vector fields usually outlines a task strongly related to the underlying computational cost. In this work, the practical aspects related to the use of parallel computing - specially the use of Graphics Processing Units (GPUS) and of the Compute Unified Device Architecture (CUDA) - are reviewed and discussed in the context of nonlinear dynamical systems characterization. In this work such characterization is performed by obtaining both local and global Lyapunov exponents for the classical forced Duffing oscillator. The local divergence measure was employed by the computation of the Lagrangian Coherent Structures (LCSS), revealing the general organization of the flow according to the obtained separatrices, while the global Lyapunov exponents were used to characterize the attractors obtained under one or more bifurcation parameters. These simulation sets also illustrate the required computation time and speedup gains provided by different parallel computing strategies, justifying the employment and the relevance of GPUS and CUDA in such extensive numerical approach. Finally, more than simply providing an overview supported by a representative set of simulations, this work also aims to be a unified introduction to the use of the mentioned parallel computing tools in the context of nonlinear dynamical systems, providing codes and examples to be executed in MATLAB and using the CUDA environment, something that is usually fragmented in different scientific communities and restricted to specialists on parallel computing strategies.

  12. History Matching in Parallel Computational Environments

    SciTech Connect

    Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Yonghwee Kim; Sharad Yadav

    2006-08-31

    A novel methodology for delineating multiple reservoir domains for the purpose of history matching in a distributed computing environment has been proposed. A fully probabilistic approach to perturb permeability within the delineated zones is implemented. The combination of robust schemes for identifying reservoir zones and distributed computing significantly increase the accuracy and efficiency of the probabilistic approach. The information pertaining to the permeability variations in the reservoir that is contained in dynamic data is calibrated in terms of a deformation parameter rD. This information is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, well configuration, flow constrains etc. The probabilistic approach then has to account for multiple r{sub D} values in different regions of the reservoir. In order to delineate reservoir domains that can be characterized with different r{sub D} parameters, principal component analysis (PCA) of the Hessian matrix has been done. The Hessian matrix summarizes the sensitivity of the objective function at a given step of the history matching to model parameters. It also measures the interaction of the parameters in affecting the objective function. The basic premise of PC analysis is to isolate the most sensitive and least correlated regions. The eigenvectors obtained during the PCA are suitably scaled and appropriate grid block volume cut-offs are defined such that the resultant domains are neither too large (which increases interactions between domains) nor too small (implying ineffective history matching). The delineation of domains requires calculation of Hessian, which could be computationally costly and as well as restricts the current

  13. History Matching in Parallel Computational Environments

    SciTech Connect

    Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Sharad Yadav

    2005-10-01

    A novel methodology for delineating multiple reservoir domains for the purpose of history matching in a distributed computing environment has been proposed. A fully probabilistic approach to perturb permeability within the delineated zones is implemented. The combination of robust schemes for identifying reservoir zones and distributed computing significantly increase the accuracy and efficiency of the probabilistic approach. The information pertaining to the permeability variations in the reservoir that is contained in dynamic data is calibrated in terms of a deformation parameter rD. This information is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, well configuration, flow constrains etc. The probabilistic approach then has to account for multiple r{sub D} values in different regions of the reservoir. In order to delineate reservoir domains that can be characterized with different rD parameters, principal component analysis (PCA) of the Hessian matrix has been done. The Hessian matrix summarizes the sensitivity of the objective function at a given step of the history matching to model parameters. It also measures the interaction of the parameters in affecting the objective function. The basic premise of PC analysis is to isolate the most sensitive and least correlated regions. The eigenvectors obtained during the PCA are suitably scaled and appropriate grid block volume cut-offs are defined such that the resultant domains are neither too large (which increases interactions between domains) nor too small (implying ineffective history matching). The delineation of domains requires calculation of Hessian, which could be computationally costly and as well as restricts the current approach to

  14. Parallel Computational Fluid Dynamics: Current Status and Future Requirements

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  15. Tutorial: Parallel Computing of Simulation Models for Risk Analysis.

    PubMed

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

    2016-10-01

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

  16. CRBLASTER: A Parallel-Processing Computational Framework for Embarrassingly-Parallel Image-Analysis Algorithms

    NASA Astrophysics Data System (ADS)

    Mighell, Kenneth John

    2011-11-01

    The development of parallel-processing image-analysis codes is generally a challenging task that requires complicated choreography of interprocessor communications. If, however, the image-analysis algorithm is embarrassingly parallel, then the development of a parallel-processing implementation of that algorithm can be a much easier task to accomplish because, by definition, there is little need for communication between the compute processes. I describe the design, implementation, and performance of a parallel-processing image-analysis application, called CRBLASTER, which does cosmic-ray rejection of CCD (charge-coupled device) images using the embarrassingly-parallel L.A.COSMIC algorithm. CRBLASTER is written in C using the high-performance computing industry standard Message Passing Interface (MPI) library. The code has been designed to be used by research scientists who are familiar with C as a parallel-processing computational framework that enables the easy development of parallel-processing image-analysis programs based on embarrassingly-parallel algorithms. The CRBLASTER source code is freely available at the official application website at the National Optical Astronomy Observatory. Removing cosmic rays from a single 800x800 pixel Hubble Space Telescope WFPC2 image takes 44 seconds with the IRAF script lacos_im.cl running on a single core of an Apple Mac Pro computer with two 2.8-GHz quad-core Intel Xeon processors. CRBLASTER is 7.4 times faster processing the same image on a single core on the same machine. Processing the same image with CRBLASTER simultaneously on all 8 cores of the same machine takes 0.875 seconds -- which is a speedup factor of 50.3 times faster than the IRAF script. A detailed analysis is presented of the performance of CRBLASTER using between 1 and 57 processors on a low-power Tilera 700-MHz 64-core TILE64 processor.

  17. 76 FR 45786 - Advanced Scientific Computing Advisory Committee; Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-01

    ... Advanced Scientific Computing Advisory Committee; Meeting AGENCY: Office of Science, Department of Energy... Computing Advisory Committee (ASCAC). Federal Advisory Committee Act (Pub. L. 92-463, 86 Stat. 770) requires... INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown...

  18. Parallel Domain Decomposition Preconditioning for Computational Fluid Dynamics

    NASA Technical Reports Server (NTRS)

    Barth, Timothy J.; Chan, Tony F.; Tang, Wei-Pai; Kutler, Paul (Technical Monitor)

    1998-01-01

    This viewgraph presentation gives an overview of the parallel domain decomposition preconditioning for computational fluid dynamics. Details are given on some difficult fluid flow problems, stabilized spatial discretizations, and Newton's method for solving the discretized flow equations. Schur complement domain decomposition is described through basic formulation, simplifying strategies (including iterative subdomain and Schur complement solves, matrix element dropping, localized Schur complement computation, and supersparse computations), and performance evaluation.

  19. InSAR Scientific Computing Environment (Invited)

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    The InSAR Scientific Computing Environment (ISCE) is a new development effort within the NASA Advanced Information Systems and Technology program, with the intent of recasting the JPL/Caltech ROI_PAC repeat-pass interferometry package into a modern, reconfigurable, open-source computing environment. The new capability initiates the next generation of geodetic imaging processing technology for InSAR sensors, providing flexibility and extensibility in reducing measurements from radar satellites and aircraft to new geophysical products. The NRC Decadal Survey recommended DESDynI mission will deliver to the science community data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth’s ecosystem. DESDynI will provide time series and multi-image measurements that permit four-dimensional models of Earth surface processes so that, for example, climate-induced changes over time become apparent and quantifiable. In this paper, we describe the Environment, and illustrate how it can facility space-based geodesy from InSAR. The ISCE invokes object oriented scripts to control legacy and new codes, and abstracts and generalizes the data model for efficient manipulation of objects among modules. The module interfaces are suitable for command-line execution or GUI-programming. It exposes users gradually to its levels of capability, allowing novices to apply it readily for simple tasks and for experienced users to mine the data with great facility. The intent of the effort is to encourage user contributions to the code, creating an open source community that will extend its life and utility.

  20. Modeling groundwater flow on massively parallel computers

    SciTech Connect

    Ashby, S.F.; Falgout, R.D.; Fogwell, T.W.; Tompson, A.F.B.

    1994-12-31

    The authors will explore the numerical simulation of groundwater flow in three-dimensional heterogeneous porous media. An interdisciplinary team of mathematicians, computer scientists, hydrologists, and environmental engineers is developing a sophisticated simulation code for use on workstation clusters and MPPs. To date, they have concentrated on modeling flow in the saturated zone (single phase), which requires the solution of a large linear system. they will discuss their implementation of preconditioned conjugate gradient solvers. The preconditioners under consideration include simple diagonal scaling, s-step Jacobi, adaptive Chebyshev polynomial preconditioning, and multigrid. They will present some preliminary numerical results, including simulations of groundwater flow at the LLNL site. They also will demonstrate the code`s scalability.

  1. Parallel and pipeline computation of fast unitary transforms

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  2. The International Conference on Vector and Parallel Computing (2nd)

    DTIC Science & Technology

    1989-01-17

    in Reservoir Simulation "... . ................... 7 "ParaScope: A Parallel Programing Environment ........................ 8 "Current Directions and...built. "Large-Scale Computing in Reservoir Simulation " In addition, a new tri-level parallel architecture pro- Pchard Ewing, University of Wyomitg...viding a large array of simple processors for image pro- The objective of reservoir simulation is to understand cessing, a medium-sized array of more

  3. 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

  4. Toward an automated parallel computing environment for geosciences

    NASA Astrophysics Data System (ADS)

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

    2007-08-01

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

  5. Solving unstructured grid problems on massively parallel computers

    NASA Technical Reports Server (NTRS)

    Hammond, Steven W.; Schreiber, Robert

    1990-01-01

    A highly parallel graph mapping technique that enables one to efficiently solve unstructured grid problems on massively parallel computers is presented. Many implicit and explicit methods for solving discretized partial differential equations require each point in the discretization to exchange data with its neighboring points every time step or iteration. The cost of this communication can negate the high performance promised by massively parallel computing. To eliminate this bottleneck, the graph of the irregular problem is mapped into the graph representing the interconnection topology of the computer such that the sum of the distances that the messages travel is minimized. It is shown that using the heuristic mapping algorithm significantly reduces the communication time compared to a naive assignment of processes to processors.

  6. CFD Analysis and Design Optimization Using Parallel Computers

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  7. Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations

    NASA Technical Reports Server (NTRS)

    Chrisochoides, Nikos

    1995-01-01

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

  8. Parallel grid generation algorithm for distributed memory computers

    NASA Technical Reports Server (NTRS)

    Moitra, Stuti; Moitra, Anutosh

    1994-01-01

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

  9. Single Circuit Parallel Computing with Phonons through Magneto-acoustics

    NASA Astrophysics Data System (ADS)

    Sklan, Sophia; Grossman, Jeffrey

    2013-03-01

    Phononic computing - the use of (typically thermal) vibrations for information processing - is a nascent technology; its capabilities are still being discovered. We analyze an alternative form of phononic computing inspired by optical, rather than electronic, computing. Using the acoustic Faraday effect, we design a phonon gyrator and thereby a means of performing computation through the manipulation of polarization in transverse phonon currents. Moreover, we establish that our gyrators act as generalized transistors and can construct digital logic gates. Exploiting the wave nature of phonons and the similarity of our logic gates, we demonstrate parallel computation within a single circuit, an effect presently unique to phonons. Finally, a generic method of designing these parallel circuits is introduced and used to analyze the feasibility of magneto-acoustic materials in realizing these circuits. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1122374.

  10. Panel on future directions in parallel computer architecture

    SciTech Connect

    VanTilborg, A.M. )

    1989-06-01

    One of the program highlights of the 15th Annual International Symposium on Computer Architecture, held May 30 - June 2, 1988 in Honolulu, was a panel session on future directions in parallel computer architecture. The panel was organized and chaired by the author, and was comprised of Prof. Jack Dennis (NASA Ames Research Institute for Advanced Computer Science), Prof. H.T. Kung (Carnegie Mellon), and Dr. Burton Smith (Tera Computer Company). The objective of the panel was to identify the likely trajectory of future parallel computer system progress, particularly from the sandpoint of marketplace acceptance. Approximately 250 attendees participated in the session, in which each panelist began with a ten minute viewgraph explanation of his views, followed by an open and sometimes lively exchange with the audience and fellow panelists. The session ran for ninety minutes.

  11. Efficient Helicopter Aerodynamic and Aeroacoustic Predictions on Parallel Computers

    NASA Technical Reports Server (NTRS)

    Wissink, Andrew M.; Lyrintzis, Anastasios S.; Strawn, Roger C.; Oliker, Leonid; Biswas, Rupak

    1996-01-01

    This paper presents parallel implementations of two codes used in a combined CFD/Kirchhoff methodology to predict the aerodynamics and aeroacoustics properties of helicopters. The rotorcraft Navier-Stokes code, TURNS, computes the aerodynamic flowfield near the helicopter blades and the Kirchhoff acoustics code computes the noise in the far field, using the TURNS solution as input. The overall parallel strategy adds MPI message passing calls to the existing serial codes to allow for communication between processors. As a result, the total code modifications required for parallel execution are relatively small. The biggest bottleneck in running the TURNS code in parallel comes from the LU-SGS algorithm that solves the implicit system of equations. We use a new hybrid domain decomposition implementation of LU-SGS to obtain good parallel performance on the SP-2. TURNS demonstrates excellent parallel speedups for quasi-steady and unsteady three-dimensional calculations of a helicopter blade in forward flight. The execution rate attained by the code on 114 processors is six times faster than the same cases run on one processor of the Cray C-90. The parallel Kirchhoff code also shows excellent parallel speedups and fast execution rates. As a performance demonstration, unsteady acoustic pressures are computed at 1886 far-field observer locations for a sample acoustics problem. The calculation requires over two hundred hours of CPU time on one C-90 processor but takes only a few hours on 80 processors of the SP2. The resultant far-field acoustic field is analyzed with state of-the-art audio and video rendering of the propagating acoustic signals.

  12. Small file aggregation in a parallel computing system

    DOEpatents

    Faibish, Sorin; Bent, John M.; Tzelnic, Percy; Grider, Gary; Zhang, Jingwang

    2014-09-02

    Techniques are provided for small file aggregation in a parallel computing system. An exemplary method for storing a plurality of files generated by a plurality of processes in a parallel computing system comprises aggregating the plurality of files into a single aggregated file; and generating metadata for the single aggregated file. The metadata comprises an offset and a length of each of the plurality of files in the single aggregated file. The metadata can be used to unpack one or more of the files from the single aggregated file.

  13. Method for implementation of recursive hierarchical segmentation on parallel computers

    NASA Technical Reports Server (NTRS)

    Tilton, James C. (Inventor)

    2005-01-01

    A method, computer readable storage, and apparatus for implementing a recursive hierarchical segmentation algorithm on a parallel computing platform. The method includes setting a bottom level of recursion that defines where a recursive division of an image into sections stops dividing, and setting an intermediate level of recursion where the recursive division changes from a parallel implementation into a serial implementation. The segmentation algorithm is implemented according to the set levels. The method can also include setting a convergence check level of recursion with which the first level of recursion communicates with when performing a convergence check.

  14. Implicit schemes and parallel computing in unstructured grid CFD

    NASA Technical Reports Server (NTRS)

    Venkatakrishnam, V.

    1995-01-01

    The development of implicit schemes for obtaining steady state solutions to the Euler and Navier-Stokes equations on unstructured grids is outlined. Applications are presented that compare the convergence characteristics of various implicit methods. Next, the development of explicit and implicit schemes to compute unsteady flows on unstructured grids is discussed. Next, the issues involved in parallelizing finite volume schemes on unstructured meshes in an MIMD (multiple instruction/multiple data stream) fashion are outlined. Techniques for partitioning unstructured grids among processors and for extracting parallelism in explicit and implicit solvers are discussed. Finally, some dynamic load balancing ideas, which are useful in adaptive transient computations, are presented.

  15. Requirements for supercomputing in energy research: The transition to massively parallel computing

    SciTech Connect

    Not Available

    1993-02-01

    This report discusses: The emergence of a practical path to TeraFlop computing and beyond; requirements of energy research programs at DOE; implementation: supercomputer production computing environment on massively parallel computers; and implementation: user transition to massively parallel computing.

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

    DOEpatents

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

    2016-03-15

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

  17. TSE computers - A means for massively parallel computations

    NASA Technical Reports Server (NTRS)

    Strong, J. P., III

    1976-01-01

    A description is presented of hardware concepts for building a massively parallel processing system for two-dimensional data. The processing system is to use logic arrays of 128 x 128 elements which perform over 16 thousand operations simultaneously. Attention is given to image data, logic arrays, basic image logic functions, a prototype negator, an interleaver device, image logic circuits, and an image memory circuit.

  18. Instant well-log inversion with a parallel computer

    SciTech Connect

    Kimminau, S.J.; Trivedi, H.

    1993-08-01

    Well-log analysis requires several vectors of input data to be inverted with a physical model that produces more vectors of output data. The problem is inherently suited to either vectorization or parallelization. PLATO (parallel log analysis, timely output) is a research prototype system that uses a parallel architecture computer with memory-mapped graphics to invert vector data and display the result rapidly. By combining this high-performance computing and display system with a graphical user interface, the analyst can interact with the system in real time'' and can visualize the result of changing parameters on up to 1,000 levels of computed volumes and reconstructed logs. It is expected that such instant'' inversion will remove the main disadvantages frequently cited for simultaneous analysis methods, namely difficulty in assessing sensitivity to different parameters and slow output response. Although the prototype system uses highly specific features of a parallel processor, a subsequent version has been implemented on a conventional (Serial) workstation with less performance but adequate functionality to preserve the apparently instant response. PLATO demonstrates the feasibility of petroleum computing applications combining an intuitive graphical interface, high-performance computing of physical models, and real-time output graphics.

  19. Parallel-vector computation for CSI-design code

    NASA Technical Reports Server (NTRS)

    Nguyen, Duc T.

    1990-01-01

    Computational aspects of Control-Structure Interaction (CSI) DESIGN code is reviewed. Numerical intensive computation portions of CSI-DESIGN code were identified. Improvements in computational speed for the CSI-DESIGN code can be achieved by exploiting parallel and vector capabilities offered by modern computers, such as the Alliant, Convex, Cray-2, and Cray-YMP. Four options to generate the coefficient stiffness matrix and to solve the system of linear, simultaneous equations are currently available in the CSI-DESIGN code. A preprocessor to use RCM (Reverse Cuthill-Mackee) algorithm for bandwidth minimization was also developed for the CSI-DESIGN code. Preliminary results obtained by solving a small-scale, 97 node CSI finite element model (for eigensolution) have indicated that this new CSI-DESIGN code is 5 to 6 times faster (using 1 Alliant processor) than the old version of CSI-DESIGN code. This speed-up was achieved due to the RCM algorithm and the use of a new skyline solver. Efforts are underway to further improve the vector speed for CSI-DESIGN code, to evaluate its performance on a larger scale CSI model (such as phase zero CSI model) to make the code run efficiently on multiprocessor, parallel computer environment, and to make the code portable among different parallel computers available at NASA LaRC, such as Alliant, Convex, and Cray computers.

  20. Solution of partial differential equations on vector and parallel computers

    NASA Technical Reports Server (NTRS)

    Ortega, J. M.; Voigt, R. G.

    1985-01-01

    The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed.

  1. 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.

  2. 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…

  3. Solving tridiagonal linear systems on the Butterfly parallel computer

    SciTech Connect

    Kumar, S.P.

    1989-01-01

    A parallel block partitioning method to solve a tri-diagonal system of linear equations is adapted to the BBN Butterfly multiprocessor. A performance analysis of the programming experiments on the 32-node Butterfly is presented. An upper bound on the number of processors to achieve the best performance with this method is derived. The computational results verify the theoretical speedup and efficiency results of the parallel algorithm over its serial counterpart. Also included is a study comparing performance runs of the same code on the Butterfly processor with a hardware floating point unit and on one with a software floating point facility. The total parallel time of the given code is considerably reduced by making use of the hardware floating point facility whereas the speedup and efficiency of the parallel program considerably improve on the system with software floating point capability. The achieved results are shown to be within 82% to 90% of the predicted performance.

  4. The science of computing - The evolution of parallel processing

    NASA Technical Reports Server (NTRS)

    Denning, P. J.

    1985-01-01

    The present paper is concerned with the approaches to be employed to overcome the set of limitations in software technology which impedes currently an effective use of parallel hardware technology. The process required to solve the arising problems is found to involve four different stages. At the present time, Stage One is nearly finished, while Stage Two is under way. Tentative explorations are beginning on Stage Three, and Stage Four is more distant. In Stage One, parallelism is introduced into the hardware of a single computer, which consists of one or more processors, a main storage system, a secondary storage system, and various peripheral devices. In Stage Two, parallel execution of cooperating programs on different machines becomes explicit, while in Stage Three, new languages will make parallelism implicit. In Stage Four, there will be very high level user interfaces capable of interacting with scientists at the same level of abstraction as scientists do with each other.

  5. A Low-Cost, Portable, Parallel Computing Cluster

    NASA Astrophysics Data System (ADS)

    Bullock, Daniel; Poppeliers, Christian; Allen, Charles

    2006-10-01

    Research in modern physical sciences has placed an increasing demand on computers for complex algorithms that push the limits of consumer personal computers. Parallel supercomputers are often required for large-scale algorithms, however the cost of these systems can be prohibitive. The purpose of this project is to construct a low-cost, portable, parallel computer system as an alternative to large-scale supercomputers, using Commercial Off The Shelf (COTS) components. These components can be networked together to allow processors to communicate with one another for faster computations. The overall design of this system is based on the development of ``Little Fe'' at Contra Costa College in San Pablo, California. Revisions to this design include improved design components, smaller physical size, easier transportation, less wiring, and a single AC power supply.

  6. Parallel algorithms for computation of the manipulator inertia matrix

    NASA Technical Reports Server (NTRS)

    Amin-Javaheri, Masoud; Orin, David E.

    1989-01-01

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

  7. Parallelization of Finite Element Analysis Codes Using Heterogeneous Distributed Computing

    NASA Technical Reports Server (NTRS)

    Ozguner, Fusun

    1996-01-01

    Performance gains in computer design are quickly consumed as users seek to analyze larger problems to a higher degree of accuracy. Innovative computational methods, such as parallel and distributed computing, seek to multiply the power of existing hardware technology to satisfy the computational demands of large applications. In the early stages of this project, experiments were performed using two large, coarse-grained applications, CSTEM and METCAN. These applications were parallelized on an Intel iPSC/860 hypercube. It was found that the overall speedup was very low, due to large, inherently sequential code segments present in the applications. The overall execution time T(sub par), of the application is dependent on these sequential segments. If these segments make up a significant fraction of the overall code, the application will have a poor speedup measure.

  8. CRBLASTER: A Parallel-Processing Computational Framework for Embarrassingly Parallel Image-Analysis Algorithms

    NASA Astrophysics Data System (ADS)

    Mighell, Kenneth John

    2010-10-01

    The development of parallel-processing image-analysis codes is generally a challenging task that requires complicated choreography of interprocessor communications. If, however, the image-analysis algorithm is embarrassingly parallel, then the development of a parallel-processing implementation of that algorithm can be a much easier task to accomplish because, by definition, there is little need for communication between the compute processes. I describe the design, implementation, and performance of a parallel-processing image-analysis application, called crblaster, which does cosmic-ray rejection of CCD images using the embarrassingly parallel l.a.cosmic algorithm. crblaster is written in C using the high-performance computing industry standard Message Passing Interface (MPI) library. crblaster uses a two-dimensional image partitioning algorithm that partitions an input image into N rectangular subimages of nearly equal area; the subimages include sufficient additional pixels along common image partition edges such that the need for communication between computer processes is eliminated. The code has been designed to be used by research scientists who are familiar with C as a parallel-processing computational framework that enables the easy development of parallel-processing image-analysis programs based on embarrassingly parallel algorithms. The crblaster source code is freely available at the official application Web site at the National Optical Astronomy Observatory. Removing cosmic rays from a single 800 × 800 pixel Hubble Space Telescope WFPC2 image takes 44 s with the IRAF script lacos_im.cl running on a single core of an Apple Mac Pro computer with two 2.8 GHz quad-core Intel Xeon processors. crblaster is 7.4 times faster when processing the same image on a single core on the same machine. Processing the same image with crblaster simultaneously on all eight cores of the same machine takes 0.875 s—which is a speedup factor of 50.3 times faster than the

  9. Variable-Complexity Multidisciplinary Optimization on Parallel Computers

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  10. Parallelization of implicit finite difference schemes in computational fluid dynamics

    NASA Technical Reports Server (NTRS)

    Decker, Naomi H.; Naik, Vijay K.; Nicoules, Michel

    1990-01-01

    Implicit finite difference schemes are often the preferred numerical schemes in computational fluid dynamics, requiring less stringent stability bounds than the explicit schemes. Each iteration in an implicit scheme involves global data dependencies in the form of second and higher order recurrences. Efficient parallel implementations of such iterative methods are considerably more difficult and non-intuitive. The parallelization of the implicit schemes that are used for solving the Euler and the thin layer Navier-Stokes equations and that require inversions of large linear systems in the form of block tri-diagonal and/or block penta-diagonal matrices is discussed. Three-dimensional cases are emphasized and schemes that minimize the total execution time are presented. Partitioning and scheduling schemes for alleviating the effects of the global data dependencies are described. An analysis of the communication and the computation aspects of these methods is presented. The effect of the boundary conditions on the parallel schemes is also discussed.

  11. Traffic simulations on parallel computers using domain decomposition techniques

    SciTech Connect

    Hanebutte, U.R.; Tentner, A.M.

    1995-12-31

    Large scale simulations of Intelligent Transportation Systems (ITS) can only be achieved by using the computing resources offered by parallel computing architectures. Domain decomposition techniques are proposed which allow the performance of traffic simulations with the standard simulation package TRAF-NETSIM on a 128 nodes IBM SPx parallel supercomputer as well as on a cluster of SUN workstations. Whilst this particular parallel implementation is based on NETSIM, a microscopic traffic simulation model, the presented strategy is applicable to a broad class of traffic simulations. An outer iteration loop must be introduced in order to converge to a global solution. A performance study that utilizes a scalable test network that consist of square-grids is presented, which addresses the performance penalty introduced by the additional iteration loop.

  12. Measuring performance of parallel computers. Progress report, 1989

    SciTech Connect

    Sullivan, F.

    1994-07-01

    Performance Measurement - the authors have developed a taxonomy of parallel algorithms based on data motion and example applications have been coded for each class of the taxonomy. Computational benchmark kernels have been extracted for several applications, and detailed measurements have been performed. Algorithms for Massively Parallel SIMD machines - measurement results and computational experiences indicate that top performance will be achieved by `iteration` type algorithms running on massively parallel SIMD machines. Reformulation as iteration may entail unorthodox approaches based on probabilistic methods. The authors have developed such methods for some applications. Here they discuss their approach to performance measurement, describe the taxonomy and measurements which have been made, and report on some general conclusions which can be drawn from the results of the measurements.

  13. Element-topology-independent preconditioners for parallel finite element computations

    NASA Technical Reports Server (NTRS)

    Park, K. C.; Alexander, Scott

    1992-01-01

    A family of preconditioners for the solution of finite element equations are presented, which are element-topology independent and thus can be applicable to element order-free parallel computations. A key feature of the present preconditioners is the repeated use of element connectivity matrices and their left and right inverses. The properties and performance of the present preconditioners are demonstrated via beam and two-dimensional finite element matrices for implicit time integration computations.

  14. Diderot: a Domain-Specific Language for Portable Parallel Scientific Visualization and Image Analysis.

    PubMed

    Kindlmann, Gordon; Chiw, Charisee; Seltzer, Nicholas; Samuels, Lamont; Reppy, John

    2016-01-01

    Many algorithms for scientific visualization and image analysis are rooted in the world of continuous scalar, vector, and tensor fields, but are programmed in low-level languages and libraries that obscure their mathematical foundations. Diderot is a parallel domain-specific language that is designed to bridge this semantic gap by providing the programmer with a high-level, mathematical programming notation that allows direct expression of mathematical concepts in code. Furthermore, Diderot provides parallel performance that takes advantage of modern multicore processors and GPUs. The high-level notation allows a concise and natural expression of the algorithms and the parallelism allows efficient execution on real-world datasets.

  15. Hardware packet pacing using a DMA in a parallel computer

    DOEpatents

    Chen, Dong; Heidelberger, Phillip; Vranas, Pavlos

    2013-08-13

    Method and system for hardware packet pacing using a direct memory access controller in a parallel computer which, in one aspect, keeps track of a total number of bytes put on the network as a result of a remote get operation, using a hardware token counter.

  16. Efficiently modeling neural networks on massively parallel computers

    NASA Technical Reports Server (NTRS)

    Farber, Robert M.

    1993-01-01

    Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

  17. Fencing data transfers in a parallel active messaging interface of a parallel computer

    DOEpatents

    Blocksome, Michael A.; Mamidala, Amith R.

    2015-06-09

    Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task; the compute nodes coupled for data communications through the PAMI and through data communications resources including at least one segment of shared random access memory; including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers through a segment of shared memory; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

  18. Fencing data transfers in a parallel active messaging interface of a parallel computer

    DOEpatents

    Blocksome, Michael A.; Mamidala, Amith R.

    2015-06-02

    Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task; the compute nodes coupled for data communications through the PAMI and through data communications resources including at least one segment of shared random access memory; including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers through a segment of shared memory; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

  19. Fencing data transfers in a parallel active messaging interface of a parallel computer

    DOEpatents

    Blocksome, Michael A.; Mamidala, Amith R.

    2015-06-30

    Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

  20. Fencing data transfers in a parallel active messaging interface of a parallel computer

    DOEpatents

    Blocksome, Michael A.; Mamidala, Amith R.

    2015-08-11

    Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

  1. Computing through Scientific Abstractions in SysBioPS

    SciTech Connect

    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 important 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.

  2. Scientific computing infrastructure and services in Moldova

    NASA Astrophysics Data System (ADS)

    Bogatencov, P. P.; Secrieru, G. V.; Degteariov, N. V.; Iliuha, N. P.

    2016-09-01

    In recent years distributed information processing and high-performance computing technologies (HPC, distributed Cloud and Grid computing infrastructures) for solving complex tasks with high demands of computing resources are actively developing. In Moldova the works on creation of high-performance and distributed computing infrastructures were started relatively recently due to participation in implementation of a number of international projects. Research teams from Moldova participated in a series of regional and pan-European projects that allowed them to begin forming the national heterogeneous computing infrastructure, get access to regional and European computing resources, and expand the range and areas of solving tasks.

  3. High Performance Input/Output for Parallel Computer Systems

    NASA Technical Reports Server (NTRS)

    Ligon, W. B.

    1996-01-01

    The goal of our project is to study the I/O characteristics of parallel applications used in Earth Science data processing systems such as Regional Data Centers (RDCs) or EOSDIS. Our approach is to study the runtime behavior of typical programs and the effect of key parameters of the I/O subsystem both under simulation and with direct experimentation on parallel systems. Our three year activity has focused on two items: developing a test bed that facilitates experimentation with parallel I/O, and studying representative programs from the Earth science data processing application domain. The Parallel Virtual File System (PVFS) has been developed for use on a number of platforms including the Tiger Parallel Architecture Workbench (TPAW) simulator, The Intel Paragon, a cluster of DEC Alpha workstations, and the Beowulf system (at CESDIS). PVFS provides considerable flexibility in configuring I/O in a UNIX- like environment. Access to key performance parameters facilitates experimentation. We have studied several key applications fiom levels 1,2 and 3 of the typical RDC processing scenario including instrument calibration and navigation, image classification, and numerical modeling codes. We have also considered large-scale scientific database codes used to organize image data.

  4. Computationally efficient implementation of combustion chemistry in parallel PDF calculations

    SciTech Connect

    Lu Liuyan Lantz, Steven R.; Ren Zhuyin; Pope, Stephen B.

    2009-08-20

    In parallel calculations of combustion processes with realistic chemistry, the serial in situ adaptive tabulation (ISAT) algorithm [S.B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combustion Theory and Modelling, 1 (1997) 41-63; L. Lu, S.B. Pope, An improved algorithm for in situ adaptive tabulation, Journal of Computational Physics 228 (2009) 361-386] substantially speeds up the chemistry calculations on each processor. To improve the parallel efficiency of large ensembles of such calculations in parallel computations, in this work, the ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble. Parallel ISAT strategies are developed by combining the existing serial ISAT algorithm with different distribution strategies, namely purely local processing (PLP), uniformly random distribution (URAN), and preferential distribution (PREF). The distribution strategies enable the queued load redistribution of chemistry calculations among processors using message passing. They are implemented in the software x2f{sub m}pi, which is a Fortran 95 library for facilitating many parallel evaluations of a general vector function. The relative performance of the parallel ISAT strategies is investigated in different computational regimes via the PDF calculations of multiple partially stirred reactors burning methane/air mixtures. The results show that the performance of ISAT with a fixed distribution strategy strongly depends on certain computational regimes, based on how much memory is available and how much overlap exists between tabulated information on different processors. No one fixed strategy consistently achieves good performance in all the regimes. Therefore, an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented. It yields consistently good performance in all regimes. In the adaptive

  5. Computationally efficient implementation of combustion chemistry in parallel PDF calculations

    NASA Astrophysics Data System (ADS)

    Lu, Liuyan; Lantz, Steven R.; Ren, Zhuyin; Pope, Stephen B.

    2009-08-01

    In parallel calculations of combustion processes with realistic chemistry, the serial in situ adaptive tabulation (ISAT) algorithm [S.B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combustion Theory and Modelling, 1 (1997) 41-63; L. Lu, S.B. Pope, An improved algorithm for in situ adaptive tabulation, Journal of Computational Physics 228 (2009) 361-386] substantially speeds up the chemistry calculations on each processor. To improve the parallel efficiency of large ensembles of such calculations in parallel computations, in this work, the ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble. Parallel ISAT strategies are developed by combining the existing serial ISAT algorithm with different distribution strategies, namely purely local processing (PLP), uniformly random distribution (URAN), and preferential distribution (PREF). The distribution strategies enable the queued load redistribution of chemistry calculations among processors using message passing. They are implemented in the software x2f_mpi, which is a Fortran 95 library for facilitating many parallel evaluations of a general vector function. The relative performance of the parallel ISAT strategies is investigated in different computational regimes via the PDF calculations of multiple partially stirred reactors burning methane/air mixtures. The results show that the performance of ISAT with a fixed distribution strategy strongly depends on certain computational regimes, based on how much memory is available and how much overlap exists between tabulated information on different processors. No one fixed strategy consistently achieves good performance in all the regimes. Therefore, an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented. It yields consistently good performance in all regimes. In the adaptive parallel

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

    DOEpatents

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

    2015-07-21

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

  7. Berkeley Lab Computing Sciences: Accelerating Scientific Discovery

    SciTech Connect

    Hules, John A

    2008-12-12

    Scientists today rely on advances in computer science, mathematics, and computational science, as well as large-scale computing and networking facilities, to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab's Computing Sciences organization researches, develops, and deploys new tools and technologies to meet these needs and to advance research in such areas as global climate change, combustion, fusion energy, nanotechnology, biology, and astrophysics.

  8. Superfast robust digital image correlation analysis with parallel computing

    NASA Astrophysics Data System (ADS)

    Pan, Bing; Tian, Long

    2015-03-01

    Existing digital image correlation (DIC) using the robust reliability-guided displacement tracking (RGDT) strategy for full-field displacement measurement is a path-dependent process that can only be executed sequentially. This path-dependent tracking strategy not only limits the potential of DIC for further improvement of its computational efficiency but also wastes the parallel computing power of modern computers with multicore processors. To maintain the robustness of the existing RGDT strategy and to overcome its deficiency, an improved RGDT strategy using a two-section tracking scheme is proposed. In the improved RGDT strategy, the calculated points with correlation coefficients higher than a preset threshold are all taken as reliably computed points and given the same priority to extend the correlation analysis to their neighbors. Thus, DIC calculation is first executed in parallel at multiple points by separate independent threads. Then for the few calculated points with correlation coefficients smaller than the threshold, DIC analysis using existing RGDT strategy is adopted. Benefiting from the improved RGDT strategy and the multithread computing, superfast DIC analysis can be accomplished without sacrificing its robustness and accuracy. Experimental results show that the presented parallel DIC method performed on a common eight-core laptop can achieve about a 7 times speedup.

  9. Boundary element analysis on vector and parallel computers

    NASA Technical Reports Server (NTRS)

    Kane, J. H.

    1994-01-01

    Boundary element analysis (BEA) can be characterized as a numerical technique that generally shifts the computational burden in the analysis toward numerical integration and the solution of nonsymmetric and either dense or blocked sparse systems of algebraic equations. Researchers have explored the concept that the fundamental characteristics of BEA can be exploited to generate effective implementations on vector and parallel computers. In this paper, the results of some of these investigations are discussed. The performance of overall algorithms for BEA on vector supercomputers, massively data parallel single instruction multiple data (SIMD), and relatively fine grained distributed memory multiple instruction multiple data (MIMD) computer systems is described. Some general trends and conclusions are discussed, along with indications of future developments that may prove fruitful in this regard.

  10. A Simple Physical Optics Algorithm Perfect for Parallel Computing

    NASA Technical Reports Server (NTRS)

    Imbriale, W. A.; Cwik, T.

    1993-01-01

    One of the simplest reflector antenna computer programs is based upon a discrete approximation of the radiation integral. This calculation replaces the actual reflector surface with a triangular facet representation so that the reflector resembles a geodesic dome. The Physical Optics (PO) current is assumed to be constant in magnitude and phase over each facet so the radiation integral is reduced to a simple summation. This program has proven to be surprisingly robust and useful for the analysis of arbitrary reflectors, particularly when the near-field is desired and surface derivatives are not known. Because of its simplicity, the algorithm has proven to be extremely easy to adapt to the parallel computing architecture of a modest number of large-grain computing elements such as are used in the Intel iPSC and Touchstone Delta parallel machines.

  11. Parallel distance matrix computation for Matlab data mining

    NASA Astrophysics Data System (ADS)

    Skurowski, Przemysław; Staniszewski, Michał

    2016-06-01

    The paper presents utility functions for computing of a distance matrix, which plays a crucial role in data mining. The goal in the design was to enable operating on relatively large datasets by overcoming basic shortcoming - computing time - with an interface easy to use. The presented solution is a set of functions, which were created with emphasis on practical applicability in real life. The proposed solution is presented along the theoretical background for the performance scaling. Furthermore, different approaches of the parallel computing are analyzed, including shared memory, which is uncommon in Matlab environment.

  12. Computing NLTE Opacities -- Node Level Parallel Calculation

    SciTech Connect

    Holladay, Daniel

    2015-09-11

    Presentation. The goal: to produce a robust library capable of computing reasonably accurate opacities inline with the assumption of LTE relaxed (non-LTE). Near term: demonstrate acceleration of non-LTE opacity computation. Far term (if funded): connect to application codes with in-line capability and compute opacities. Study science problems. Use efficient algorithms that expose many levels of parallelism and utilize good memory access patterns for use on advanced architectures. Portability to multiple types of hardware including multicore processors, manycore processors such as KNL, GPUs, etc. Easily coupled to radiation hydrodynamics and thermal radiative transfer codes.

  13. Parallelism in computational chemistry: Applications in quantum and statistical mechanics

    NASA Astrophysics Data System (ADS)

    Clementi, E.; Corongiu, G.; Detrich, J. H.; Kahnmohammadbaigi, H.; Chin, S.; Domingo, L.; Laaksonen, A.; Nguyen, N. L.

    1985-08-01

    Often very fundamental biochemical and biophysical problems defy simulations because of limitation in today's computers. We present and discuss a distributed system composed of two IBM-4341 and one IBM-4381, as front-end processors, and ten FPS-164 attached array processors. This parallel system-called LCAP-has presently a peak performance of about 120 MFlops; extensions to higher performance are discussed. Presently, the system applications use a modified version of VM/SP as the operating system: description of the modifications is given. Three applications programs have migrated from sequential to parallel; a molecular quantum mechanical, a Metropolis-Monte Carlo and a Molecular Dynamics program. Descriptions of the parallel codes are briefly outlined. As examples and tests of these applications we report on a study for proton tunneling in DNA base-pairs, very relevant to spontaneous mutations in genetics. As a second example, we present a Monte Carlo study of liquid water at room temperature where not only two- and three-body interactions are considered but-for the first time-also four-body interactions are included. Finally we briefly summarize a molecular dynamics study where two- and three-body interactions have been considered. These examples, and very positive performance comparison with today's supercomputers allow us to conclude that parallel computers and programming of the type we have considered, represent a pragmatic answer to many computer intensive problems.

  14. Parallel computing in genomic research: advances and applications

    PubMed Central

    Ocaña, Kary; de Oliveira, Daniel

    2015-01-01

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

  15. New Parallel computing framework for radiation transport codes

    SciTech Connect

    Kostin, M.A.; Mokhov, N.V.; Niita, K.; /JAERI, Tokai

    2010-09-01

    A new parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. The module is significantly independent of radiation transport codes it can be used with, and is connected to the codes by means of a number of interface functions. The framework was integrated with the MARS15 code, and an effort is under way to deploy it in PHITS. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility can be used in single process calculations as well as in the parallel regime. Several checkpoint files can be merged into one thus combining results of several calculations. The framework also corrects some of the known problems with the scheduling and load balancing found in the original implementations of the parallel computing functionality in MARS15 and PHITS. The framework can be used efficiently on homogeneous systems and networks of workstations, where the interference from the other users is possible.

  16. Parallel computing in genomic research: advances and applications.

    PubMed

    Ocaña, Kary; de Oliveira, Daniel

    2015-01-01

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

  17. Experiences with the Lanczos method on a parallel computer

    NASA Technical Reports Server (NTRS)

    Bostic, Susan W.; Fulton, Robert E.

    1987-01-01

    A parallel computer implementation of the Lanczos method for the free-vibration analysis of structures is considered, and results for two example problems show substantial time-reduction over the sequential solutions. The major Lanczos calculation tasks are subdivided into subtasks, and parallelism is introduced at the subtask level. A speedup of 7.8 on eight processors was obtained for the decomposition step of the problem involving a 60-m three-longeron space mast, and a speedup of 14.6 on 16 processors was obtained for the decomposition step of the problem involving a blade-stiffened graphite-epoxy panel.

  18. A language comparison for scientific computing on MIMD architectures

    NASA Technical Reports Server (NTRS)

    Jones, Mark T.; Patrick, Merrell L.; Voigt, Robert G.

    1989-01-01

    Choleski's method for solving banded symmetric, positive definite systems is implemented on a multiprocessor computer using three FORTRAN based parallel programming languages, the Force, PISCES and Concurrent FORTRAN. The capabilities of the language for expressing parallelism and their user friendliness are discussed, including readability of the code, debugging assistance offered, and expressiveness of the languages. The performance of the different implementations is compared. It is argued that PISCES, using the Force for medium-grained parallelism, is the appropriate choice for programming Choleski's method on the multiprocessor computer, Flex/32.

  19. The 2nd Symposium on the Frontiers of Massively Parallel Computations

    NASA Technical Reports Server (NTRS)

    Mills, Ronnie (Editor)

    1988-01-01

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

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

    DOEpatents

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

    2015-02-03

    Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a SEND instruction, the SEND instruction specifying a transmission of transfer data from the origin endpoint to a first target endpoint; transmitting from the origin endpoint to the first target endpoint a Request-To-Send (`RTS`) message advising the first target endpoint of the location and size of the transfer data; assigning by the first target endpoint to each of a plurality of target endpoints separate portions of the transfer data; and receiving by the plurality of target endpoints the transfer data.

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

    DOEpatents

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

    2014-11-18

    Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a SEND instruction, the SEND instruction specifying a transmission of transfer data from the origin endpoint to a first target endpoint; transmitting from the origin endpoint to the first target endpoint a Request-To-Send (`RTS`) message advising the first target endpoint of the location and size of the transfer data; assigning by the first target endpoint to each of a plurality of target endpoints separate portions of the transfer data; and receiving by the plurality of target endpoints the transfer data.

  2. 3D seismic imaging on massively parallel computers

    SciTech Connect

    Womble, D.E.; Ober, C.C.; Oldfield, R.

    1997-02-01

    The ability to image complex geologies such as salt domes in the Gulf of Mexico and thrusts in mountainous regions is a key to reducing the risk and cost associated with oil and gas exploration. Imaging these structures, however, is computationally expensive. Datasets can be terabytes in size, and the processing time required for the multiple iterations needed to produce a velocity model can take months, even with the massively parallel computers available today. Some algorithms, such as 3D, finite-difference, prestack, depth migration remain beyond the capacity of production seismic processing. Massively parallel processors (MPPs) and algorithms research are the tools that will enable this project to provide new seismic processing capabilities to the oil and gas industry. The goals of this work are to (1) develop finite-difference algorithms for 3D, prestack, depth migration; (2) develop efficient computational approaches for seismic imaging and for processing terabyte datasets on massively parallel computers; and (3) develop a modular, portable, seismic imaging code.

  3. Distributed parallel computing in stochastic modeling of groundwater systems.

    PubMed

    Dong, Yanhui; Li, Guomin; Xu, Haizhen

    2013-03-01

    Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling.

  4. 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

  5. Implementation of ADI: Schemes on MIMD parallel computers

    NASA Technical Reports Server (NTRS)

    Vanderwijngaart, Rob F.

    1993-01-01

    In order to simulate the effects of the impingement of hot exhaust jets of High Performance Aircraft on landing surfaces a multi-disciplinary computation coupling flow dynamics to heat conduction in the runway needs to be carried out. Such simulations, which are essentially unsteady, require very large computational power in order to be completed within a reasonable time frame of the order of an hour. Such power can be furnished by the latest generation of massively parallel computers. These remove the bottleneck of ever more congested data paths to one or a few highly specialized central processing units (CPU's) by having many off-the-shelf CPU's work independently on their own data, and exchange information only when needed. During the past year the first phase of this project was completed, in which the optimal strategy for mapping an ADI-algorithm for the three dimensional unsteady heat equation to a MIMD parallel computer was identified. This was done by implementing and comparing three different domain decomposition techniques that define the tasks for the CPU's in the parallel machine. These implementations were done for a Cartesian grid and Dirichlet boundary conditions. The most promising technique was then used to implement the heat equation solver on a general curvilinear grid with a suite of nontrivial boundary conditions. Finally, this technique was also used to implement the Scalar Penta-diagonal (SP) benchmark, which was taken from the NAS Parallel Benchmarks report. All implementations were done in the programming language C on the Intel iPSC/860 computer.

  6. 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…

  7. Executing a gather operation on a parallel computer

    DOEpatents

    Archer, Charles J [Rochester, MN; Ratterman, Joseph D [Rochester, MN

    2012-03-20

    Methods, apparatus, and computer program products are disclosed for executing a gather operation on a parallel computer according to embodiments of the present invention. Embodiments include configuring, by the logical root, a result buffer or the logical root, the result buffer having positions, each position corresponding to a ranked node in the operational group and for storing contribution data gathered from that ranked node. Embodiments also include repeatedly for each position in the result buffer: determining, by each compute node of an operational group, whether the current position in the result buffer corresponds with the rank of the compute node, if the current position in the result buffer corresponds with the rank of the compute node, contributing, by that compute node, the compute node's contribution data, if the current position in the result buffer does not correspond with the rank of the compute node, contributing, by that compute node, a value of zero for the contribution data, and storing, by the logical root in the current position in the result buffer, results of a bitwise OR operation of all the contribution data by all compute nodes of the operational group for the current position, the results received through the global combining network.

  8. A Parallel Computational Model for Multichannel Phase Unwrapping Problem

    NASA Astrophysics Data System (ADS)

    Imperatore, Pasquale; Pepe, Antonio; Lanari, Riccardo

    2015-05-01

    In this paper, a parallel model for the solution of the computationally intensive multichannel phase unwrapping (MCh-PhU) problem is proposed. Firstly, the Extended Minimum Cost Flow (EMCF) algorithm for solving MCh-PhU problem is revised within the rigorous mathematical framework of the discrete calculus ; thus permitting to capture its topological structure in terms of meaningful discrete differential operators. Secondly, emphasis is placed on those methodological and practical aspects, which lead to a parallel reformulation of the EMCF algorithm. Thus, a novel dual-level parallel computational model, in which the parallelism is hierarchically implemented at two different (i.e., process and thread) levels, is presented. The validity of our approach has been demonstrated through a series of experiments that have revealed a significant speedup. Therefore, the attained high-performance prototype is suitable for the solution of large-scale phase unwrapping problems in reasonable time frames, with a significant impact on the systematic exploitation of the existing, and rapidly growing, large archives of SAR data.

  9. Final Report: Center for Programming Models for Scalable Parallel Computing

    SciTech Connect

    Mellor-Crummey, John

    2011-09-13

    As part of the Center for Programming Models for Scalable Parallel Computing, Rice University collaborated with project partners in the design, development and deployment of language, compiler, and runtime support for parallel programming models to support application development for the “leadership-class” computer systems at DOE national laboratories. Work over the course of this project has focused on the design, implementation, and evaluation of a second-generation version of Coarray Fortran. Research and development efforts of the project have focused on the CAF 2.0 language, compiler, runtime system, and supporting infrastructure. This has involved working with the teams that provide infrastructure for CAF that we rely on, implementing new language and runtime features, producing an open source compiler that enabled us to evaluate our ideas, and evaluating our design and implementation through the use of benchmarks. The report details the research, development, findings, and conclusions from this work.

  10. Probabilistic structural mechanics research for parallel processing computers

    NASA Technical Reports Server (NTRS)

    Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Martin, William R.

    1991-01-01

    Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical.

  11. Performing a local reduction operation on a parallel computer

    SciTech Connect

    Blocksome, Michael A.; Faraj, Daniel A.

    2012-12-11

    A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.

  12. Performing a local reduction operation on a parallel computer

    DOEpatents

    Blocksome, Michael A; Faraj, Daniel A

    2013-06-04

    A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.

  13. Establishing a group of endpoints in a parallel computer

    DOEpatents

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

    2016-02-02

    A parallel computer executes a number of tasks, each task includes a number of endpoints and the endpoints are configured to support collective operations. In such a parallel computer, establishing a group of endpoints receiving a user specification of a set of endpoints included in a global collection of endpoints, where the user specification defines the set in accordance with a predefined virtual representation of the endpoints, the predefined virtual representation is a data structure setting forth an organization of tasks and endpoints included in the global collection of endpoints and the user specification defines the set of endpoints without a user specification of a particular endpoint; and defining a group of endpoints in dependence upon the predefined virtual representation of the endpoints and the user specification.

  14. Temporal locality optimizations for stencil operations for parallel object-oriented scientific frameworks on cache-based architectures

    SciTech Connect

    Bassetti, F.; Davis, K.; Quinlan, D.

    1998-12-01

    High-performance scientific computing relies increasingly on high-level large-scale object-oriented software frameworks to manage both algorithmic complexity and the complexities of parallelism: distributed data management, process management, inter-process communication, and load balancing. This encapsulation of data management, together with the prescribed semantics of a typical fundamental component of such object-oriented frameworks--a parallel or serial array-class library--provides an opportunity for increasingly sophisticated compile-time optimization techniques. This paper describes a technique for introducing cache blocking suitable for certain classes of numerical algorithms, demonstrates and analyzes the resulting performance gains, and indicates how this optimization transformation is being automated.

  15. Optimizing transformations of stencil operations for parallel object-oriented scientific frameworks on cache-based architectures

    SciTech Connect

    Bassetti, F.; Davis, K.; Quinlan, D.

    1998-12-31

    High-performance scientific computing relies increasingly on high-level large-scale object-oriented software frameworks to manage both algorithmic complexity and the complexities of parallelism: distributed data management, process management, inter-process communication, and load balancing. This encapsulation of data management, together with the prescribed semantics of a typical fundamental component of such object-oriented frameworks--a parallel or serial array-class library--provides an opportunity for increasingly sophisticated compile-time optimization techniques. This paper describes two optimizing transformations suitable for certain classes of numerical algorithms, one for reducing the cost of inter-processor communication, and one for improving cache utilization; demonstrates and analyzes the resulting performance gains; and indicates how these transformations are being automated.

  16. Modeling of supersonic combustor flows using parallel computing

    NASA Technical Reports Server (NTRS)

    Riggins, D.; Underwood, M.; Mcmillin, B.; Reeves, L.; Lu, E. J.-L.

    1992-01-01

    While current 3D CFD codes and modeling techniques have been shown capable of furnishing engineering data for complex scramjet flowfields, the usefulness of such efforts is primarily limited by solutions' CPU time requirements, and secondarily by memory requirements. Attention is presently given to the use of parallel computing capabilities for engineering CFD tools for the analysis of supersonic reacting flows, and to an illustrative incompressible CFD problem using up to 16 iPSC/2 processors with single-domain decomposition.

  17. Simulation methods for advanced scientific computing

    SciTech Connect

    Booth, T.E.; Carlson, J.A.; Forster, R.A.

    1998-11-01

    This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of the project was to create effective new algorithms for solving N-body problems by computer simulation. The authors concentrated on developing advanced classical and quantum Monte Carlo techniques. For simulations of phase transitions in classical systems, they produced a framework generalizing the famous Swendsen-Wang cluster algorithms for Ising and Potts models. For spin-glass-like problems, they demonstrated the effectiveness of an extension of the multicanonical method for the two-dimensional, random bond Ising model. For quantum mechanical systems, they generated a new method to compute the ground-state energy of systems of interacting electrons. They also improved methods to compute excited states when the diffusion quantum Monte Carlo method is used and to compute longer time dynamics when the stationary phase quantum Monte Carlo method is used.

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

    DOEpatents

    Faraj, Ahmad [Rochester, MN

    2012-04-17

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

  19. Piecewise - Parabolic Methods for Parallel Computation with Applications to Unstable Fluid Flow in 2 and 3 Dimensions

    SciTech Connect

    Woodward, P. R.

    2003-03-26

    This report summarizes the results of the project entitled, ''Piecewise-Parabolic Methods for Parallel Computation with Applications to Unstable Fluid Flow in 2 and 3 Dimensions'' This project covers a span of many years, beginning in early 1987. It has provided over that considerable period the core funding to my research activities in scientific computation at the University of Minnesota. It has supported numerical algorithm development, application of those algorithms to fundamental fluid dynamics problems in order to demonstrate their effectiveness, and the development of scientific visualization software and systems to extract scientific understanding from those applications.

  20. Domain decomposition methods for the parallel computation of reacting flows

    NASA Technical Reports Server (NTRS)

    Keyes, David E.

    1988-01-01

    Domain decomposition is a natural route to parallel computing for partial differential equation solvers. Subdomains of which the original domain of definition is comprised are assigned to independent processors at the price of periodic coordination between processors to compute global parameters and maintain the requisite degree of continuity of the solution at the subdomain interfaces. In the domain-decomposed solution of steady multidimensional systems of PDEs by finite difference methods using a pseudo-transient version of Newton iteration, the only portion of the computation which generally stands in the way of efficient parallelization is the solution of the large, sparse linear systems arising at each Newton step. For some Jacobian matrices drawn from an actual two-dimensional reacting flow problem, comparisons are made between relaxation-based linear solvers and also preconditioned iterative methods of Conjugate Gradient and Chebyshev type, focusing attention on both iteration count and global inner product count. The generalized minimum residual method with block-ILU preconditioning is judged the best serial method among those considered, and parallel numerical experiments on the Encore Multimax demonstrate for it approximately 10-fold speedup on 16 processors.

  1. Parallel and vector computation for stochastic optimal control applications

    NASA Technical Reports Server (NTRS)

    Hanson, F. B.

    1989-01-01

    A general method for parallel and vector numerical solutions of stochastic dynamic programming problems is described for optimal control of general nonlinear, continuous time, multibody dynamical systems, perturbed by Poisson as well as Gaussian random white noise. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random atmospheric fluctuations. The numerical formulation is highly suitable for a vector multiprocessor or vectorizing supercomputer, and results exhibit high processor efficiency and numerical stability. Advanced computing techniques, data structures, and hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations.

  2. Local rollback for fault-tolerance in parallel computing systems

    DOEpatents

    Blumrich, Matthias A [Yorktown Heights, NY; Chen, Dong [Yorktown Heights, NY; Gara, Alan [Yorktown Heights, NY; Giampapa, Mark E [Yorktown Heights, NY; Heidelberger, Philip [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Steinmacher-Burow, Burkhard [Boeblingen, DE; Sugavanam, Krishnan [Yorktown Heights, NY

    2012-01-24

    A control logic device performs a local rollback in a parallel super computing system. The super computing system includes at least one cache memory device. The control logic device determines a local rollback interval. The control logic device runs at least one instruction in the local rollback interval. The control logic device evaluates whether an unrecoverable condition occurs while running the at least one instruction during the local rollback interval. The control logic device checks whether an error occurs during the local rollback. The control logic device restarts the local rollback interval if the error occurs and the unrecoverable condition does not occur during the local rollback interval.

  3. 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

  4. Runtime optimization of an application executing on a parallel computer

    DOEpatents

    Faraj, Daniel A; Smith, Brian E

    2014-11-18

    Identifying a collective operation within an application executing on a parallel computer; identifying a call site of the collective operation; determining whether the collective operation is root-based; if the collective operation is not root-based: establishing a tuning session and executing the collective operation in the tuning session; if the collective operation is root-based, determining whether all compute nodes executing the application identified the collective operation at the same call site; if all compute nodes identified the collective operation at the same call site, establishing a tuning session and executing the collective operation in the tuning session; and if all compute nodes executing the application did not identify the collective operation at the same call site, executing the collective operation without establishing a tuning session.

  5. Runtime optimization of an application executing on a parallel computer

    DOEpatents

    Faraj, Daniel A.; Smith, Brian E.

    2013-01-29

    Identifying a collective operation within an application executing on a parallel computer; identifying a call site of the collective operation; determining whether the collective operation is root-based; if the collective operation is not root-based: establishing a tuning session and executing the collective operation in the tuning session; if the collective operation is root-based, determining whether all compute nodes executing the application identified the collective operation at the same call site; if all compute nodes identified the collective operation at the same call site, establishing a tuning session and executing the collective operation in the tuning session; and if all compute nodes executing the application did not identify the collective operation at the same call site, executing the collective operation without establishing a tuning session.

  6. Runtime optimization of an application executing on a parallel computer

    DOEpatents

    Faraj, Daniel A; Smith, Brian E

    2014-11-25

    Identifying a collective operation within an application executing on a parallel computer; identifying a call site of the collective operation; determining whether the collective operation is root-based; if the collective operation is not root-based: establishing a tuning session and executing the collective operation in the tuning session; if the collective operation is root-based, determining whether all compute nodes executing the application identified the collective operation at the same call site; if all compute nodes identified the collective operation at the same call site, establishing a tuning session and executing the collective operation in the tuning session; and if all compute nodes executing the application did not identify the collective operation at the same call site, executing the collective operation without establishing a tuning session.

  7. National Energy Research Scientific Computing Center 2007 Annual Report

    SciTech Connect

    Hules, John A.; Bashor, Jon; Wang, Ucilia; Yarris, Lynn; Preuss, Paul

    2008-10-23

    This report presents highlights of the research conducted on NERSC computers in a variety of scientific disciplines during the year 2007. It also reports on changes and upgrades to NERSC's systems and services aswell as activities of NERSC staff.

  8. 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.

  9. Developing Concept-Based User Interfaces for Scientific Computing

    SciTech Connect

    Chin, George; Stephan, Eric G.; Gracio, Deborah K.; Kuchar, Olga A.; Whitney, Paul D.; Schuchardt, Karen L.

    2006-09-01

    From our interactions with researchers from different scientific fields and disciplines, we have observed that scientists often describe and convey concepts, theories, processes, and results using basic graphs and diagrams. Semantic graphs such as these provide a universal language that all scientists may apply to document their scientific knowledge and to communicate this knowledge to others. Furthermore, studies have shown that the cognitive processing of complex subject matter is improved when the structure of ideas and concepts are made explicit [39] and that semantic graphs may serve as effective “scaffolds” for cognitive processing [29]. At Pacific Northwest National Laboratory, we are deploying semantic graphs within scientific computing systems as central user representations of scientific knowledge. These systems provide concept-based user interfaces that allow scientists to visually define and capture conceptual models of their scientific problems, hypotheses, theories, and processes. Once defined, the visual models then become interaction framework for accessing and applying scientific and computational resources and capabilities. In this paper, through the examination of three visual research systems, we illustrate different ways concept-based user interfaces and semantic graph knowledge representations may make scientific knowledge concrete, usable, shareable, and computable in scientific computing systems.

  10. Use Computer-Aided Tools to Parallelize Large CFD Applications

    NASA Technical Reports Server (NTRS)

    Jin, H.; Frumkin, M.; Yan, J.

    2000-01-01

    Porting applications to high performance parallel computers is always a challenging task. It is time consuming and costly. With rapid progressing in hardware architectures and increasing complexity of real applications in recent years, the problem becomes even more sever. Today, scalability and high performance are mostly involving handwritten parallel programs using message-passing libraries (e.g. MPI). However, this process is very difficult and often error-prone. The recent reemergence of shared memory parallel (SMP) architectures, such as the cache coherent Non-Uniform Memory Access (ccNUMA) architecture used in the SGI Origin 2000, show good prospects for scaling beyond hundreds of processors. Programming on an SMP is simplified by working in a globally accessible address space. The user can supply compiler directives, such as OpenMP, to parallelize the code. As an industry standard for portable implementation of parallel programs for SMPs, OpenMP is a set of compiler directives and callable runtime library routines that extend Fortran, C and C++ to express shared memory parallelism. It promises an incremental path for parallel conversion of existing software, as well as scalability and performance for a complete rewrite or an entirely new development. Perhaps the main disadvantage of programming with directives is that inserted directives may not necessarily enhance performance. In the worst cases, it can create erroneous results. While vendors have provided tools to perform error-checking and profiling, automation in directive insertion is very limited and often failed on large programs, primarily due to the lack of a thorough enough data dependence analysis. To overcome the deficiency, we have developed a toolkit, CAPO, to automatically insert OpenMP directives in Fortran programs and apply certain degrees of optimization. CAPO is aimed at taking advantage of detailed inter-procedural dependence analysis provided by CAPTools, developed by the University of

  11. Computational Epigenetics: the new scientific paradigm

    PubMed Central

    Lim, Shen Jean; Tan, Tin Wee; Tong, Joo Chuan

    2010-01-01

    Epigenetics has recently emerged as a critical field for studying how non-gene factors can influence the traits and functions of an organism. At the core of this new wave of research is the use of computational tools that play critical roles not only in directing the selection of key experiments, but also in formulating new testable hypotheses through detailed analysis of complex genomic information that is not achievable using traditional approaches alone. Epigenomics, which combines traditional genomics with computer science, mathematics, chemistry, biochemistry and proteomics for the large-scale analysis of heritable changes in phenotype, gene function or gene expression that are not dependent on gene sequence, offers new opportunities to further our understanding of transcriptional regulation, nuclear organization, development and disease. This article examines existing computational strategies for the study of epigenetic factors. The most important databases and bioinformatic tools in this rapidly growing field have been reviewed. PMID:20978607

  12. Fencing direct memory access data transfers in a parallel active messaging interface of a parallel computer

    DOEpatents

    Blocksome, Michael A.; Mamidala, Amith R.

    2013-09-03

    Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to segments of shared random access memory through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and a segment of shared memory; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.

  13. Fencing direct memory access data transfers in a parallel active messaging interface of a parallel computer

    DOEpatents

    Blocksome, Michael A; Mamidala, Amith R

    2014-02-11

    Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to segments of shared random access memory through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and a segment of shared memory; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.

  14. Event parallelism: Distributed memory parallel computing for high energy physics experiments

    SciTech Connect

    Nash, T.

    1989-05-01

    This paper describes the present and expected future development of distributed memory parallel computers for high energy physics experiments. It covers the use of event parallel microprocessor farms, particularly at Fermilab, including both ACP multiprocessors and farms of MicroVAXES. These systems have proven very cost effective in the past. A case is made for moving to the more open environment of UNIX and RISC processors. The 2nd Generation ACP Multiprocessor System, which is based on powerful RISC systems, is described. Given the promise of still more extraordinary increases in processor performance, a new emphasis on point to point, rather than bussed, communication will be required. Developments in this direction are described. 6 figs.

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

    DOEpatents

    Davis, Kristan D.; Faraj, Daniel A.

    2014-07-22

    Algorithm selection for data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI, including associating in the PAMI data communications algorithms and ranges of message sizes so that each algorithm is associated with a separate range of message sizes; receiving in an origin endpoint of the PAMI a data communications instruction, the instruction specifying transmission of a data communications message from the origin endpoint to a target endpoint, the data communications message characterized by a message size; selecting, from among the associated algorithms and ranges, a data communications algorithm in dependence upon the message size; and transmitting, according to the selected data communications algorithm from the origin endpoint to the target endpoint, the data communications message.

  16. Data communications for a collective operation in a parallel active messaging interface of a parallel computer

    DOEpatents

    Faraj, Daniel A

    2013-07-16

    Algorithm selection for data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI, including associating in the PAMI data communications algorithms and bit masks; receiving in an origin endpoint of the PAMI a collective instruction, the instruction specifying transmission of a data communications message from the origin endpoint to a target endpoint; constructing a bit mask for the received collective instruction; selecting, from among the associated algorithms and bit masks, a data communications algorithm in dependence upon the constructed bit mask; and executing the collective instruction, transmitting, according to the selected data communications algorithm from the origin endpoint to the target endpoint, the data communications message.

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

    DOEpatents

    Davis, Kristan D; Faraj, Daniel A

    2013-07-09

    Algorithm selection for data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI, including associating in the PAMI data communications algorithms and ranges of message sizes so that each algorithm is associated with a separate range of message sizes; receiving in an origin endpoint of the PAMI a data communications instruction, the instruction specifying transmission of a data communications message from the origin endpoint to a target endpoint, the data communications message characterized by a message size; selecting, from among the associated algorithms and ranges, a data communications algorithm in dependence upon the message size; and transmitting, according to the selected data communications algorithm from the origin endpoint to the target endpoint, the data communications message.

  18. Data communications for a collective operation in a parallel active messaging interface of a parallel computer

    DOEpatents

    Faraj, Daniel A.

    2015-11-19

    Algorithm selection for data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI, including associating in the PAMI data communications algorithms and bit masks; receiving in an origin endpoint of the PAMI a collective instruction, the instruction specifying transmission of a data communications message from the origin endpoint to a target endpoint; constructing a bit mask for the received collective instruction; selecting, from among the associated algorithms and bit masks, a data communications algorithm in dependence upon the constructed bit mask; and executing the collective instruction, transmitting, according to the selected data communications algorithm from the origin endpoint to the target endpoint, the data communications message.

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

    DOEpatents

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

    2014-09-16

    Eager send data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints that specify a client, a context, and a task, including receiving an eager send data communications instruction with transfer data disposed in a send buffer characterized by a read/write send buffer memory address in a read/write virtual address space of the origin endpoint; determining for the send buffer a read-only send buffer memory address in a read-only virtual address space, the read-only virtual address space shared by both the origin endpoint and the target endpoint, with all frames of physical memory mapped to pages of virtual memory in the read-only virtual address space; and communicating by the origin endpoint to the target endpoint an eager send message header that includes the read-only send buffer memory address.

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

    DOEpatents

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

    2014-09-02

    Eager send data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints that specify a client, a context, and a task, including receiving an eager send data communications instruction with transfer data disposed in a send buffer characterized by a read/write send buffer memory address in a read/write virtual address space of the origin endpoint; determining for the send buffer a read-only send buffer memory address in a read-only virtual address space, the read-only virtual address space shared by both the origin endpoint and the target endpoint, with all frames of physical memory mapped to pages of virtual memory in the read-only virtual address space; and communicating by the origin endpoint to the target endpoint an eager send message header that includes the read-only send buffer memory address.

  1. 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.

  2. A Framework to Simulate Semiconductor Devices Using Parallel Computer Architecture

    NASA Astrophysics Data System (ADS)

    Kumar, Gaurav; Singh, Mandeep; Bulusu, Anand; Trivedi, Gaurav

    2016-10-01

    Device simulations have become an integral part of semiconductor technology to address many issues (short channel effects, narrow width effects, hot-electron effect) as it goes into nano regime, helping us to continue further with the Moore's Law. TCAD provides a simulation environment to design and develop novel devices, thus a leap forward to study their electrical behaviour in advance. In this paper, a parallel 2D simulator for semiconductor devices using Discontinuous Galerkin Finite Element Method (DG-FEM) is presented. Discontinuous Galerkin (DG) method is used to discretize essential device equations and later these equations are analyzed by using a suitable methodology to find the solution. DG method is characterized to provide more accurate solution as it efficiently conserve the flux and easily handles complex geometries. OpenMP is used to parallelize solution of device equations on manycore processors and a speed of 1.4x is achieved during assembly process of discretization. This study is important for more accurate analysis of novel devices (such as FinFET, GAAFET etc.) on a parallel computing platform and will help us to develop a parallel device simulator which will be able to address this issue efficiently. A case study of PN junction diode is presented to show the effectiveness of proposed approach.

  3. Semi-coarsening multigrid methods for parallel computing

    SciTech Connect

    Jones, J.E.

    1996-12-31

    Standard multigrid methods are not well suited for problems with anisotropic coefficients which can occur, for example, on grids that are stretched to resolve a boundary layer. There are several different modifications of the standard multigrid algorithm that yield efficient methods for anisotropic problems. In the paper, we investigate the parallel performance of these multigrid algorithms. Multigrid algorithms which work well for anisotropic problems are based on line relaxation and/or semi-coarsening. In semi-coarsening multigrid algorithms a grid is coarsened in only one of the coordinate directions unlike standard or full-coarsening multigrid algorithms where a grid is coarsened in each of the coordinate directions. When both semi-coarsening and line relaxation are used, the resulting multigrid algorithm is robust and automatic in that it requires no knowledge of the nature of the anisotropy. This is the basic multigrid algorithm whose parallel performance we investigate in the paper. The algorithm is currently being implemented on an IBM SP2 and its performance is being analyzed. In addition to looking at the parallel performance of the basic semi-coarsening algorithm, we present algorithmic modifications with potentially better parallel efficiency. One modification reduces the amount of computational work done in relaxation at the expense of using multiple coarse grids. This modification is also being implemented with the aim of comparing its performance to that of the basic semi-coarsening algorithm.

  4. Massively parallel finite element computation of three dimensional flow problems

    NASA Astrophysics Data System (ADS)

    Tezduyar, T.; Aliabadi, S.; Behr, M.; Johnson, A.; Mittal, S.

    1992-12-01

    The parallel finite element computation of three-dimensional compressible, and incompressible flows, with emphasis on the space-time formulations, mesh moving schemes and implementations on the Connection Machines CM-200 and CM-5 are presented. For computation of unsteady compressible and incompressible flows involving moving boundaries and interfaces, the Deformable-Spatial-Domain/Stabilized-Space-Time (DSD/SST) formulation that previously developed are employed. In this approach, the stabilized finite element formulations of the governing equations are written over the space-time domain of the problem; therefore, the deformation of the spatial domain with respect to time is taken into account automatically. This approach gives the capability to solve a large class of problems involving free surfaces, moving interfaces, and fluid-structure and fluid-particle interactions. By using special mesh moving schemes, the frequency of remeshing is minimized to reduce the projection errors involved in remeshing and also to increase the parallelization ease of the computations. The implicit equation systems arising from the finite element discretizations are solved iteratively by using the GMRES update technique with the diagonal and nodal-block-diagonal preconditioners. These formulations have all been implemented on the CM-200 and CM-5, and have been applied to several large-scale problems. The three-dimensional problems in this report were all computed on the CM-200 and CM-5.

  5. Parallelization of Nullspace Algorithm for the computation of metabolic pathways.

    PubMed

    Jevremović, Dimitrije; Trinh, Cong T; Srienc, Friedrich; Sosa, Carlos P; Boley, Daniel

    2011-06-01

    Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100-1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency.

  6. High performance parallel computers for science: New developments at the Fermilab advanced computer program

    SciTech Connect

    Nash, T.; Areti, H.; Atac, R.; Biel, J.; Cook, A.; Deppe, J.; Edel, M.; Fischler, M.; Gaines, I.; Hance, R.

    1988-08-01

    Fermilab's Advanced Computer Program (ACP) has been developing highly cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 MFlops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction. 10 refs., 7 figs.

  7. Parallel matrix transpose algorithms on distributed memory concurrent computers

    SciTech Connect

    Choi, J.; Walker, D.W.; Dongarra, J.J. |

    1993-10-01

    This paper describes parallel matrix transpose algorithms on distributed memory concurrent processors. It is assumed that the matrix is distributed over a P x Q processor template with a block scattered data distribution. P, Q, and the block size can be arbitrary, so the algorithms have wide applicability. The communication schemes of the algorithms are determined by the greatest common divisor (GCD) of P and Q. If P and Q are relatively prime, the matrix transpose algorithm involves complete exchange communication. If P and Q are not relatively prime, processors are divided into GCD groups and the communication operations are overlapped for different groups of processors. Processors transpose GCD wrapped diagonal blocks simultaneously, and the matrix can be transposed with LCM/GCD steps, where LCM is the least common multiple of P and Q. The algorithms make use of non-blocking, point-to-point communication between processors. The use of nonblocking communication allows a processor to overlap the messages that it sends to different processors, thereby avoiding unnecessary synchronization. Combined with the matrix multiplication routine, C = A{center_dot}B, the algorithms are used to compute parallel multiplications of transposed matrices, C = A{sup T}{center_dot}B{sup T}, in the PUMMA package. Details of the parallel implementation of the algorithms are given, and results are presented for runs on the Intel Touchstone Delta computer.

  8. Fast electrostatic force calculation on parallel computer clusters

    SciTech Connect

    Kia, Amirali Kim, Daejoong Darve, Eric

    2008-10-01

    The fast multipole method (FMM) and smooth particle mesh Ewald (SPME) are well known fast algorithms to evaluate long range electrostatic interactions in molecular dynamics and other fields. FMM is a multi-scale method which reduces the computation cost by approximating the potential due to a group of particles at a large distance using few multipole functions. This algorithm scales like O(N) for N particles. SPME algorithm is an O(NlnN) method which is based on an interpolation of the Fourier space part of the Ewald sum and evaluating the resulting convolutions using fast Fourier transform (FFT). Those algorithms suffer from relatively poor efficiency on large parallel machines especially for mid-size problems around hundreds of thousands of atoms. A variation of the FMM, called PWA, based on plane wave expansions is presented in this paper. A new parallelization strategy for PWA, which takes advantage of the specific form of this expansion, is described. Its parallel efficiency is compared with SPME through detail time measurements on two different computer clusters.

  9. DMA shared byte counters in a parallel computer

    DOEpatents

    Chen, Dong; Gara, Alan G.; Heidelberger, Philip; Vranas, Pavlos

    2010-04-06

    A parallel computer system is constructed as a network of interconnected compute nodes. Each of the compute nodes includes at least one processor, a memory and a DMA engine. The DMA engine includes a processor interface for interfacing with the at least one processor, DMA logic, a memory interface for interfacing with the memory, a DMA network interface for interfacing with the network, injection and reception byte counters, injection and reception FIFO metadata, and status registers and control registers. The injection FIFOs maintain memory locations of the injection FIFO metadata memory locations including its current head and tail, and the reception FIFOs maintain the reception FIFO metadata memory locations including its current head and tail. The injection byte counters and reception byte counters may be shared between messages.

  10. Determining collective barrier operation skew in a parallel computer

    SciTech Connect

    Faraj, Daniel A.

    2015-11-24

    Determining collective barrier operation skew in a parallel computer that includes a number of compute nodes organized into an operational group includes: for each of the nodes until each node has been selected as a delayed node: selecting one of the nodes as a delayed node; entering, by each node other than the delayed node, a collective barrier operation; entering, after a delay by the delayed node, the collective barrier operation; receiving an exit signal from a root of the collective barrier operation; and measuring, for the delayed node, a barrier completion time. The barrier operation skew is calculated by: identifying, from the compute nodes' barrier completion times, a maximum barrier completion time and a minimum barrier completion time and calculating the barrier operation skew as the difference of the maximum and the minimum barrier completion time.

  11. Parallel computation of transverse wakes in linear colliders

    SciTech Connect

    Zhan, Xiaowei; Ko, Kwok

    1996-11-01

    SLAC has proposed the detuned structure (DS) as one possible design to control the emittance growth of long bunch trains due to transverse wakefields in the Next Linear Collider (NLC). The DS consists of 206 cells with tapering from cell to cell of the order of few microns to provide Gaussian detuning of the dipole modes. The decoherence of these modes leads to two orders of magnitude reduction in wakefield experienced by the trailing bunch. To model such a large heterogeneous structure realistically is impractical with finite-difference codes using structured grids. The authors have calculated the wakefield in the DS on a parallel computer with a finite-element code using an unstructured grid. The parallel implementation issues are presented along with simulation results that include contributions from higher dipole bands and wall dissipation.

  12. Parallelized Vlasov-Fokker-Planck solver for desktop personal computers

    NASA Astrophysics Data System (ADS)

    Schönfeldt, Patrik; Brosi, Miriam; Schwarz, Markus; Steinmann, Johannes L.; Müller, Anke-Susanne

    2017-03-01

    The numerical solution of the Vlasov-Fokker-Planck equation is a well established method to simulate the dynamics, including the self-interaction with its own wake field, of an electron bunch in a storage ring. In this paper we present Inovesa, a modularly extensible program that uses opencl to massively parallelize the computation. It allows a standard desktop PC to work with appropriate accuracy and yield reliable results within minutes. We provide numerical stability-studies over a wide parameter range and compare our numerical findings to known results. Simulation results for the case of coherent synchrotron radiation will be compared to measurements that probe the effects of the microbunching instability occurring in the short bunch operation at ANKA. It will be shown that the impedance model based on the shielding effect of two parallel plates can not only describe the instability threshold, but also the presence of multiple regimes that show differences in the emission of coherent synchrotron radiation.

  13. 3D finite-difference seismic migration with parallel computers

    SciTech Connect

    Ober, C.C.; Gjertsen, R.; Minkoff, S.; Womble, D.E.

    1998-11-01

    The ability to image complex geologies such as salt domes in the Gulf of Mexico and thrusts in mountainous regions is essential for reducing the risk associated with oil exploration. Imaging these structures, however, is computationally expensive as datasets can be terabytes in size. Traditional ray-tracing migration methods cannot handle complex velocity variations commonly found near such salt structures. Instead the authors use the full 3D acoustic wave equation, discretized via a finite difference algorithm. They reduce the cost of solving the apraxial wave equation by a number of numerical techniques including the method of fractional steps and pipelining the tridiagonal solves. The imaging code, Salvo, uses both frequency parallelism (generally 90% efficient) and spatial parallelism (65% efficient). Salvo has been tested on synthetic and real data and produces clear images of the subsurface even beneath complicated salt structures.

  14. Center for Programming Models for Scalable Parallel Computing

    SciTech Connect

    John Mellor-Crummey

    2008-02-29

    Rice University's achievements as part of the Center for Programming Models for Scalable Parallel Computing include: (1) design and implemention of cafc, the first multi-platform CAF compiler for distributed and shared-memory machines, (2) performance studies of the efficiency of programs written using the CAF and UPC programming models, (3) a novel technique to analyze explicitly-parallel SPMD programs that facilitates optimization, (4) design, implementation, and evaluation of new language features for CAF, including communication topologies, multi-version variables, and distributed multithreading to simplify development of high-performance codes in CAF, and (5) a synchronization strength reduction transformation for automatically replacing barrier-based synchronization with more efficient point-to-point synchronization. The prototype Co-array Fortran compiler cafc developed in this project is available as open source software from http://www.hipersoft.rice.edu/caf.

  15. Planet crossing asteroids and parallel computing: Project spaceguard

    NASA Astrophysics Data System (ADS)

    Milani, Andrea

    1988-03-01

    The orbits of the asteroids crossing the orbit of the Earth and other planets are chaotic and cannot be computed in a deterministic way for a time span long enough to study the probability of collisions. It is possible to study the statistical behaviour of a large number of such orbits over a long span of time, provided enough computing resources and intelligent post processing software are available. The former, problem can be handled by exploiting the enormous power of parallel computing systems. The orbit of the asteroids can be studied as a restricted (N+M)-body problem which is suitable for the use of parallel processing, by using one processor to compute the orbits of the planets and the others to compute the orbits the asteroids. This scheme has been implemented on LCAP-2, an array of IBM and FPS processors with shared memory designed by E. Clementi (IBM). The parallelisation efficiency has been over 80%, and the overall speed over 90 MegaFLOPS; the orbits of all the asteroids with perihelia lower than the aphelion of Mars (410 objects) have been computed for 200,000, years (Project SPACEGUARD). The most difficult step of the project is the post processing of the very large amount of output data and to gather qualitative information on the behaviour of so many orbits without resorting to the traditional technique, i.e. human examination of output in graphical form. Within Project SPACEGUARD we have developed a qualitative classification of the orbits of the planet crossers. To develop an entirely automated classification of the qualitative orbital behaviour-including crossing behaviour, resonances (mean motion and secular), and protection mechanisms avoiding collisions-is a challenge to be met.

  16. Scalable, massively parallel approaches to upstream drainage area computation

    NASA Astrophysics Data System (ADS)

    Richardson, A.; Hill, C. N.; Perron, T.

    2011-12-01

    Accumulated drainage area maps of large regions are required for several applications. Among these are assessments of regional patterns of flow and sediment routing, high-resolution landscape evolution models in which drainage basin geometry evolves with time, and surveys of the characteristics of river basins that drain to continental margins. The computation of accumulated drainage areas is accomplished by inferring the vector field of drainage flow directions from a two-dimensional digital elevation map, and then computing the area that drains to each tile. From this map of elevations we can compute the integrated, upstream area that drains to each tile of the map. Generally this last step is done with a recursive algorithm, that accumulates upstream areas sequentially. The inherently serial nature of this restricts the number of tiles that can be included, thereby limiting the resolution of continental-size domains. This is because of the requirements of both memory, which will rise proportionally to the number of tiles, N, and computing time, which is O(N2). The fundamental sequential property of this approach prohibits effective use of large scale parallelism. An alternate method of calculating accumulated drainage area from drainage direction data can be arrived at by reformulating the problem as the solution of a system of simultaneous linear equations. The equations define the relation that the total upslope area of a particular tile is the sum of all the upslope areas for tiles immediately adjacent to that tile that drain to it, and the tile's own area. Solving these equations amounts to finding the solution of a sparse, nine-diagonal matrix operating on a vector for a right-hand-side that is simply the individual tile areas and where the diagonals of the matrix are determined by the landscape geometry. We show how an iterative method, Bi-CGSTAB, can be used to solve this problem in a scalable, massively parallel manner. However, this introduces

  17. Parallel computation of multigroup reactivity coefficient using iterative method

    NASA Astrophysics Data System (ADS)

    Susmikanti, Mike; Dewayatna, Winter

    2013-09-01

    One of the research activities to support the commercial radioisotope production program is a safety research target irradiation FPM (Fission Product Molybdenum). FPM targets form a tube made of stainless steel in which the nuclear degrees of superimposed high-enriched uranium. FPM irradiation tube is intended to obtain fission. The fission material widely used in the form of kits in the world of nuclear medicine. Irradiation FPM tube reactor core would interfere with performance. One of the disorders comes from changes in flux or reactivity. It is necessary to study a method for calculating safety terrace ongoing configuration changes during the life of the reactor, making the code faster became an absolute necessity. Neutron safety margin for the research reactor can be reused without modification to the calculation of the reactivity of the reactor, so that is an advantage of using perturbation method. The criticality and flux in multigroup diffusion model was calculate at various irradiation positions in some uranium content. This model has a complex computation. Several parallel algorithms with iterative method have been developed for the sparse and big matrix solution. The Black-Red Gauss Seidel Iteration and the power iteration parallel method can be used to solve multigroup diffusion equation system and calculated the criticality and reactivity coeficient. This research was developed code for reactivity calculation which used one of safety analysis with parallel processing. It can be done more quickly and efficiently by utilizing the parallel processing in the multicore computer. This code was applied for the safety limits calculation of irradiated targets FPM with increment Uranium.

  18. Parallel computation of multigroup reactivity coefficient using iterative method

    SciTech Connect

    Susmikanti, Mike; Dewayatna, Winter

    2013-09-09

    One of the research activities to support the commercial radioisotope production program is a safety research target irradiation FPM (Fission Product Molybdenum). FPM targets form a tube made of stainless steel in which the nuclear degrees of superimposed high-enriched uranium. FPM irradiation tube is intended to obtain fission. The fission material widely used in the form of kits in the world of nuclear medicine. Irradiation FPM tube reactor core would interfere with performance. One of the disorders comes from changes in flux or reactivity. It is necessary to study a method for calculating safety terrace ongoing configuration changes during the life of the reactor, making the code faster became an absolute necessity. Neutron safety margin for the research reactor can be reused without modification to the calculation of the reactivity of the reactor, so that is an advantage of using perturbation method. The criticality and flux in multigroup diffusion model was calculate at various irradiation positions in some uranium content. This model has a complex computation. Several parallel algorithms with iterative method have been developed for the sparse and big matrix solution. The Black-Red Gauss Seidel Iteration and the power iteration parallel method can be used to solve multigroup diffusion equation system and calculated the criticality and reactivity coeficient. This research was developed code for reactivity calculation which used one of safety analysis with parallel processing. It can be done more quickly and efficiently by utilizing the parallel processing in the multicore computer. This code was applied for the safety limits calculation of irradiated targets FPM with increment Uranium.

  19. 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…

  20. 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.

  1. Evaluation of cache-based superscalar and cacheless vector architectures for scientific computations

    SciTech Connect

    Oliker, Leonid; Canning, Andrew; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; Van der Wijngaart, Rob

    2003-05-01

    The growing gap between sustained and peak performance for scientific applications is a well-known problem in high end computing. The recent development of parallel vector systems offers the potential to bridge this gap for many computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX-6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of scientific computing areas. First, we present the performance of a microbenchmark suite that examines low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks. Finally, we evaluate the performance of several scientific computing codes. Results demonstrate that the SX-6 achieves high performance on a large fraction of our applications and often significantly out performs the cache-based architectures. However, certain applications are not easily amenable to vectorization and would re quire extensive algorithm and implementation reengineering to utilize the SX-6 effectively.

  2. Hyper-parallel photonic quantum computation with coupled quantum dots

    PubMed Central

    Ren, Bao-Cang; Deng, Fu-Guo

    2014-01-01

    It is well known that a parallel quantum computer is more powerful than a classical one. So far, there are some important works about the construction of universal quantum logic gates, the key elements in quantum computation. However, they are focused on operating on one degree of freedom (DOF) of quantum systems. Here, we investigate the possibility of achieving scalable hyper-parallel quantum computation based on two DOFs of photon systems. We construct a deterministic hyper-controlled-not (hyper-CNOT) gate operating on both the spatial-mode and the polarization DOFs of a two-photon system simultaneously, by exploiting the giant optical circular birefringence induced by quantum-dot spins in double-sided optical microcavities as a result of cavity quantum electrodynamics (QED). This hyper-CNOT gate is implemented by manipulating the four qubits in the two DOFs of a two-photon system without auxiliary spatial modes or polarization modes. It reduces the operation time and the resources consumed in quantum information processing, and it is more robust against the photonic dissipation noise, compared with the integration of several cascaded CNOT gates in one DOF. PMID:24721781

  3. An experiment in hurricane track prediction using parallel computing methods

    NASA Technical Reports Server (NTRS)

    Song, Chang G.; Jwo, Jung-Sing; Lakshmivarahan, S.; Dhall, S. K.; Lewis, John M.; Velden, Christopher S.

    1994-01-01

    The barotropic model is used to explore the advantages of parallel processing in deterministic forecasting. We apply this model to the track forecasting of hurricane Elena (1985). In this particular application, solutions to systems of elliptic equations are the essence of the computational mechanics. One set of equations is associated with the decomposition of the wind into irrotational and nondivergent components - this determines the initial nondivergent state. Another set is associated with recovery of the streamfunction from the forecasted vorticity. We demonstrate that direct parallel methods based on accelerated block cyclic reduction (BCR) significantly reduce the computational time required to solve the elliptic equations germane to this decomposition and forecast problem. A 72-h track prediction was made using incremental time steps of 16 min on a network of 3000 grid points nominally separated by 100 km. The prediction took 30 sec on the 8-processor Alliant FX/8 computer. This was a speed-up of 3.7 when compared to the one-processor version. The 72-h prediction of Elena's track was made as the storm moved toward Florida's west coast. Approximately 200 km west of Tampa Bay, Elena executed a dramatic recurvature that ultimately changed its course toward the northwest. Although the barotropic track forecast was unable to capture the hurricane's tight cycloidal looping maneuver, the subsequent northwesterly movement was accurately forecasted as was the location and timing of landfall near Mobile Bay.

  4. 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.

  5. ASCR Cybersecurity for Scientific Computing Integrity

    SciTech Connect

    Piesert, Sean

    2015-02-27

    The Department of Energy (DOE) has the responsibility to address the energy, environmental, and nuclear security challenges that face our nation. Much of DOE’s enterprise involves distributed, collaborative teams; a signi¬cant fraction involves “open science,” which depends on multi-institutional, often international collaborations that must access or share signi¬cant amounts of information between institutions and over networks around the world. The mission of the Office of Science is the delivery of scienti¬c discoveries and major scienti¬c tools to transform our understanding of nature and to advance the energy, economic, and national security of the United States. The ability of DOE to execute its responsibilities depends critically on its ability to assure the integrity and availability of scienti¬c facilities and computer systems, and of the scienti¬c, engineering, and operational software and data that support its mission.

  6. An efficient parallel algorithm for accelerating computational protein design

    PubMed Central

    Zhou, Yichao; Xu, Wei; Donald, Bruce R.; Zeng, Jianyang

    2014-01-01

    Motivation: Structure-based computational protein design (SCPR) is an important topic in protein engineering. Under the assumption of a rigid backbone and a finite set of discrete conformations of side-chains, various methods have been proposed to address this problem. A popular method is to combine the dead-end elimination (DEE) and A* tree search algorithms, which provably finds the global minimum energy conformation (GMEC) solution. Results: In this article, we improve the efficiency of computing A* heuristic functions for protein design and propose a variant of A* algorithm in which the search process can be performed on a single GPU in a massively parallel fashion. In addition, we make some efforts to address the memory exceeding problem in A* search. As a result, our enhancements can achieve a significant speedup of the A*-based protein design algorithm by four orders of magnitude on large-scale test data through pre-computation and parallelization, while still maintaining an acceptable memory overhead. We also show that our parallel A* search algorithm could be successfully combined with iMinDEE, a state-of-the-art DEE criterion, for rotamer pruning to further improve SCPR with the consideration of continuous side-chain flexibility. Availability: Our software is available and distributed open-source under the GNU Lesser General License Version 2.1 (GNU, February 1999). The source code can be downloaded from http://www.cs.duke.edu/donaldlab/osprey.php or http://iiis.tsinghua.edu.cn/∼compbio/software.html. Contact: zengjy321@tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24931991

  7. The FORCE: A portable parallel programming language supporting computational structural mechanics

    NASA Technical Reports Server (NTRS)

    Jordan, Harry F.; Benten, Muhammad S.; Brehm, Juergen; Ramanan, Aruna

    1989-01-01

    This project supports the conversion of codes in Computational Structural Mechanics (CSM) to a parallel form which will efficiently exploit the computational power available from multiprocessors. The work is a part of a comprehensive, FORTRAN-based system to form a basis for a parallel version of the NICE/SPAR combination which will form the CSM Testbed. The software is macro-based and rests on the force methodology developed by the principal investigator in connection with an early scientific multiprocessor. Machine independence is an important characteristic of the system so that retargeting it to the Flex/32, or any other multiprocessor on which NICE/SPAR might be imnplemented, is well supported. The principal investigator has experience in producing parallel software for both full and sparse systems of linear equations using the force macros. Other researchers have used the Force in finite element programs. It has been possible to rapidly develop software which performs at maximum efficiency on a multiprocessor. The inherent machine independence of the system also means that the parallelization will not be limited to a specific multiprocessor.

  8. Charon Toolkit for Parallel, Implicit Structured-Grid Computations: Functional Design

    NASA Technical Reports Server (NTRS)

    VanderWijngaart, Rob F.; Kutler, Paul (Technical Monitor)

    1997-01-01

    In a previous report the design concepts of Charon were presented. Charon is a toolkit that aids engineers in developing scientific programs for structured-grid applications to be run on MIMD parallel computers. It constitutes an augmentation of the general-purpose MPI-based message-passing layer, and provides the user with a hierarchy of tools for rapid prototyping and validation of parallel programs, and subsequent piecemeal performance tuning. Here we describe the implementation of the domain decomposition tools used for creating data distributions across sets of processors. We also present the hierarchy of parallelization tools that allows smooth translation of legacy code (or a serial design) into a parallel program. Along with the actual tool descriptions, we will present the considerations that led to the particular design choices. Many of these are motivated by the requirement that Charon must be useful within the traditional computational environments of Fortran 77 and C. Only the Fortran 77 syntax will be presented in this report.

  9. Routing performance analysis and optimization within a massively parallel computer

    DOEpatents

    Archer, Charles Jens; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen

    2013-04-16

    An apparatus, program product and method optimize the operation of a massively parallel computer system by, in part, receiving actual performance data concerning an application executed by the plurality of interconnected nodes, and analyzing the actual performance data to identify an actual performance pattern. A desired performance pattern may be determined for the application, and an algorithm may be selected from among a plurality of algorithms stored within a memory, the algorithm being configured to achieve the desired performance pattern based on the actual performance data.

  10. Parallel Computation of Persistent Homology using the Blowup Complex

    SciTech Connect

    Lewis, Ryan; Morozov, Dmitriy

    2015-04-27

    We describe a parallel algorithm that computes persistent homology, an algebraic descriptor of a filtered topological space. Our algorithm is distinguished by operating on a spatial decomposition of the domain, as opposed to a decomposition with respect to the filtration. We rely on a classical construction, called the Mayer--Vietoris blowup complex, to glue global topological information about a space from its disjoint subsets. We introduce an efficient algorithm to perform this gluing operation, which may be of independent interest, and describe how to process the domain hierarchically. We report on a set of experiments that help assess the strengths and identify the limitations of our method.

  11. Particle orbit tracking on a parallel computer: Hypertrack

    SciTech Connect

    Cole, B.; Bourianoff, G.; Pilat, F. ); Talman, R. )

    1991-05-01

    A program has been written which performs particle orbit tracking on the Intel iPSC/860 distributed memory parallel computer. The tracking is performed using a thin element approach. A brief description of the structure and performance of the code is presented, along with applications of the code to the analysis of accelerator lattices for the SSC. The concept of ensemble tracking'', i.e. the tracking of ensemble averages of noninteracting particles, such as the emittance, is presented. Preliminary results of such studies will be presented. 2 refs., 6 figs.

  12. Representing and computing regular languages on massively parallel networks

    SciTech Connect

    Miller, M.I.; O'Sullivan, J.A. ); Boysam, B. ); Smith, K.R. )

    1991-01-01

    This paper proposes a general method for incorporating rule-based constraints corresponding to regular languages into stochastic inference problems, thereby allowing for a unified representation of stochastic and syntactic pattern constraints. The authors' approach first established the formal connection of rules to Chomsky grammars, and generalizes the original work of Shannon on the encoding of rule-based channel sequences to Markov chains of maximum entropy. This maximum entropy probabilistic view leads to Gibb's representations with potentials which have their number of minima growing at precisely the exponential rate that the language of deterministically constrained sequences grow. These representations are coupled to stochastic diffusion algorithms, which sample the language-constrained sequences by visiting the energy minima according to the underlying Gibbs' probability law. The coupling to stochastic search methods yields the all-important practical result that fully parallel stochastic cellular automata may be derived to generate samples from the rule-based constraint sets. The production rules and neighborhood state structure of the language of sequences directly determines the necessary connection structures of the required parallel computing surface. Representations of this type have been mapped to the DAP-510 massively-parallel processor consisting of 1024 mesh-connected bit-serial processing elements for performing automated segmentation of electron-micrograph images.

  13. Solving the Cauchy-Riemann equations on parallel computers

    NASA Technical Reports Server (NTRS)

    Fatoohi, Raad A.; Grosch, Chester E.

    1987-01-01

    Discussed is the implementation of a single algorithm on three parallel-vector computers. The algorithm is a relaxation scheme for the solution of the Cauchy-Riemann equations; a set of coupled first order partial differential equations. The computers were chosen so as to encompass a variety of architectures. They are: the MPP, and SIMD machine with 16K bit serial processors; FLEX/32, an MIMD machine with 20 processors; and CRAY/2, an MIMD machine with four vector processors. The machine architectures are briefly described. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Conclusions are presented.

  14. Analytic reconstruction approach for parallel translational computed tomography.

    PubMed

    Kong, Huihua; Yu, Hengyong

    2015-01-01

    To develop low-cost and low-dose computed tomography (CT) scanners for developing countries, recently a parallel translational computed tomography (PTCT) is proposed, and the source and detector are translated oppositely with respect to the imaging object without a slip-ring. In this paper, we develop an analytic filtered-backprojection (FBP)-type reconstruction algorithm for two dimensional (2D) fan-beam PTCT and extend it to three dimensional (3D) cone-beam geometry in a Feldkamp-type framework. Particularly, a weighting function is constructed to deal with data redundancy for multiple translations PTCT to eliminate image artifacts. Extensive numerical simulations are performed to validate and evaluate the proposed analytic reconstruction algorithms, and the results confirm their correctness and merits.

  15. Signal processing applications of massively parallel charge domain computing devices

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

    The present invention is embodied in a charge coupled device (CCD)/charge injection device (CID) architecture capable of performing a Fourier transform by simultaneous matrix vector multiplication (MVM) operations in respective plural CCD/CID arrays in parallel in O(1) steps. For example, in one embodiment, a first CCD/CID array stores charge packets representing a first matrix operator based upon permutations of a Hartley transform and computes the Fourier transform of an incoming vector. A second CCD/CID array stores charge packets representing a second matrix operator based upon different permutations of a Hartley transform and computes the Fourier transform of an incoming vector. The incoming vector is applied to the inputs of the two CCD/CID arrays simultaneously, and the real and imaginary parts of the Fourier transform are produced simultaneously in the time required to perform a single MVM operation in a CCD/CID array.

  16. Scaling and performance of a 3-D radiation hydrodynamics code on message-passing parallel computers: final report

    SciTech Connect

    Hayes, J C; Norman, M

    1999-10-28

    This report details an investigation into the efficacy of two approaches to solving the radiation diffusion equation within a radiation hydrodynamic simulation. Because leading-edge scientific computing platforms have evolved from large single-node vector processors to parallel aggregates containing tens to thousands of individual CPU's, the ability of an algorithm to maintain high compute efficiency when distributed over a large array of nodes is critically important. The viability of an algorithm thus hinges upon the tripartite question of numerical accuracy, total time to solution, and parallel efficiency.

  17. On the relationship between parallel computation and graph embedding

    SciTech Connect

    Gupta, A.K.

    1989-01-01

    The problem of efficiently simulating an algorithm designed for an n-processor parallel machine G on an m-processor parallel machine H with n > m arises when parallel algorithms designed for an ideal size machine are simulated on existing machines which are of a fixed size. The author studies this problem when every processor of H takes over the function of a number of processors in G, and he phrases the simulation problem as a graph embedding problem. New embeddings presented address relevant issues arising from the parallel computation environment. The main focus centers around embedding complete binary trees into smaller-sized binary trees, butterflies, and hypercubes. He also considers simultaneous embeddings of r source machines into a single hypercube. Constant factors play a crucial role in his embeddings since they are not only important in practice but also lead to interesting theoretical problems. All of his embeddings minimize dilation and load, which are the conventional cost measures in graph embeddings and determine the maximum amount of time required to simulate one step of G on H. His embeddings also optimize a new cost measure called ({alpha},{beta})-utilization which characterizes how evenly the processors of H are used by the processors of G. Ideally, the utilization should be balanced (i.e., every processor of H simulates at most (n/m) processors of G) and the ({alpha},{beta})-utilization measures how far off from a balanced utilization the embedding is. He presents embeddings for the situation when some processors of G have different capabilities (e.g. memory or I/O) than others and the processors with different capabilities are to be distributed uniformly among the processors of H. Placing such conditions on an embedding results in an increase in some of the cost measures.

  18. InSAR Scientific Computing Environment

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    This computing environment is the next generation of geodetic image processing technology for repeat-pass Interferometric Synthetic Aperture (InSAR) sensors, identified by the community as a needed capability to provide flexibility and extensibility in reducing measurements from radar satellites and aircraft to new geophysical products. This software allows users of interferometric radar data the flexibility to process from Level 0 to Level 4 products using a variety of algorithms and for a range of available sensors. There are many radar satellites in orbit today delivering to the science community data of unprecedented quantity and quality, making possible large-scale studies in climate research, natural hazards, and the Earth's ecosystem. The proposed DESDynI mission, now under consideration by NASA for launch later in this decade, would provide time series and multiimage measurements that permit 4D models of Earth surface processes so that, for example, climate-induced changes over time would become apparent and quantifiable. This advanced data processing technology, applied to a global data set such as from the proposed DESDynI mission, enables a new class of analyses at time and spatial scales unavailable using current approaches. This software implements an accurate, extensible, and modular processing system designed to realize the full potential of InSAR data from future missions such as the proposed DESDynI, existing radar satellite data, as well as data from the NASA UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar), and other airborne platforms. The processing approach has been re-thought in order to enable multi-scene analysis by adding new algorithms and data interfaces, to permit user-reconfigurable operation and extensibility, and to capitalize on codes already developed by NASA and the science community. The framework incorporates modern programming methods based on recent research, including object-oriented scripts controlling legacy and

  19. Energy Proportionality and Performance in Data Parallel Computing Clusters

    SciTech Connect

    Kim, Jinoh; Chou, Jerry; Rotem, Doron

    2011-02-14

    Energy consumption in datacenters has recently become a major concern due to the rising operational costs andscalability issues. Recent solutions to this problem propose the principle of energy proportionality, i.e., the amount of energy consumedby the server nodes must be proportional to the amount of work performed. For data parallelism and fault tolerancepurposes, most common file systems used in MapReduce-type clusters maintain a set of replicas for each data block. A coveringset is a group of nodes that together contain at least one replica of the data blocks needed for performing computing tasks. In thiswork, we develop and analyze algorithms to maintain energy proportionality by discovering a covering set that minimizesenergy consumption while placing the remaining nodes in lowpower standby mode. Our algorithms can also discover coveringsets in heterogeneous computing environments. In order to allow more data parallelism, we generalize our algorithms so that itcan discover k-covering sets, i.e., a set of nodes that contain at least k replicas of the data blocks. Our experimental results showthat we can achieve substantial energy saving without significant performance loss in diverse cluster configurations and workingenvironments.

  20. A Parallel Implementation of a Smoothed Particle Hydrodynamics Method on Graphics Hardware Using the Compute Unified Device Architecture

    SciTech Connect

    Wong Unhong; Wong Honcheng; Tang Zesheng

    2010-05-21

    The smoothed particle hydrodynamics (SPH), which is a class of meshfree particle methods (MPMs), has a wide range of applications from micro-scale to macro-scale as well as from discrete systems to continuum systems. Graphics hardware, originally designed for computer graphics, now provide unprecedented computational power for scientific computation. Particle system needs a huge amount of computations in physical simulation. In this paper, an efficient parallel implementation of a SPH method on graphics hardware using the Compute Unified Device Architecture is developed for fluid simulation. Comparing to the corresponding CPU implementation, our experimental results show that the new approach allows significant speedups of fluid simulation through handling huge amount of computations in parallel on graphics hardware.

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

    SciTech Connect

    Hey, Tony; Agarwal, Deborah; Borgman, Christine; Cartaro, Concetta; Crivelli, Silvia; Van Dam, Kerstin Kleese; Luce, Richard; Arjun, Shankar; Trefethen, Anne; Wade, Alex; Williams, Dean

    2015-09-04

    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.

  2. Computational performance of a smoothed particle hydrodynamics simulation for shared-memory parallel computing

    NASA Astrophysics Data System (ADS)

    Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide

    2015-09-01

    The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.

  3. Parallel Computation of Unsteady Flows on a Network of Workstations

    NASA Technical Reports Server (NTRS)

    1997-01-01

    Parallel computation of unsteady flows requires significant computational resources. The utilization of a network of workstations seems an efficient solution to the problem where large problems can be treated at a reasonable cost. This approach requires the solution of several problems: 1) the partitioning and distribution of the problem over a network of workstation, 2) efficient communication tools, 3) managing the system efficiently for a given problem. Of course, there is the question of the efficiency of any given numerical algorithm to such a computing system. NPARC code was chosen as a sample for the application. For the explicit version of the NPARC code both two- and three-dimensional problems were studied. Again both steady and unsteady problems were investigated. The issues studied as a part of the research program were: 1) how to distribute the data between the workstations, 2) how to compute and how to communicate at each node efficiently, 3) how to balance the load distribution. In the following, a summary of these activities is presented. Details of the work have been presented and published as referenced.

  4. Parallel Computations in Insect and Mammalian Visual Motion Processing.

    PubMed

    Clark, Damon A; Demb, Jonathan B

    2016-10-24

    Sensory systems use receptors to extract information from the environment and neural circuits to perform subsequent computations. These computations may be described as algorithms composed of sequential mathematical operations. Comparing these operations across taxa reveals how different neural circuits have evolved to solve the same problem, even when using different mechanisms to implement the underlying math. In this review, we compare how insect and mammalian neural circuits have solved the problem of motion estimation, focusing on the fruit fly Drosophila and the mouse retina. Although the two systems implement computations with grossly different anatomy and molecular mechanisms, the underlying circuits transform light into motion signals with strikingly similar processing steps. These similarities run from photoreceptor gain control and spatiotemporal tuning to ON and OFF pathway structures, motion detection, and computed motion signals. The parallels between the two systems suggest that a limited set of algorithms for estimating motion satisfies both the needs of sighted creatures and the constraints imposed on them by metabolism, anatomy, and the structure and regularities of the visual world.

  5. Low latency, high bandwidth data communications between compute nodes in a parallel computer

    DOEpatents

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

    2010-11-02

    Methods, parallel computers, and computer program products are disclosed for low latency, high bandwidth data communications between compute nodes in a parallel computer. Embodiments include receiving, by an origin direct memory access (`DMA`) engine of an origin compute node, data for transfer to a target compute node; sending, by the origin DMA engine of the origin compute node to a target DMA engine on the target compute node, a request to send (`RTS`) message; transferring, by the origin DMA engine, a predetermined portion of the data to the target compute node using memory FIFO operation; determining, by the origin DMA engine whether an acknowledgement of the RTS message has been received from the target DMA engine; if the an acknowledgement of the RTS message has not been received, transferring, by the origin DMA engine, another predetermined portion of the data to the target compute node using a memory FIFO operation; and if the acknowledgement of the RTS message has been received by the origin DMA engine, transferring, by the origin DMA engine, any remaining portion of the data to the target compute node using a direct put operation.

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

    SciTech Connect

    Sadooghi, Iman; Hernandez Martin, Jesus; Li, Tonglin; Brandstatter, Kevin; Zhao, Yong; Maheshwari, Ketan; Pais Pitta de Lacerda Ruivo, Tiago; Timm, Steven; Garzoglio, Gabriele; Raicu, Ioan

    2015-01-01

    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 to 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.

  7. Parallel processing using an optical delay-based reservoir computer

    NASA Astrophysics Data System (ADS)

    Van der Sande, Guy; Nguimdo, Romain Modeste; Verschaffelt, Guy

    2016-04-01

    Delay systems subject to delayed optical feedback have recently shown great potential in solving computationally hard tasks. By implementing a neuro-inspired computational scheme relying on the transient response to optical data injection, high processing speeds have been demonstrated. However, reservoir computing systems based on delay dynamics discussed in the literature are designed by coupling many different stand-alone components which lead to bulky, lack of long-term stability, non-monolithic systems. Here we numerically investigate the possibility of implementing reservoir computing schemes based on semiconductor ring lasers. Semiconductor ring lasers are semiconductor lasers where the laser cavity consists of a ring-shaped waveguide. SRLs are highly integrable and scalable, making them ideal candidates for key components in photonic integrated circuits. SRLs can generate light in two counterpropagating directions between which bistability has been demonstrated. We demonstrate that two independent machine learning tasks , even with different nature of inputs with different input data signals can be simultaneously computed using a single photonic nonlinear node relying on the parallelism offered by photonics. We illustrate the performance on simultaneous chaotic time series prediction and a classification of the Nonlinear Channel Equalization. We take advantage of different directional modes to process individual tasks. Each directional mode processes one individual task to mitigate possible crosstalk between the tasks. Our results indicate that prediction/classification with errors comparable to the state-of-the-art performance can be obtained even with noise despite the two tasks being computed simultaneously. We also find that a good performance is obtained for both tasks for a broad range of the parameters. The results are discussed in detail in [Nguimdo et al., IEEE Trans. Neural Netw. Learn. Syst. 26, pp. 3301-3307, 2015

  8. Cloud identification using genetic algorithms and massively parallel computation

    NASA Technical Reports Server (NTRS)

    Buckles, Bill P.; Petry, Frederick E.

    1996-01-01

    As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user

  9. Seismic imaging using finite-differences and parallel computers

    SciTech Connect

    Ober, C.C.

    1997-12-31

    A key to reducing the risks and costs of associated with oil and gas exploration is the fast, accurate imaging of complex geologies, such as salt domes in the Gulf of Mexico and overthrust regions in US onshore regions. Prestack depth migration generally yields the most accurate images, and one approach to this is to solve the scalar wave equation using finite differences. As part of an ongoing ACTI project funded by the US Department of Energy, a finite difference, 3-D prestack, depth migration code has been developed. The goal of this work is to demonstrate that massively parallel computers can be used efficiently for seismic imaging, and that sufficient computing power exists (or soon will exist) to make finite difference, prestack, depth migration practical for oil and gas exploration. Several problems had to be addressed to get an efficient code for the Intel Paragon. These include efficient I/O, efficient parallel tridiagonal solves, and high single-node performance. Furthermore, to provide portable code the author has been restricted to the use of high-level programming languages (C and Fortran) and interprocessor communications using MPI. He has been using the SUNMOS operating system, which has affected many of his programming decisions. He will present images created from two verification datasets (the Marmousi Model and the SEG/EAEG 3D Salt Model). Also, he will show recent images from real datasets, and point out locations of improved imaging. Finally, he will discuss areas of current research which will hopefully improve the image quality and reduce computational costs.

  10. Development of magnetron sputtering simulator with GPU parallel computing

    NASA Astrophysics Data System (ADS)

    Sohn, Ilyoup; Kim, Jihun; Bae, Junkyeong; Lee, Jinpil

    2014-12-01

    Sputtering devices are widely used in the semiconductor and display panel manufacturing process. Currently, a number of surface treatment applications using magnetron sputtering techniques are being used to improve the efficiency of the sputtering process, through the installation of magnets outside the vacuum chamber. Within the internal space of the low pressure chamber, plasma generated from the combination of a rarefied gas and an electric field is influenced interactively. Since the quality of the sputtering and deposition rate on the substrate is strongly dependent on the multi-physical phenomena of the plasma regime, numerical simulations using PIC-MCC (Particle In Cell, Monte Carlo Collision) should be employed to develop an efficient sputtering device. In this paper, the development of a magnetron sputtering simulator based on the PIC-MCC method and the associated numerical techniques are discussed. To solve the electric field equations in the 2-D Cartesian domain, a Poisson equation solver based on the FDM (Finite Differencing Method) is developed and coupled with the Monte Carlo Collision method to simulate the motion of gas particles influenced by an electric field. The magnetic field created from the permanent magnet installed outside the vacuum chamber is also numerically calculated using Biot-Savart's Law. All numerical methods employed in the present PIC code are validated by comparison with analytical and well-known commercial engineering software results, with all of the results showing good agreement. Finally, the developed PIC-MCC code is parallelized to be suitable for general purpose computing on graphics processing unit (GPGPU) acceleration, so as to reduce the large computation time which is generally required for particle simulations. The efficiency and accuracy of the GPGPU parallelized magnetron sputtering simulator are examined by comparison with the calculated results and computation times from the original serial code. It is found that

  11. Pacing a data transfer operation between compute nodes on a parallel computer

    DOEpatents

    Blocksome, Michael A.

    2011-09-13

    Methods, systems, and products are disclosed for pacing a data transfer between compute nodes on a parallel computer that include: transferring, by an origin compute node, a chunk of an application message to a target compute node; sending, by the origin compute node, a pacing request to a target direct memory access (`DMA`) engine on the target compute node using a remote get DMA operation; determining, by the origin compute node, whether a pacing response to the pacing request has been received from the target DMA engine; and transferring, by the origin compute node, a next chunk of the application message if the pacing response to the pacing request has been received from the target DMA engine.

  12. Understanding Performance of Parallel Scientific Simulation Codes using Open|SpeedShop

    SciTech Connect

    Ghosh, K K

    2011-11-07

    Conclusions of this presentation are: (1) Open SpeedShop's (OSS) is convenient to use for large, parallel, scientific simulation codes; (2) Large codes benefit from uninstrumented execution; (3) Many experiments can be run in a short time - might need multiple shots e.g. usertime for caller-callee, hwcsamp for HW counters; (4) Decent idea of code's performance is easily obtained; (5) Statistical sampling calls for decent number of samples; and (6) HWC data is very useful for micro-analysis but can be tricky to analyze.

  13. PARLO: PArallel Run-Time Layout Optimization for Scientific Data Explorations with Heterogeneous Access Pattern

    SciTech Connect

    Gong, Zhenhuan; Boyuka, David; Zou, X; Liu, Gary; Podhorszki, Norbert; Klasky, Scott A; Ma, Xiaosong; Samatova, Nagiza F

    2013-01-01

    Download Citation Email Print Request Permissions Save to Project The size and scope of cutting-edge scientific simulations are growing much faster than the I/O and storage capabilities of their run-time environments. The growing gap is exacerbated by exploratory, data-intensive analytics, such as querying simulation data with multivariate, spatio-temporal constraints, which induces heterogeneous access patterns that stress the performance of the underlying storage system. Previous work addresses data layout and indexing techniques to improve query performance for a single access pattern, which is not sufficient for complex analytics jobs. We present PARLO a parallel run-time layout optimization framework, to achieve multi-level data layout optimization for scientific applications at run-time before data is written to storage. The layout schemes optimize for heterogeneous access patterns with user-specified priorities. PARLO is integrated with ADIOS, a high-performance parallel I/O middleware for large-scale HPC applications, to achieve user-transparent, light-weight layout optimization for scientific datasets. It offers simple XML-based configuration for users to achieve flexible layout optimization without the need to modify or recompile application codes. Experiments show that PARLO improves performance by 2 to 26 times for queries with heterogeneous access patterns compared to state-of-the-art scientific database management systems. Compared to traditional post-processing approaches, its underlying run-time layout optimization achieves a 56% savings in processing time and a reduction in storage overhead of up to 50%. PARLO also exhibits a low run-time resource requirement, while also limiting the performance impact on running applications to a reasonable level.

  14. Programming a massively parallel, computation universal system: Static behavior

    NASA Astrophysics Data System (ADS)

    Lapedes, Alan; Farber, Robert

    1986-08-01

    Massively parallel systems are presently the focus of intense interest for a variety of reasons. A key problem is how to control, or ``program'' these systems. In previous work by the authors, the ``optimum finding'' properties of Hopfield neural nets were applied to the nets themselves to create a ``neural compiler.'' This was done in such a way that the problem of programming the attractors of one neural net (called the Slave net) was expressed as an optimization problem that was in turn solved by a second neural net (the Master net). The procedure is effective and efficient. In this series of papers we extend that approach to programming nets that contain interneurons (sometimes called ``hidden neurons''), and thus we deal with nets capable of universal computation. Our work is closely related to recent work of Rummelhart et al. (also Parker, and LeChun), which may be viewed as a special case of this formalism and therefore of ``computing with attractors.'' In later papers in this series, we present the theory for programming time dependent behavior, and consider practical implementations. One may expect numerous applications in view of the computation universality of these networks.

  15. Implementation of Parallel Computing Technology to Vortex Flow

    NASA Technical Reports Server (NTRS)

    Dacles-Mariani, Jennifer

    1999-01-01

    Mainframe supercomputers such as the Cray C90 was invaluable in obtaining large scale computations using several millions of grid points to resolve salient features of a tip vortex flow over a lifting wing. However, real flight configurations require tracking not only of the flow over several lifting wings but its growth and decay in the near- and intermediate- wake regions, not to mention the interaction of these vortices with each other. Resolving and tracking the evolution and interaction of these vortices shed from complex bodies is computationally intensive. Parallel computing technology is an attractive option in solving these flows. In planetary science vortical flows are also important in studying how planets and protoplanets form when cosmic dust and gases become gravitationally unstable and eventually form planets or protoplanets. The current paradigm for the formation of planetary systems maintains that the planets accreted from the nebula of gas and dust left over from the formation of the Sun. Traditional theory also indicate that such a preplanetary nebula took the form of flattened disk. The coagulation of dust led to the settling of aggregates toward the midplane of the disk, where they grew further into asteroid-like planetesimals. Some of the issues still remaining in this process are the onset of gravitational instability, the role of turbulence in the damping of particles and radial effects. In this study the focus will be with the role of turbulence and the radial effects.

  16. Optimized collectives using a DMA on a parallel computer

    DOEpatents

    Chen, Dong; Gabor, Dozsa; Giampapa, Mark E.; Heidelberger; Phillip

    2011-02-08

    Optimizing collective operations using direct memory access controller on a parallel computer, in one aspect, may comprise establishing a byte counter associated with a direct memory access controller for each submessage in a message. The byte counter includes at least a base address of memory and a byte count associated with a submessage. A byte counter associated with a submessage is monitored to determine whether at least a block of data of the submessage has been received. The block of data has a predetermined size, for example, a number of bytes. The block is processed when the block has been fully received, for example, when the byte count indicates all bytes of the block have been received. The monitoring and processing may continue for all blocks in all submessages in the message.

  17. On implicit Runge-Kutta methods for parallel computations

    NASA Technical Reports Server (NTRS)

    Keeling, Stephen L.

    1987-01-01

    Implicit Runge-Kutta methods which are well-suited for parallel computations are characterized. It is claimed that such methods are first of all, those for which the associated rational approximation to the exponential has distinct poles, and these are called multiply explicit (MIRK) methods. Also, because of the so-called order reduction phenomenon, there is reason to require that these poles be real. Then, it is proved that a necessary condition for a q-stage, real MIRK to be A sub 0-stable with maximal order q + 1 is that q = 1, 2, 3, or 5. Nevertheless, it is shown that for every positive integer q, there exists a q-stage, real MIRK which is I-stable with order q. Finally, some useful examples of algebraically stable MIRKs are given.

  18. Efficient relaxed-Jacobi smoothers for multigrid on parallel computers

    NASA Astrophysics Data System (ADS)

    Yang, Xiang; Mittal, Rajat

    2017-03-01

    In this Technical Note, we present a family of Jacobi-based multigrid smoothers suitable for the solution of discretized elliptic equations. These smoothers are based on the idea of scheduled-relaxation Jacobi proposed recently by Yang & Mittal (2014) [18] and employ two or three successive relaxed Jacobi iterations with relaxation factors derived so as to maximize the smoothing property of these iterations. The performance of these new smoothers measured in terms of convergence acceleration and computational workload, is assessed for multi-domain implementations typical of parallelized solvers, and compared to the lexicographic point Gauss-Seidel smoother. The tests include the geometric multigrid method on structured grids as well as the algebraic grid method on unstructured grids. The tests demonstrate that unlike Gauss-Seidel, the convergence of these Jacobi-based smoothers is unaffected by domain decomposition, and furthermore, they outperform the lexicographic Gauss-Seidel by factors that increase with domain partition count.

  19. 76 FR 64330 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-18

    ... Advanced Scientific Computing Advisory Committee AGENCY: Department of Energy, Office of Science. ACTION... Reliability, Diffusion on Complex Networks, and Reversible Software Execution Systems Report from Applied Math... at: (301) 903-7486 or by email at: Melea.Baker@science.doe.gov . You must make your request for...

  20. 78 FR 56871 - Advanced Scientific Computing Advisory Committee

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-16

    ... Advanced Scientific Computing Advisory Committee AGENCY: Office of Science, Department of Energy. ACTION... Exascale technical approaches subcommittee Facilities update Report from Applied Math Committee of Visitors...: ( Melea.Baker@science.doe.gov ). You must make your request for an oral statement at least five...

  1. 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…

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

    PubMed

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

    2010-10-01

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

  3. Low cost, highly effective parallel computing achieved through a Beowulf cluster.

    PubMed

    Bitner, Marc; Skelton, Gordon

    2003-01-01

    A Beowulf cluster is a means of bringing together several computers and using software and network components to make this cluster of computers appear and function as one computer with multiple parallel computing processors. A cluster of computers can provide comparable computing power usually found only in very expensive super computers or servers.

  4. Institute for Scientific Computing Research Annual Report: Fiscal Year 2004

    SciTech Connect

    Keyes, D E

    2005-02-07

    Large-scale scientific computation and all of the disciplines that support and help to validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of computational simulation as a tool of scientific and engineering research is underscored in the November 2004 statement of the Secretary of Energy that, ''high performance computing is the backbone of the nation's science and technology enterprise''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use efficiently. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche of data. Advances in scientific computing research have, therefore, never been more vital to LLNL's core missions than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In Fiscal Year 2004, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for short- and

  5. Fast parallel Markov clustering in bioinformatics using massively parallel computing on GPU with CUDA and ELLPACK-R sparse format.

    PubMed

    Bustamam, Alhadi; Burrage, Kevin; Hamilton, Nicholas A

    2012-01-01

    Markov clustering (MCL) is becoming a key algorithm within bioinformatics for determining clusters in networks. However,with increasing vast amount of data on biological networks, performance and scalability issues are becoming a critical limiting factor in applications. Meanwhile, GPU computing, which uses CUDA tool for implementing a massively parallel computing environment in the GPU card, is becoming a very powerful, efficient, and low-cost option to achieve substantial performance gains over CPU approaches. The use of on-chip memory on the GPU is efficiently lowering the latency time, thus, circumventing a major issue in other parallel computing environments, such as MPI. We introduce a very fast Markov clustering algorithm using CUDA (CUDA-MCL) to perform parallel sparse matrix-matrix computations and parallel sparse Markov matrix normalizations, which are at the heart of MCL. We utilized ELLPACK-R sparse format to allow the effective and fine-grain massively parallel processing to cope with the sparse nature of interaction networks data sets in bioinformatics applications. As the results show, CUDA-MCL is significantly faster than the original MCL running on CPU. Thus, large-scale parallel computation on off-the-shelf desktop-machines, that were previously only possible on supercomputing architectures, can significantly change the way bioinformaticians and biologists deal with their data.

  6. 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

  7. SAF - Sets and Fields parallel I/O and scientific data modeling system

    SciTech Connect

    Matzke, Robb; Illescas, Eric; Espen, Peter; Jones, Jake S.; Sjaardema, Gregory; Miller, Mark C.; Schoof, Larry A.; Reus, James F.; Arrighi, William; Hitt, Ray T.; O'Brien, Matthew J.

    2005-07-01

    SAF is being developed as part of the Data Models and Formats (DMF) component of the Accelerated Strategic Computing Initiative (ASCI). SAF represents a revolutionary approach to interoperation of high performance, scientific computing applications based upon rigorous, math oriented data modeling principles. Previous technologies have required all applications to use the same data structures and/or mesh objects to represent scientific data or lead to an ever expanding set of incrementally different data structures and/or mesh objects. SAF addresses this problem by providing a small set of mathematical building blocks, sets, relations and fields, out of which a wide variety of scientific data can be characterized. Applications literally model their data by assembling these building blocks. Sets and fields building blocks are at once, both primitive and abstract: * They are primitive enough to model a wide variety of scientific data. * They are abstract enough to model the data in terms of what it represents in a mathematical or physical sense independent of how it is represented in an implementation sense. For example, while there are many ways to represent the airflow over the wing of a supersonic aircraft in a computer program, there is only one mathematical/physical interpretation: a field of 3D velocity vectors over a 2D surface. This latter description is immutable. It is independent of any particular representation or implementation choices. Understanding this what versus how relationship, that is what is represented versus how it is represented, is key to developing a solution for large scale integration of scientific software.

  8. Scalable High Performance Computing: Direct and Large-Eddy Turbulent Flow Simulations Using Massively Parallel Computers

    NASA Technical Reports Server (NTRS)

    Morgan, Philip E.

    2004-01-01

    This final report contains reports of research related to the tasks "Scalable High Performance Computing: Direct and Lark-Eddy Turbulent FLow Simulations Using Massively Parallel Computers" and "Devleop High-Performance Time-Domain Computational Electromagnetics Capability for RCS Prediction, Wave Propagation in Dispersive Media, and Dual-Use Applications. The discussion of Scalable High Performance Computing reports on three objectives: validate, access scalability, and apply two parallel flow solvers for three-dimensional Navier-Stokes flows; develop and validate a high-order parallel solver for Direct Numerical Simulations (DNS) and Large Eddy Simulation (LES) problems; and Investigate and develop a high-order Reynolds averaged Navier-Stokes turbulence model. The discussion of High-Performance Time-Domain Computational Electromagnetics reports on five objectives: enhancement of an electromagnetics code (CHARGE) to be able to effectively model antenna problems; utilize lessons learned in high-order/spectral solution of swirling 3D jets to apply to solving electromagnetics project; transition a high-order fluids code, FDL3DI, to be able to solve Maxwell's Equations using compact-differencing; develop and demonstrate improved radiation absorbing boundary conditions for high-order CEM; and extend high-order CEM solver to address variable material properties. The report also contains a review of work done by the systems engineer.

  9. Modeling the fracture of ice sheets on parallel computers.

    SciTech Connect

    Waisman, Haim; Bell, Robin; Keyes, David; Boman, Erik Gunnar; Tuminaro, Raymond Stephen

    2010-03-01

    The objective of this project is to investigate the complex fracture of ice and understand its role within larger ice sheet simulations and global climate change. At the present time, ice fracture is not explicitly considered within ice sheet models due in part to large computational costs associated with the accurate modeling of this complex phenomena. However, fracture not only plays an extremely important role in regional behavior but also influences ice dynamics over much larger zones in ways that are currently not well understood. Dramatic illustrations of fracture-induced phenomena most notably include the recent collapse of ice shelves in Antarctica (e.g. partial collapse of the Wilkins shelf in March of 2008 and the diminishing extent of the Larsen B shelf from 1998 to 2002). Other fracture examples include ice calving (fracture of icebergs) which is presently approximated in simplistic ways within ice sheet models, and the draining of supraglacial lakes through a complex network of cracks, a so called ice sheet plumbing system, that is believed to cause accelerated ice sheet flows due essentially to lubrication of the contact surface with the ground. These dramatic changes are emblematic of the ongoing change in the Earth's polar regions and highlight the important role of fracturing ice. To model ice fracture, a simulation capability will be designed centered around extended finite elements and solved by specialized multigrid methods on parallel computers. In addition, appropriate dynamic load balancing techniques will be employed to ensure an approximate equal amount of work for each processor.

  10. Dynamic modeling of Tampa Bay urban development using parallel computing

    USGS Publications Warehouse

    Xian, G.; Crane, M.; Steinwand, D.

    2005-01-01

    Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively. ?? 2005 Elsevier Ltd. All rights reserved.

  11. Dynamic modeling of Tampa Bay urban development using parallel computing

    NASA Astrophysics Data System (ADS)

    Xian, George; Crane, Mike; Steinwand, Dan

    2005-08-01

    Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively.

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

    SciTech Connect

    Schlicher, Bob G; Kulesz, James J; Abercrombie, Robert K; Kruse, Kara L

    2015-01-01

    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 Oak 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 .

  13. Massively parallel computational fluid dynamics calculations for aerodynamics and aerothermodynamics applications

    SciTech Connect

    Payne, J.L.; Hassan, B.

    1998-09-01

    Massively parallel computers have enabled the analyst to solve complicated flow fields (turbulent, chemically reacting) that were previously intractable. Calculations are presented using a massively parallel CFD code called SACCARA (Sandia Advanced Code for Compressible Aerothermodynamics Research and Analysis) currently under development at Sandia National Laboratories as part of the Department of Energy (DOE) Accelerated Strategic Computing Initiative (ASCI). Computations were made on a generic reentry vehicle in a hypersonic flowfield utilizing three different distributed parallel computers to assess the parallel efficiency of the code with increasing numbers of processors. The parallel efficiencies for the SACCARA code will be presented for cases using 1, 150, 100 and 500 processors. Computations were also made on a subsonic/transonic vehicle using both 236 and 521 processors on a grid containing approximately 14.7 million grid points. Ongoing and future plans to implement a parallel overset grid capability and couple SACCARA with other mechanics codes in a massively parallel environment are discussed.

  14. 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

  15. Acts -- A collection of high performing software tools for scientific computing

    SciTech Connect

    Drummond, L.A.; Marques, O.A.

    2002-11-01

    During the past decades there has been a continuous growth in the number of physical and societal problems that have been successfully studied and solved by means of computational modeling and simulation. Further, many new discoveries depend on high performance computer simulations to satisfy their demands for large computational resources and short response time. The Advanced CompuTational Software (ACTS) Collection brings together a number of general-purpose computational tool development projects funded and supported by the U.S. Department of Energy (DOE). These tools make it easier for scientific code developers to write high performance applications for parallel computers. They tackle a number of computational issues that are common to a large number of scientific applications, mainly implementation of numerical algorithms, and support for code development, execution and optimization. The ACTS collection promotes code portability, reusability, reduction of duplicate efforts, and tool maturity. This paper presents a brief introduction to the functionality available in ACTS. It also highlight the tools that are in demand by Climate and Weather modelers.

  16. Analysis of composite ablators using massively parallel computation

    NASA Technical Reports Server (NTRS)

    Shia, David

    1995-01-01

    In this work, the feasibility of using massively parallel computation to study the response of ablative materials is investigated. Explicit and implicit finite difference methods are used on a massively parallel computer, the Thinking Machines CM-5. The governing equations are a set of nonlinear partial differential equations. The governing equations are developed for three sample problems: (1) transpiration cooling, (2) ablative composite plate, and (3) restrained thermal growth testing. The transpiration cooling problem is solved using a solution scheme based solely on the explicit finite difference method. The results are compared with available analytical steady-state through-thickness temperature and pressure distributions and good agreement between the numerical and analytical solutions is found. It is also found that a solution scheme based on the explicit finite difference method has the following advantages: incorporates complex physics easily, results in a simple algorithm, and is easily parallelizable. However, a solution scheme of this kind needs very small time steps to maintain stability. A solution scheme based on the implicit finite difference method has the advantage that it does not require very small times steps to maintain stability. However, this kind of solution scheme has the disadvantages that complex physics cannot be easily incorporated into the algorithm and that the solution scheme is difficult to parallelize. A hybrid solution scheme is then developed to combine the strengths of the explicit and implicit finite difference methods and minimize their weaknesses. This is achieved by identifying the critical time scale associated with the governing equations and applying the appropriate finite difference method according to this critical time scale. The hybrid solution scheme is then applied to the ablative composite plate and restrained thermal growth problems. The gas storage term is included in the explicit pressure calculation of both

  17. Dynamic remapping decisions in multi-phase parallel computations

    NASA Technical Reports Server (NTRS)

    Nicol, D. M.; Reynolds, P. F., Jr.

    1986-01-01

    The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.

  18. Iterative algorithms for large sparse linear systems on parallel computers

    NASA Technical Reports Server (NTRS)

    Adams, L. M.

    1982-01-01

    Algorithms for assembling in parallel the sparse system of linear equations that result from finite difference or finite element discretizations of elliptic partial differential equations, such as those that arise in structural engineering are developed. Parallel linear stationary iterative algorithms and parallel preconditioned conjugate gradient algorithms are developed for solving these systems. In addition, a model for comparing parallel algorithms on array architectures is developed and results of this model for the algorithms are given.

  19. Massively parallel computation of RCS with finite elements

    NASA Technical Reports Server (NTRS)

    Parker, Jay

    1993-01-01

    One of the promising combinations of finite element approaches for scattering problems uses Whitney edge elements, spherical vector wave-absorbing boundary conditions, and bi-conjugate gradient solution for the frequency-domain near field. Each of these approaches may be criticized. Low-order elements require high mesh density, but also result in fast, reliable iterative convergence. Spherical wave-absorbing boundary conditions require additional space to be meshed beyond the most minimal near-space region, but result in fully sparse, symmetric matrices which keep storage and solution times low. Iterative solution is somewhat unpredictable and unfriendly to multiple right-hand sides, yet we find it to be uniformly fast on large problems to date, given the other two approaches. Implementation of these approaches on a distributed memory, message passing machine yields huge dividends, as full scalability to the largest machines appears assured and iterative solution times are well-behaved for large problems. We present times and solutions for computed RCS for a conducting cube and composite permeability/conducting sphere on the Intel ipsc860 with up to 16 processors solving over 200,000 unknowns. We estimate problems of approximately 10 million unknowns, encompassing 1000 cubic wavelengths, may be attempted on a currently available 512 processor machine, but would be exceedingly tedious to prepare. The most severe bottlenecks are due to the slow rate of mesh generation on non-parallel machines and the large transfer time from such a machine to the parallel processor. One solution, in progress, is to create and then distribute a coarse mesh among the processors, followed by systematic refinement within each processor. Elimination of redundant node definitions at the mesh-partition surfaces, snap-to-surface post processing of the resulting mesh for good modelling of curved surfaces, and load-balancing redistribution of new elements after the refinement are auxiliary

  20. An Efficient Objective Analysis System for Parallel Computers

    NASA Technical Reports Server (NTRS)

    Stobie, J.

    1999-01-01

    A new atmospheric objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 1 X 1 lat-lon grid with 18 levels of heights and winds and 10 levels of moisture) using 120,000 observations in 17 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system is totally portable and can run on several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from 1 to 32 CPUs is 18%. In addition, the analysis results are identical regardless of the number of processors used. This system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. Static tests with a 2 X 2.5 resolution version of this system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from several months of cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (O-F statistics) as the current operational system.

  1. An Efficient Objective Analysis System for Parallel Computers

    NASA Technical Reports Server (NTRS)

    Stobie, James G.

    1999-01-01

    A new objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 2 x 2.5 lat-lon grid with 20 levels of heights and winds and 10 levels of moisture) using 120,000 observations in less than 3 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system Ls totally portable and can run on -several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from I to 32 CPus is 18%. in addition, the analysis results are identical regardless of the number of processors used. T'his system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. It also includes a new quality control (buddy check) system. Static tests with the system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from a 2-month cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (0-F statistics) throughout the entire two months.

  2. The Potential of the Cell Processor for Scientific Computing

    SciTech Connect

    Williams, Samuel; Shalf, John; Oliker, Leonid; Husbands, Parry; Kamil, Shoaib; Yelick, Katherine

    2005-10-14

    The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of the using the forth coming STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. We are the first to present quantitative Cell performance data on scientific kernels and show direct comparisons against leading superscalar (AMD Opteron), VLIW (IntelItanium2), and vector (Cray X1) architectures. Since neither Cell hardware nor cycle-accurate simulators are currently publicly available, we develop both analytical models and simulators to predict kernel performance. Our work also explores the complexity of mapping several important scientific algorithms onto the Cells unique architecture. Additionally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

  3. Nexus: An interoperability layer for parallel and distributed computer systems

    SciTech Connect

    Foster, I.; Kesselman, C.; Olson, R.; Tuecke, S.

    1994-05-01

    Nexus is a set of services that can be used to implement various task-parallel languages, data-parallel languages, and message-passing libraries. Nexus is designed to permit the efficient portable implementation of individual parallel programming systems and the interoperability of programs developed with different tools. Nexus supports lightweight threading and active message technology, allowing integration of message passing and threads.

  4. Design of a massively parallel computer using bit serial processing elements

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  5. A Visual Database System for Image Analysis on Parallel Computers and its Application to the EOS Amazon Project

    NASA Technical Reports Server (NTRS)

    Shapiro, Linda G.; Tanimoto, Steven L.; Ahrens, James P.

    1996-01-01

    The goal of this task was to create a design and prototype implementation of a database environment that is particular suited for handling the image, vision and scientific data associated with the NASA's EOC Amazon project. The focus was on a data model and query facilities that are designed to execute efficiently on parallel computers. A key feature of the environment is an interface which allows a scientist to specify high-level directives about how query execution should occur.

  6. Genetic algorithm based task reordering to improve the performance of batch scheduled massively parallel scientific applications

    DOE PAGES

    Sankaran, Ramanan; Angel, Jordan; Brown, W. Michael

    2015-04-08

    The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on themore » performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.« less

  7. Genetic algorithm based task reordering to improve the performance of batch scheduled massively parallel scientific applications

    SciTech Connect

    Sankaran, Ramanan; Angel, Jordan; Brown, W. Michael

    2015-04-08

    The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on the performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.

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

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

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

  9. 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.

  10. Full tensor gravity gradiometry data inversion: Performance analysis of parallel computing algorithms

    NASA Astrophysics Data System (ADS)

    Hou, Zhen-Long; Wei, Xiao-Hui; Huang, Da-Nian; Sun, Xu

    2015-09-01

    We apply reweighted inversion focusing to full tensor gravity gradiometry data using message-passing interface (MPI) and compute unified device architecture (CUDA) parallel computing algorithms, and then combine MPI with CUDA to formulate a hybrid algorithm. Parallel computing performance metrics are introduced to analyze and compare the performance of the algorithms. We summarize the rules for the performance evaluation of parallel algorithms. We use model and real data from the Vinton salt dome to test the algorithms. We find good match between model and real density data, and verify the high efficiency and feasibility of parallel computing algorithms in the inversion of full tensor gravity gradiometry data.

  11. Smart Libraries: Best SQE Practices for Libraries with an Emphasis on Scientific Computing

    SciTech Connect

    Miller, M C; Reus, J F; Matzke, R P; Koziol, Q A; Cheng, A P

    2004-12-15

    As scientific computing applications grow in complexity, more and more functionality is being packaged in independently developed libraries. Worse, as the computing environments in which these applications run grow in complexity, it gets easier to make mistakes in building, installing and using libraries as well as the applications that depend on them. Unfortunately, SQA standards so far developed focus primarily on applications, not libraries. We show that SQA standards for libraries differ from applications in many respects. We introduce and describe a variety of practices aimed at minimizing the likelihood of making mistakes in using libraries and at maximizing users' ability to diagnose and correct them when they occur. We introduce the term Smart Library to refer to a library that is developed with these basic principles in mind. We draw upon specific examples from existing products we believe incorporate smart features: MPI, a parallel message passing library, and HDF5 and SAF, both of which are parallel I/O libraries supporting scientific computing applications. We conclude with a narrative of some real-world experiences in using smart libraries with Ale3d, VisIt and SAF.

  12. Performance Evaluation of Three Distributed Computing Environments for Scientific Applications

    NASA Technical Reports Server (NTRS)

    Fatoohi, Rod; Weeratunga, Sisira; Lasinski, T. A. (Technical Monitor)

    1994-01-01

    We present performance results for three distributed computing environments using the three simulated CFD applications in the NAS Parallel Benchmark suite. These environments are the DCF cluster, the LACE cluster, and an Intel iPSC/860 machine. The DCF is a prototypic cluster of loosely coupled SGI R3000 machines connected by Ethernet. The LACE cluster is a tightly coupled cluster of 32 IBM RS6000/560 machines connected by Ethernet as well as by either FDDI or an IBM Allnode switch. Results of several parallel algorithms for the three simulated applications are presented and analyzed based on the interplay between the communication requirements of an algorithm and the characteristics of the communication network of a distributed system.

  13. Three-dimensional radiative transfer on a massively parallel computer

    NASA Technical Reports Server (NTRS)

    Vath, H. M.

    1994-01-01

    We perform 3D radiative transfer calculations in non-local thermodynamic equilibrium (NLTE) in the simple two-level atom approximation on the Mas-Par MP-1, which contains 8192 processors and is a single instruction multiple data (SIMD) machine, an example of the new generation of massively parallel computers. On such a machine, all processors execute the same command at a given time, but on different data. To make radiative transfer calculations efficient, we must re-consider the numerical methods and storage of data. To solve the transfer equation, we adopt the short characteristic method and examine different acceleration methods to obtain the source function. We use the ALI method and test local and non-local operators. Furthermore, we compare the Ng and the orthomin methods of acceleration. We also investigate the use of multi-grid methods to get fast solutions for the NLTE case. In order to test these numerical methods, we apply them to two problems with and without periodic boundary conditions.

  14. Parallel multiphysics algorithms and software for computational nuclear engineering

    NASA Astrophysics Data System (ADS)

    Gaston, D.; Hansen, G.; Kadioglu, S.; Knoll, D. A.; Newman, C.; Park, H.; Permann, C.; Taitano, W.

    2009-07-01

    There is a growing trend in nuclear reactor simulation to consider multiphysics problems. This can be seen in reactor analysis where analysts are interested in coupled flow, heat transfer and neutronics, and in fuel performance simulation where analysts are interested in thermomechanics with contact coupled to species transport and chemistry. These more ambitious simulations usually motivate some level of parallel computing. Many of the coupling efforts to date utilize simple code coupling or first-order operator splitting, often referred to as loose coupling. While these approaches can produce answers, they usually leave questions of accuracy and stability unanswered. Additionally, the different physics often reside on separate grids which are coupled via simple interpolation, again leaving open questions of stability and accuracy. Utilizing state of the art mathematics and software development techniques we are deploying next generation tools for nuclear engineering applications. The Jacobian-free Newton-Krylov (JFNK) method combined with physics-based preconditioning provide the underlying mathematical structure for our tools. JFNK is understood to be a modern multiphysics algorithm, but we are also utilizing its unique properties as a scale bridging algorithm. To facilitate rapid development of multiphysics applications we have developed the Multiphysics Object-Oriented Simulation Environment (MOOSE). Examples from two MOOSE-based applications: PRONGHORN, our multiphysics gas cooled reactor simulation tool and BISON, our multiphysics, multiscale fuel performance simulation tool will be presented.

  15. Massively parallel computation of three-dimensional scramjet combustor

    NASA Astrophysics Data System (ADS)

    Zheng, Z. H.; Le, J. L.

    Recent progress of computational study of scramjet combustor has been described in Refs 1-3. However, detailed flow properties, especially the lateral properties and the sidewall effects are not considered. In this paper, a parallel simulation of an experimental dual-mode scramjet combustor configuration is presented, considering the jet-to-jet symmetry and the full-duct modeling. Turbulence is modeled with the k-ɛ two-equation turbulence model and a 7-specie, 8-equation kinetics model is used to model hydrogen/air combustion. The conservation form of the Navier-Stokes equations with finite-rate chemistry reactions is solved using a diagonal implicit finite-volume method. For the two cases, the three-dimension flow-fields with equivalence ratio Φ=0.0 and 0.35 have been respectively simulated on the COW and MPP. Wall pressure comparisons between CFD and experiments (CARDC and NAL) show fair agreement for the jet-to-jet case. For the full-duct modeling, more detailed flow properties are obtained. The fuelpenetrating heights of the injectors are different because of the effects of the sidewall boundary layer and the shock wave in the combustor. According to numerical results, if adjusting the locations of the injectors, the combustion efficiency could be improved.

  16. Parallelizing Sylvester-like operations on a distributed memory computer

    SciTech Connect

    Hu, D.Y.; Sorensen, D.C.

    1994-12-31

    Discretization of linear operators arising in applied mathematics often leads to matrices with the following structure: M(x) = (D {circle_times} A + B {circle_times} I{sub n} + V)x, where x {element_of} R{sup mn}, B, D {element_of} R{sup nxn}, A {element_of} R{sup mxm} and V {element_of} R{sup mnxmn}; both D and V are diagonal. For the notational convenience, the authors assume that both A and B are symmetric. All the results through this paper can be easily extended to the cases with general A and B. The linear operator on R{sup mn} defined above can be viewed as a generalization of the Sylvester operator: S(x) = (I{sub m} {circle_times} A + B {circle_times} I{sub n})x. The authors therefore refer to it as a Sylvester-like operator. The schemes discussed in this paper therefore also apply to Sylvester operator. In this paper, the authors present the SIMD scheme for parallelization of the Sylvester-like operator on a distributed memory computer. This scheme is designed to approach the best possible efficiency by avoiding unnecessary communication among processors.

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

    DOEpatents

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

    2014-11-18

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

  18. Research in Computational Aeroscience Applications Implemented on Advanced Parallel Computing Systems

    NASA Technical Reports Server (NTRS)

    Wigton, Larry

    1996-01-01

    Improving the numerical linear algebra routines for use in new Navier-Stokes codes, specifically Tim Barth's unstructured grid code, with spin-offs to TRANAIR is reported. A fast distance calculation routine for Navier-Stokes codes using the new one-equation turbulence models is written. The primary focus of this work was devoted to improving matrix-iterative methods. New algorithms have been developed which activate the full potential of classical Cray-class computers as well as distributed-memory parallel computers.

  19. Interfacing parallel scientific applications with multiple visualization systems: The CUMULVS approach

    SciTech Connect

    Kohl, J.A.; Papadopoulos, P.M.

    1998-03-01

    As high-performance computer simulation increasingly replaces more expensive and time-consuming conventional alternatives, namely physical prototyping/experimentation, it becomes important to provide mechanisms for interacting with parallel or distributed simulation programs. Such interactive exchanges can close the loop on simulation experiments by providing visualization of intermediate results and then allowing scientists to respond by manipulating the simulation, while it is running. This type of visualization and computation steering feedback system can dramatically shorten the experimental cycle by pruning off experiments that are quickly seen to be undesirable. Further, such interaction can provide enhanced capabilities for what if analyses, even beyond what would be possible in a physical environment. This approach also introduces new forms of collaboration, by allowing multiple remote collaborators to cooperate and interact via the running simulation programs, each person exploring their own view of the data and then sharing their understanding with the group. The CUMULVS (Collaborative User Migration User Library for Visualization and Steering) system is a middleware library infrastructure that allows multiple, potentially remote, scientists to monitor and coordinate control over a parallel simulation program. Using CUMULVS, various front-end viewers can dynamically attach to a simulation to view snapshots of the ongoing computation, or manipulate (steer) parameters of the simulation, and then detach. The snapshots of intermediate data array values can be rendered using a variant of visualization systems, including AVS, Tcl/Tk, and VTK, or as simple text dumps. CUMULVS provides the interfacing between the simulation tasks and the visualization systems, and transparently handles the viewer connection protocols and the data collection required for decomposed or distributed data. CUMULVS also provides mechanisms for developing fault-tolerant applications in

  20. Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

    NASA Technical Reports Server (NTRS)

    Larson, Jay W.

    1998-01-01

    Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

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

    DOEpatents

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

    2014-11-11

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

  2. Charon Message-Passing Toolkit for Scientific Computations

    NASA Technical Reports Server (NTRS)

    VanderWijngaart, Rob F.; Yan, Jerry (Technical Monitor)

    2000-01-01

    Charon is a library, callable from C and Fortran, that aids the conversion of structured-grid legacy codes-such as those used in the numerical computation of fluid flows-into parallel, high- performance codes. Key are functions that define distributed arrays, that map between distributed and non-distributed arrays, and that allow easy specification of common communications on structured grids. The library is based on the widely accepted MPI message passing standard. We present an overview of the functionality of Charon, and some representative results.

  3. Parallel computations using a cluster of workstations to simulate elasticity problems

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

    Computational physics has played important roles in real world problems. This paper is within the applied computational physics area. The aim of this study is to observe the performance of parallel computations using a cluster of workstations (COW) to simulate elasticity problems. Parallel computations with the COW configuration are conducted using the Message Passing Interface (MPI) standard. In parallel computations with COW, we consider five scenarios with twenty simulations. In addition to the execution time, efficiency is used to evaluate programming algorithm scenarios. Sequential and parallel programming performances are evaluated based on their execution time and efficiency. Results show that the one-dimensional elasticity equations are not appropriate to be solved in parallel with MPI_Send and MPI_Recv technique in the MPI standard, because the total amount of time to exchange data is considered more dominant compared with the total amount of time to conduct the basic elasticity computation.

  4. Parallel Computation of Vernier Offsets, Curvature, and Chevrons in Humans

    DTIC Science & Technology

    1989-12-01

    parallel by the visual system. This interpretation supports the original claim by Julesz and Spivack (1967) of parallel processing in the hyperacuity...vision. TINS 7, 41-45. Julesz B. & Spivack , G.J. (1967) Stereopsis based on vernier cues alone. Science 157, 563-565. Klein, S.A. & Levi, D.M. (1985

  5. Parallel Guessing: A Strategy for High-Speed Computation

    DTIC Science & Technology

    1984-09-19

    for using additional hardware to obtain higher processing speed). In this paper we argue that "parallel guessing" for image analysis is a useful...34distance" from a true solution, or the correctness of a guess, can be readily checked. We review image - analysis algorithms having a parallel guessing or

  6. Algorithmic support for commodity-based parallel computing systems.

    SciTech Connect

    Leung, Vitus Joseph; Bender, Michael A.; Bunde, David P.; Phillips, Cynthia Ann

    2003-10-01

    The Computational Plant or Cplant is a commodity-based distributed-memory supercomputer under development at Sandia National Laboratories. Distributed-memory supercomputers run many parallel programs simultaneously. Users submit their programs to a job queue. When a job is scheduled to run, it is assigned to a set of available processors. Job runtime depends not only on the number of processors but also on the particular set of processors assigned to it. Jobs should be allocated to localized clusters of processors to minimize communication costs and to avoid bandwidth contention caused by overlapping jobs. This report introduces new allocation strategies and performance metrics based on space-filling curves and one dimensional allocation strategies. These algorithms are general and simple. Preliminary simulations and Cplant experiments indicate that both space-filling curves and one-dimensional packing improve processor locality compared to the sorted free list strategy previously used on Cplant. These new allocation strategies are implemented in Release 2.0 of the Cplant System Software that was phased into the Cplant systems at Sandia by May 2002. Experimental results then demonstrated that the average number of communication hops between the processors allocated to a job strongly correlates with the job's completion time. This report also gives processor-allocation algorithms for minimizing the average number of communication hops between the assigned processors for grid architectures. The associated clustering problem is as follows: Given n points in {Re}d, find k points that minimize their average pairwise L{sub 1} distance. Exact and approximate algorithms are given for these optimization problems. One of these algorithms has been implemented on Cplant and will be included in Cplant System Software, Version 2.1, to be released. In more preliminary work, we suggest improvements to the scheduler separate from the allocator.

  7. Memory Benchmarks for SMP-Based High Performance Parallel Computers

    SciTech Connect

    Yoo, A B; de Supinski, B; Mueller, F; Mckee, S A

    2001-11-20

    As the speed gap between CPU and main memory continues to grow, memory accesses increasingly dominates the performance of many applications. The problem is particularly acute for symmetric multiprocessor (SMP) systems, where the shared memory may be accessed concurrently by a group of threads running on separate CPUs. Unfortunately, several key issues governing memory system performance in current systems are not well understood. Complex interactions between the levels of the memory hierarchy, buses or switches, DRAM back-ends, system software, and application access patterns can make it difficult to pinpoint bottlenecks and determine appropriate optimizations, and the situation is even more complex for SMP systems. To partially address this problem, we formulated a set of multi-threaded microbenchmarks for characterizing and measuring the performance of the underlying memory system in SMP-based high-performance computers. We report our use of these microbenchmarks on two important SMP-based machines. This paper has four primary contributions. First, we introduce a microbenchmark suite to systematically assess and compare the performance of different levels in SMP memory hierarchies. Second, we present a new tool based on hardware performance monitors to determine a wide array of memory system characteristics, such as cache sizes, quickly and easily; by using this tool, memory performance studies can be targeted to the full spectrum of performance regimes with many fewer data points than is otherwise required. Third, we present experimental results indicating that the performance of applications with large memory footprints remains largely constrained by memory. Fourth, we demonstrate that thread-level parallelism further degrades memory performance, even for the latest SMPs with hardware prefetching and switch-based memory interconnects.

  8. InSAR Scientific Computing Environment on the Cloud

    NASA Astrophysics Data System (ADS)

    Rosen, P. A.; Shams, K. S.; Gurrola, E. M.; George, B. A.; Knight, D. S.

    2012-12-01

    In response to the needs of the international scientific and operational Earth observation communities, spaceborne Synthetic Aperture Radar (SAR) systems are being tasked to produce enormous volumes of raw data daily, with availability to scientists to increase substantially as more satellites come online and data becomes more accessible through more open data policies. The availability of these unprecedentedly dense and rich datasets has led to the development of sophisticated algorithms that can take advantage of them. In particular, interferometric time series analysis of SAR data provides insights into the changing earth and requires substantial computational power to process data across large regions and over large time periods. This poses challenges for existing infrastructure, software, and techniques required to process, store, and deliver the results to the global community of scientists. The current state-of-the-art solutions employ traditional data storage and processing applications that require download of data to the local repositories before processing. This approach is becoming untenable in light of the enormous volume of data that must be processed in an iterative and collaborative manner. We have analyzed and tested new cloud computing and virtualization approaches to address these challenges within the context of InSAR in the earth science community. Cloud computing is democratizing computational and storage capabilities for science users across the world. The NASA Jet Propulsion Laboratory has been an early adopter of this technology, successfully integrating cloud computing in a variety of production applications ranging from mission operations to downlink data processing. We have ported a new InSAR processing suite called ISCE (InSAR Scientific Computing Environment) to a scalable distributed system running in the Amazon GovCloud to demonstrate the efficacy of cloud computing for this application. We have integrated ISCE with Polyphony to

  9. The transition to massively parallel computing within a production environment at a DOE access center

    SciTech Connect

    McCoy, M.G.

    1993-04-01

    In contemplating the transition from sequential to MP computing, the National Energy Research Supercomputer Center (NERSC) is faced with the frictions inherent in the duality of its mission. There have been two goals, the first has been to provide a stable, serviceable, production environment to the user base, the second to bring the most capable early serial supercomputers to the Center to make possible the leading edge simulations. This seeming conundrum has in reality been a source of strength. The task of meeting both goals was faced before with the CRAY 1 which, as delivered, was all iron; so the problems associated with the advent of parallel computers are not entirely new, but they are serious. Current vector supercomputers, such as the C90, offer mature production environments, including software tools, a large applications base, and generality; these machines can be used to attack the spectrum of scientific applications by a large user base knowledgeable in programming techniques for this architecture. Parallel computers to date have offered less developed, even rudimentary, working environments, a sparse applications base, and forced specialization. They have been specialized in terms of programming models, and specialized in terms of the kinds of applications which would do well on the machines. Given this context, why do many service computer centers feel that now is the time to cease or slow the procurement of traditional vector supercomputers in favor of MP systems? What are some of the issues that NERSC must face to engineer a smooth transition? The answers to these questions are multifaceted and by no means completely clear. However, a route exists as a result of early efforts at the Laboratories combined with research within the HPCC Program. One can begin with an analysis of why the hardware and software appearing shortly should be made available to the mainstream, and then address what would be required in an initial production environment.

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

    NASA Astrophysics Data System (ADS)

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

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

  11. Parallel paving: An algorithm for generating distributed, adaptive, all-quadrilateral meshes on parallel computers

    SciTech Connect

    Lober, R.R.; Tautges, T.J.; Vaughan, C.T.

    1997-03-01

    Paving is an automated mesh generation algorithm which produces all-quadrilateral elements. It can additionally generate these elements in varying sizes such that the resulting mesh adapts to a function distribution, such as an error function. While powerful, conventional paving is a very serial algorithm in its operation. Parallel paving is the extension of serial paving into parallel environments to perform the same meshing functions as conventional paving only on distributed, discretized models. This extension allows large, adaptive, parallel finite element simulations to take advantage of paving`s meshing capabilities for h-remap remeshing. A significantly modified version of the CUBIT mesh generation code has been developed to host the parallel paving algorithm and demonstrate its capabilities on both two dimensional and three dimensional surface geometries and compare the resulting parallel produced meshes to conventionally paved meshes for mesh quality and algorithm performance. Sandia`s {open_quotes}tiling{close_quotes} dynamic load balancing code has also been extended to work with the paving algorithm to retain parallel efficiency as subdomains undergo iterative mesh refinement.

  12. 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.

  13. National Energy Research Scientific Computing Center (NERSC): Advancing the frontiers of computational science and technology

    SciTech Connect

    Hules, J.

    1996-11-01

    National Energy Research Scientific Computing Center (NERSC) provides researchers with high-performance computing tools to tackle science`s biggest and most challenging problems. Founded in 1974 by DOE/ER, the Controlled Thermonuclear Research Computer Center was the first unclassified supercomputer center and was the model for those that followed. Over the years the center`s name was changed to the National Magnetic Fusion Energy Computer Center and then to NERSC; it was relocated to LBNL. NERSC, one of the largest unclassified scientific computing resources in the world, is the principal provider of general-purpose computing services to DOE/ER programs: Magnetic Fusion Energy, High Energy and Nuclear Physics, Basic Energy Sciences, Health and Environmental Research, and the Office of Computational and Technology Research. NERSC users are a diverse community located throughout US and in several foreign countries. This brochure describes: the NERSC advantage, its computational resources and services, future technologies, scientific resources, and computational science of scale (interdisciplinary research over a decade or longer; examples: combustion in engines, waste management chemistry, global climate change modeling).

  14. The Visualization Management System Approach To Visualization In Scientific Computing

    NASA Astrophysics Data System (ADS)

    Butler, David M.; Pendley, Michael H.

    1989-09-01

    We introduce the visualization management system (ViMS), a new approach to the development of software for visualization in scientific computing (ViSC). The conceptual foundation for a ViMS is an abstract visualization model which specifies a class of geometric objects, the graphic representations of the objects and the operations on both. A ViMS provides a modular implementation of its visualization model. We describe ViMS requirements and a model-independent ViMS architecture. We briefly describe the vector bundle visualization model and the visualization taxonomy it generates. We conclude by summarizing the benefits of the ViMS approach.

  15. Molecular Science Computing Facility Scientific Challenges: Linking Across Scales

    SciTech Connect

    De Jong, Wibe A.; Windus, Theresa L.

    2005-07-01

    The purpose of this document is to define the evolving science drivers for performing environmental molecular research at the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and to provide guidance associated with the next-generation high-performance computing center that must be developed at EMSL's Molecular Science Computing Facility (MSCF) in order to address this critical research. The MSCF is the pre-eminent computing facility?supported by the U.S. Department of Energy's (DOE's) Office of Biological and Environmental Research (BER)?tailored to provide the fastest time-to-solution for current computational challenges in chemistry and biology, as well as providing the means for broad research in the molecular and environmental sciences. The MSCF provides integral resources and expertise to emerging EMSL Scientific Grand Challenges and Collaborative Access Teams that are designed to leverage the multiple integrated research capabilities of EMSL, thereby creating a synergy between computation and experiment to address environmental molecular science challenges critical to DOE and the nation.

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

    NASA Astrophysics Data System (ADS)

    Strayer, Michael

    2005-01-01

    Good morning. Welcome to SciDAC 2005 and San Francisco. SciDAC is all about computational science and scientific discovery. In a large sense, computational science characterizes SciDAC and its intent is change. It transforms both our approach and our understanding of science. It opens new doors and crosses traditional boundaries while seeking discovery. In terms of twentieth century methodologies, computational science may be said to be transformational. There are a number of examples to this point. First are the sciences that encompass climate modeling. The application of computational science has in essence created the field of climate modeling. This community is now international in scope and has provided precision results that are challenging our understanding of our environment. A second example is that of lattice quantum chromodynamics. Lattice QCD, while adding precision and insight to our fundamental understanding of strong interaction dynamics, has transformed our approach to particle and nuclear science. The individual investigator approach has evolved to teams of scientists from different disciplines working side-by-side towards a common goal. SciDAC is also undergoing a transformation. This meeting is a prime example. Last year it was a small programmatic meeting tracking progress in SciDAC. This year, we have a major computational science meeting with a variety of disciplines and enabling technologies represented. SciDAC 2005 should position itself as a new corner stone for Computational Science and its impact on science. As we look to the immediate future, FY2006 will bring a new cycle to SciDAC. Most of the program elements of SciDAC will be re-competed in FY2006. The re-competition will involve new instruments for computational science, new approaches for collaboration, as well as new disciplines. There will be new opportunities for virtual experiments in carbon sequestration, fusion, and nuclear power and nuclear waste, as well as collaborations

  17. Experimental free-space optical network for massively parallel computers

    NASA Astrophysics Data System (ADS)

    Araki, S.; Kajita, M.; Kasahara, K.; Kubota, K.; Kurihara, K.; Redmond, I.; Schenfeld, E.; Suzaki, T.

    1996-03-01

    A free-space optical interconnection scheme is described for massively parallel processors based on the interconnection-cached network architecture. The optical network operates in a circuit-switching mode. Combined with a packet-switching operation among the circuit-switched optical channels, a high-bandwidth, low-latency network for massively parallel processing results. The design and assembly of a 64-channel experimental prototype is discussed, and operational results are presented.

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

    DOEpatents

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

    2015-11-10

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

  19. Parallel computation of a maximum-likelihood estimator of a physical map.

    PubMed Central

    Bhandarkar, S M; Machaka, S A; Shete, S S; Kota, R N

    2001-01-01

    Reconstructing a physical map of a chromosome from a genomic library presents a central computational problem in genetics. Physical map reconstruction in the presence of errors is a problem of high computational complexity that provides the motivation for parallel computing. Parallelization strategies for a maximum-likelihood estimation-based approach to physical map reconstruction are presented. The estimation procedure entails a gradient descent search for determining the optimal spacings between probes for a given probe ordering. The optimal probe ordering is determined using a stochastic optimization algorithm such as simulated annealing or microcanonical annealing. A two-level parallelization strategy is proposed wherein the gradient descent search is parallelized at the lower level and the stochastic optimization algorithm is simultaneously parallelized at the higher level. Implementation and experimental results on a distributed-memory multiprocessor cluster running the parallel virtual machine (PVM) environment are presented using simulated and real hybridization data. PMID:11238392

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  1. Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation. Appendix A.

    DTIC Science & Technology

    1983-03-01

    Modeling of Asynchronous Parallel Computation 1983 Progress Report L.J. Siegel, H.J. Siegel, PMH . Swain, G.B. Adams 111, W.E. Kuhn III, R .J...used in reduction machines), and vector. A complete and very detailed taxonomy based on these concepts is presented in Ji181]. Its length is too great...representation [(1oL731. A banyan is a directed graph composed of vertices and edges or arcs such that. it is irreflexive, asymmetric , and intransitive (a

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

    PubMed

    Aono, Masashi; Gunji, Yukio-Pegio

    2003-10-01

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

  3. A comparative study of serial and parallel aeroelastic computations of wings

    NASA Technical Reports Server (NTRS)

    Byun, Chansup; Guruswamy, Guru P.

    1994-01-01

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

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

    PubMed

    Jiang, Yuning; Kang, Jinfeng; Wang, Xinan

    2017-03-24

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

  5. Scientific misconduct and unethical human experimentation: historic parallels and moral implications.

    PubMed

    Lefor, Alan T

    2005-01-01

    Although a great deal of human experimentation has been performed to elucidate information otherwise not obtainable, there are many recorded instances of unethical human experimentation. There is also a history of crimes that were committed and disguised as human experiments, best exemplified by the activities of some physicians in Nazi Germany from 1933 until 1945. As a direct result of these activities, a war-crimes trial after World War II resulted in the creation of the Nuremberg Code, to guide future human experimentation. Despite this, unethical experiments were conducted at major academic institutions in the United States in the years after World War II by otherwise normal physicians who did not feel that the Nuremberg Code applied to them personally. There are several possible explanations for such activities, but the desire for personal advancement is prominent among these. Episodes of scientific misconduct such as falsification of experimental data or of personal qualifications seem to be more commonly reported recently and have also been described in the popular press. This activity may also be motivated by desire for personal advancement, giving it a parallel to the conduct of unethical human experimentation. Education may be the best way to prevent these activities that may have similar motivating factors.

  6. 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.

  7. Parallel computation of the SAR distribution in a 3D human head model

    NASA Astrophysics Data System (ADS)

    Walendziuk, Wojciech

    2008-01-01

    This work presents a way of parallel computation of the Specific Absorption Rate distribution. The parallel program used in the computation was based on the FDTD (Finite-Difference Time-Domain) method [1,2,3]. In order to establish communication among the computational nodes, the MPI (Message Passing Interface) standard was used [4,5,6]. The presented example of a human head numerical model was built with the use of MRI (Magnetic Resonance Image) pictures.

  8. Efficient solid state NMR powder simulations using SMP and MPP parallel computation

    NASA Astrophysics Data System (ADS)

    Kristensen, Jørgen Holm; Farnan, Ian

    2003-04-01

    Methods for parallel simulation of solid state NMR powder spectra are presented for both shared and distributed memory parallel supercomputers. For shared memory architectures the performance of simulation programs implementing the OpenMP application programming interface is evaluated. It is demonstrated that the design of correct and efficient shared memory parallel programs is difficult as the performance depends on data locality and cache memory effects. The distributed memory parallel programming model is examined for simulation programs using the MPI message passing interface. The results reveal that both shared and distributed memory parallel computation are very efficient with an almost perfect application speedup and may be applied to the most advanced powder simulations.

  9. Chaining direct memory access data transfer operations for compute nodes in a parallel computer

    DOEpatents

    Archer, Charles J.; Blocksome, Michael A.

    2010-09-28

    Methods, systems, and products are disclosed for chaining DMA data transfer operations for compute nodes in a parallel computer that include: receiving, by an origin DMA engine on an origin node in an origin injection FIFO buffer for the origin DMA engine, a RGET data descriptor specifying a DMA transfer operation data descriptor on the origin node and a second RGET data descriptor on the origin node, the second RGET data descriptor specifying a target RGET data descriptor on the target node, the target RGET data descriptor specifying an additional DMA transfer operation data descriptor on the origin node; creating, by the origin DMA engine, an RGET packet in dependence upon the RGET data descriptor, the RGET packet containing the DMA transfer operation data descriptor and the second RGET data descriptor; and transferring, by the origin DMA engine to a target DMA engine on the target node, the RGET packet.

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

    DOEpatents

    Faraj, Ahmad

    2013-07-09

    Methods, apparatus, and products are disclosed for performing an allreduce operation on a plurality of compute nodes of a parallel computer, each node including at least two processing cores, that include: establishing, for each node, a plurality of logical rings, each ring including a different set of at least one core on that node, each ring including the cores on at least two of the nodes; iteratively for each node: assigning each core of that node to one of the rings established for that node to which the core has not previously been assigned, and performing, for each ring for that node, a global allreduce operation using contribution data for the cores assigned to that ring or any global allreduce results from previous global allreduce operations, yielding current global allreduce results for each core; and performing, for each node, a local allreduce operation using the global allreduce results.

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

    DOEpatents

    Faraj, Ahmad

    2013-02-12

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

  12. Advances in time-domain electromagnetic simulation capabilities through the use of overset grids and massively parallel computing

    NASA Astrophysics Data System (ADS)

    Blake, Douglas Clifton

    A new methodology is presented for conducting numerical simulations of electromagnetic scattering and wave-propagation phenomena on massively parallel computing platforms. A process is constructed which is rooted in the Finite-Volume Time-Domain (FVTD) technique to create a simulation capability that is both versatile and practical. In terms of versatility, the method is platform independent, is easily modifiable, and is capable of solving a large number of problems with no alterations. In terms of practicality, the method is sophisticated enough to solve problems of engineering significance and is not limited to mere academic exercises. In order to achieve this capability, techniques are integrated from several scientific disciplines including computational fluid dynamics, computational electromagnetics, and parallel computing. The end result is the first FVTD solver capable of utilizing the highly flexible overset-gridding process in a distributed-memory computing environment. In the process of creating this capability, work is accomplished to conduct the first study designed to quantify the effects of domain-decomposition dimensionality on the parallel performance of hyperbolic partial differential equations solvers; to develop a new method of partitioning a computational domain comprised of overset grids; and to provide the first detailed assessment of the applicability of overset grids to the field of computational electromagnetics. Using these new methods and capabilities, results from a large number of wave propagation and scattering simulations are presented. The overset-grid FVTD algorithm is demonstrated to produce results of comparable accuracy to single-grid simulations while simultaneously shortening the grid-generation process and increasing the flexibility and utility of the FVTD technique. Furthermore, the new domain-decomposition approaches developed for overset grids are shown to be capable of producing partitions that are better load balanced and

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

    DOEpatents

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

    2010-01-12

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

  14. Portable programming on parallel/networked computers using the Application Portable Parallel Library (APPL)

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

    The Application Portable Parallel Library (APPL) is a subroutine-based library of communication primitives that is callable from applications written in FORTRAN or C. APPL provides a consistent programmer interface to a variety of distributed and shared-memory multiprocessor MIMD machines. The objective of APPL is to minimize the effort required to move parallel applications from one machine to another, or to a network of homogeneous machines. APPL encompasses many of the message-passing primitives that are currently available on commercial multiprocessor systems. This paper describes APPL (version 2.3.1) and its usage, reports the status of the APPL project, and indicates possible directions for the future. Several applications using APPL are discussed, as well as performance and overhead results.

  15. Parallel computing for simultaneous iterative tomographic imaging by graphics processing units

    NASA Astrophysics Data System (ADS)

    Bello-Maldonado, Pedro D.; López, Ricardo; Rogers, Colleen; Jin, Yuanwei; Lu, Enyue

    2016-05-01

    In this paper, we address the problem of accelerating inversion algorithms for nonlinear acoustic tomographic imaging by parallel computing on graphics processing units (GPUs). Nonlinear inversion algorithms for tomographic imaging often rely on iterative algorithms for solving an inverse problem, thus computationally intensive. We study the simultaneous iterative reconstruction technique (SIRT) for the multiple-input-multiple-output (MIMO) tomography algorithm which enables parallel computations of the grid points as well as the parallel execution of multiple source excitation. Using graphics processing units (GPUs) and the Compute Unified Device Architecture (CUDA) programming model an overall improvement of 26.33x was achieved when combining both approaches compared with sequential algorithms. Furthermore we propose an adaptive iterative relaxation factor and the use of non-uniform weights to improve the overall convergence of the algorithm. Using these techniques, fast computations can be performed in parallel without the loss of image quality during the reconstruction process.

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

    NASA Technical Reports Server (NTRS)

    Weeks, Cindy Lou

    1986-01-01

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

  17. Domain analysis of computational science - Fifty years of a scientific computing group

    SciTech Connect

    Tanaka, M.

    2010-02-23

    I employed bibliometric- and historical-methods to study the domain of the Scientific Computing group at Brookhaven National Laboratory (BNL) for an extended period of fifty years, from 1958 to 2007. I noted and confirmed the growing emergence of interdisciplinarity within the group. I also identified a strong, consistent mathematics and physics orientation within it.

  18. An Adaptive Middleware Framework for Scientific Computing at Extreme Scales

    SciTech Connect

    Gosney, Arzu; Oehmen, Christopher S.; Wynne, Adam S.; Almquist, Justin P.

    2010-08-04

    Large computing systems including clusters, clouds, and grids, provide high-performance capabilities that can be utilized for many applications. But as the ubiquity of these systems increases and the scope of analysis being done on them grows, there is a growing need for applications that 1) do not require users to learn the details of high performance systems, and 2) are flexible and adaptive in their usage of these systems to accommodate the best time-to-solution for end users. We introduce a new adaptive interface design and a prototype implementation within the framework of an established middleware framework, MeDICi, for high performance computing systems and describe the applicability of this adaptive design to a real-life scientific workflow. This adaptive framework provides an access model for implementing a processing pipeline using high performance systems that are not local to the data source, making it possible for the compute capabilities at one site to be applied to analysis on data being generated at another site in an automated process. This adaptive design improves overall time-to-solution by moving the data analysis task to the most appropriate resource dynamically, reacting to failures and load fluctuations.

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

    PubMed Central

    2014-01-01

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

  20. MEDUSA - An overset grid flow solver for network-based parallel computer systems

    NASA Technical Reports Server (NTRS)

    Smith, Merritt H.; Pallis, Jani M.

    1993-01-01

    Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.

  1. ClustalW-MPI: ClustalW analysis using distributed and parallel computing.

    PubMed

    Li, Kuo-Bin

    2003-08-12

    ClustalW is a tool for aligning multiple protein or nucleotide sequences. The alignment is achieved via three steps: pairwise alignment, guide-tree generation and progressive alignment. ClustalW-MPI is a distributed and parallel implementation of ClustalW. All three steps have been parallelized to reduce the execution time. The software uses a message-passing library called MPI (Message Passing Interface) and runs on distributed workstation clusters as well as on traditional parallel computers.

  2. A parallel finite-difference method for computational aerodynamics

    NASA Technical Reports Server (NTRS)

    Swisshelm, Julie M.

    1989-01-01

    A finite-difference scheme for solving complex three-dimensional aerodynamic flow on parallel-processing supercomputers is presented. The method consists of a basic flow solver with multigrid convergence acceleration, embedded grid refinements, and a zonal equation scheme. Multitasking and vectorization have been incorporated into the algorithm. Results obtained include multiprocessed flow simulations from the Cray X-MP and Cray-2. Speedups as high as 3.3 for the two-dimensional case and 3.5 for segments of the three-dimensional case have been achieved on the Cray-2. The entire solver attained a factor of 2.7 improvement over its unitasked version on the Cray-2. The performance of the parallel algorithm on each machine is analyzed.

  3. Execution models for mapping programs onto distributed memory parallel computers

    NASA Technical Reports Server (NTRS)

    Sussman, Alan

    1992-01-01

    The problem of exploiting the parallelism available in a program to efficiently employ the resources of the target machine is addressed. The problem is discussed in the context of building a mapping compiler for a distributed memory parallel machine. The paper describes using execution models to drive the process of mapping a program in the most efficient way onto a particular machine. Through analysis of the execution models for several mapping techniques for one class of programs, we show that the selection of the best technique for a particular program instance can make a significant difference in performance. On the other hand, the results of benchmarks from an implementation of a mapping compiler show that our execution models are accurate enough to select the best mapping technique for a given program.

  4. Finding Tropical Cyclones on a Cloud Computing Cluster: Using Parallel Virtualization for Large-Scale Climate Simulation Analysis

    SciTech Connect

    Hasenkamp, Daren; Sim, Alexander; Wehner, Michael; Wu, Kesheng

    2010-09-30

    Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data; however, many of the data analysis programs currently only run a single processor. In this work, we explore the possibility of using the emerging cloud computing platform to parallelize such sequential data analysis tasks. As a proof of concept, we wrap a program for analyzing trends of tropical cyclones in a set of virtual machines (VMs). This approach allows the user to keep their familiar data analysis environment in the VMs, while we provide the coordination and data transfer services to ensure the necessary input and output are directed to the desired locations. This work extensively exercises the networking capability of the cloud computing systems and has revealed a number of weaknesses in the current cloud system software. In our tests, we are able to scale the parallel data analysis job to a modest number of VMs and achieve a speedup that is comparable to running the same analysis task using MPI. However, compared to MPI based parallelization, the cloud-based approach has a number of advantages. The cloud-based approach is more flexible because the VMs can capture arbitrary software dependencies without requiring the user to rewrite their programs. The cloud-based approach is also more resilient to failure; as long as a single VM is running, it can make progress while as soon as one MPI node fails the whole analysis job fails. In short, this initial work demonstrates that a cloud computing system is a viable platform for distributed scientific data analyses traditionally conducted on dedicated supercomputing systems.

  5. Match and Move, an Approach to Data Parallel Computing

    DTIC Science & Technology

    1992-10-01

    is the "scan" or "parallel prefix" operation. For any binary associative operator, ED, with an identity element 0, and a vector v whose sites are...based on the sizes of the groups. The table is nearly identical to the one for mappings resulting from Unique fields. The justification for the resulting... identity elements for edge multiplication. The key insight to implementing the graph squaring operation is to recognize that new edges are created wherever

  6. rasterEngine: an easy-to-use R function for applying complex geostatistical models to raster datasets in a parallel computing environment

    NASA Astrophysics Data System (ADS)

    Greenberg, J. A.

    2013-12-01

    As geospatial analyses progress in tandem with increasing availability of large complex geographic data sets and high performance computing (HPC), there is an increasing gap in the ability of end-user tools to take advantage of these advances. Specifically, the practical implementation of complex statistical models on large gridded geographic datasets (e.g. remote sensing analysis, species distribution mapping, topographic transformations, and local neighborhood analyses) currently requires a significant knowledge base. A user must be proficient in the chosen model as well as the nuances of scientific programming, raster data models, memory management, parallel computing, and system design. This is further complicated by the fact that many of the cutting-edge analytical tools were developed for non-geospatial datasets and are not part of standard GIS packages, but are available in scientific computing languages such as R and MATLAB. We present a computing function 'rasterEngine' written in the R scientific computing language and part of the CRAN package 'spatial.tools' with these challenges in mind. The goal of rasterEngine is to allow a user to quickly develop and apply analytical models within the R computing environment to arbitrarily large gridded datasets, taking advantage of available parallel computing resources, and without requiring a deep understanding of HPC and raster data models. We provide several examples of rasterEngine being used to solve common grid based analyses, including remote sensing image analyses, topographic transformations, and species distribution modeling. With each example, the parallel processing performance results are presented.

  7. Brain-like and massively-parallel computers

    SciTech Connect

    Soucek, B.

    1987-01-01

    This text/reference bridges the gap between computer engineering and life sciences. It covers trends in computing and control, presenting the continuation of the current fifth generation, and the research in psychology and linguistics, producing the systems with features of perception, learning and cognition. Different brain models are also examined. Describes new computing systems currently under development such as cognitrons, goal-directed systems, and pseudo-associative memories. Presents an overview of the biological signals and their computer processing, and describes selected models of biological information processing systems. Details a concrete example of a biological language that has been successfully decoded. Includes concrete chart flows and programs (in BASIC).

  8. A note on parallel and pipeline computation of fast unitary transforms

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

    The parallel and pipeline organization of fast unitary transform algorithms such as the Fast Fourier Transform are discussed. The efficiency is pointed out of a combined parallel-pipeline processor of a transform such as the Haar transform in which 2 to the n minus 1 power hardware butterflies generate a transform of order 2 to the n power every computation cycle.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  10. Paging memory from random access memory to backing storage in a parallel computer

    DOEpatents

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

    2013-05-21

    Paging memory from random access memory (`RAM`) to backing storage in a parallel computer that includes a plurality of compute nodes, including: executing a data processing application on a virtual machine operating system in a virtual machine on a first compute node; providing, by a second compute node, backing storage for the contents of RAM on the first compute node; and swapping, by the virtual machine operating system in the virtual machine on the first compute node, a page of memory from RAM on the first compute node to the backing storage on the second compute node.

  11. Parallel Computers for Region-Level Image Processing.

    DTIC Science & Technology

    1980-11-01

    34corner" proces- sor in each region, we can use it as the region’s represen- tative in the adjacency-graph- structured computer ; but we need to give it the...graph of bounded degree (% 5). We now briefly describe how to construct a quadtree- structured computer corresponding to (the quadtree of) a given

  12. Tradeoffs Between Synchronization, Communication, and Work in Parallel Linear Algebra Computations

    DTIC Science & Technology

    2014-01-25

    2001. [24] A. Tiskin. Communication-efficient parallel generic pairwise elimination. Future Generation Computer Systems , 23(2):179 – 188, 2007. [25] S. Warshall. A theorem on boolean matrices. J. ACM, 9:11–12, January 1962. 17

  13. Computer simulation program for parallel SITAN. [Sandia Inertia Terrain-Aided Navigation, in FORTRAN

    SciTech Connect

    Andreas, R.D.; Sheives, T.C.

    1980-11-01

    This computer program simulates the operation of parallel SITAN using digitized terrain data. An actual trajectory is modeled including the effects of inertial navigation errors and radar altimeter measurements.

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

    PubMed

    Furuta, Takuya; Sato, Tatsuhiko

    2015-01-01

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

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

    DOEpatents

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

    2010-11-23

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

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

    DOEpatents

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

    2010-06-08

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

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

    DOEpatents

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

    2012-04-17

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

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

    DOEpatents

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

    2012-01-10

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

  19. Low latency, high bandwidth data communications between compute nodes in a parallel computer

    DOEpatents

    Blocksome, Michael A

    2014-04-01

    Methods, systems, and products are disclosed for data transfers between nodes in a parallel computer that include: receiving, by an origin DMA on an origin node, a buffer identifier for a buffer containing data for transfer to a target node; sending, by the origin DMA to the target node, a RTS message; transferring, by the origin DMA, a data portion to the target node using a memory FIFO operation that specifies one end of the buffer from which to begin transferring the data; receiving, by the origin DMA, an acknowledgement of the RTS message from the target node; and transferring, by the origin DMA in response to receiving the acknowledgement, any remaining data portion to the target node using a direct put operation that specifies the other end of the buffer from which to begin transferring the data, including initiating the direct put operation without invoking an origin processing core.

  20. Low latency, high bandwidth data communications between compute nodes in a parallel computer

    DOEpatents

    Blocksome, Michael A

    2013-07-02

    Methods, systems, and products are disclosed for data transfers between nodes in a parallel computer that include: receiving, by an origin DMA on an origin node, a buffer identifier for a buffer containing data for transfer to a target node; sending, by the origin DMA to the target node, a RTS message; transferring, by the origin DMA, a data portion to the target node using a memory FIFO operation that specifies one end of the buffer from which to begin transferring the data; receiving, by the origin DMA, an acknowledgement of the RTS message from the target node; and transferring, by the origin DMA in response to receiving the acknowledgement, any remaining data portion to the target node using a direct put operation that specifies the other end of the buffer from which to begin transferring the data, including initiating the direct put operation without invoking an origin processing core.