An object-oriented approach to nested data parallelism

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.; Chatterjee, Siddhartha

1994-01-01

This paper describes an implementation technique for integrating nested data parallelism into an object-oriented language. Data-parallel programming employs sets of data called 'collections' and expresses parallelism as operations performed over the elements of a collection. When the elements of a collection are also collections, then there is the possibility for 'nested data parallelism.' Few current programming languages support nested data parallelism however. In an object-oriented framework, a collection is a single object. Its type defines the parallel operations that may be applied to it. Our goal is to design and build an object-oriented data-parallel programming environment supporting nested data parallelism. Our initial approach is built upon three fundamental additions to C++. We add new parallel base types by implementing them as classes, and add a new parallel collection type called a 'vector' that is implemented as a template. Only one new language feature is introduced: the 'foreach' construct, which is the basis for exploiting elementwise parallelism over collections. The strength of the method lies in the compilation strategy, which translates nested data-parallel C++ into ordinary C++. Extracting the potential parallelism in nested 'foreach' constructs is called 'flattening' nested parallelism. We show how to flatten 'foreach' constructs using a simple program transformation. Our prototype system produces vector code which has been successfully run on workstations, a CM-2, and a CM-5.

Parallelization of Program to Optimize Simulated Trajectories (POST3D)

NASA Technical Reports Server (NTRS)

Hammond, Dana P.; Korte, John J. (Technical Monitor)

2001-01-01

This paper describes the parallelization of the Program to Optimize Simulated Trajectories (POST3D). POST3D uses a gradient-based optimization algorithm that reaches an optimum design point by moving from one design point to the next. The gradient calculations required to complete the optimization process, dominate the computational time and have been parallelized using a Single Program Multiple Data (SPMD) on a distributed memory NUMA (non-uniform memory access) architecture. The Origin2000 was used for the tests presented.

Massively parallel sparse matrix function calculations with NTPoly

NASA Astrophysics Data System (ADS)

Dawson, William; Nakajima, Takahito

2018-04-01

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

Exploiting Vector and Multicore Parallelsim for Recursive, Data- and Task-Parallel Programs

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

Ren, Bin; Krishnamoorthy, Sriram; Agrawal, Kunal

Modern hardware contains parallel execution resources that are well-suited for data-parallelism-vector units-and task parallelism-multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present a scheduling framework that allows for a unified treatment of task- and data-parallelism. Our key insight is an abstraction, task blocks, that uniformly handles data-parallel iterations and task-parallel tasks, allowing them to be scheduled on vector units or executed independently as multicores. Our framework allows us to define schedulers that can dynamically select between executing task- blocks on vector units or multicores. We show that thesemore » schedulers are asymptotically optimal, and deliver the maximum amount of parallelism available in computation trees. To evaluate our schedulers, we develop program transformations that can convert mixed data- and task-parallel pro- grams into task block-based programs. Using a prototype instantiation of our scheduling framework, we show that, on an 8-core system, we can simultaneously exploit vector and multicore parallelism to achieve 14×-108× speedup over sequential baselines.« less

Implementation and performance of parallel Prolog interpreter

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

Wei, S.; Kale, L.V.; Balkrishna, R.

1988-01-01

In this paper, the authors discuss the implementation of a parallel Prolog interpreter on different parallel machines. The implementation is based on the REDUCE--OR process model which exploits both AND and OR parallelism in logic programs. It is machine independent as it runs on top of the chare-kernel--a machine-independent parallel programming system. The authors also give the performance of the interpreter running a diverse set of benchmark pargrams on parallel machines including shared memory systems: an Alliant FX/8, Sequent and a MultiMax, and a non-shared memory systems: Intel iPSC/32 hypercube, in addition to its performance on a multiprocessor simulation system.

What Multilevel Parallel Programs do when you are not Watching: A Performance Analysis Case Study Comparing MPI/OpenMP, MLP, and Nested OpenMP

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Labarta, Jesus; Gimenez, Judit

2004-01-01

With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.

Array processor architecture

NASA Technical Reports Server (NTRS)

Barnes, George H. (Inventor); Lundstrom, Stephen F. (Inventor); Shafer, Philip E. (Inventor)

1983-01-01

A high speed parallel array data processing architecture fashioned under a computational envelope approach includes a data base memory for secondary storage of programs and data, and a plurality of memory modules interconnected to a plurality of processing modules by a connection network of the Omega gender. Programs and data are fed from the data base memory to the plurality of memory modules and from hence the programs are fed through the connection network to the array of processors (one copy of each program for each processor). Execution of the programs occur with the processors operating normally quite independently of each other in a multiprocessing fashion. For data dependent operations and other suitable operations, all processors are instructed to finish one given task or program branch before all are instructed to proceed in parallel processing fashion on the next instruction. Even when functioning in the parallel processing mode however, the processors are not locked-step but execute their own copy of the program individually unless or until another overall processor array synchronization instruction is issued.

Trace-Driven Debugging of Message Passing Programs

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Hood, Robert; Lopez, Louis; Bailey, David (Technical Monitor)

1998-01-01

In this paper we report on features added to a parallel debugger to simplify the debugging of parallel message passing programs. These features include replay, setting consistent breakpoints based on interprocess event causality, a parallel undo operation, and communication supervision. These features all use trace information collected during the execution of the program being debugged. We used a number of different instrumentation techniques to collect traces. We also implemented trace displays using two different trace visualization systems. The implementation was tested on an SGI Power Challenge cluster and a network of SGI workstations.

PyPele Rewritten To Use MPI

NASA Technical Reports Server (NTRS)

Hockney, George; Lee, Seungwon

2008-01-01

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

Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

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

The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

Characterizing Task-Based OpenMP Programs

PubMed Central

Muddukrishna, Ananya; Jonsson, Peter A.; Brorsson, Mats

2015-01-01

Programmers struggle to understand performance of task-based OpenMP programs since profiling tools only report thread-based performance. Performance tuning also requires task-based performance in order to balance per-task memory hierarchy utilization against exposed task parallelism. We provide a cost-effective method to extract detailed task-based performance information from OpenMP programs. We demonstrate the utility of our method by quickly diagnosing performance problems and characterizing exposed task parallelism and per-task instruction profiles of benchmarks in the widely-used Barcelona OpenMP Tasks Suite. Programmers can tune performance faster and understand performance tradeoffs more effectively than existing tools by using our method to characterize task-based performance. PMID:25860023

Distributed and parallel Ada and the Ada 9X recommendations

NASA Technical Reports Server (NTRS)

Volz, Richard A.; Goldsack, Stephen J.; Theriault, R.; Waldrop, Raymond S.; Holzbacher-Valero, A. A.

1992-01-01

Recently, the DoD has sponsored work towards a new version of Ada, intended to support the construction of distributed systems. The revised version, often called Ada 9X, will become the new standard sometimes in the 1990s. It is intended that Ada 9X should provide language features giving limited support for distributed system construction. The requirements for such features are given. Many of the most advanced computer applications involve embedded systems that are comprised of parallel processors or networks of distributed computers. If Ada is to become the widely adopted language envisioned by many, it is essential that suitable compilers and tools be available to facilitate the creation of distributed and parallel Ada programs for these applications. The major languages issues impacting distributed and parallel programming are reviewed, and some principles upon which distributed/parallel language systems should be built are suggested. Based upon these, alternative language concepts for distributed/parallel programming are analyzed.

A parallel row-based algorithm with error control for standard-cell replacement on a hypercube multiprocessor

NASA Technical Reports Server (NTRS)

Sargent, Jeff Scott

1988-01-01

A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel new approaches to controlling error in parallel cell-placement algorithms; Heuristic Cell-Coloring and Adaptive (Parallel Move) Sequence Control. Heuristic Cell-Coloring identifies sets of noninteracting cells that can be moved repeatedly, and in parallel, with no buildup of error in the placement cost. Adaptive Sequence Control allows multiple parallel cell moves to take place between global cell-position updates. This feedback mechanism is based on an error bound derived analytically from the traditional annealing move-acceptance profile. Placement results are presented for real industry circuits and the performance is summarized of an implementation on the Intel iPSC/2 Hypercube. The runtime of this algorithm is 5 to 16 times faster than a previous program developed for the Hypercube, while producing equivalent quality placement. An integrated place and route program for the Intel iPSC/2 Hypercube is currently being developed.

Optics Program Modified for Multithreaded Parallel Computing

NASA Technical Reports Server (NTRS)

Lou, John; Bedding, Dave; Basinger, Scott

2006-01-01

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

SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws

NASA Technical Reports Server (NTRS)

Cooke, Daniel; Rushton, Nelson

2013-01-01

With the introduction of new parallel architectures like the cell and multicore chips from IBM, Intel, AMD, and ARM, as well as the petascale processing available for highend computing, a larger number of programmers will need to write parallel codes. Adding the parallel control structure to the sequence, selection, and iterative control constructs increases the complexity of code development, which often results in increased development costs and decreased reliability. SequenceL is a high-level programming language that is, a programming language that is closer to a human s way of thinking than to a machine s. Historically, high-level languages have resulted in decreased development costs and increased reliability, at the expense of performance. In recent applications at JSC and in industry, SequenceL has demonstrated the usual advantages of high-level programming in terms of low cost and high reliability. SequenceL programs, however, have run at speeds typically comparable with, and in many cases faster than, their counterparts written in C and C++ when run on single-core processors. Moreover, SequenceL is able to generate parallel executables automatically for multicore hardware, gaining parallel speedups without any extra effort from the programmer beyond what is required to write the sequen tial/singlecore code. A SequenceL-to-C++ translator has been developed that automatically renders readable multithreaded C++ from a combination of a SequenceL program and sample data input. The SequenceL language is based on two fundamental computational laws, Consume-Simplify- Produce (CSP) and Normalize-Trans - pose (NT), which enable it to automate the creation of parallel algorithms from high-level code that has no annotations of parallelism whatsoever. In our anecdotal experience, SequenceL development has been in every case less costly than development of the same algorithm in sequential (that is, single-core, single process) C or C++, and an order of magnitude less costly than development of comparable parallel code. Moreover, SequenceL not only automatically parallelizes the code, but since it is based on CSP-NT, it is provably race free, thus eliminating the largest quality challenge the parallelized software developer faces.

Parent-Child Parallel-Group Intervention for Childhood Aggression in Hong Kong

ERIC Educational Resources Information Center

Fung, Annis L. C.; Tsang, Sandra H. K. M.

2006-01-01

This article reports the original evidence-based outcome study on parent-child parallel group-designed Anger Coping Training (ACT) program for children aged 8-10 with reactive aggression and their parents in Hong Kong. This research program involved experimental and control groups with pre- and post-comparison. Quantitative data collection…

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

NASA Technical Reports Server (NTRS)

Dorband, John E.; Aburdene, Maurice F.

2002-01-01

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

Concurrency-based approaches to parallel programming

NASA Technical Reports Server (NTRS)

Kale, L.V.; Chrisochoides, N.; Kohl, J.; Yelick, K.

1995-01-01

The inevitable transition to parallel programming can be facilitated by appropriate tools, including languages and libraries. After describing the needs of applications developers, this paper presents three specific approaches aimed at development of efficient and reusable parallel software for irregular and dynamic-structured problems. A salient feature of all three approaches in their exploitation of concurrency within a processor. Benefits of individual approaches such as these can be leveraged by an interoperability environment which permits modules written using different approaches to co-exist in single applications.

Reliability models for dataflow computer systems

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

Petascale Simulation Initiative Tech Base: FY2007 Final Report

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

May, J; Chen, R; Jefferson, D

The Petascale Simulation Initiative began as an LDRD project in the middle of Fiscal Year 2004. The goal of the project was to develop techniques to allow large-scale scientific simulation applications to better exploit the massive parallelism that will come with computers running at petaflops per second. One of the major products of this work was the design and prototype implementation of a programming model and a runtime system that lets applications extend data-parallel applications to use task parallelism. By adopting task parallelism, applications can use processing resources more flexibly, exploit multiple forms of parallelism, and support more sophisticated multiscalemore » and multiphysics models. Our programming model was originally called the Symponents Architecture but is now known as Cooperative Parallelism, and the runtime software that supports it is called Coop. (However, we sometimes refer to the programming model as Coop for brevity.) We have documented the programming model and runtime system in a submitted conference paper [1]. This report focuses on the specific accomplishments of the Cooperative Parallelism project (as we now call it) under Tech Base funding in FY2007. Development and implementation of the model under LDRD funding alone proceeded to the point of demonstrating a large-scale materials modeling application using Coop on more than 1300 processors by the end of FY2006. Beginning in FY2007, the project received funding from both LDRD and the Computation Directorate Tech Base program. Later in the year, after the three-year term of the LDRD funding ended, the ASC program supported the project with additional funds. The goal of the Tech Base effort was to bring Coop from a prototype to a production-ready system that a variety of LLNL users could work with. Specifically, the major tasks that we planned for the project were: (1) Port SARS [former name of the Coop runtime system] to another LLNL platform, probably Thunder or Peloton (depending on when Peloton becomes available); (2) Improve SARS's robustness and ease-of-use, and develop user documentation; and (3) Work with LLNL code teams to help them determine how Symponents could benefit their applications. The original funding request was $296,000 for the year, and we eventually received $252,000. The remainder of this report describes our efforts and accomplishments for each of the goals listed above.« less

LDRD final report on massively-parallel linear programming : the parPCx system.

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

Parekh, Ojas; Phillips, Cynthia Ann; Boman, Erik Gunnar

2005-02-01

This report summarizes the research and development performed from October 2002 to September 2004 at Sandia National Laboratories under the Laboratory-Directed Research and Development (LDRD) project ''Massively-Parallel Linear Programming''. We developed a linear programming (LP) solver designed to use a large number of processors. LP is the optimization of a linear objective function subject to linear constraints. Companies and universities have expended huge efforts over decades to produce fast, stable serial LP solvers. Previous parallel codes run on shared-memory systems and have little or no distribution of the constraint matrix. We have seen no reports of general LP solver runsmore » on large numbers of processors. Our parallel LP code is based on an efficient serial implementation of Mehrotra's interior-point predictor-corrector algorithm (PCx). The computational core of this algorithm is the assembly and solution of a sparse linear system. We have substantially rewritten the PCx code and based it on Trilinos, the parallel linear algebra library developed at Sandia. Our interior-point method can use either direct or iterative solvers for the linear system. To achieve a good parallel data distribution of the constraint matrix, we use a (pre-release) version of a hypergraph partitioner from the Zoltan partitioning library. We describe the design and implementation of our new LP solver called parPCx and give preliminary computational results. We summarize a number of issues related to efficient parallel solution of LPs with interior-point methods including data distribution, numerical stability, and solving the core linear system using both direct and iterative methods. We describe a number of applications of LP specific to US Department of Energy mission areas and we summarize our efforts to integrate parPCx (and parallel LP solvers in general) into Sandia's massively-parallel integer programming solver PICO (Parallel Interger and Combinatorial Optimizer). We conclude with directions for long-term future algorithmic research and for near-term development that could improve the performance of parPCx.« less

YAPPA: a Compiler-Based Parallelization Framework for Irregular Applications on MPSoCs

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

Lovergine, Silvia; Tumeo, Antonino; Villa, Oreste

Modern embedded systems include hundreds of cores. Because of the difficulty in providing a fast, coherent memory architecture, these systems usually rely on non-coherent, non-uniform memory architectures with private memories for each core. However, programming these systems poses significant challenges. The developer must extract large amounts of parallelism, while orchestrating communication among cores to optimize application performance. These issues become even more significant with irregular applications, which present data sets difficult to partition, unpredictable memory accesses, unbalanced control flow and fine grained communication. Hand-optimizing every single aspect is hard and time-consuming, and it often does not lead to the expectedmore » performance. There is a growing gap between such complex and highly-parallel architectures and the high level languages used to describe the specification, which were designed for simpler systems and do not consider these new issues. In this paper we introduce YAPPA (Yet Another Parallel Programming Approach), a compilation framework for the automatic parallelization of irregular applications on modern MPSoCs based on LLVM. We start by considering an efficient parallel programming approach for irregular applications on distributed memory systems. We then propose a set of transformations that can reduce the development and optimization effort. The results of our initial prototype confirm the correctness of the proposed approach.« less

GRADSPMHD: A parallel MHD code based on the SPH formalism

NASA Astrophysics Data System (ADS)

Vanaverbeke, S.; Keppens, R.; Poedts, S.

2014-03-01

We present GRADSPMHD, a completely Lagrangian parallel magnetohydrodynamics code based on the SPH formalism. The implementation of the equations of SPMHD in the “GRAD-h” formalism assembles known results, including the derivation of the discretized MHD equations from a variational principle, the inclusion of time-dependent artificial viscosity, resistivity and conductivity terms, as well as the inclusion of a mixed hyperbolic/parabolic correction scheme for satisfying the ∇ṡB→ constraint on the magnetic field. The code uses a tree-based formalism for neighbor finding and can optionally use the tree code for computing the self-gravity of the plasma. The structure of the code closely follows the framework of our parallel GRADSPH FORTRAN 90 code which we added previously to the CPC program library. We demonstrate the capabilities of GRADSPMHD by running 1, 2, and 3 dimensional standard benchmark tests and we find good agreement with previous work done by other researchers. The code is also applied to the problem of simulating the magnetorotational instability in 2.5D shearing box tests as well as in global simulations of magnetized accretion disks. We find good agreement with available results on this subject in the literature. Finally, we discuss the performance of the code on a parallel supercomputer with distributed memory architecture. Catalogue identifier: AERP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERP_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 620503 No. of bytes in distributed program, including test data, etc.: 19837671 Distribution format: tar.gz Programming language: FORTRAN 90/MPI. Computer: HPC cluster. Operating system: Unix. Has the code been vectorized or parallelized?: Yes, parallelized using MPI. RAM: ˜30 MB for a Sedov test including 15625 particles on a single CPU. Classification: 12. Nature of problem: Evolution of a plasma in the ideal MHD approximation. Solution method: The equations of magnetohydrodynamics are solved using the SPH method. Running time: The test provided takes approximately 20 min using 4 processors.

New NAS Parallel Benchmarks Results

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; Saphir, William; VanderWijngaart, Rob; Woo, Alex; Kutler, Paul (Technical Monitor)

1997-01-01

NPB2 (NAS (NASA Advanced Supercomputing) Parallel Benchmarks 2) is an implementation, based on Fortran and the MPI (message passing interface) message passing standard, of the original NAS Parallel Benchmark specifications. NPB2 programs are run with little or no tuning, in contrast to NPB vendor implementations, which are highly optimized for specific architectures. NPB2 results complement, rather than replace, NPB results. Because they have not been optimized by vendors, NPB2 implementations approximate the performance a typical user can expect for a portable parallel program on distributed memory parallel computers. Together these results provide an insightful comparison of the real-world performance of high-performance computers. New NPB2 features: New implementation (CG), new workstation class problem sizes, new serial sample versions, more performance statistics.

Testing New Programming Paradigms with NAS Parallel Benchmarks

NASA Technical Reports Server (NTRS)

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

2000-01-01

Over the past decade, high performance computing has evolved rapidly, not only in hardware architectures but also with increasing complexity of real applications. Technologies have been developing to aim at scaling up to thousands of processors on both distributed and shared memory systems. Development of parallel programs on these computers is always a challenging task. Today, writing parallel programs with message passing (e.g. MPI) is the most popular way of achieving scalability and high performance. However, writing message passing programs is difficult and error prone. Recent years new effort has been made in defining new parallel programming paradigms. The best examples are: HPF (based on data parallelism) and OpenMP (based on shared memory parallelism). Both provide simple and clear extensions to sequential programs, thus greatly simplify the tedious tasks encountered in writing message passing programs. HPF is independent of memory hierarchy, however, due to the immaturity of compiler technology its performance is still questionable. Although use of parallel compiler directives is not new, OpenMP offers a portable solution in the shared-memory domain. Another important development involves the tremendous progress in the internet and its associated technology. Although still in its infancy, Java promisses portability in a heterogeneous environment and offers possibility to "compile once and run anywhere." In light of testing these new technologies, we implemented new parallel versions of the NAS Parallel Benchmarks (NPBs) with HPF and OpenMP directives, and extended the work with Java and Java-threads. The purpose of this study is to examine the effectiveness of alternative programming paradigms. NPBs consist of five kernels and three simulated applications that mimic the computation and data movement of large scale computational fluid dynamics (CFD) applications. We started with the serial version included in NPB2.3. Optimization of memory and cache usage was applied to several benchmarks, noticeably BT and SP, resulting in better sequential performance. In order to overcome the lack of an HPF performance model and guide the development of the HPF codes, we employed an empirical performance model for several primitives found in the benchmarks. We encountered a few limitations of HPF, such as lack of supporting the "REDISTRIBUTION" directive and no easy way to handle irregular computation. The parallelization with OpenMP directives was done at the outer-most loop level to achieve the largest granularity. The performance of six HPF and OpenMP benchmarks is compared with their MPI counterparts for the Class-A problem size in the figure in next page. These results were obtained on an SGI Origin2000 (195MHz) with MIPSpro-f77 compiler 7.2.1 for OpenMP and MPI codes and PGI pghpf-2.4.3 compiler with MPI interface for HPF programs.

Implementation and performance of FDPS: a framework for developing parallel particle simulation codes

NASA Astrophysics Data System (ADS)

Iwasawa, Masaki; Tanikawa, Ataru; Hosono, Natsuki; Nitadori, Keigo; Muranushi, Takayuki; Makino, Junichiro

2016-08-01

We present the basic idea, implementation, measured performance, and performance model of FDPS (Framework for Developing Particle Simulators). FDPS is an application-development framework which helps researchers to develop simulation programs using particle methods for large-scale distributed-memory parallel supercomputers. A particle-based simulation program for distributed-memory parallel computers needs to perform domain decomposition, exchange of particles which are not in the domain of each computing node, and gathering of the particle information in other nodes which are necessary for interaction calculation. Also, even if distributed-memory parallel computers are not used, in order to reduce the amount of computation, algorithms such as the Barnes-Hut tree algorithm or the Fast Multipole Method should be used in the case of long-range interactions. For short-range interactions, some methods to limit the calculation to neighbor particles are required. FDPS provides all of these functions which are necessary for efficient parallel execution of particle-based simulations as "templates," which are independent of the actual data structure of particles and the functional form of the particle-particle interaction. By using FDPS, researchers can write their programs with the amount of work necessary to write a simple, sequential and unoptimized program of O(N2) calculation cost, and yet the program, once compiled with FDPS, will run efficiently on large-scale parallel supercomputers. A simple gravitational N-body program can be written in around 120 lines. We report the actual performance of these programs and the performance model. The weak scaling performance is very good, and almost linear speed-up was obtained for up to the full system of the K computer. The minimum calculation time per timestep is in the range of 30 ms (N = 107) to 300 ms (N = 109). These are currently limited by the time for the calculation of the domain decomposition and communication necessary for the interaction calculation. We discuss how we can overcome these bottlenecks.

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.

Networked Workstations and Parallel Processing Utilizing Functional Languages

DTIC Science & Technology

1993-03-01

program . This frees the programmer to concentrate on what the program is to do, not how the program is...traditional ’von Neumann’ architecture uses a timer based (e.g., the program counter), sequentially pro- grammed, single processor approach to problem...traditional ’von Neumann’ architecture uses a timer based (e.g., the program counter), sequentially programmed , single processor approach to

The Automated Instrumentation and Monitoring System (AIMS): Design and Architecture. 3.2

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Schmidt, Melisa; Schulbach, Cathy; Bailey, David (Technical Monitor)

1997-01-01

Whether a researcher is designing the 'next parallel programming paradigm', another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of such information can help computer and software architects to capture, and therefore, exploit behavioral variations among/within various parallel programs to take advantage of specific hardware characteristics. A software tool-set that facilitates performance evaluation of parallel applications on multiprocessors has been put together at NASA Ames Research Center under the sponsorship of NASA's High Performance Computing and Communications Program over the past five years. The Automated Instrumentation and Monitoring Systematic has three major software components: a source code instrumentor which automatically inserts active event recorders into program source code before compilation; a run-time performance monitoring library which collects performance data; and a visualization tool-set which reconstructs program execution based on the data collected. Besides being used as a prototype for developing new techniques for instrumenting, monitoring and presenting parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware testbeds to evaluate their impact on user productivity. Currently, the execution of FORTRAN and C programs on the Intel Paragon and PALM workstations can be automatically instrumented and monitored. Performance data thus collected can be displayed graphically on various workstations. The process of performance tuning with AIMS will be illustrated using various NAB Parallel Benchmarks. This report includes a description of the internal architecture of AIMS and a listing of the source code.

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

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

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

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

NAS Parallel Benchmark. Results 11-96: Performance Comparison of HPF and MPI Based NAS Parallel Benchmarks. 1.0

NASA Technical Reports Server (NTRS)

Saini, Subash; Bailey, David; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

High Performance Fortran (HPF), the high-level language for parallel Fortran programming, is based on Fortran 90. HALF was defined by an informal standards committee known as the High Performance Fortran Forum (HPFF) in 1993, and modeled on TMC's CM Fortran language. Several HPF features have since been incorporated into the draft ANSI/ISO Fortran 95, the next formal revision of the Fortran standard. HPF allows users to write a single parallel program that can execute on a serial machine, a shared-memory parallel machine, or a distributed-memory parallel machine. HPF eliminates the complex, error-prone task of explicitly specifying how, where, and when to pass messages between processors on distributed-memory machines, or when to synchronize processors on shared-memory machines. HPF is designed in a way that allows the programmer to code an application at a high level, and then selectively optimize portions of the code by dropping into message-passing or calling tuned library routines as 'extrinsics'. Compilers supporting High Performance Fortran features first appeared in late 1994 and early 1995 from Applied Parallel Research (APR) Digital Equipment Corporation, and The Portland Group (PGI). IBM introduced an HPF compiler for the IBM RS/6000 SP/2 in April of 1996. Over the past two years, these implementations have shown steady improvement in terms of both features and performance. The performance of various hardware/ programming model (HPF and MPI (message passing interface)) combinations will be compared, based on latest NAS (NASA Advanced Supercomputing) Parallel Benchmark (NPB) results, thus providing a cross-machine and cross-model comparison. Specifically, HPF based NPB results will be compared with MPI based NPB results to provide perspective on performance currently obtainable using HPF versus MPI or versus hand-tuned implementations such as those supplied by the hardware vendors. In addition we would also present NPB (Version 1.0) performance results for the following systems: DEC Alpha Server 8400 5/440, Fujitsu VPP Series (VX, VPP300, and VPP700), HP/Convex Exemplar SPP2000, IBM RS/6000 SP P2SC node (120 MHz) NEC SX-4/32, SGI/CRAY T3E, SGI Origin2000.

3-D parallel program for numerical calculation of gas dynamics problems with heat conductivity on distributed memory computational systems (CS)

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

Sofronov, I.D.; Voronin, B.L.; Butnev, O.I.

1997-12-31

The aim of the work performed is to develop a 3D parallel program for numerical calculation of gas dynamics problem with heat conductivity on distributed memory computational systems (CS), satisfying the condition of numerical result independence from the number of processors involved. Two basically different approaches to the structure of massive parallel computations have been developed. The first approach uses the 3D data matrix decomposition reconstructed at temporal cycle and is a development of parallelization algorithms for multiprocessor CS with shareable memory. The second approach is based on using a 3D data matrix decomposition not reconstructed during a temporal cycle.more » The program was developed on 8-processor CS MP-3 made in VNIIEF and was adapted to a massive parallel CS Meiko-2 in LLNL by joint efforts of VNIIEF and LLNL staffs. A large number of numerical experiments has been carried out with different number of processors up to 256 and the efficiency of parallelization has been evaluated in dependence on processor number and their parameters.« less

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.

A Tutorial on Parallel and Concurrent Programming in Haskell

NASA Astrophysics Data System (ADS)

Peyton Jones, Simon; Singh, Satnam

This practical tutorial introduces the features available in Haskell for writing parallel and concurrent programs. We first describe how to write semi-explicit parallel programs by using annotations to express opportunities for parallelism and to help control the granularity of parallelism for effective execution on modern operating systems and processors. We then describe the mechanisms provided by Haskell for writing explicitly parallel programs with a focus on the use of software transactional memory to help share information between threads. Finally, we show how nested data parallelism can be used to write deterministically parallel programs which allows programmers to use rich data types in data parallel programs which are automatically transformed into flat data parallel versions for efficient execution on multi-core processors.

Automatic data partitioning on distributed memory multicomputers. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gupta, Manish

1992-01-01

Distributed-memory parallel computers are increasingly being used to provide high levels of performance for scientific applications. Unfortunately, such machines are not very easy to program. A number of research efforts seek to alleviate this problem by developing compilers that take over the task of generating communication. The communication overheads and the extent of parallelism exploited in the resulting target program are determined largely by the manner in which data is partitioned across different processors of the machine. Most of the compilers provide no assistance to the programmer in the crucial task of determining a good data partitioning scheme. A novel approach is presented, the constraints-based approach, to the problem of automatic data partitioning for numeric programs. In this approach, the compiler identifies some desirable requirements on the distribution of various arrays being referenced in each statement, based on performance considerations. These desirable requirements are referred to as constraints. For each constraint, the compiler determines a quality measure that captures its importance with respect to the performance of the program. The quality measure is obtained through static performance estimation, without actually generating the target data-parallel program with explicit communication. Each data distribution decision is taken by combining all the relevant constraints. The compiler attempts to resolve any conflicts between constraints such that the overall execution time of the parallel program is minimized. This approach has been implemented as part of a compiler called Paradigm, that accepts Fortran 77 programs, and specifies the partitioning scheme to be used for each array in the program. We have obtained results on some programs taken from the Linpack and Eispack libraries, and the Perfect Benchmarks. These results are quite promising, and demonstrate the feasibility of automatic data partitioning for a significant class of scientific application programs with regular computations.

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.

Item Selection for the Development of Parallel Forms from an IRT-Based Seed Test Using a Sampling and Classification Approach

ERIC Educational Resources Information Center

Chen, Pei-Hua; Chang, Hua-Hua; Wu, Haiyan

2012-01-01

Two sampling-and-classification-based procedures were developed for automated test assembly: the Cell Only and the Cell and Cube methods. A simulation study based on a 540-item bank was conducted to compare the performance of the procedures with the performance of a mixed-integer programming (MIP) method for assembling multiple parallel test…

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

GPU accelerated dynamic functional connectivity analysis for functional MRI data.

PubMed

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

2015-07-01

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

Distributed Function Mining for Gene Expression Programming Based on Fast Reduction.

PubMed

Deng, Song; Yue, Dong; Yang, Le-chan; Fu, Xiong; Feng, Ya-zhou

2016-01-01

For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene expression programming based on fast reduction (DFMGEP-FR). In DFMGEP-FR, fast attribution reduction in binary search algorithms (FAR-BSA) is proposed to quickly find the optimal attribution set, and the function consistency replacement algorithm is given to solve integration of the local function model. Thorough comparative experiments for DFMGEP-FR, centralized GEP and the parallel gene expression programming algorithm based on simulated annealing (parallel GEPSA) are included in this paper. For the waveform, mushroom, connect-4 and musk datasets, the comparative results show that the average time-consumption of DFMGEP-FR drops by 89.09%%, 88.85%, 85.79% and 93.06%, respectively, in contrast to centralized GEP and by 12.5%, 8.42%, 9.62% and 13.75%, respectively, compared with parallel GEPSA. Six well-studied UCI test data sets demonstrate the efficiency and capability of our proposed DFMGEP-FR algorithm for distributed function mining.

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

PubMed Central

Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

2008-01-01

Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

Dynamic programming in parallel boundary detection with application to ultrasound intima-media segmentation.

PubMed

Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin

2013-12-01

Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.

A CFD Heterogeneous Parallel Solver Based on Collaborating CPU and GPU

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

On the utility of threads for data parallel programming

NASA Technical Reports Server (NTRS)

Fahringer, Thomas; Haines, Matthew; Mehrotra, Piyush

1995-01-01

Threads provide a useful programming model for asynchronous behavior because of their ability to encapsulate units of work that can then be scheduled for execution at runtime, based on the dynamic state of a system. Recently, the threaded model has been applied to the domain of data parallel scientific codes, and initial reports indicate that the threaded model can produce performance gains over non-threaded approaches, primarily through the use of overlapping useful computation with communication latency. However, overlapping computation with communication is possible without the benefit of threads if the communication system supports asynchronous primitives, and this comparison has not been made in previous papers. This paper provides a critical look at the utility of lightweight threads as applied to data parallel scientific programming.

MPI, HPF or OpenMP: A Study with the NAS Benchmarks

NASA Technical Reports Server (NTRS)

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

1999-01-01

Porting applications to new high performance parallel and distributed platforms is a challenging task. Writing parallel code by hand is time consuming and costly, but the task can be simplified by high level languages and would even better be automated by parallelizing tools and compilers. The definition of HPF (High Performance Fortran, based on data parallel model) and OpenMP (based on shared memory parallel model) standards has offered great opportunity in this respect. Both provide simple and clear interfaces to language like FORTRAN and simplify many tedious tasks encountered in writing message passing programs. In our study we implemented the parallel versions of the NAS Benchmarks with HPF and OpenMP directives. Comparison of their performance with the MPI implementation and pros and cons of different approaches will be discussed along with experience of using computer-aided tools to help parallelize these benchmarks. Based on the study,potentials of applying some of the techniques to realistic aerospace applications will be presented

MPI, HPF or OpenMP: A Study with the NAS Benchmarks

NASA Technical Reports Server (NTRS)

Jin, H.; Frumkin, M.; Hribar, M.; Waheed, A.; Yan, J.; Saini, Subhash (Technical Monitor)

1999-01-01

Porting applications to new high performance parallel and distributed platforms is a challenging task. Writing parallel code by hand is time consuming and costly, but this task can be simplified by high level languages and would even better be automated by parallelizing tools and compilers. The definition of HPF (High Performance Fortran, based on data parallel model) and OpenMP (based on shared memory parallel model) standards has offered great opportunity in this respect. Both provide simple and clear interfaces to language like FORTRAN and simplify many tedious tasks encountered in writing message passing programs. In our study, we implemented the parallel versions of the NAS Benchmarks with HPF and OpenMP directives. Comparison of their performance with the MPI implementation and pros and cons of different approaches will be discussed along with experience of using computer-aided tools to help parallelize these benchmarks. Based on the study, potentials of applying some of the techniques to realistic aerospace applications will be presented.

MLP: A Parallel Programming Alternative to MPI for New Shared Memory Parallel Systems

NASA Technical Reports Server (NTRS)

Taft, James R.

1999-01-01

Recent developments at the NASA AMES Research Center's NAS Division have demonstrated that the new generation of NUMA based Symmetric Multi-Processing systems (SMPs), such as the Silicon Graphics Origin 2000, can successfully execute legacy vector oriented CFD production codes at sustained rates far exceeding processing rates possible on dedicated 16 CPU Cray C90 systems. This high level of performance is achieved via shared memory based Multi-Level Parallelism (MLP). This programming approach, developed at NAS and outlined below, is distinct from the message passing paradigm of MPI. It offers parallelism at both the fine and coarse grained level, with communication latencies that are approximately 50-100 times lower than typical MPI implementations on the same platform. Such latency reductions offer the promise of performance scaling to very large CPU counts. The method draws on, but is also distinct from, the newly defined OpenMP specification, which uses compiler directives to support a limited subset of multi-level parallel operations. The NAS MLP method is general, and applicable to a large class of NASA CFD codes.

Fenix, A Fault Tolerant Programming Framework for MPI Applications

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

Gamel, Marc; Teranihi, Keita; Valenzuela, Eric

2016-10-05

Fenix provides APIs to allow the users to add fault tolerance capability to MPI-based parallel programs in a transparent manner. Fenix-enabled programs can run through process failures during program execution using a pool of spare processes accommodated by Fenix.

High Performance Programming Using Explicit Shared Memory Model on the Cray T3D

NASA Technical Reports Server (NTRS)

Saini, Subhash; Simon, Horst D.; Lasinski, T. A. (Technical Monitor)

1994-01-01

The Cray T3D is the first-phase system in Cray Research Inc.'s (CRI) three-phase massively parallel processing program. In this report we describe the architecture of the T3D, as well as the CRAFT (Cray Research Adaptive Fortran) programming model, and contrast it with PVM, which is also supported on the T3D We present some performance data based on the NAS Parallel Benchmarks to illustrate both architectural and software features of the T3D.

Automatic differentiation for design sensitivity analysis of structural systems using multiple processors

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Storaasli, Olaf O.; Qin, Jiangning; Qamar, Ramzi

1994-01-01

An automatic differentiation tool (ADIFOR) is incorporated into a finite element based structural analysis program for shape and non-shape design sensitivity analysis of structural systems. The entire analysis and sensitivity procedures are parallelized and vectorized for high performance computation. Small scale examples to verify the accuracy of the proposed program and a medium scale example to demonstrate the parallel vector performance on multiple CRAY C90 processors are included.

Managing Algorithmic Skeleton Nesting Requirements in Realistic Image Processing Applications: The Case of the SKiPPER-II Parallel Programming Environment's Operating Model

NASA Astrophysics Data System (ADS)

Coudarcher, Rémi; Duculty, Florent; Serot, Jocelyn; Jurie, Frédéric; Derutin, Jean-Pierre; Dhome, Michel

2005-12-01

SKiPPER is a SKeleton-based Parallel Programming EnviRonment being developed since 1996 and running at LASMEA Laboratory, the Blaise-Pascal University, France. The main goal of the project was to demonstrate the applicability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This paper deals with the special features embedded in the latest version of the project: algorithmic skeleton nesting capabilities and a fully dynamic operating model. Throughout the case study of a complete and realistic image processing application, in which we have pointed out the requirement for skeleton nesting, we are presenting the operating model of this feature. The work described here is one of the few reported experiments showing the application of skeleton nesting facilities for the parallelisation of a realistic application, especially in the area of image processing. The image processing application we have chosen is a 3D face-tracking algorithm from appearance.

A portable MPI-based parallel vector template library

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.

1995-01-01

This paper discusses the design and implementation of a polymorphic collection library for distributed address-space parallel computers. The library provides a data-parallel programming model for C++ by providing three main components: a single generic collection class, generic algorithms over collections, and generic algebraic combining functions. Collection elements are the fourth component of a program written using the library and may be either of the built-in types of C or of user-defined types. Many ideas are borrowed from the Standard Template Library (STL) of C++, although a restricted programming model is proposed because of the distributed address-space memory model assumed. Whereas the STL provides standard collections and implementations of algorithms for uniprocessors, this paper advocates standardizing interfaces that may be customized for different parallel computers. Just as the STL attempts to increase programmer productivity through code reuse, a similar standard for parallel computers could provide programmers with a standard set of algorithms portable across many different architectures. The efficacy of this approach is verified by examining performance data collected from an initial implementation of the library running on an IBM SP-2 and an Intel Paragon.

A Portable MPI-Based Parallel Vector Template Library

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.

1995-01-01

This paper discusses the design and implementation of a polymorphic collection library for distributed address-space parallel computers. The library provides a data-parallel programming model for C + + by providing three main components: a single generic collection class, generic algorithms over collections, and generic algebraic combining functions. Collection elements are the fourth component of a program written using the library and may be either of the built-in types of c or of user-defined types. Many ideas are borrowed from the Standard Template Library (STL) of C++, although a restricted programming model is proposed because of the distributed address-space memory model assumed. Whereas the STL provides standard collections and implementations of algorithms for uniprocessors, this paper advocates standardizing interfaces that may be customized for different parallel computers. Just as the STL attempts to increase programmer productivity through code reuse, a similar standard for parallel computers could provide programmers with a standard set of algorithms portable across many different architectures. The efficacy of this approach is verified by examining performance data collected from an initial implementation of the library running on an IBM SP-2 and an Intel Paragon.

A computer program for converting rectangular coordinates to latitude-longitude coordinates

USGS Publications Warehouse

Rutledge, A.T.

1989-01-01

A computer program was developed for converting the coordinates of any rectangular grid on a map to coordinates on a grid that is parallel to lines of equal latitude and longitude. Using this program in conjunction with groundwater flow models, the user can extract data and results from models with varying grid orientations and place these data into grid structure that is oriented parallel to lines of equal latitude and longitude. All cells in the rectangular grid must have equal dimensions, and all cells in the latitude-longitude grid measure one minute by one minute. This program is applicable if the map used shows lines of equal latitude as arcs and lines of equal longitude as straight lines and assumes that the Earth 's surface can be approximated as a sphere. The program user enters the row number , column number, and latitude and longitude of the midpoint of the cell for three test cells on the rectangular grid. The latitude and longitude of boundaries of the rectangular grid also are entered. By solving sets of simultaneous linear equations, the program calculates coefficients that are used for making the conversion. As an option in the program, the user may build a groundwater model file based on a grid that is parallel to lines of equal latitude and longitude. The program reads a data file based on the rectangular coordinates and automatically forms the new data file. (USGS)

pWeb: A High-Performance, Parallel-Computing Framework for Web-Browser-Based Medical Simulation.

PubMed

Halic, Tansel; Ahn, Woojin; De, Suvranu

2014-01-01

This work presents a pWeb - a new language and compiler for parallelization of client-side compute intensive web applications such as surgical simulations. The recently introduced HTML5 standard has enabled creating unprecedented applications on the web. Low performance of the web browser, however, remains the bottleneck of computationally intensive applications including visualization of complex scenes, real time physical simulations and image processing compared to native ones. The new proposed language is built upon web workers for multithreaded programming in HTML5. The language provides fundamental functionalities of parallel programming languages as well as the fork/join parallel model which is not supported by web workers. The language compiler automatically generates an equivalent parallel script that complies with the HTML5 standard. A case study on realistic rendering for surgical simulations demonstrates enhanced performance with a compact set of instructions.

A parallel finite element procedure for contact-impact problems using edge-based smooth triangular element and GPU

NASA Astrophysics Data System (ADS)

Cai, Yong; Cui, Xiangyang; Li, Guangyao; Liu, Wenyang

2018-04-01

The edge-smooth finite element method (ES-FEM) can improve the computational accuracy of triangular shell elements and the mesh partition efficiency of complex models. In this paper, an approach is developed to perform explicit finite element simulations of contact-impact problems with a graphical processing unit (GPU) using a special edge-smooth triangular shell element based on ES-FEM. Of critical importance for this problem is achieving finer-grained parallelism to enable efficient data loading and to minimize communication between the device and host. Four kinds of parallel strategies are then developed to efficiently solve these ES-FEM based shell element formulas, and various optimization methods are adopted to ensure aligned memory access. Special focus is dedicated to developing an approach for the parallel construction of edge systems. A parallel hierarchy-territory contact-searching algorithm (HITA) and a parallel penalty function calculation method are embedded in this parallel explicit algorithm. Finally, the program flow is well designed, and a GPU-based simulation system is developed, using Nvidia's CUDA. Several numerical examples are presented to illustrate the high quality of the results obtained with the proposed methods. In addition, the GPU-based parallel computation is shown to significantly reduce the computing time.

Functional and space programming.

PubMed

Hayward, C

1988-01-01

In this article, the author expands the earlier stated case for functional and space programming based on objective evidence of user needs. It provides an in-depth examination of the logic and processes of programming as a continuum which precedes, then parallels, architectural design.

A parallel solver for huge dense linear systems

NASA Astrophysics Data System (ADS)

Badia, J. M.; Movilla, J. L.; Climente, J. I.; Castillo, M.; Marqués, M.; Mayo, R.; Quintana-Ortí, E. S.; Planelles, J.

2011-11-01

HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facilitate the parallel solution of very large dense systems to scientists and engineers. The API makes use of parallelism to yield an efficient solution of the systems on a wide range of parallel platforms, from clusters of processors to massively parallel multiprocessors. It exploits out-of-core strategies to leverage the secondary memory in order to solve huge linear systems O(100.000). The API is based on the parallel linear algebra library PLAPACK, and on its Out-Of-Core (OOC) extension POOCLAPACK. Both PLAPACK and POOCLAPACK use the Message Passing Interface (MPI) as the communication layer and BLAS to perform the local matrix operations. The API provides a friendly interface to the users, hiding almost all the technical aspects related to the parallel execution of the code and the use of the secondary memory to solve the systems. In particular, the API can automatically select the best way to store and solve the systems, depending of the dimension of the system, the number of processes and the main memory of the platform. Experimental results on several parallel platforms report high performance, reaching more than 1 TFLOP with 64 cores to solve a system with more than 200 000 equations and more than 10 000 right-hand side vectors. New version program summaryProgram title: Huge Dense System Solver (HDSS) Catalogue identifier: AEHU_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHU_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 87 062 No. of bytes in distributed program, including test data, etc.: 1 069 110 Distribution format: tar.gz Programming language: Fortran90, C Computer: Parallel architectures: multiprocessors, computer clusters Operating system: Linux/Unix Has the code been vectorized or parallelized?: Yes, includes MPI primitives. RAM: Tested for up to 190 GB Classification: 6.5 External routines: MPI ( http://www.mpi-forum.org/), BLAS ( http://www.netlib.org/blas/), PLAPACK ( http://www.cs.utexas.edu/~plapack/), POOCLAPACK ( ftp://ftp.cs.utexas.edu/pub/rvdg/PLAPACK/pooclapack.ps) (code for PLAPACK and POOCLAPACK is included in the distribution). Catalogue identifier of previous version: AEHU_v1_0 Journal reference of previous version: Comput. Phys. Comm. 182 (2011) 533 Does the new version supersede the previous version?: Yes Nature of problem: Huge scale dense systems of linear equations, Ax=B, beyond standard LAPACK capabilities. Solution method: The linear systems are solved by means of parallelized routines based on the LU factorization, using efficient secondary storage algorithms when the available main memory is insufficient. Reasons for new version: In many applications we need to guarantee a high accuracy in the solution of very large linear systems and we can do it by using double-precision arithmetic. Summary of revisions: Version 1.1 Can be used to solve linear systems using double-precision arithmetic. New version of the initialization routine. The user can choose the kind of arithmetic and the values of several parameters of the environment. Running time: About 5 hours to solve a system with more than 200 000 equations and more than 10 000 right-hand side vectors using double-precision arithmetic on an eight-node commodity cluster with a total of 64 Intel cores.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed

Nadkarni, P M; Miller, P L

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations.

The Many Ways Data Must Flow.

ERIC Educational Resources Information Center

La Brecque, Mort

1984-01-01

To break the bottleneck inherent in today's linear computer architectures, parallel schemes (which allow computers to perform multiple tasks at one time) are being devised. Several of these schemes are described. Dataflow devices, parallel number-crunchers, programing languages, and a device based on a neurological model are among the areas…

Automatic Construction of English/Chinese Parallel Corpora.

ERIC Educational Resources Information Center

Yang, Christopher C.; Li, Kar Wing

2003-01-01

Discussion of multilingual corpora and cross-lingual information retrieval focuses on research that constructed English/Chinese parallel corpus automatically from the World Wide Web. Presents an alignment method which is based on dynamic programming to identify one-to-one Chinese and English title pairs and discusses results of experiments…

Real-Time MENTAT programming language and architecture

NASA Technical Reports Server (NTRS)

Grimshaw, Andrew S.; Silberman, Ami; Liu, Jane W. S.

1989-01-01

Real-time MENTAT, a programming environment designed to simplify the task of programming real-time applications in distributed and parallel environments, is described. It is based on the same data-driven computation model and object-oriented programming paradigm as MENTAT. It provides an easy-to-use mechanism to exploit parallelism, language constructs for the expression and enforcement of timing constraints, and run-time support for scheduling and exciting real-time programs. The real-time MENTAT programming language is an extended C++. The extensions are added to facilitate automatic detection of data flow and generation of data flow graphs, to express the timing constraints of individual granules of computation, and to provide scheduling directives for the runtime system. A high-level view of the real-time MENTAT system architecture and programming language constructs is provided.

Thread concept for automatic task parallelization in image analysis

NASA Astrophysics Data System (ADS)

Lueckenhaus, Maximilian; Eckstein, Wolfgang

1998-09-01

Parallel processing of image analysis tasks is an essential method to speed up image processing and helps to exploit the full capacity of distributed systems. However, writing parallel code is a difficult and time-consuming process and often leads to an architecture-dependent program that has to be re-implemented when changing the hardware. Therefore it is highly desirable to do the parallelization automatically. For this we have developed a special kind of thread concept for image analysis tasks. Threads derivated from one subtask may share objects and run in the same context but may process different threads of execution and work on different data in parallel. In this paper we describe the basics of our thread concept and show how it can be used as basis of an automatic task parallelization to speed up image processing. We further illustrate the design and implementation of an agent-based system that uses image analysis threads for generating and processing parallel programs by taking into account the available hardware. The tests made with our system prototype show that the thread concept combined with the agent paradigm is suitable to speed up image processing by an automatic parallelization of image analysis tasks.

An FPGA-based High Speed Parallel Signal Processing System for Adaptive Optics Testbed

NASA Astrophysics Data System (ADS)

Kim, H.; Choi, Y.; Yang, Y.

In this paper a state-of-the-art FPGA (Field Programmable Gate Array) based high speed parallel signal processing system (SPS) for adaptive optics (AO) testbed with 1 kHz wavefront error (WFE) correction frequency is reported. The AO system consists of Shack-Hartmann sensor (SHS) and deformable mirror (DM), tip-tilt sensor (TTS), tip-tilt mirror (TTM) and an FPGA-based high performance SPS to correct wavefront aberrations. The SHS is composed of 400 subapertures and the DM 277 actuators with Fried geometry, requiring high speed parallel computing capability SPS. In this study, the target WFE correction speed is 1 kHz; therefore, it requires massive parallel computing capabilities as well as strict hard real time constraints on measurements from sensors, matrix computation latency for correction algorithms, and output of control signals for actuators. In order to meet them, an FPGA based real-time SPS with parallel computing capabilities is proposed. In particular, the SPS is made up of a National Instrument's (NI's) real time computer and five FPGA boards based on state-of-the-art Xilinx Kintex 7 FPGA. Programming is done with NI's LabView environment, providing flexibility when applying different algorithms for WFE correction. It also facilitates faster programming and debugging environment as compared to conventional ones. One of the five FPGA's is assigned to measure TTS and calculate control signals for TTM, while the rest four are used to receive SHS signal, calculate slops for each subaperture and correction signal for DM. With this parallel processing capabilities of the SPS the overall closed-loop WFE correction speed of 1 kHz has been achieved. System requirements, architecture and implementation issues are described; furthermore, experimental results are also given.

Study of the Discipline-Based Education vs. Liberal Education in the Department of Social Sciences, S. P. J. C. [St. Petersburg Junior College, Florida].

ERIC Educational Resources Information Center

McCuskey, E. Scott; Worley, William E.

The heterogeneous nature of community college populations has resulted in an academic dichotomy within two-year institutions. Most institutions offer two types of programs: (1) discipline-based, university parallel programs, oriented toward transferring students to four-year institutions; (2) vocational/technical programs, oriented toward terminal…

Genetic Parallel Programming: design and implementation.

PubMed

Cheang, Sin Man; Leung, Kwong Sak; Lee, Kin Hong

2006-01-01

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed Central

Nadkarni, P. M.; Miller, P. L.

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations. PMID:1807632

Flexible language constructs for large parallel programs

NASA Technical Reports Server (NTRS)

Rosing, Matthew; Schnabel, Robert

1993-01-01

The goal of the research described is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (MIMD) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include SIMD (Single Instruction Multiple Data), SPMD (Single Program Multiple Data), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression of the variety of algorithms that occur in large scientific computations. An overview of a new language that combines many of these programming models in a clean manner is given. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. An overview of the language and discussion of some of the critical implementation details is given.

High-energy physics software parallelization using database techniques

NASA Astrophysics Data System (ADS)

Argante, E.; van der Stok, P. D. V.; Willers, I.

1997-02-01

A programming model for software parallelization, called CoCa, is introduced that copes with problems caused by typical features of high-energy physics software. By basing CoCa on the database transaction paradimg, the complexity induced by the parallelization is for a large part transparent to the programmer, resulting in a higher level of abstraction than the native message passing software. CoCa is implemented on a Meiko CS-2 and on a SUN SPARCcenter 2000 parallel computer. On the CS-2, the performance is comparable with the performance of native PVM and MPI.

Investigation of the applicability of a functional programming model to fault-tolerant parallel processing for knowledge-based systems

NASA Technical Reports Server (NTRS)

Harper, Richard

1989-01-01

In a fault-tolerant parallel computer, a functional programming model can facilitate distributed checkpointing, error recovery, load balancing, and graceful degradation. Such a model has been implemented on the Draper Fault-Tolerant Parallel Processor (FTPP). When used in conjunction with the FTPP's fault detection and masking capabilities, this implementation results in a graceful degradation of system performance after faults. Three graceful degradation algorithms have been implemented and are presented. A user interface has been implemented which requires minimal cognitive overhead by the application programmer, masking such complexities as the system's redundancy, distributed nature, variable complement of processing resources, load balancing, fault occurrence and recovery. This user interface is described and its use demonstrated. The applicability of the functional programming style to the Activation Framework, a paradigm for intelligent systems, is then briefly described.

Support of Multidimensional Parallelism in the OpenMP Programming Model

NASA Technical Reports Server (NTRS)

Jin, Hao-Qiang; Jost, Gabriele

2003-01-01

OpenMP is the current standard for shared-memory programming. While providing ease of parallel programming, the OpenMP programming model also has limitations which often effect the scalability of applications. Examples for these limitations are work distribution and point-to-point synchronization among threads. We propose extensions to the OpenMP programming model which allow the user to easily distribute the work in multiple dimensions and synchronize the workflow among the threads. The proposed extensions include four new constructs and the associated runtime library. They do not require changes to the source code and can be implemented based on the existing OpenMP standard. We illustrate the concept in a prototype translator and test with benchmark codes and a cloud modeling code.

cljam: a library for handling DNA sequence alignment/map (SAM) with parallel processing.

PubMed

Takeuchi, Toshiki; Yamada, Atsuo; Aoki, Takashi; Nishimura, Kunihiro

2016-01-01

Next-generation sequencing can determine DNA bases and the results of sequence alignments are generally stored in files in the Sequence Alignment/Map (SAM) format and the compressed binary version (BAM) of it. SAMtools is a typical tool for dealing with files in the SAM/BAM format. SAMtools has various functions, including detection of variants, visualization of alignments, indexing, extraction of parts of the data and loci, and conversion of file formats. It is written in C and can execute fast. However, SAMtools requires an additional implementation to be used in parallel with, for example, OpenMP (Open Multi-Processing) libraries. For the accumulation of next-generation sequencing data, a simple parallelization program, which can support cloud and PC cluster environments, is required. We have developed cljam using the Clojure programming language, which simplifies parallel programming, to handle SAM/BAM data. Cljam can run in a Java runtime environment (e.g., Windows, Linux, Mac OS X) with Clojure. Cljam can process and analyze SAM/BAM files in parallel and at high speed. The execution time with cljam is almost the same as with SAMtools. The cljam code is written in Clojure and has fewer lines than other similar tools.

Use of RORA for Complex Ground-Water Flow Conditions

USGS Publications Warehouse

Rutledge, A.T.

2004-01-01

The RORA computer program for estimating recharge is based on a condition in which ground water flows perpendicular to the nearest stream that receives ground-water discharge. The method, therefore, does not explicitly account for the ground-water-flow component that is parallel to the stream. Hypothetical finite-difference simulations are used to demonstrate effects of complex flow conditions that consist of two components: one that is perpendicular to the stream and one that is parallel to the stream. Results of the simulations indicate that the RORA program can be used if certain constraints are applied in the estimation of the recession index, an input variable to the program. These constraints apply to a mathematical formulation based on aquifer properties, recession of ground-water levels, and recession of streamflow.

A Review of Lightweight Thread Approaches for High Performance Computing

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

Castello, Adrian; Pena, Antonio J.; Seo, Sangmin

High-level, directive-based solutions are becoming the programming models (PMs) of the multi/many-core architectures. Several solutions relying on operating system (OS) threads perfectly work with a moderate number of cores. However, exascale systems will spawn hundreds of thousands of threads in order to exploit their massive parallel architectures and thus conventional OS threads are too heavy for that purpose. Several lightweight thread (LWT) libraries have recently appeared offering lighter mechanisms to tackle massive concurrency. In order to examine the suitability of LWTs in high-level runtimes, we develop a set of microbenchmarks consisting of commonlyfound patterns in current parallel codes. Moreover, wemore » study the semantics offered by some LWT libraries in order to expose the similarities between different LWT application programming interfaces. This study reveals that a reduced set of LWT functions can be sufficient to cover the common parallel code patterns and that those LWT libraries perform better than OS threads-based solutions in cases where task and nested parallelism are becoming more popular with new architectures.« less

Development, Verification and Validation of Parallel, Scalable Volume of Fluid CFD Program for Propulsion Applications

NASA Technical Reports Server (NTRS)

West, Jeff; Yang, H. Q.

2014-01-01

There are many instances involving liquid/gas interfaces and their dynamics in the design of liquid engine powered rockets such as the Space Launch System (SLS). Some examples of these applications are: Propellant tank draining and slosh, subcritical condition injector analysis for gas generators, preburners and thrust chambers, water deluge mitigation for launch induced environments and even solid rocket motor liquid slag dynamics. Commercially available CFD programs simulating gas/liquid interfaces using the Volume of Fluid approach are currently limited in their parallel scalability. In 2010 for instance, an internal NASA/MSFC review of three commercial tools revealed that parallel scalability was seriously compromised at 8 cpus and no additional speedup was possible after 32 cpus. Other non-interface CFD applications at the time were demonstrating useful parallel scalability up to 4,096 processors or more. Based on this review, NASA/MSFC initiated an effort to implement a Volume of Fluid implementation within the unstructured mesh, pressure-based algorithm CFD program, Loci-STREAM. After verification was achieved by comparing results to the commercial CFD program CFD-Ace+, and validation by direct comparison with data, Loci-STREAM-VoF is now the production CFD tool for propellant slosh force and slosh damping rate simulations at NASA/MSFC. On these applications, good parallel scalability has been demonstrated for problems sizes of tens of millions of cells and thousands of cpu cores. Ongoing efforts are focused on the application of Loci-STREAM-VoF to predict the transient flow patterns of water on the SLS Mobile Launch Platform in order to support the phasing of water for launch environment mitigation so that vehicle determinantal effects are not realized.

MIST: An Open Source Environmental Modelling Programming Language Incorporating Easy to Use Data Parallelism.

NASA Astrophysics Data System (ADS)

Bellerby, Tim

2014-05-01

Model Integration System (MIST) is open-source environmental modelling programming language that directly incorporates data parallelism. The language is designed to enable straightforward programming structures, such as nested loops and conditional statements to be directly translated into sequences of whole-array (or more generally whole data-structure) operations. MIST thus enables the programmer to use well-understood constructs, directly relating to the mathematical structure of the model, without having to explicitly vectorize code or worry about details of parallelization. A range of common modelling operations are supported by dedicated language structures operating on cell neighbourhoods rather than individual cells (e.g.: the 3x3 local neighbourhood needed to implement an averaging image filter can be simply accessed from within a simple loop traversing all image pixels). This facility hides details of inter-process communication behind more mathematically relevant descriptions of model dynamics. The MIST automatic vectorization/parallelization process serves both to distribute work among available nodes and separately to control storage requirements for intermediate expressions - enabling operations on very large domains for which memory availability may be an issue. MIST is designed to facilitate efficient interpreter based implementations. A prototype open source interpreter is available, coded in standard FORTRAN 95, with tools to rapidly integrate existing FORTRAN 77 or 95 code libraries. The language is formally specified and thus not limited to FORTRAN implementation or to an interpreter-based approach. A MIST to FORTRAN compiler is under development and volunteers are sought to create an ANSI-C implementation. Parallel processing is currently implemented using OpenMP. However, parallelization code is fully modularised and could be replaced with implementations using other libraries. GPU implementation is potentially possible.

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

PubMed

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP

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

Tsugane, Keisuke; Boku, Taisuke; Murai, Hitoshi

Recently, the Partitioned Global Address Space (PGAS) parallel programming model has emerged as a usable distributed memory programming model. XcalableMP (XMP) is a PGAS parallel programming language that extends base languages such as C and Fortran with directives in OpenMP-like style. XMP supports a global-view model that allows programmers to define global data and to map them to a set of processors, which execute the distributed global data as a single thread. In XMP, the concept of a coarray is also employed for local-view programming. In this study, we port Gyrokinetic Toroidal Code - Princeton (GTC-P), which is a three-dimensionalmore » gyrokinetic PIC code developed at Princeton University to study the microturbulence phenomenon in magnetically confined fusion plasmas, to XMP as an example of hybrid memory model coding with the global-view and local-view programming models. In local-view programming, the coarray notation is simple and intuitive compared with Message Passing Interface (MPI) programming while the performance is comparable to that of the MPI version. Thus, because the global-view programming model is suitable for expressing the data parallelism for a field of grid space data, we implement a hybrid-view version using a global-view programming model to compute the field and a local-view programming model to compute the movement of particles. Finally, the performance is degraded by 20% compared with the original MPI version, but the hybrid-view version facilitates more natural data expression for static grid space data (in the global-view model) and dynamic particle data (in the local-view model), and it also increases the readability of the code for higher productivity.« less

Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP

DOE PAGES

Tsugane, Keisuke; Boku, Taisuke; Murai, Hitoshi; ...

2016-06-01

Recently, the Partitioned Global Address Space (PGAS) parallel programming model has emerged as a usable distributed memory programming model. XcalableMP (XMP) is a PGAS parallel programming language that extends base languages such as C and Fortran with directives in OpenMP-like style. XMP supports a global-view model that allows programmers to define global data and to map them to a set of processors, which execute the distributed global data as a single thread. In XMP, the concept of a coarray is also employed for local-view programming. In this study, we port Gyrokinetic Toroidal Code - Princeton (GTC-P), which is a three-dimensionalmore » gyrokinetic PIC code developed at Princeton University to study the microturbulence phenomenon in magnetically confined fusion plasmas, to XMP as an example of hybrid memory model coding with the global-view and local-view programming models. In local-view programming, the coarray notation is simple and intuitive compared with Message Passing Interface (MPI) programming while the performance is comparable to that of the MPI version. Thus, because the global-view programming model is suitable for expressing the data parallelism for a field of grid space data, we implement a hybrid-view version using a global-view programming model to compute the field and a local-view programming model to compute the movement of particles. Finally, the performance is degraded by 20% compared with the original MPI version, but the hybrid-view version facilitates more natural data expression for static grid space data (in the global-view model) and dynamic particle data (in the local-view model), and it also increases the readability of the code for higher productivity.« less

The force on the flex: Global parallelism and portability

NASA Technical Reports Server (NTRS)

Jordan, H. F.

1986-01-01

A parallel programming methodology, called the force, supports the construction of programs to be executed in parallel by an unspecified, but potentially large, number of processes. The methodology was originally developed on a pipelined, shared memory multiprocessor, the Denelcor HEP, and embodies the primitive operations of the force in a set of macros which expand into multiprocessor Fortran code. A small set of primitives is sufficient to write large parallel programs, and the system has been used to produce 10,000 line programs in computational fluid dynamics. The level of complexity of the force primitives is intermediate. It is high enough to mask detailed architectural differences between multiprocessors but low enough to give the user control over performance. The system is being ported to a medium scale multiprocessor, the Flex/32, which is a 20 processor system with a mixture of shared and local memory. Memory organization and the type of processor synchronization supported by the hardware on the two machines lead to some differences in efficient implementations of the force primitives, but the user interface remains the same. An initial implementation was done by retargeting the macros to Flexible Computer Corporation's ConCurrent C language. Subsequently, the macros were caused to directly produce the system calls which form the basis for ConCurrent C. The implementation of the Fortran based system is in step with Flexible Computer Corporations's implementation of a Fortran system in the parallel environment.

Optimized and parallelized implementation of the electronegativity equalization method and the atom-bond electronegativity equalization method.

PubMed

Vareková, R Svobodová; Koca, J

2006-02-01

The most common way to calculate charge distribution in a molecule is ab initio quantum mechanics (QM). Some faster alternatives to QM have also been developed, the so-called "equalization methods" EEM and ABEEM, which are based on DFT. We have implemented and optimized the EEM and ABEEM methods and created the EEM SOLVER and ABEEM SOLVER programs. It has been found that the most time-consuming part of equalization methods is the reduction of the matrix belonging to the equation system generated by the method. Therefore, for both methods this part was replaced by the parallel algorithm WIRS and implemented within the PVM environment. The parallelized versions of the programs EEM SOLVER and ABEEM SOLVER showed promising results, especially on a single computer with several processors (compact PVM). The implemented programs are available through the Web page http://ncbr.chemi.muni.cz/~n19n/eem_abeem.

Developing Information Power Grid Based Algorithms and Software

NASA Technical Reports Server (NTRS)

Dongarra, Jack

1998-01-01

This exploratory study initiated our effort to understand performance modeling on parallel systems. The basic goal of performance modeling is to understand and predict the performance of a computer program or set of programs on a computer system. Performance modeling has numerous applications, including evaluation of algorithms, optimization of code implementations, parallel library development, comparison of system architectures, parallel system design, and procurement of new systems. Our work lays the basis for the construction of parallel libraries that allow for the reconstruction of application codes on several distinct architectures so as to assure performance portability. Following our strategy, once the requirements of applications are well understood, one can then construct a library in a layered fashion. The top level of this library will consist of architecture-independent geometric, numerical, and symbolic algorithms that are needed by the sample of applications. These routines should be written in a language that is portable across the targeted architectures.

Memory-based frame synchronizer. [for digital communication systems

NASA Technical Reports Server (NTRS)

Stattel, R. J.; Niswander, J. K. (Inventor)

1981-01-01

A frame synchronizer for use in digital communications systems wherein data formats can be easily and dynamically changed is described. The use of memory array elements provide increased flexibility in format selection and sync word selection in addition to real time reconfiguration ability. The frame synchronizer comprises a serial-to-parallel converter which converts a serial input data stream to a constantly changing parallel data output. This parallel data output is supplied to programmable sync word recognizers each consisting of a multiplexer and a random access memory (RAM). The multiplexer is connected to both the parallel data output and an address bus which may be connected to a microprocessor or computer for purposes of programming the sync word recognizer. The RAM is used as an associative memory or decorder and is programmed to identify a specific sync word. Additional programmable RAMs are used as counter decoders to define word bit length, frame word length, and paragraph frame length.

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

NASA Astrophysics Data System (ADS)

Rostrup, Scott; De Sterck, Hans

2010-12-01

Increasingly, high-performance computing is looking towards data-parallel computational devices to enhance computational performance. Two technologies that have received significant attention are IBM's Cell Processor and NVIDIA's CUDA programming model for graphics processing unit (GPU) computing. In this paper we investigate the acceleration of parallel hyperbolic partial differential equation simulation on structured grids with explicit time integration on clusters with Cell and GPU backends. The message passing interface (MPI) is used for communication between nodes at the coarsest level of parallelism. Optimizations of the simulation code at the several finer levels of parallelism that the data-parallel devices provide are described in terms of data layout, data flow and data-parallel instructions. Optimized Cell and GPU performance are compared with reference code performance on a single x86 central processing unit (CPU) core in single and double precision. We further compare the CPU, Cell and GPU platforms on a chip-to-chip basis, and compare performance on single cluster nodes with two CPUs, two Cell processors or two GPUs in a shared memory configuration (without MPI). We finally compare performance on clusters with 32 CPUs, 32 Cell processors, and 32 GPUs using MPI. Our GPU cluster results use NVIDIA Tesla GPUs with GT200 architecture, but some preliminary results on recently introduced NVIDIA GPUs with the next-generation Fermi architecture are also included. This paper provides computational scientists and engineers who are considering porting their codes to accelerator environments with insight into how structured grid based explicit algorithms can be optimized for clusters with Cell and GPU accelerators. It also provides insight into the speed-up that may be gained on current and future accelerator architectures for this class of applications. Program summaryProgram title: SWsolver Catalogue identifier: AEGY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGY_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL v3 No. of lines in distributed program, including test data, etc.: 59 168 No. of bytes in distributed program, including test data, etc.: 453 409 Distribution format: tar.gz Programming language: C, CUDA Computer: Parallel Computing Clusters. Individual compute nodes may consist of x86 CPU, Cell processor, or x86 CPU with attached NVIDIA GPU accelerator. Operating system: Linux Has the code been vectorised or parallelized?: Yes. Tested on 1-128 x86 CPU cores, 1-32 Cell Processors, and 1-32 NVIDIA GPUs. RAM: Tested on Problems requiring up to 4 GB per compute node. Classification: 12 External routines: MPI, CUDA, IBM Cell SDK Nature of problem: MPI-parallel simulation of Shallow Water equations using high-resolution 2D hyperbolic equation solver on regular Cartesian grids for x86 CPU, Cell Processor, and NVIDIA GPU using CUDA. Solution method: SWsolver provides 3 implementations of a high-resolution 2D Shallow Water equation solver on regular Cartesian grids, for CPU, Cell Processor, and NVIDIA GPU. Each implementation uses MPI to divide work across a parallel computing cluster. Additional comments: Sub-program numdiff is used for the test run.

Analysis and selection of optimal function implementations in massively parallel computer

DOEpatents

Archer, Charles Jens [Rochester, MN; Peters, Amanda [Rochester, MN; Ratterman, Joseph D [Rochester, MN

2011-05-31

An apparatus, program product and method optimize the operation of a parallel computer system by, in part, collecting performance data for a set of implementations of a function capable of being executed on the parallel computer system based upon the execution of the set of implementations under varying input parameters in a plurality of input dimensions. The collected performance data may be used to generate selection program code that is configured to call selected implementations of the function in response to a call to the function under varying input parameters. The collected performance data may be used to perform more detailed analysis to ascertain the comparative performance of the set of implementations of the function under the varying input parameters.

Development for SSV on a parallel processing system (PARAGON)

NASA Astrophysics Data System (ADS)

Gothard, Benny M.; Allmen, Mark; Carroll, Michael J.; Rich, Dan

1995-12-01

A goal of the surrogate semi-autonomous vehicle (SSV) program is to have multiple vehicles navigate autonomously and cooperatively with other vehicles. This paper describes the process and tools used in porting UGV/SSV (unmanned ground vehicle) autonomous mobility and target recognition algorithms from a SISD (single instruction single data) processor architecture (i.e., a Sun SPARC workstation running C/UNIX) to a MIMD (multiple instruction multiple data) parallel processor architecture (i.e., PARAGON-a parallel set of i860 processors running C/UNIX). It discusses the gains in performance and the pitfalls of such a venture. It also examines the merits of this processor architecture (based on this conceptual prototyping effort) and programming paradigm to meet the final SSV demonstration requirements.

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.

Innovative Language-Based & Object-Oriented Structured AMR Using Fortran 90 and OpenMP

NASA Technical Reports Server (NTRS)

Norton, C.; Balsara, D.

1999-01-01

Parallel adaptive mesh refinement (AMR) is an important numerical technique that leads to the efficient solution of many physical and engineering problems. In this paper, we describe how AMR programing can be performed in an object-oreinted way using the modern aspects of Fortran 90 combined with the parallelization features of OpenMP.

A scalable parallel algorithm for multiple objective linear programs

NASA Technical Reports Server (NTRS)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

Automated Vectorization of Decision-Based Algorithms

NASA Technical Reports Server (NTRS)

James, Mark

2006-01-01

Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.

Parallel Signal Processing and System Simulation using aCe

NASA Technical Reports Server (NTRS)

Dorband, John E.; Aburdene, Maurice F.

2003-01-01

Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

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.

Computer Science Techniques Applied to Parallel Atomistic Simulation

NASA Astrophysics Data System (ADS)

Nakano, Aiichiro

1998-03-01

Recent developments in parallel processing technology and multiresolution numerical algorithms have established large-scale molecular dynamics (MD) simulations as a new research mode for studying materials phenomena such as fracture. However, this requires large system sizes and long simulated times. We have developed: i) Space-time multiresolution schemes; ii) fuzzy-clustering approach to hierarchical dynamics; iii) wavelet-based adaptive curvilinear-coordinate load balancing; iv) multilevel preconditioned conjugate gradient method; and v) spacefilling-curve-based data compression for parallel I/O. Using these techniques, million-atom parallel MD simulations are performed for the oxidation dynamics of nanocrystalline Al. The simulations take into account the effect of dynamic charge transfer between Al and O using the electronegativity equalization scheme. The resulting long-range Coulomb interaction is calculated efficiently with the fast multipole method. Results for temperature and charge distributions, residual stresses, bond lengths and bond angles, and diffusivities of Al and O will be presented. The oxidation of nanocrystalline Al is elucidated through immersive visualization in virtual environments. A unique dual-degree education program at Louisiana State University will also be discussed in which students can obtain a Ph.D. in Physics & Astronomy and a M.S. from the Department of Computer Science in five years. This program fosters interdisciplinary research activities for interfacing High Performance Computing and Communications with large-scale atomistic simulations of advanced materials. This work was supported by NSF (CAREER Program), ARO, PRF, and Louisiana LEQSF.

Bayer image parallel decoding based on GPU

NASA Astrophysics Data System (ADS)

Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua

2012-11-01

In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

NASA Astrophysics Data System (ADS)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and Diamantaras, K.: 'Programming and architecture of parallel processing systems', 1st Edition, Eds. Kleidarithmos, 2011 [4] NVIDIA.: 'NVidia CUDA C Programming Guide', version 5.0, NVidia (reference book) [5] Konstantaras, A.: 'Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc', IEEE Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6 (4), pp. 1857-1863, 2013 [6] Konstantaras, A. Varley, M.R.,. Valianatos, F., Collins, G. and Holifield, P.: 'Recognition of electric earthquake precursors using neuro-fuzzy models: methodology and simulation results', Proc. IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 2002, pp 303-308, 2002 [7] Konstantaras, A., Katsifarakis, E., Maravelakis, E., Skounakis, E., Kokkinos, E. and Karapidakis, E.: 'Intelligent Spatial-Clustering of Seismicity in the Vicinity of the Hellenic Seismic Arc', Earth Science Research, vol. 1 (2), pp. 1-10, 2012 [8] Georgoulas, G., Konstantaras, A., Katsifarakis, E., Stylios, C.D., Maravelakis, E. and Vachtsevanos, G.: '"Seismic-Mass" Density-based Algorithm for Spatio-Temporal Clustering', Expert Systems with Applications, vol. 40 (10), pp. 4183-4189, 2013 [9] Konstantaras, A. J.: 'Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters', Earth Science Informatics, 2015 (In Press, see: www.scopus.com) [10] Drakatos, G. and Latoussakis, J.: 'A catalog of aftershock sequences in Greece (1971-1997): Their spatial and temporal characteristics', Journal of Seismology, vol. 5, pp. 137-145, 2001

Flexible Language Constructs for Large Parallel Programs

DOE PAGES

Rosing, Matt; Schnabel, Robert

1994-01-01

The goal of the research described in this article is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (multiple instruction multiple data [MIMD]) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include single instruction multiple data (SIMD), single program multiple data (SPMD), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression ofmore » the variety of algorithms that occur in large scientific computations. In this article, we give an overview of a new language that combines many of these programming models in a clean manner. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. In this article, we give an overview of the language and discuss some of the critical implementation details.« less

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets.

PubMed

Shrimankar, D D; Sathe, S R

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today's supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures.

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets

PubMed Central

Shrimankar, D. D.; Sathe, S. R.

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today’s supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures. PMID:27932868

An interactive parallel programming environment applied in atmospheric science

NASA Technical Reports Server (NTRS)

vonLaszewski, G.

1996-01-01

This article introduces an interactive parallel programming environment (IPPE) that simplifies the generation and execution of parallel programs. One of the tasks of the environment is to generate message-passing parallel programs for homogeneous and heterogeneous computing platforms. The parallel programs are represented by using visual objects. This is accomplished with the help of a graphical programming editor that is implemented in Java and enables portability to a wide variety of computer platforms. In contrast to other graphical programming systems, reusable parts of the programs can be stored in a program library to support rapid prototyping. In addition, runtime performance data on different computing platforms is collected in a database. A selection process determines dynamically the software and the hardware platform to be used to solve the problem in minimal wall-clock time. The environment is currently being tested on a Grand Challenge problem, the NASA four-dimensional data assimilation system.

Support for Debugging Automatically Parallelized Programs

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

West Virginia US Department of Energy experimental program to stimulate competitive research. Section 2: Human resource development; Section 3: Carbon-based structural materials research cluster; Section 3: Data parallel algorithms for scientific computing

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

Not Available

1994-02-02

This report consists of three separate but related reports. They are (1) Human Resource Development, (2) Carbon-based Structural Materials Research Cluster, and (3) Data Parallel Algorithms for Scientific Computing. To meet the objectives of the Human Resource Development plan, the plan includes K--12 enrichment activities, undergraduate research opportunities for students at the state`s two Historically Black Colleges and Universities, graduate research through cluster assistantships and through a traineeship program targeted specifically to minorities, women and the disabled, and faculty development through participation in research clusters. One research cluster is the chemistry and physics of carbon-based materials. The objective of thismore » cluster is to develop a self-sustaining group of researchers in carbon-based materials research within the institutions of higher education in the state of West Virginia. The projects will involve analysis of cokes, graphites and other carbons in order to understand the properties that provide desirable structural characteristics including resistance to oxidation, levels of anisotropy and structural characteristics of the carbons themselves. In the proposed cluster on parallel algorithms, research by four WVU faculty and three state liberal arts college faculty are: (1) modeling of self-organized critical systems by cellular automata; (2) multiprefix algorithms and fat-free embeddings; (3) offline and online partitioning of data computation; and (4) manipulating and rendering three dimensional objects. This cluster furthers the state Experimental Program to Stimulate Competitive Research plan by building on existing strengths at WVU in parallel algorithms.« less

Finding Tropical Cyclones on a Cloud Computing Cluster: Using Parallel Virtualization for Large-Scale Climate Simulation Analysis

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

Hasenkamp, Daren; Sim, Alexander; Wehner, Michael

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, whilemore » 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.« less

Methodologies and Tools for Tuning Parallel Programs: 80% Art, 20% Science, and 10% Luck

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Bailey, David (Technical Monitor)

1996-01-01

The need for computing power has forced a migration from serial computation on a single processor to parallel processing on multiprocessors. However, without effective means to monitor (and analyze) program execution, tuning the performance of parallel programs becomes exponentially difficult as program complexity and machine size increase. In the past few years, the ubiquitous introduction of performance tuning tools from various supercomputer vendors (Intel's ParAide, TMC's PRISM, CRI's Apprentice, and Convex's CXtrace) seems to indicate the maturity of performance instrumentation/monitor/tuning technologies and vendors'/customers' recognition of their importance. However, a few important questions remain: What kind of performance bottlenecks can these tools detect (or correct)? How time consuming is the performance tuning process? What are some important technical issues that remain to be tackled in this area? This workshop reviews the fundamental concepts involved in analyzing and improving the performance of parallel and heterogeneous message-passing programs. Several alternative strategies will be contrasted, and for each we will describe how currently available tuning tools (e.g. AIMS, ParAide, PRISM, Apprentice, CXtrace, ATExpert, Pablo, IPS-2) can be used to facilitate the process. We will characterize the effectiveness of the tools and methodologies based on actual user experiences at NASA Ames Research Center. Finally, we will discuss their limitations and outline recent approaches taken by vendors and the research community to address them.

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

PubMed

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

2014-01-16

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

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

PubMed Central

2014-01-01

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

COMP Superscalar, an interoperable programming framework

NASA Astrophysics Data System (ADS)

Badia, Rosa M.; Conejero, Javier; Diaz, Carlos; Ejarque, Jorge; Lezzi, Daniele; Lordan, Francesc; Ramon-Cortes, Cristian; Sirvent, Raul

2015-12-01

COMPSs is a programming framework that aims to facilitate the parallelization of existing applications written in Java, C/C++ and Python scripts. For that purpose, it offers a simple programming model based on sequential development in which the user is mainly responsible for (i) identifying the functions to be executed as asynchronous parallel tasks and (ii) annotating them with annotations or standard Python decorators. A runtime system is in charge of exploiting the inherent concurrency of the code, automatically detecting and enforcing the data dependencies between tasks and spawning these tasks to the available resources, which can be nodes in a cluster, clouds or grids. In cloud environments, COMPSs provides scalability and elasticity features allowing the dynamic provision of resources.

Binary tree eigen solver in finite element analysis

NASA Technical Reports Server (NTRS)

Akl, F. A.; Janetzke, D. C.; Kiraly, L. J.

1993-01-01

This paper presents a transputer-based binary tree eigensolver for the solution of the generalized eigenproblem in linear elastic finite element analysis. The algorithm is based on the method of recursive doubling, which parallel implementation of a number of associative operations on an arbitrary set having N elements is of the order of o(log2N), compared to (N-1) steps if implemented sequentially. The hardware used in the implementation of the binary tree consists of 32 transputers. The algorithm is written in OCCAM which is a high-level language developed with the transputers to address parallel programming constructs and to provide the communications between processors. The algorithm can be replicated to match the size of the binary tree transputer network. Parallel and sequential finite element analysis programs have been developed to solve for the set of the least-order eigenpairs using the modified subspace method. The speed-up obtained for a typical analysis problem indicates close agreement with the theoretical prediction given by the method of recursive doubling.

Performance enhancement of various real-time image processing techniques via speculative execution

NASA Astrophysics Data System (ADS)

Younis, Mohamed F.; Sinha, Purnendu; Marlowe, Thomas J.; Stoyenko, Alexander D.

1996-03-01

In real-time image processing, an application must satisfy a set of timing constraints while ensuring the semantic correctness of the system. Because of the natural structure of digital data, pure data and task parallelism have been used extensively in real-time image processing to accelerate the handling time of image data. These types of parallelism are based on splitting the execution load performed by a single processor across multiple nodes. However, execution of all parallel threads is mandatory for correctness of the algorithm. On the other hand, speculative execution is an optimistic execution of part(s) of the program based on assumptions on program control flow or variable values. Rollback may be required if the assumptions turn out to be invalid. Speculative execution can enhance average, and sometimes worst-case, execution time. In this paper, we target various image processing techniques to investigate applicability of speculative execution. We identify opportunities for safe and profitable speculative execution in image compression, edge detection, morphological filters, and blob recognition.

Architecture Adaptive Computing Environment

NASA Technical Reports Server (NTRS)

Dorband, John E.

2006-01-01

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

Parallel 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.

Joint Services Electronics Program

DTIC Science & Technology

1991-03-05

Parallel Computing Network and Program Professor Abhiram Ranade with M.T. Raghunath and Robert Boothe The goal of our research is to develop high...References/Publications [1] M. T. Raghunath and A. 0. Ranade. "A Simulation-Based Comparison of Interconnection Networks," Proceedings of the 2nd IEEE

Beyond the Renderer: Software Architecture for Parallel Graphics and Visualization

NASA Technical Reports Server (NTRS)

Crockett, Thomas W.

1996-01-01

As numerous implementations have demonstrated, software-based parallel rendering is an effective way to obtain the needed computational power for a variety of challenging applications in computer graphics and scientific visualization. To fully realize their potential, however, parallel renderers need to be integrated into a complete environment for generating, manipulating, and delivering visual data. We examine the structure and components of such an environment, including the programming and user interfaces, rendering engines, and image delivery systems. We consider some of the constraints imposed by real-world applications and discuss the problems and issues involved in bringing parallel rendering out of the lab and into production.

Optimizing transformations of stencil operations for parallel cache-based architectures

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

Bassetti, F.; Davis, K.

This paper describes a new technique for optimizing serial and parallel stencil- and stencil-like operations for cache-based architectures. This technique takes advantage of the semantic knowledge implicity in stencil-like computations. The technique is implemented as a source-to-source program transformation; because of its specificity it could not be expected of a conventional compiler. Empirical results demonstrate a uniform factor of two speedup. The experiments clearly show the benefits of this technique to be a consequence, as intended, of the reduction in cache misses. The test codes are based on a 5-point stencil obtained by the discretization of the Poisson equation andmore » applied to a two-dimensional uniform grid using the Jacobi method as an iterative solver. Results are presented for a 1-D tiling for a single processor, and in parallel using 1-D data partition. For the parallel case both blocking and non-blocking communication are tested. The same scheme of experiments has bee n performed for the 2-D tiling case. However, for the parallel case the 2-D partitioning is not discussed here, so the parallel case handled for 2-D is 2-D tiling with 1-D data partitioning.« less

Implementing the PM Programming Language using MPI and OpenMP - a New Tool for Programming Geophysical Models on Parallel Systems

NASA Astrophysics Data System (ADS)

Bellerby, Tim

2015-04-01

PM (Parallel Models) is a new parallel programming language specifically designed for writing environmental and geophysical models. The language is intended to enable implementers to concentrate on the science behind the model rather than the details of running on parallel hardware. At the same time PM leaves the programmer in control - all parallelisation is explicit and the parallel structure of any given program may be deduced directly from the code. This paper describes a PM implementation based on the Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) standards, looking at issues involved with translating the PM parallelisation model to MPI/OpenMP protocols and considering performance in terms of the competing factors of finer-grained parallelisation and increased communication overhead. In order to maximise portability, the implementation stays within the MPI 1.3 standard as much as possible, with MPI-2 MPI-IO file handling the only significant exception. Moreover, it does not assume a thread-safe implementation of MPI. PM adopts a two-tier abstract representation of parallel hardware. A PM processor is a conceptual unit capable of efficiently executing a set of language tasks, with a complete parallel system consisting of an abstract N-dimensional array of such processors. PM processors may map to single cores executing tasks using cooperative multi-tasking, to multiple cores or even to separate processing nodes, efficiently sharing tasks using algorithms such as work stealing. While tasks may move between hardware elements within a PM processor, they may not move between processors without specific programmer intervention. Tasks are assigned to processors using a nested parallelism approach, building on ideas from Reyes et al. (2009). The main program owns all available processors. When the program enters a parallel statement then either processors are divided out among the newly generated tasks (number of new tasks < number of processors) or tasks are divided out among the available processors (number of tasks > number of processors). Nested parallel statements may further subdivide the processor set owned by a given task. Tasks or processors are distributed evenly by default, but uneven distributions are possible under programmer control. It is also possible to explicitly enable child tasks to migrate within the processor set owned by their parent task, reducing load unbalancing at the potential cost of increased inter-processor message traffic. PM incorporates some programming structures from the earlier MIST language presented at a previous EGU General Assembly, while adopting a significantly different underlying parallelisation model and type system. PM code is available at www.pm-lang.org under an unrestrictive MIT license. Reference Ruymán Reyes, Antonio J. Dorta, Francisco Almeida, Francisco de Sande, 2009. Automatic Hybrid MPI+OpenMP Code Generation with llc, Recent Advances in Parallel Virtual Machine and Message Passing Interface, Lecture Notes in Computer Science Volume 5759, 185-195

Using OpenMP vs. Threading Building Blocks for Medical Imaging on Multi-cores

NASA Astrophysics Data System (ADS)

Kegel, Philipp; Schellmann, Maraike; Gorlatch, Sergei

We compare two parallel programming approaches for multi-core systems: the well-known OpenMP and the recently introduced Threading Building Blocks (TBB) library by Intel®. The comparison is made using the parallelization of a real-world numerical algorithm for medical imaging. We develop several parallel implementations, and compare them w.r.t. programming effort, programming style and abstraction, and runtime performance. We show that TBB requires a considerable program re-design, whereas with OpenMP simple compiler directives are sufficient. While TBB appears to be less appropriate for parallelizing existing implementations, it fosters a good programming style and higher abstraction level for newly developed parallel programs. Our experimental measurements on a dual quad-core system demonstrate that OpenMP slightly outperforms TBB in our implementation.

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.

ng: What next-generation languages can teach us about HENP frameworks in the manycore era

NASA Astrophysics Data System (ADS)

Binet, Sébastien

2011-12-01

Current High Energy and Nuclear Physics (HENP) frameworks were written before multicore systems became widely deployed. A 'single-thread' execution model naturally emerged from that environment, however, this no longer fits into the processing model on the dawn of the manycore era. Although previous work focused on minimizing the changes to be applied to the LHC frameworks (because of the data taking phase) while still trying to reap the benefits of the parallel-enhanced CPU architectures, this paper explores what new languages could bring to the design of the next-generation frameworks. Parallel programming is still in an intensive phase of R&D and no silver bullet exists despite the 30+ years of literature on the subject. Yet, several parallel programming styles have emerged: actors, message passing, communicating sequential processes, task-based programming, data flow programming, ... to name a few. We present the work of the prototyping of a next-generation framework in new and expressive languages (python and Go) to investigate how code clarity and robustness are affected and what are the downsides of using languages younger than FORTRAN/C/C++.

DIALIGN P: fast pair-wise and multiple sequence alignment using parallel processors.

PubMed

Schmollinger, Martin; Nieselt, Kay; Kaufmann, Michael; Morgenstern, Burkhard

2004-09-09

Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics. Herein, a parallel version of the multi-alignment program DIALIGN is introduced. We propose two ways of dividing the program into independent sub-routines that can be run on different processors: (a) pair-wise sequence alignments that are used as a first step to multiple alignment account for most of the CPU time in DIALIGN. Since alignments of different sequence pairs are completely independent of each other, they can be distributed to multiple processors without any effect on the resulting output alignments. (b) For alignments of large genomic sequences, we use a heuristics by splitting up sequences into sub-sequences based on a previously introduced anchored alignment procedure. For our test sequences, this combined approach reduces the program running time of DIALIGN by up to 97%. By distributing sub-routines to multiple processors, the running time of DIALIGN can be crucially improved. With these improvements, it is possible to apply the program in large-scale genomics and proteomics projects that were previously beyond its scope.

MPI_XSTAR: MPI-based parallelization of XSTAR program

NASA Astrophysics Data System (ADS)

Danehkar, A.

2017-12-01

MPI_XSTAR parallelizes execution of multiple XSTAR runs using Message Passing Interface (MPI). XSTAR (ascl:9910.008), part of the HEASARC's HEAsoft (ascl:1408.004) package, calculates the physical conditions and emission spectra of ionized gases. MPI_XSTAR invokes XSTINITABLE from HEASoft to generate a job list of XSTAR commands for given physical parameters. The job list is used to make directories in ascending order, where each individual XSTAR is spawned on each processor and outputs are saved. HEASoft's XSTAR2TABLE program is invoked upon the contents of each directory in order to produce table model FITS files for spectroscopy analysis tools.

Adapting high-level language programs for parallel processing using data flow

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1988-01-01

EASY-FLOW, a very high-level data flow language, is introduced for the purpose of adapting programs written in a conventional high-level language to a parallel environment. The level of parallelism provided is of the large-grained variety in which parallel activities take place between subprograms or processes. A program written in EASY-FLOW is a set of subprogram calls as units, structured by iteration, branching, and distribution constructs. A data flow graph may be deduced from an EASY-FLOW program.

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

NASA Astrophysics Data System (ADS)

Qin, Cheng-Zhi; Zhan, Lijun

2012-06-01

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

Approximation algorithms for scheduling unrelated parallel machines with release dates

NASA Astrophysics Data System (ADS)

Avdeenko, T. V.; Mesentsev, Y. A.; Estraykh, I. V.

2017-01-01

In this paper we propose approaches to optimal scheduling of unrelated parallel machines with release dates. One approach is based on the scheme of dynamic programming modified with adaptive narrowing of search domain ensuring its computational effectiveness. We discussed complexity of the exact schedules synthesis and compared it with approximate, close to optimal, solutions. Also we explain how the algorithm works for the example of two unrelated parallel machines and five jobs with release dates. Performance results that show the efficiency of the proposed approach have been given.

Collectively loading programs in a multiple program multiple data environment

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

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

Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the programmore » needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.« less

ParallelStructure: A R Package to Distribute Parallel Runs of the Population Genetics Program STRUCTURE on Multi-Core Computers

PubMed Central

Besnier, Francois; Glover, Kevin A.

2013-01-01

This software package provides an R-based framework to make use of multi-core computers when running analyses in the population genetics program STRUCTURE. It is especially addressed to those users of STRUCTURE dealing with numerous and repeated data analyses, and who could take advantage of an efficient script to automatically distribute STRUCTURE jobs among multiple processors. It also consists of additional functions to divide analyses among combinations of populations within a single data set without the need to manually produce multiple projects, as it is currently the case in STRUCTURE. The package consists of two main functions: MPI_structure() and parallel_structure() as well as an example data file. We compared the performance in computing time for this example data on two computer architectures and showed that the use of the present functions can result in several-fold improvements in terms of computation time. ParallelStructure is freely available at https://r-forge.r-project.org/projects/parallstructure/. PMID:23923012

Performance of a parallel code for the Euler equations on hypercube computers

NASA Technical Reports Server (NTRS)

Barszcz, Eric; Chan, Tony F.; Jesperson, Dennis C.; Tuminaro, Raymond S.

1990-01-01

The performance of hypercubes were evaluated on a computational fluid dynamics problem and the parallel environment issues were considered that must be addressed, such as algorithm changes, implementation choices, programming effort, and programming environment. The evaluation focuses on a widely used fluid dynamics code, FLO52, which solves the two dimensional steady Euler equations describing flow around the airfoil. The code development experience is described, including interacting with the operating system, utilizing the message-passing communication system, and code modifications necessary to increase parallel efficiency. Results from two hypercube parallel computers (a 16-node iPSC/2, and a 512-node NCUBE/ten) are discussed and compared. In addition, a mathematical model of the execution time was developed as a function of several machine and algorithm parameters. This model accurately predicts the actual run times obtained and is used to explore the performance of the code in interesting but yet physically realizable regions of the parameter space. Based on this model, predictions about future hypercubes are made.

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.

High Performance Computing Based Parallel HIearchical Modal Association Clustering (HPAR HMAC)

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

Patlolla, Dilip R; Surendran Nair, Sujithkumar; Graves, Daniel A.

For many applications, clustering is a crucial step in order to gain insight into the makeup of a dataset. The best approach to a given problem often depends on a variety of factors, such as the size of the dataset, time restrictions, and soft clustering requirements. The HMAC algorithm seeks to combine the strengths of 2 particular clustering approaches: model-based and linkage-based clustering. One particular weakness of HMAC is its computational complexity. HMAC is not practical for mega-scale data clustering. For high-definition imagery, a user would have to wait months or years for a result; for a 16-megapixel image, themore » estimated runtime skyrockets to over a decade! To improve the execution time of HMAC, it is reasonable to consider an multi-core implementation that utilizes available system resources. An existing imple-mentation (Ray and Cheng 2014) divides the dataset into N partitions - one for each thread prior to executing the HMAC algorithm. This implementation benefits from 2 types of optimization: parallelization and divide-and-conquer. By running each partition in parallel, the program is able to accelerate computation by utilizing more system resources. Although the parallel implementation provides considerable improvement over the serial HMAC, it still suffers from poor computational complexity, O(N2). Once the maximum number of cores on a system is exhausted, the program exhibits slower behavior. We now consider a modification to HMAC that involves a recursive partitioning scheme. Our modification aims to exploit divide-and-conquer benefits seen by the parallel HMAC implementation. At each level in the recursion tree, partitions are divided into 2 sub-partitions until a threshold size is reached. When the partition can no longer be divided without falling below threshold size, the base HMAC algorithm is applied. This results in a significant speedup over the parallel HMAC.« less

Parallel evolutionary computation in bioinformatics applications.

PubMed

Pinho, Jorge; Sobral, João Luis; Rocha, Miguel

2013-05-01

A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

IOPA: I/O-aware parallelism adaption for parallel programs

PubMed Central

Liu, Tao; Liu, Yi; Qian, Chen; Qian, Depei

2017-01-01

With the development of multi-/many-core processors, applications need to be written as parallel programs to improve execution efficiency. For data-intensive applications that use multiple threads to read/write files simultaneously, an I/O sub-system can easily become a bottleneck when too many of these types of threads exist; on the contrary, too few threads will cause insufficient resource utilization and hurt performance. Therefore, programmers must pay much attention to parallelism control to find the appropriate number of I/O threads for an application. This paper proposes a parallelism control mechanism named IOPA that can adjust the parallelism of applications to adapt to the I/O capability of a system and balance computing resources and I/O bandwidth. The programming interface of IOPA is also provided to programmers to simplify parallel programming. IOPA is evaluated using multiple applications with both solid state and hard disk drives. The results show that the parallel applications using IOPA can achieve higher efficiency than those with a fixed number of threads. PMID:28278236

IOPA: I/O-aware parallelism adaption for parallel programs.

PubMed

Liu, Tao; Liu, Yi; Qian, Chen; Qian, Depei

2017-01-01

With the development of multi-/many-core processors, applications need to be written as parallel programs to improve execution efficiency. For data-intensive applications that use multiple threads to read/write files simultaneously, an I/O sub-system can easily become a bottleneck when too many of these types of threads exist; on the contrary, too few threads will cause insufficient resource utilization and hurt performance. Therefore, programmers must pay much attention to parallelism control to find the appropriate number of I/O threads for an application. This paper proposes a parallelism control mechanism named IOPA that can adjust the parallelism of applications to adapt to the I/O capability of a system and balance computing resources and I/O bandwidth. The programming interface of IOPA is also provided to programmers to simplify parallel programming. IOPA is evaluated using multiple applications with both solid state and hard disk drives. The results show that the parallel applications using IOPA can achieve higher efficiency than those with a fixed number of threads.

Parallelized seeded region growing using CUDA.

PubMed

Park, Seongjin; Lee, Jeongjin; Lee, Hyunna; Shin, Juneseuk; Seo, Jinwook; Lee, Kyoung Ho; Shin, Yeong-Gil; Kim, Bohyoung

2014-01-01

This paper presents a novel method for parallelizing the seeded region growing (SRG) algorithm using Compute Unified Device Architecture (CUDA) technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests.

An Element-Based Concurrent Partitioner for Unstructured Finite Element Meshes

NASA Technical Reports Server (NTRS)

Ding, Hong Q.; Ferraro, Robert D.

1996-01-01

A concurrent partitioner for partitioning unstructured finite element meshes on distributed memory architectures is developed. The partitioner uses an element-based partitioning strategy. Its main advantage over the more conventional node-based partitioning strategy is its modular programming approach to the development of parallel applications. The partitioner first partitions element centroids using a recursive inertial bisection algorithm. Elements and nodes then migrate according to the partitioned centroids, using a data request communication template for unpredictable incoming messages. Our scalable implementation is contrasted to a non-scalable implementation which is a straightforward parallelization of a sequential partitioner.

Performance Metrics for Monitoring Parallel Program Executions

NASA Technical Reports Server (NTRS)

Sarukkai, Sekkar R.; Gotwais, Jacob K.; Yan, Jerry; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

Existing tools for debugging performance of parallel programs either provide graphical representations of program execution or profiles of program executions. However, for performance debugging tools to be useful, such information has to be augmented with information that highlights the cause of poor program performance. Identifying the cause of poor performance necessitates the need for not only determining the significance of various performance problems on the execution time of the program, but also needs to consider the effect of interprocessor communications of individual source level data structures. In this paper, we present a suite of normalized indices which provide a convenient mechanism for focusing on a region of code with poor performance and highlights the cause of the problem in terms of processors, procedures and data structure interactions. All the indices are generated from trace files augmented with data structure information.. Further, we show with the help of examples from the NAS benchmark suite that the indices help in detecting potential cause of poor performance, based on augmented execution traces obtained by monitoring the program.

Terrace Layout Using a Computer Assisted System

USDA-ARS?s Scientific Manuscript database

Development of a web-based terrace design tool based on the MOTERR program is presented, along with representative layouts for conventional and parallel terrace systems. Using digital elevation maps and geographic information systems (GIS), this tool utilizes personal computers to rapidly construct ...

Parallel language constructs for tensor product computations on loosely coupled architectures

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Vanrosendale, John

1989-01-01

Distributed memory architectures offer high levels of performance and flexibility, but have proven awkard to program. Current languages for nonshared memory architectures provide a relatively low level programming environment, and are poorly suited to modular programming, and to the construction of libraries. A set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level is described. Tensor product array computations are focused on along with a simple but important class of numerical algorithms. The problem of programming 1-D kernal routines is focused on first, such as parallel tridiagonal solvers, and then how such parallel kernels can be combined to form parallel tensor product algorithms is examined.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

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

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation

PubMed Central

Su, Huayou; Wen, Mei; Wu, Nan; Ren, Ju; Zhang, Chunyuan

2014-01-01

Through reorganizing the execution order and optimizing the data structure, we proposed an efficient parallel framework for H.264/AVC encoder based on massively parallel architecture. We implemented the proposed framework by CUDA on NVIDIA's GPU. Not only the compute intensive components of the H.264 encoder are parallelized but also the control intensive components are realized effectively, such as CAVLC and deblocking filter. In addition, we proposed serial optimization methods, including the multiresolution multiwindow for motion estimation, multilevel parallel strategy to enhance the parallelism of intracoding as much as possible, component-based parallel CAVLC, and direction-priority deblocking filter. More than 96% of workload of H.264 encoder is offloaded to GPU. Experimental results show that the parallel implementation outperforms the serial program by 20 times of speedup ratio and satisfies the requirement of the real-time HD encoding of 30 fps. The loss of PSNR is from 0.14 dB to 0.77 dB, when keeping the same bitrate. Through the analysis to the kernels, we found that speedup ratios of the compute intensive algorithms are proportional with the computation power of the GPU. However, the performance of the control intensive parts (CAVLC) is much related to the memory bandwidth, which gives an insight for new architecture design. PMID:24757432

Parallelization of MRCI based on hole-particle symmetry.

PubMed

Suo, Bing; Zhai, Gaohong; Wang, Yubin; Wen, Zhenyi; Hu, Xiangqian; Li, Lemin

2005-01-15

The parallel implementation of multireference configuration interaction program based on the hole-particle symmetry is described. The platform to implement the parallelization is an Intel-Architectural cluster consisting of 12 nodes, each of which is equipped with two 2.4-G XEON processors, 3-GB memory, and 36-GB disk, and are connected by a Gigabit Ethernet Switch. The dependence of speedup on molecular symmetries and task granularities is discussed. Test calculations show that the scaling with the number of nodes is about 1.9 (for C1 and Cs), 1.65 (for C2v), and 1.55 (for D2h) when the number of nodes is doubled. The largest calculation performed on this cluster involves 5.6 x 10(8) CSFs.

Shared Memory Parallelization of an Implicit ADI-type CFD Code

NASA Technical Reports Server (NTRS)

Hauser, Th.; Huang, P. G.

1999-01-01

A parallelization study designed for ADI-type algorithms is presented using the OpenMP specification for shared-memory multiprocessor programming. Details of optimizations specifically addressed to cache-based computer architectures are described and performance measurements for the single and multiprocessor implementation are summarized. The paper demonstrates that optimization of memory access on a cache-based computer architecture controls the performance of the computational algorithm. A hybrid MPI/OpenMP approach is proposed for clusters of shared memory machines to further enhance the parallel performance. The method is applied to develop a new LES/DNS code, named LESTool. A preliminary DNS calculation of a fully developed channel flow at a Reynolds number of 180, Re(sub tau) = 180, has shown good agreement with existing data.

Computer-aided programming for message-passing system; Problems and a solution

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

Wu, M.Y.; Gajski, D.D.

1989-12-01

As the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. Parallel models of computation, parallelization problems, and tools for computer-aided programming (CAP) are discussed. As an example, a CAP tool that performs scheduling and inserts communication primitives automatically is described. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs.

Algorithms for the Construction of Parallel Tests by Zero-One Programming. Project Psychometric Aspects of Item Banking No. 7. Research Report 86-7.

ERIC Educational Resources Information Center

Boekkooi-Timminga, Ellen

Nine methods for automated test construction are described. All are based on the concepts of information from item response theory. Two general kinds of methods for the construction of parallel tests are presented: (1) sequential test design; and (2) simultaneous test design. Sequential design implies that the tests are constructed one after the…

Parallel implementation of an adaptive and parameter-free N-body integrator

NASA Astrophysics Data System (ADS)

Pruett, C. David; Ingham, William H.; Herman, Ralph D.

2011-05-01

Previously, Pruett et al. (2003) [3] described an N-body integrator of arbitrarily high order M with an asymptotic operation count of O(MN). The algorithm's structure lends itself readily to data parallelization, which we document and demonstrate here in the integration of point-mass systems subject to Newtonian gravitation. High order is shown to benefit parallel efficiency. The resulting N-body integrator is robust, parameter-free, highly accurate, and adaptive in both time-step and order. Moreover, it exhibits linear speedup on distributed parallel processors, provided that each processor is assigned at least a handful of bodies. Program summaryProgram title: PNB.f90 Catalogue identifier: AEIK_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIK_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3052 No. of bytes in distributed program, including test data, etc.: 68 600 Distribution format: tar.gz Programming language: Fortran 90 and OpenMPI Computer: All shared or distributed memory parallel processors Operating system: Unix/Linux Has the code been vectorized or parallelized?: The code has been parallelized but has not been explicitly vectorized. RAM: Dependent upon N Classification: 4.3, 4.12, 6.5 Nature of problem: High accuracy numerical evaluation of trajectories of N point masses each subject to Newtonian gravitation. Solution method: Parallel and adaptive extrapolation in time via power series of arbitrary degree. Running time: 5.1 s for the demo program supplied with the package.

Parallel solution of sparse one-dimensional dynamic programming problems

NASA Technical Reports Server (NTRS)

Nicol, David M.

1989-01-01

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

Performance of the Heavy Flavor Tracker (HFT) detector in star experiment at RHIC

NASA Astrophysics Data System (ADS)

Alruwaili, Manal

With the growing technology, the number of the processors is becoming massive. Current supercomputer processing will be available on desktops in the next decade. For mass scale application software development on massive parallel computing available on desktops, existing popular languages with large libraries have to be augmented with new constructs and paradigms that exploit massive parallel computing and distributed memory models while retaining the user-friendliness. Currently, available object oriented languages for massive parallel computing such as Chapel, X10 and UPC++ exploit distributed computing, data parallel computing and thread-parallelism at the process level in the PGAS (Partitioned Global Address Space) memory model. However, they do not incorporate: 1) any extension at for object distribution to exploit PGAS model; 2) the programs lack the flexibility of migrating or cloning an object between places to exploit load balancing; and 3) lack the programming paradigms that will result from the integration of data and thread-level parallelism and object distribution. In the proposed thesis, I compare different languages in PGAS model; propose new constructs that extend C++ with object distribution and object migration; and integrate PGAS based process constructs with these extensions on distributed objects. Object cloning and object migration. Also a new paradigm MIDD (Multiple Invocation Distributed Data) is presented when different copies of the same class can be invoked, and work on different elements of a distributed data concurrently using remote method invocations. I present new constructs, their grammar and their behavior. The new constructs have been explained using simple programs utilizing these constructs.

76 FR 66309 - Pilot Program for Parallel Review of Medical Products; Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-26

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Medicare and Medicaid Services [CMS-3180-N2] Food and Drug Administration [Docket No. FDA-2010-N-0308] Pilot Program for Parallel Review of Medical... technologies to participate in a program of parallel FDA-CMS review. The document was published with an...

Kranc: a Mathematica package to generate numerical codes for tensorial evolution equations

NASA Astrophysics Data System (ADS)

Husa, Sascha; Hinder, Ian; Lechner, Christiane

2006-06-01

We present a suite of Mathematica-based computer-algebra packages, termed "Kranc", which comprise a toolbox to convert certain (tensorial) systems of partial differential evolution equations to parallelized C or Fortran code for solving initial boundary value problems. Kranc can be used as a "rapid prototyping" system for physicists or mathematicians handling very complicated systems of partial differential equations, but through integration into the Cactus computational toolkit we can also produce efficient parallelized production codes. Our work is motivated by the field of numerical relativity, where Kranc is used as a research tool by the authors. In this paper we describe the design and implementation of both the Mathematica packages and the resulting code, we discuss some example applications, and provide results on the performance of an example numerical code for the Einstein equations. Program summaryTitle of program: Kranc Catalogue identifier: ADXS_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXS_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computer for which the program is designed and others on which it has been tested: General computers which run Mathematica (for code generation) and Cactus (for numerical simulations), tested under Linux Programming language used: Mathematica, C, Fortran 90 Memory required to execute with typical data: This depends on the number of variables and gridsize, the included ADM example requires 4308 KB Has the code been vectorized or parallelized: The code is parallelized based on the Cactus framework. Number of bytes in distributed program, including test data, etc.: 1 578 142 Number of lines in distributed program, including test data, etc.: 11 711 Nature of physical problem: Solution of partial differential equations in three space dimensions, which are formulated as an initial value problem. In particular, the program is geared towards handling very complex tensorial equations as they appear, e.g., in numerical relativity. The worked out examples comprise the Klein-Gordon equations, the Maxwell equations, and the ADM formulation of the Einstein equations. Method of solution: The method of numerical solution is finite differencing and method of lines time integration, the numerical code is generated through a high level Mathematica interface. Restrictions on the complexity of the program: Typical numerical relativity applications will contain up to several dozen evolution variables and thousands of source terms, Cactus applications have shown scaling up to several thousand processors and grid sizes exceeding 500 3. Typical running time: This depends on the number of variables and the grid size: the included ADM example takes approximately 100 seconds on a 1600 MHz Intel Pentium M processor. Unusual features of the program: based on Mathematica and Cactus

Parallel computing works

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

Not Available

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

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

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Owen, Jeffrey E.

1988-01-01

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

HeNCE: A Heterogeneous Network Computing Environment

DOE PAGES

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

1994-01-01

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

The AIS-5000 parallel processor

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

Schmitt, L.A.; Wilson, S.S.

1988-05-01

The AIS-5000 is a commercially available massively parallel processor which has been designed to operate in an industrial environment. It has fine-grained parallelism with up to 1024 processing elements arranged in a single-instruction multiple-data (SIMD) architecture. The processing elements are arranged in a one-dimensional chain that, for computer vision applications, can be as wide as the image itself. This architecture has superior cost/performance characteristics than two-dimensional mesh-connected systems. The design of the processing elements and their interconnections as well as the software used to program the system allow a wide variety of algorithms and applications to be implemented. In thismore » paper, the overall architecture of the system is described. Various components of the system are discussed, including details of the processing elements, data I/O pathways and parallel memory organization. A virtual two-dimensional model for programming image-based algorithms for the system is presented. This model is supported by the AIS-5000 hardware and software and allows the system to be treated as a full-image-size, two-dimensional, mesh-connected parallel processor. Performance bench marks are given for certain simple and complex functions.« less

Massively parallel implementation of 3D-RISM calculation with volumetric 3D-FFT.

PubMed

Maruyama, Yutaka; Yoshida, Norio; Tadano, Hiroto; Takahashi, Daisuke; Sato, Mitsuhisa; Hirata, Fumio

2014-07-05

A new three-dimensional reference interaction site model (3D-RISM) program for massively parallel machines combined with the volumetric 3D fast Fourier transform (3D-FFT) was developed, and tested on the RIKEN K supercomputer. The ordinary parallel 3D-RISM program has a limitation on the number of parallelizations because of the limitations of the slab-type 3D-FFT. The volumetric 3D-FFT relieves this limitation drastically. We tested the 3D-RISM calculation on the large and fine calculation cell (2048(3) grid points) on 16,384 nodes, each having eight CPU cores. The new 3D-RISM program achieved excellent scalability to the parallelization, running on the RIKEN K supercomputer. As a benchmark application, we employed the program, combined with molecular dynamics simulation, to analyze the oligomerization process of chymotrypsin Inhibitor 2 mutant. The results demonstrate that the massive parallel 3D-RISM program is effective to analyze the hydration properties of the large biomolecular systems. Copyright © 2014 Wiley Periodicals, Inc.

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

NASA Astrophysics Data System (ADS)

Sylwestrzak, Marcin; Szlag, Daniel; Marchand, Paul J.; Kumar, Ashwin S.; Lasser, Theo

2017-08-01

We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for many applications based on SOCM. In view of this difficulty, we implemented and adapted quantitative total flow estimation algorithms on graphics processing units (GPU) and achieved a 150 fold reduction in processing time when compared to a former CPU implementation. As SOCM constitutes the microscopy counterpart to spectral optical coherence tomography (SOCT), the developed processing procedure can be applied to both imaging modalities. We present the developed DLL library integrated in MATLAB (with an example) and have included the source code for adaptations and future improvements. Catalogue identifier: AFBT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPLv3 No. of lines in distributed program, including test data, etc.: 913552 No. of bytes in distributed program, including test data, etc.: 270876249 Distribution format: tar.gz Programming language: CUDA/C, MATLAB. Computer: Intel x64 CPU, GPU supporting CUDA technology. Operating system: 64-bit Windows 7 Professional. Has the code been vectorized or parallelized?: Yes, CPU code has been vectorized in MATLAB, CUDA code has been parallelized. RAM: Dependent on users parameters, typically between several gigabytes and several tens of gigabytes Classification: 6.5, 18. Nature of problem: Speed up of data processing in optical coherence microscopy Solution method: Utilization of GPU for massively parallel data processing Additional comments: Compiled DLL library with source code and documentation, example of utilization (MATLAB script with raw data) Running time: 1,8 s for one B-scan (150 × faster in comparison to the CPU data processing time)

NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations

NASA Astrophysics Data System (ADS)

Valiev, M.; Bylaska, E. J.; Govind, N.; Kowalski, K.; Straatsma, T. P.; Van Dam, H. J. J.; Wang, D.; Nieplocha, J.; Apra, E.; Windus, T. L.; de Jong, W. A.

2010-09-01

The latest release of NWChem delivers an open-source computational chemistry package with extensive capabilities for large scale simulations of chemical and biological systems. Utilizing a common computational framework, diverse theoretical descriptions can be used to provide the best solution for a given scientific problem. Scalable parallel implementations and modular software design enable efficient utilization of current computational architectures. This paper provides an overview of NWChem focusing primarily on the core theoretical modules provided by the code and their parallel performance. Program summaryProgram title: NWChem Catalogue identifier: AEGI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGI_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Open Source Educational Community License No. of lines in distributed program, including test data, etc.: 11 709 543 No. of bytes in distributed program, including test data, etc.: 680 696 106 Distribution format: tar.gz Programming language: Fortran 77, C Computer: all Linux based workstations and parallel supercomputers, Windows and Apple machines Operating system: Linux, OS X, Windows Has the code been vectorised or parallelized?: Code is parallelized Classification: 2.1, 2.2, 3, 7.3, 7.7, 16.1, 16.2, 16.3, 16.10, 16.13 Nature of problem: Large-scale atomistic simulations of chemical and biological systems require efficient and reliable methods for ground and excited solutions of many-electron Hamiltonian, analysis of the potential energy surface, and dynamics. Solution method: Ground and excited solutions of many-electron Hamiltonian are obtained utilizing density-functional theory, many-body perturbation approach, and coupled cluster expansion. These solutions or a combination thereof with classical descriptions are then used to analyze potential energy surface and perform dynamical simulations. Additional comments: Full documentation is provided in the distribution file. This includes an INSTALL file giving details of how to build the package. A set of test runs is provided in the examples directory. The distribution file for this program is over 90 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. Running time: Running time depends on the size of the chemical system, complexity of the method, number of cpu's and the computational task. It ranges from several seconds for serial DFT energy calculations on a few atoms to several hours for parallel coupled cluster energy calculations on tens of atoms or ab-initio molecular dynamics simulation on hundreds of atoms.

Portable parallel portfolio optimization in the Aurora Financial Management System

NASA Astrophysics Data System (ADS)

Laure, Erwin; Moritsch, Hans

2001-07-01

Financial planning problems are formulated as large scale, stochastic, multiperiod, tree structured optimization problems. An efficient technique for solving this kind of problems is the nested Benders decomposition method. In this paper we present a parallel, portable, asynchronous implementation of this technique. To achieve our portability goals we elected the programming language Java for our implementation and used a high level Java based framework, called OpusJava, for expressing the parallelism potential as well as synchronization constraints. Our implementation is embedded within a modular decision support tool for portfolio and asset liability management, the Aurora Financial Management System.

Implementations of BLAST for parallel computers.

PubMed

Jülich, A

1995-02-01

The BLAST sequence comparison programs have been ported to a variety of parallel computers-the shared memory machine Cray Y-MP 8/864 and the distributed memory architectures Intel iPSC/860 and nCUBE. Additionally, the programs were ported to run on workstation clusters. We explain the parallelization techniques and consider the pros and cons of these methods. The BLAST programs are very well suited for parallelization for a moderate number of processors. We illustrate our results using the program blastp as an example. As input data for blastp, a 799 residue protein query sequence and the protein database PIR were used.

Programming parallel architectures: The BLAZE family of languages

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush

1988-01-01

Programming multiprocessor architectures is a critical research issue. An overview is given of the various approaches to programming these architectures that are currently being explored. It is argued that two of these approaches, interactive programming environments and functional parallel languages, are particularly attractive since they remove much of the burden of exploiting parallel architectures from the user. Also described is recent work by the author in the design of parallel languages. Research on languages for both shared and nonshared memory multiprocessors is described, as well as the relations of this work to other current language research projects.

Static analysis techniques for semiautomatic synthesis of message passing software skeletons

DOE PAGES

Sottile, Matthew; Dagit, Jason; Zhang, Deli; ...

2015-06-29

The design of high-performance computing architectures demands performance analysis of large-scale parallel applications to derive various parameters concerning hardware design and software development. The process of performance analysis and benchmarking an application can be done in several ways with varying degrees of fidelity. One of the most cost-effective ways is to do a coarse-grained study of large-scale parallel applications through the use of program skeletons. The concept of a “program skeleton” that we discuss in this article is an abstracted program that is derived from a larger program where source code that is determined to be irrelevant is removed formore » the purposes of the skeleton. In this work, we develop a semiautomatic approach for extracting program skeletons based on compiler program analysis. Finally, we demonstrate correctness of our skeleton extraction process by comparing details from communication traces, as well as show the performance speedup of using skeletons by running simulations in the SST/macro simulator.« less

A DNA-based semantic fusion model for remote sensing data.

PubMed

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

A DNA-Based Semantic Fusion Model for Remote Sensing Data

PubMed Central

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H.

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology. PMID:24116207

High-performance computing — an overview

NASA Astrophysics Data System (ADS)

Marksteiner, Peter

1996-08-01

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

Programming model for distributed intelligent systems

NASA Technical Reports Server (NTRS)

Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

1988-01-01

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

DataForge: Modular platform for data storage and analysis

NASA Astrophysics Data System (ADS)

Nozik, Alexander

2018-04-01

DataForge is a framework for automated data acquisition, storage and analysis based on modern achievements of applied programming. The aim of the DataForge is to automate some standard tasks like parallel data processing, logging, output sorting and distributed computing. Also the framework extensively uses declarative programming principles via meta-data concept which allows a certain degree of meta-programming and improves results reproducibility.

RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

PubMed

Stamatakis, Alexandros

2006-11-01

RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak

Real-time implementations of image segmentation algorithms on shared memory multicore architecture: a survey (Conference Presentation)

NASA Astrophysics Data System (ADS)

Akil, Mohamed

2017-05-01

The real-time processing is getting more and more important in many image processing applications. Image segmentation is one of the most fundamental tasks image analysis. As a consequence, many different approaches for image segmentation have been proposed. The watershed transform is a well-known image segmentation tool. The watershed transform is a very data intensive task. To achieve acceleration and obtain real-time processing of watershed algorithms, parallel architectures and programming models for multicore computing have been developed. This paper focuses on the survey of the approaches for parallel implementation of sequential watershed algorithms on multicore general purpose CPUs: homogeneous multicore processor with shared memory. To achieve an efficient parallel implementation, it's necessary to explore different strategies (parallelization/distribution/distributed scheduling) combined with different acceleration and optimization techniques to enhance parallelism. In this paper, we give a comparison of various parallelization of sequential watershed algorithms on shared memory multicore architecture. We analyze the performance measurements of each parallel implementation and the impact of the different sources of overhead on the performance of the parallel implementations. In this comparison study, we also discuss the advantages and disadvantages of the parallel programming models. Thus, we compare the OpenMP (an application programming interface for multi-Processing) with Ptheads (POSIX Threads) to illustrate the impact of each parallel programming model on the performance of the parallel implementations.

A real time microcomputer implementation of sensor failure detection for turbofan engines

NASA Technical Reports Server (NTRS)

Delaat, John C.; Merrill, Walter C.

1989-01-01

An algorithm was developed which detects, isolates, and accommodates sensor failures using analytical redundancy. The performance of this algorithm was demonstrated on a full-scale F100 turbofan engine. The algorithm was implemented in real-time on a microprocessor-based controls computer which includes parallel processing and high order language programming. Parallel processing was used to achieve the required computational power for the real-time implementation. High order language programming was used in order to reduce the programming and maintenance costs of the algorithm implementation software. The sensor failure algorithm was combined with an existing multivariable control algorithm to give a complete control implementation with sensor analytical redundancy. The real-time microprocessor implementation of the algorithm which resulted in the successful completion of the algorithm engine demonstration, is described.

The GPU implementation of micro - Doppler period estimation

NASA Astrophysics Data System (ADS)

Yang, Liyuan; Wang, Junling; Bi, Ran

2018-03-01

Aiming at the problem that the computational complexity and the deficiency of real-time of the wideband radar echo signal, a program is designed to improve the performance of real-time extraction of micro-motion feature in this paper based on the CPU-GPU heterogeneous parallel structure. Firstly, we discuss the principle of the micro-Doppler effect generated by the rolling of the scattering points on the orbiting satellite, analyses how to use Kalman filter to compensate the translational motion of tumbling satellite and how to use the joint time-frequency analysis and inverse Radon transform to extract the micro-motion features from the echo after compensation. Secondly, the advantages of GPU in terms of real-time processing and the working principle of CPU-GPU heterogeneous parallelism are analysed, and a program flow based on GPU to extract the micro-motion feature from the radar echo signal of rolling satellite is designed. At the end of the article the results of extraction are given to verify the correctness of the program and algorithm.

DOE SBIR Phase-1 Report on Hybrid CPU-GPU Parallel Development of the Eulerian-Lagrangian Barracuda Multiphase Program

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

Dr. Dale M. Snider

2011-02-28

This report gives the result from the Phase-1 work on demonstrating greater than 10x speedup of the Barracuda computer program using parallel methods and GPU processors (General-Purpose Graphics Processing Unit or Graphics Processing Unit). Phase-1 demonstrated a 12x speedup on a typical Barracuda function using the GPU processor. The problem test case used about 5 million particles and 250,000 Eulerian grid cells. The relative speedup, compared to a single CPU, increases with increased number of particles giving greater than 12x speedup. Phase-1 work provided a path for reformatting data structure modifications to give good parallel performance while keeping a friendlymore » environment for new physics development and code maintenance. The implementation of data structure changes will be in Phase-2. Phase-1 laid the ground work for the complete parallelization of Barracuda in Phase-2, with the caveat that implemented computer practices for parallel programming done in Phase-1 gives immediate speedup in the current Barracuda serial running code. The Phase-1 tasks were completed successfully laying the frame work for Phase-2. The detailed results of Phase-1 are within this document. In general, the speedup of one function would be expected to be higher than the speedup of the entire code because of I/O functions and communication between the algorithms. However, because one of the most difficult Barracuda algorithms was parallelized in Phase-1 and because advanced parallelization methods and proposed parallelization optimization techniques identified in Phase-1 will be used in Phase-2, an overall Barracuda code speedup (relative to a single CPU) is expected to be greater than 10x. This means that a job which takes 30 days to complete will be done in 3 days. Tasks completed in Phase-1 are: Task 1: Profile the entire Barracuda code and select which subroutines are to be parallelized (See Section Choosing a Function to Accelerate) Task 2: Select a GPU consultant company and jointly parallelize subroutines (CPFD chose the small business EMPhotonics for the Phase-1 the technical partner. See Section Technical Objective and Approach) Task 3: Integrate parallel subroutines into Barracuda (See Section Results from Phase-1 and its subsections) Task 4: Testing, refinement, and optimization of parallel methodology (See Section Results from Phase-1 and Section Result Comparison Program) Task 5: Integrate Phase-1 parallel subroutines into Barracuda and release (See Section Results from Phase-1 and its subsections) Task 6: Roadmap of Phase-2 (See Section Plan for Phase-2) With the completion of Phase 1 we have the base understanding to completely parallelize Barracuda. An overview of the work to move Barracuda to a parallelized code is given in Plan for Phase-2.« less

Python based high-level synthesis compiler

NASA Astrophysics Data System (ADS)

Cieszewski, Radosław; Pozniak, Krzysztof; Romaniuk, Ryszard

2014-11-01

This paper presents a python based High-Level synthesis (HLS) compiler. The compiler interprets an algorithmic description of a desired behavior written in Python and map it to VHDL. FPGA combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be reconfigured 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 article describes design, implementation and first results of created Python based compiler.

Parallelized Seeded Region Growing Using CUDA

PubMed Central

Park, Seongjin; Lee, Hyunna; Seo, Jinwook; Lee, Kyoung Ho; Shin, Yeong-Gil; Kim, Bohyoung

2014-01-01

This paper presents a novel method for parallelizing the seeded region growing (SRG) algorithm using Compute Unified Device Architecture (CUDA) technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests. PMID:25309619

Graphics processing unit based computation for NDE applications

NASA Astrophysics Data System (ADS)

Nahas, C. A.; Rajagopal, Prabhu; Balasubramaniam, Krishnan; Krishnamurthy, C. V.

2012-05-01

Advances in parallel processing in recent years are helping to improve the cost of numerical simulation. Breakthroughs in Graphical Processing Unit (GPU) based computation now offer the prospect of further drastic improvements. The introduction of 'compute unified device architecture' (CUDA) by NVIDIA (the global technology company based in Santa Clara, California, USA) has made programming GPUs for general purpose computing accessible to the average programmer. Here we use CUDA to develop parallel finite difference schemes as applicable to two problems of interest to NDE community, namely heat diffusion and elastic wave propagation. The implementations are for two-dimensions. Performance improvement of the GPU implementation against serial CPU implementation is then discussed.

Myria: Scalable Analytics as a Service

NASA Astrophysics Data System (ADS)

Howe, B.; Halperin, D.; Whitaker, A.

2014-12-01

At the UW eScience Institute, we're working to empower non-experts, especially in the sciences, to write and use data-parallel algorithms. To this end, we are building Myria, a web-based platform for scalable analytics and data-parallel programming. Myria's internal model of computation is the relational algebra extended with iteration, such that every program is inherently data-parallel, just as every query in a database is inherently data-parallel. But unlike databases, iteration is a first class concept, allowing us to express machine learning tasks, graph traversal tasks, and more. Programs can be expressed in a number of languages and can be executed on a number of execution environments, but we emphasize a particular language called MyriaL that supports both imperative and declarative styles and a particular execution engine called MyriaX that uses an in-memory column-oriented representation and asynchronous iteration. We deliver Myria over the web as a service, providing an editor, performance analysis tools, and catalog browsing features in a single environment. We find that this web-based "delivery vector" is critical in reaching non-experts: they are insulated from irrelevant effort technical work associated with installation, configuration, and resource management. The MyriaX backend, one of several execution runtimes we support, is a main-memory, column-oriented, RDBMS-on-the-worker system that supports cyclic data flows as a first-class citizen and has been shown to outperform competitive systems on 100-machine cluster sizes. I will describe the Myria system, give a demo, and present some new results in large-scale oceanographic microbiology.

Parallel programming of industrial applications

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

Heroux, M; Koniges, A; Simon, H

1998-07-21

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

HADY-I, a FORTRAN program for the compressible stability analysis of three-dimensional boundary layers. [on swept and tapered wings

NASA Technical Reports Server (NTRS)

El-Hady, N. M.

1981-01-01

A computer program HADY-I for calculating the linear incompressible or compressible stability characteristics of the laminar boundary layer on swept and tapered wings is described. The eigenvalue problem and its adjoint arising from the linearized disturbance equations with the appropriate boundary conditions are solved numerically using a combination of Newton-Raphson interative scheme and a variable step size integrator based on the Runge-Kutta-Fehlburh fifth-order formulas. The integrator is used in conjunction with a modified Gram-Schmidt orthonormalization procedure. The computer program HADY-I calculates the growth rates of crossflow or streamwise Tollmien-Schlichting instabilities. It also calculates the group velocities of these disturbances. It is restricted to parallel stability calculations, where the boundary layer (meanflow) is assumed to be parallel. The meanflow solution is an input to the program.

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.

Bin-Hash Indexing: A Parallel Method for Fast Query Processing

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

Bethel, Edward W; Gosink, Luke J.; Wu, Kesheng

2008-06-27

This paper presents a new parallel indexing data structure for answering queries. The index, called Bin-Hash, offers extremely high levels of concurrency, and is therefore well-suited for the emerging commodity of parallel processors, such as multi-cores, cell processors, and general purpose graphics processing units (GPU). The Bin-Hash approach first bins the base data, and then partitions and separately stores the values in each bin as a perfect spatial hash table. To answer a query, we first determine whether or not a record satisfies the query conditions based on the bin boundaries. For the bins with records that can not bemore » resolved, we examine the spatial hash tables. The procedures for examining the bin numbers and the spatial hash tables offer the maximum possible level of concurrency; all records are able to be evaluated by our procedure independently in parallel. Additionally, our Bin-Hash procedures access much smaller amounts of data than similar parallel methods, such as the projection index. This smaller data footprint is critical for certain parallel processors, like GPUs, where memory resources are limited. To demonstrate the effectiveness of Bin-Hash, we implement it on a GPU using the data-parallel programming language CUDA. The concurrency offered by the Bin-Hash index allows us to fully utilize the GPU's massive parallelism in our work; over 12,000 records can be simultaneously evaluated at any one time. We show that our new query processing method is an order of magnitude faster than current state-of-the-art CPU-based indexing technologies. Additionally, we compare our performance to existing GPU-based projection index strategies.« less

Cloud parallel processing of tandem mass spectrometry based proteomics data.

PubMed

Mohammed, Yassene; Mostovenko, Ekaterina; Henneman, Alex A; Marissen, Rob J; Deelder, André M; Palmblad, Magnus

2012-10-05

Data analysis in mass spectrometry based proteomics struggles to keep pace with the advances in instrumentation and the increasing rate of data acquisition. Analyzing this data involves multiple steps requiring diverse software, using different algorithms and data formats. Speed and performance of the mass spectral search engines are continuously improving, although not necessarily as needed to face the challenges of acquired big data. Improving and parallelizing the search algorithms is one possibility; data decomposition presents another, simpler strategy for introducing parallelism. We describe a general method for parallelizing identification of tandem mass spectra using data decomposition that keeps the search engine intact and wraps the parallelization around it. We introduce two algorithms for decomposing mzXML files and recomposing resulting pepXML files. This makes the approach applicable to different search engines, including those relying on sequence databases and those searching spectral libraries. We use cloud computing to deliver the computational power and scientific workflow engines to interface and automate the different processing steps. We show how to leverage these technologies to achieve faster data analysis in proteomics and present three scientific workflows for parallel database as well as spectral library search using our data decomposition programs, X!Tandem and SpectraST.

Equalizer: a scalable parallel rendering framework.

PubMed

Eilemann, Stefan; Makhinya, Maxim; Pajarola, Renato

2009-01-01

Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems are non-trivial to develop and often only application specific implementations have been proposed. The task of developing a scalable parallel rendering framework is even more difficult if it should be generic to support various types of data and visualization applications, and at the same time work efficiently on a cluster with distributed graphics cards. In this paper we introduce a novel system called Equalizer, a toolkit for scalable parallel rendering based on OpenGL which provides an application programming interface (API) to develop scalable graphics applications for a wide range of systems ranging from large distributed visualization clusters and multi-processor multipipe graphics systems to single-processor single-pipe desktop machines. We describe the system architecture, the basic API, discuss its advantages over previous approaches, present example configurations and usage scenarios as well as scalability results.

Multiprocessor speed-up, Amdahl's Law, and the Activity Set Model of parallel program behavior

NASA Technical Reports Server (NTRS)

Gelenbe, Erol

1988-01-01

An important issue in the effective use of parallel processing is the estimation of the speed-up one may expect as a function of the number of processors used. Amdahl's Law has traditionally provided a guideline to this issue, although it appears excessively pessimistic in the light of recent experimental results. In this note, Amdahl's Law is amended by giving a greater importance to the capacity of a program to make effective use of parallel processing, but also recognizing the fact that imbalance of the workload of each processor is bound to occur. An activity set model of parallel program behavior is then introduced along with the corresponding parallelism index of a program, leading to upper and lower bounds to the speed-up.

Multi-mode sensor processing on a dynamically reconfigurable massively parallel processor array

NASA Astrophysics Data System (ADS)

Chen, Paul; Butts, Mike; Budlong, Brad; Wasson, Paul

2008-04-01

This paper introduces a novel computing architecture that can be reconfigured in real time to adapt on demand to multi-mode sensor platforms' dynamic computational and functional requirements. This 1 teraOPS reconfigurable Massively Parallel Processor Array (MPPA) has 336 32-bit processors. The programmable 32-bit communication fabric provides streamlined inter-processor connections with deterministically high performance. Software programmability, scalability, ease of use, and fast reconfiguration time (ranging from microseconds to milliseconds) are the most significant advantages over FPGAs and DSPs. This paper introduces the MPPA architecture, its programming model, and methods of reconfigurability. An MPPA platform for reconfigurable computing is based on a structural object programming model. Objects are software programs running concurrently on hundreds of 32-bit RISC processors and memories. They exchange data and control through a network of self-synchronizing channels. A common application design pattern on this platform, called a work farm, is a parallel set of worker objects, with one input and one output stream. Statically configured work farms with homogeneous and heterogeneous sets of workers have been used in video compression and decompression, network processing, and graphics applications.

Experiences with hypercube operating system instrumentation

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Rudolph, David C.

1989-01-01

The difficulties in conceptualizing the interactions among a large number of processors make it difficult both to identify the sources of inefficiencies and to determine how a parallel program could be made more efficient. This paper describes an instrumentation system that can trace the execution of distributed memory parallel programs by recording the occurrence of parallel program events. The resulting event traces can be used to compile summary statistics that provide a global view of program performance. In addition, visualization tools permit the graphic display of event traces. Visual presentation of performance data is particularly useful, indeed, necessary for large-scale parallel computers; the enormous volume of performance data mandates visual display.

Communications oriented programming of parallel iterative solutions of sparse linear systems

NASA Technical Reports Server (NTRS)

Patrick, M. L.; Pratt, T. W.

1986-01-01

Parallel algorithms are developed for a class of scientific computational problems by partitioning the problems into smaller problems which may be solved concurrently. The effectiveness of the resulting parallel solutions is determined by the amount and frequency of communication and synchronization and the extent to which communication can be overlapped with computation. Three different parallel algorithms for solving the same class of problems are presented, and their effectiveness is analyzed from this point of view. The algorithms are programmed using a new programming environment. Run-time statistics and experience obtained from the execution of these programs assist in measuring the effectiveness of these algorithms.

Parallel programming of saccades during natural scene viewing: evidence from eye movement positions.

PubMed

Wu, Esther X W; Gilani, Syed Omer; van Boxtel, Jeroen J A; Amihai, Ido; Chua, Fook Kee; Yen, Shih-Cheng

2013-10-24

Previous studies have shown that saccade plans during natural scene viewing can be programmed in parallel. This evidence comes mainly from temporal indicators, i.e., fixation durations and latencies. In the current study, we asked whether eye movement positions recorded during scene viewing also reflect parallel programming of saccades. As participants viewed scenes in preparation for a memory task, their inspection of the scene was suddenly disrupted by a transition to another scene. We examined whether saccades after the transition were invariably directed immediately toward the center or were contingent on saccade onset times relative to the transition. The results, which showed a dissociation in eye movement behavior between two groups of saccades after the scene transition, supported the parallel programming account. Saccades with relatively long onset times (>100 ms) after the transition were directed immediately toward the center of the scene, probably to restart scene exploration. Saccades with short onset times (<100 ms) moved to the center only one saccade later. Our data on eye movement positions provide novel evidence of parallel programming of saccades during scene viewing. Additionally, results from the analyses of intersaccadic intervals were also consistent with the parallel programming hypothesis.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform

PubMed Central

Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance. PMID:29861711

NDL-v2.0: A new version of the numerical differentiation library for parallel architectures

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Voglis, C.; Papageorgiou, D. G.; Lagaris, I. E.

2014-07-01

We present a new version of the numerical differentiation library (NDL) used for the numerical estimation of first and second order partial derivatives of a function by finite differencing. In this version we have restructured the serial implementation of the code so as to achieve optimal task-based parallelization. The pure shared-memory parallelization of the library has been based on the lightweight OpenMP tasking model allowing for the full extraction of the available parallelism and efficient scheduling of multiple concurrent library calls. On multicore clusters, parallelism is exploited by means of TORC, an MPI-based multi-threaded tasking library. The new MPI implementation of NDL provides optimal performance in terms of function calls and, furthermore, supports asynchronous execution of multiple library calls within legacy MPI programs. In addition, a Python interface has been implemented for all cases, exporting the functionality of our library to sequential Python codes. Catalog identifier: AEDG_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDG_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 63036 No. of bytes in distributed program, including test data, etc.: 801872 Distribution format: tar.gz Programming language: ANSI Fortran-77, ANSI C, Python. Computer: Distributed systems (clusters), shared memory systems. Operating system: Linux, Unix. Has the code been vectorized or parallelized?: Yes. RAM: The library uses O(N) internal storage, N being the dimension of the problem. It can use up to O(N2) internal storage for Hessian calculations, if a task throttling factor has not been set by the user. Classification: 4.9, 4.14, 6.5. Catalog identifier of previous version: AEDG_v1_0 Journal reference of previous version: Comput. Phys. Comm. 180(2009)1404 Does the new version supersede the previous version?: Yes Nature of problem: The numerical estimation of derivatives at several accuracy levels is a common requirement in many computational tasks, such as optimization, solution of nonlinear systems, and sensitivity analysis. For a large number of scientific and engineering applications, the underlying functions correspond to simulation codes for which analytical estimation of derivatives is difficult or almost impossible. A parallel implementation that exploits systems with multiple CPUs is very important for large scale and computationally expensive problems. Solution method: Finite differencing is used with a carefully chosen step that minimizes the sum of the truncation and round-off errors. The parallel versions employ both OpenMP and MPI libraries. Reasons for new version: The updated version was motivated by our endeavors to extend a parallel Bayesian uncertainty quantification framework [1], by incorporating higher order derivative information as in most state-of-the-art stochastic simulation methods such as Stochastic Newton MCMC [2] and Riemannian Manifold Hamiltonian MC [3]. The function evaluations are simulations with significant time-to-solution, which also varies with the input parameters such as in [1, 4]. The runtime of the N-body-type of problem changes considerably with the introduction of a longer cut-off between the bodies. In the first version of the library, the OpenMP-parallel subroutines spawn a new team of threads and distribute the function evaluations with a PARALLEL DO directive. This limits the functionality of the library as multiple concurrent calls require nested parallelism support from the OpenMP environment. Therefore, either their function evaluations will be serialized or processor oversubscription is likely to occur due to the increased number of OpenMP threads. In addition, the Hessian calculations include two explicit parallel regions that compute first the diagonal and then the off-diagonal elements of the array. Due to the barrier between the two regions, the parallelism of the calculations is not fully exploited. These issues have been addressed in the new version by first restructuring the serial code and then running the function evaluations in parallel using OpenMP tasks. Although the MPI-parallel implementation of the first version is capable of fully exploiting the task parallelism of the PNDL routines, it does not utilize the caching mechanism of the serial code and, therefore, performs some redundant function evaluations in the Hessian and Jacobian calculations. This can lead to: (a) higher execution times if the number of available processors is lower than the total number of tasks, and (b) significant energy consumption due to wasted processor cycles. Overcoming these drawbacks, which become critical as the time of a single function evaluation increases, was the primary goal of this new version. Due to the code restructure, the MPI-parallel implementation (and the OpenMP-parallel in accordance) avoids redundant calls, providing optimal performance in terms of the number of function evaluations. Another limitation of the library was that the library subroutines were collective and synchronous calls. In the new version, each MPI process can issue any number of subroutines for asynchronous execution. We introduce two library calls that provide global and local task synchronizations, similarly to the BARRIER and TASKWAIT directives of OpenMP. The new MPI-implementation is based on TORC, a new tasking library for multicore clusters [5-7]. TORC improves the portability of the software, as it relies exclusively on the POSIX-Threads and MPI programming interfaces. It allows MPI processes to utilize multiple worker threads, offering a hybrid programming and execution environment similar to MPI+OpenMP, in a completely transparent way. Finally, to further improve the usability of our software, a Python interface has been implemented on top of both the OpenMP and MPI versions of the library. This allows sequential Python codes to exploit shared and distributed memory systems. Summary of revisions: The revised code improves the performance of both parallel (OpenMP and MPI) implementations. The functionality and the user-interface of the MPI-parallel version have been extended to support the asynchronous execution of multiple PNDL calls, issued by one or multiple MPI processes. A new underlying tasking library increases portability and allows MPI processes to have multiple worker threads. For both implementations, an interface to the Python programming language has been added. Restrictions: The library uses only double precision arithmetic. The MPI implementation assumes the homogeneity of the execution environment provided by the operating system. Specifically, the processes of a single MPI application must have identical address space and a user function resides at the same virtual address. In addition, address space layout randomization should not be used for the application. Unusual features: The software takes into account bound constraints, in the sense that only feasible points are used to evaluate the derivatives, and given the level of the desired accuracy, the proper formula is automatically employed. Running time: Running time depends on the function's complexity. The test run took 23 ms for the serial distribution, 25 ms for the OpenMP with 2 threads, 53 ms and 1.01 s for the MPI parallel distribution using 2 threads and 2 processes respectively and yield-time for idle workers equal to 10 ms. References: [1] P. Angelikopoulos, C. Paradimitriou, P. Koumoutsakos, Bayesian uncertainty quantification and propagation in molecular dynamics simulations: a high performance computing framework, J. Chem. Phys 137 (14). [2] H.P. Flath, L.C. Wilcox, V. Akcelik, J. Hill, B. van Bloemen Waanders, O. Ghattas, Fast algorithms for Bayesian uncertainty quantification in large-scale linear inverse problems based on low-rank partial Hessian approximations, SIAM J. Sci. Comput. 33 (1) (2011) 407-432. [3] M. Girolami, B. Calderhead, Riemann manifold Langevin and Hamiltonian Monte Carlo methods, J. R. Stat. Soc. Ser. B (Stat. Methodol.) 73 (2) (2011) 123-214. [4] P. Angelikopoulos, C. Paradimitriou, P. Koumoutsakos, Data driven, predictive molecular dynamics for nanoscale flow simulations under uncertainty, J. Phys. Chem. B 117 (47) (2013) 14808-14816. [5] P.E. Hadjidoukas, E. Lappas, V.V. Dimakopoulos, A runtime library for platform-independent task parallelism, in: PDP, IEEE, 2012, pp. 229-236. [6] C. Voglis, P.E. Hadjidoukas, D.G. Papageorgiou, I. Lagaris, A parallel hybrid optimization algorithm for fitting interatomic potentials, Appl. Soft Comput. 13 (12) (2013) 4481-4492. [7] P.E. Hadjidoukas, C. Voglis, V.V. Dimakopoulos, I. Lagaris, D.G. Papageorgiou, Supporting adaptive and irregular parallelism for non-linear numerical optimization, Appl. Math. Comput. 231 (2014) 544-559.

NavP: Structured and Multithreaded Distributed Parallel Programming

NASA Technical Reports Server (NTRS)

Pan, Lei

2007-01-01

We present Navigational Programming (NavP) -- a distributed parallel programming methodology based on the principles of migrating computations and multithreading. The four major steps of NavP are: (1) Distribute the data using the data communication pattern in a given algorithm; (2) Insert navigational commands for the computation to migrate and follow large-sized distributed data; (3) Cut the sequential migrating thread and construct a mobile pipeline; and (4) Loop back for refinement. NavP is significantly different from the current prevailing Message Passing (MP) approach. The advantages of NavP include: (1) NavP is structured distributed programming and it does not change the code structure of an original algorithm. This is in sharp contrast to MP as MP implementations in general do not resemble the original sequential code; (2) NavP implementations are always competitive with the best MPI implementations in terms of performance. Approaches such as DSM or HPF have failed to deliver satisfying performance as of today in contrast, even if they are relatively easy to use compared to MP; (3) NavP provides incremental parallelization, which is beyond the reach of MP; and (4) NavP is a unifying approach that allows us to exploit both fine- (multithreading on shared memory) and coarse- (pipelined tasks on distributed memory) grained parallelism. This is in contrast to the currently popular hybrid use of MP+OpenMP, which is known to be complex to use. We present experimental results that demonstrate the effectiveness of NavP.

A survey of parallel programming tools

NASA Technical Reports Server (NTRS)

Cheng, Doreen Y.

1991-01-01

This survey examines 39 parallel programming tools. Focus is placed on those tool capabilites needed for parallel scientific programming rather than for general computer science. The tools are classified with current and future needs of Numerical Aerodynamic Simulator (NAS) in mind: existing and anticipated NAS supercomputers and workstations; operating systems; programming languages; and applications. They are divided into four categories: suggested acquisitions, tools already brought in; tools worth tracking; and tools eliminated from further consideration at this time.

Parallel computing and first-principles calculations: Applications to complex ceramics and Vitamin B12

NASA Astrophysics Data System (ADS)

Ouyang, Lizhi

A systematic improvement and extension of the orthogonalized linear combinations of atomic orbitals method was carried out using a combined computational and theoretical approach. For high performance parallel computing, a Beowulf class personal computer cluster was constructed. It also served as a parallel program development platform that helped us to port the programs of the method to the national supercomputer facilities. The program, received a language upgrade from Fortran 77 to Fortran 90, and a dynamic memory allocation feature. A preliminary parallel High Performance Fortran version of the program has been developed as well. To be of more benefit though, scalability improvements are needed. In order to circumvent the difficulties of the analytical force calculation in the method, we developed a geometry optimization scheme using the finite difference approximation based on the total energy calculation. The implementation of this scheme was facilitated by the powerful general utility lattice program, which offers many desired features such as multiple optimization schemes and usage of space group symmetry. So far, many ceramic oxides have been tested with the geometry optimization program. Their optimized geometries were in excellent agreement with the experimental data. For nine ceramic oxide crystals, the optimized cell parameters differ from the experimental ones within 0.5%. Moreover, the geometry optimization was recently used to predict a new phase of TiNx. The method has also been used to investigate a complex Vitamin B12-derivative, the OHCbl crystals. In order to overcome the prohibitive disk I/O demand, an on-demand version of the method was developed. Based on the electronic structure calculation of the OHCbl crystal, a partial density of states analysis and a bond order analysis were carried out. The calculated bonding of the corrin ring of OHCbl model was coincident with the big open-ring pi bond. One interesting find of the calculation was that the Co-OH bond was weak. This, together with the ongoing projects studying different Vitamin B12 derivatives, might help us to answer questions about the Co-C cleavage of the B12 coenzyme, which is involved in many important B12 enzymatic reactions.

Time Warp Operating System, Version 2.5.1

NASA Technical Reports Server (NTRS)

Bellenot, Steven F.; Gieselman, John S.; Hawley, Lawrence R.; Peterson, Judy; Presley, Matthew T.; Reiher, Peter L.; Springer, Paul L.; Tupman, John R.; Wedel, John J., Jr.; Wieland, Frederick P.;

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

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

IMa2p - Parallel MCMC and inference of ancient demography under the Isolation with Migration (IM) model

PubMed Central

Sethuraman, Arun; Hey, Jody

2015-01-01

IMa2 and related programs are used to study the divergence of closely related species and of populations within species. These methods are based on the sampling of genealogies using MCMC, and they can proceed quite slowly for larger data sets. We describe a parallel implementation, called IMa2p, that provides a nearly linear increase in genealogy sampling rate with the number of processors in use. IMa2p is written in OpenMPI and C++, and scales well for demographic analyses of a large number of loci and populations, which are difficult to study using the serial version of the program. PMID:26059786

Experiences using OpenMP based on Computer Directed Software DSM on a PC Cluster

NASA Technical Reports Server (NTRS)

Hess, Matthias; Jost, Gabriele; Mueller, Matthias; Ruehle, Roland

2003-01-01

In this work we report on our experiences running OpenMP programs on a commodity cluster of PCs running a software distributed shared memory (DSM) system. We describe our test environment and report on the performance of a subset of the NAS Parallel Benchmarks that have been automaticaly parallelized for OpenMP. We compare the performance of the OpenMP implementations with that of their message passing counterparts and discuss performance differences.

Proceedings of the Conference on Knowledge-Based Software Assistant (5th) Held in Liverpool, New York on 24-28 September 1990

DTIC Science & Technology

1991-03-01

factor which made TTL-design so powerful was the implicit knowledge that for any object in the TTL Databook, that object’s implementation and...functions as values. Thus, its reasoning power matches the descriptive power of the higher order languages in the previous section. First, the definitions...developing parallel algorithms to better utilize the power of the explicitly parallel programming language constructs. Currently, the methodologies

Parallelization of an Object-Oriented Unstructured Aeroacoustics Solver

NASA Technical Reports Server (NTRS)

Baggag, Abdelkader; Atkins, Harold; Oezturan, Can; Keyes, David

1999-01-01

A computational aeroacoustics code based on the discontinuous Galerkin method is ported to several parallel platforms using MPI. The discontinuous Galerkin method is a compact high-order method that retains its accuracy and robustness on non-smooth unstructured meshes. In its semi-discrete form, the discontinuous Galerkin method can be combined with explicit time marching methods making it well suited to time accurate computations. The compact nature of the discontinuous Galerkin method also makes it well suited for distributed memory parallel platforms. The original serial code was written using an object-oriented approach and was previously optimized for cache-based machines. The port to parallel platforms was achieved simply by treating partition boundaries as a type of boundary condition. Code modifications were minimal because boundary conditions were abstractions in the original program. Scalability results are presented for the SCI Origin, IBM SP2, and clusters of SGI and Sun workstations. Slightly superlinear speedup is achieved on a fixed-size problem on the Origin, due to cache effects.

Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Hao-Qiang; anMey, Dieter; Hatay, Ferhat F.

2003-01-01

Clusters of SMP (Symmetric Multi-Processors) nodes provide support for a wide range of parallel programming paradigms. The shared address space within each node is suitable for OpenMP parallelization. Message passing can be employed within and across the nodes of a cluster. Multiple levels of parallelism can be achieved by combining message passing and OpenMP parallelization. Which programming paradigm is the best will depend on the nature of the given problem, the hardware components of the cluster, the network, and the available software. In this study we compare the performance of different implementations of the same CFD benchmark application, using the same numerical algorithm but employing different programming paradigms.

OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems.

PubMed

Stone, John E; Gohara, David; Shi, Guochun

2010-05-01

We provide an overview of the key architectural features of recent microprocessor designs and describe the programming model and abstractions provided by OpenCL, a new parallel programming standard targeting these architectures.

Knowledge Based Synthesis of Efficient Structures for Concurrent Computation Using Fat-Trees and Pipelining.

DTIC Science & Technology

1986-12-31

synthesize synchronization skeletons"Science of Computer Programming 2, 1982, pp. 241-266 [Gel85] Gelernter, David, "Generative communication in...effective computation based on given primitives . An architecture is an abstract object-type, whose instances are computing systems. By a parallel computing...explaining the language primitives on this basis. We explain how such a basis can be "simpler" than a general-purpose manual-programming language such as

Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Haoqiang; anMey, Dieter; Hatay, Ferhat F.

2003-01-01

With the advent of parallel hardware and software technologies users are faced with the challenge to choose a programming paradigm best suited for the underlying computer architecture. With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors (SMP), parallel programming techniques have evolved to support parallelism beyond a single level. Which programming paradigm is the best will depend on the nature of the given problem, the hardware architecture, and the available software. In this study we will compare different programming paradigms for the parallelization of a selected benchmark application on a cluster of SMP nodes. We compare the timings of different implementations of the same CFD benchmark application employing the same numerical algorithm on a cluster of Sun Fire SMP nodes. The rest of the paper is structured as follows: In section 2 we briefly discuss the programming models under consideration. We describe our compute platform in section 3. The different implementations of our benchmark code are described in section 4 and the performance results are presented in section 5. We conclude our study in section 6.

Rubus: A compiler for seamless and extensible parallelism.

PubMed

Adnan, Muhammad; Aslam, Faisal; Nawaz, Zubair; Sarwar, Syed Mansoor

2017-01-01

Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU), originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer's expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84 times has been achieved by Rubus on the same GPU. Moreover, Rubus achieves this performance without drastically increasing the memory footprint of a program.

Rubus: A compiler for seamless and extensible parallelism

PubMed Central

Adnan, Muhammad; Aslam, Faisal; Sarwar, Syed Mansoor

2017-01-01

Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU), originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer’s expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84 times has been achieved by Rubus on the same GPU. Moreover, Rubus achieves this performance without drastically increasing the memory footprint of a program. PMID:29211758

Efficient partitioning and assignment on programs for multiprocessor execution

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1993-01-01

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

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

PubMed

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

2013-04-01

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

A mechanism for efficient debugging of parallel programs

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

Miller, B.P.; Choi, J.D.

1988-01-01

This paper addresses the design and implementation of an integrated debugging system for parallel programs running on shared memory multi-processors (SMMP). The authors describe the use of flowback analysis to provide information on causal relationships between events in a program's execution without re-executing the program for debugging. The authors introduce a mechanism called incremental tracing that, by using semantic analyses of the debugged program, makes the flowback analysis practical with only a small amount of trace generated during execution. The extend flowback analysis to apply to parallel programs and describe a method to detect race conditions in the interactions ofmore » the co-operating processes.« less

Development of an Algorithm for Automatic Analysis of the Impedance Spectrum Based on a Measurement Model

NASA Astrophysics Data System (ADS)

Kobayashi, Kiyoshi; Suzuki, Tohru S.

2018-03-01

A new algorithm for the automatic estimation of an equivalent circuit and the subsequent parameter optimization is developed by combining the data-mining concept and complex least-squares method. In this algorithm, the program generates an initial equivalent-circuit model based on the sampling data and then attempts to optimize the parameters. The basic hypothesis is that the measured impedance spectrum can be reproduced by the sum of the partial-impedance spectra presented by the resistor, inductor, resistor connected in parallel to a capacitor, and resistor connected in parallel to an inductor. The adequacy of the model is determined by using a simple artificial-intelligence function, which is applied to the output function of the Levenberg-Marquardt module. From the iteration of model modifications, the program finds an adequate equivalent-circuit model without any user input to the equivalent-circuit model.

OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems

PubMed Central

Stone, John E.; Gohara, David; Shi, Guochun

2010-01-01

We provide an overview of the key architectural features of recent microprocessor designs and describe the programming model and abstractions provided by OpenCL, a new parallel programming standard targeting these architectures. PMID:21037981

An Expert System for the Development of Efficient Parallel Code

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Chun, Robert; Jin, Hao-Qiang; Labarta, Jesus; Gimenez, Judit

2004-01-01

We have built the prototype of an expert system to assist the user in the development of efficient parallel code. The system was integrated into the parallel programming environment that is currently being developed at NASA Ames. The expert system interfaces to tools for automatic parallelization and performance analysis. It uses static program structure information and performance data in order to automatically determine causes of poor performance and to make suggestions for improvements. In this paper we give an overview of our programming environment, describe the prototype implementation of our expert system, and demonstrate its usefulness with several case studies.

Joint Services Electronics Program

DTIC Science & Technology

1992-03-05

Packaging Considerations M. T. Raghunath (Professor Abhiram Ranade) A central issue in massively parallel computation is the design of the interconnection...programs on promising network architectures. Publications: [1] M. T. Raghunath and A. G. Ranade, A Simulation-Based Compari- son of Interconnection Networks...more difficult analog function approximation task. Network Design Issues for Fast Global Communication Professor A. Ranade with M.T. Raghunath A

Solving Integer Programs from Dependence and Synchronization Problems

DTIC Science & Technology

1993-03-01

DEFF.NSNE Solving Integer Programs from Dependence and Synchronization Problems Jaspal Subhlok March 1993 CMU-CS-93-130 School of Computer ScienceT IC...method Is an exact and efficient way of solving integer programming problems arising in dependence and synchronization analysis of parallel programs...7/;- p Keywords: Exact dependence tesing, integer programming. parallelilzng compilers, parallel program analysis, synchronization analysis Solving

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

PubMed

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

A Multibody Formulation for Three Dimensional Brick Finite Element Based Parallel and Scalable Rotor Dynamic Analysis

DTIC Science & Technology

2010-05-01

connections near the hub end, and containing up to 0.48 million degrees of freedom. The models are analyzed for scala - bility and timing for hover and...Parallel and Scalable Rotor Dynamic Analysis 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK...will enable the modeling of critical couplings that occur in hingeless and bearingless hubs with advanced flex structures. Second , it will enable the

Experiences Using OpenMP Based on Compiler Directed Software DSM on a PC Cluster

NASA Technical Reports Server (NTRS)

Hess, Matthias; Jost, Gabriele; Mueller, Matthias; Ruehle, Roland; Biegel, Bryan (Technical Monitor)

2002-01-01

In this work we report on our experiences running OpenMP (message passing) programs on a commodity cluster of PCs (personal computers) running a software distributed shared memory (DSM) system. We describe our test environment and report on the performance of a subset of the NAS (NASA Advanced Supercomputing) Parallel Benchmarks that have been automatically parallelized for OpenMP. We compare the performance of the OpenMP implementations with that of their message passing counterparts and discuss performance differences.

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

NASA Technical Reports Server (NTRS)

Mak, Victor W. K.

1986-01-01

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

The FORCE - A highly portable parallel programming language

NASA Technical Reports Server (NTRS)

Jordan, Harry F.; Benten, Muhammad S.; Alaghband, Gita; Jakob, Ruediger

1989-01-01

This paper explains why the FORCE parallel programming language is easily portable among six different shared-memory multiprocessors, and how a two-level macro preprocessor makes it possible to hide low-level machine dependencies and to build machine-independent high-level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared-memory multiprocessor executing them.

The FORCE: A highly portable parallel programming language

NASA Technical Reports Server (NTRS)

Jordan, Harry F.; Benten, Muhammad S.; Alaghband, Gita; Jakob, Ruediger

1989-01-01

Here, it is explained why the FORCE parallel programming language is easily portable among six different shared-memory microprocessors, and how a two-level macro preprocessor makes it possible to hide low level machine dependencies and to build machine-independent high level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared memory multiprocessor executing them.

Heterogeneous computing architecture for fast detection of SNP-SNP interactions.

PubMed

Sluga, Davor; Curk, Tomaz; Zupan, Blaz; Lotric, Uros

2014-06-25

The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems.

Heterogeneous computing architecture for fast detection of SNP-SNP interactions

PubMed Central

2014-01-01

Background The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. Results We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. Conclusions General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems. PMID:24964802

Characterizing and Mitigating Work Time Inflation in Task Parallel Programs

DOE PAGES

Olivier, Stephen L.; de Supinski, Bronis R.; Schulz, Martin; ...

2013-01-01

Task parallelism raises the level of abstraction in shared memory parallel programming to simplify the development of complex applications. However, task parallel applications can exhibit poor performance due to thread idleness, scheduling overheads, and work time inflation – additional time spent by threads in a multithreaded computation beyond the time required to perform the same work in a sequential computation. We identify the contributions of each factor to lost efficiency in various task parallel OpenMP applications and diagnose the causes of work time inflation in those applications. Increased data access latency can cause significant work time inflation in NUMA systems.more » Our locality framework for task parallel OpenMP programs mitigates this cause of work time inflation. Our extensions to the Qthreads library demonstrate that locality-aware scheduling can improve performance up to 3X compared to the Intel OpenMP task scheduler.« less

Evaluation of Turkish and Mathematics Curricula According to Value-Based Evaluation Model

ERIC Educational Resources Information Center

Duman, Serap Nur; Akbas, Oktay

2017-01-01

This study evaluated secondary school seventh-grade Turkish and mathematics programs using the Context-Input-Process-Product Evaluation Model based on student, teacher, and inspector views. The convergent parallel mixed method design was used in the study. Student values were identified using the scales for socio-level identification, traditional…

Support for Debugging Automatically Parallelized Programs

NASA Technical Reports Server (NTRS)

Hood, Robert; Jost, Gabriele

2001-01-01

This viewgraph presentation provides information on support sources available for the automatic parallelization of computer program. CAPTools, a support tool developed at the University of Greenwich, transforms, with user guidance, existing sequential Fortran code into parallel message passing code. Comparison routines are then run for debugging purposes, in essence, ensuring that the code transformation was accurate.

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

PubMed

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

2012-09-25

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

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

PubMed Central

2012-01-01

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

On the suitability of the connection machine for direct particle simulation

NASA Technical Reports Server (NTRS)

Dagum, Leonard

1990-01-01

The algorithmic structure was examined of the vectorizable Stanford particle simulation (SPS) method and the structure is reformulated in data parallel form. Some of the SPS algorithms can be directly translated to data parallel, but several of the vectorizable algorithms have no direct data parallel equivalent. This requires the development of new, strictly data parallel algorithms. In particular, a new sorting algorithm is developed to identify collision candidates in the simulation and a master/slave algorithm is developed to minimize communication cost in large table look up. Validation of the method is undertaken through test calculations for thermal relaxation of a gas, shock wave profiles, and shock reflection from a stationary wall. A qualitative measure is provided of the performance of the Connection Machine for direct particle simulation. The massively parallel architecture of the Connection Machine is found quite suitable for this type of calculation. However, there are difficulties in taking full advantage of this architecture because of lack of a broad based tradition of data parallel programming. An important outcome of this work has been new data parallel algorithms specifically of use for direct particle simulation but which also expand the data parallel diction.

Parallelizing serial code for a distributed processing environment with an application to high frequency electromagnetic scattering

NASA Astrophysics Data System (ADS)

Work, Paul R.

1991-12-01

This thesis investigates the parallelization of existing serial programs in computational electromagnetics for use in a parallel environment. Existing algorithms for calculating the radar cross section of an object are covered, and a ray-tracing code is chosen for implementation on a parallel machine. Current parallel architectures are introduced and a suitable parallel machine is selected for the implementation of the chosen ray-tracing algorithm. The standard techniques for the parallelization of serial codes are discussed, including load balancing and decomposition considerations, and appropriate methods for the parallelization effort are selected. A load balancing algorithm is modified to increase the efficiency of the application, and a high level design of the structure of the serial program is presented. A detailed design of the modifications for the parallel implementation is also included, with both the high level and the detailed design specified in a high level design language called UNITY. The correctness of the design is proven using UNITY and standard logic operations. The theoretical and empirical results show that it is possible to achieve an efficient parallel application for a serial computational electromagnetic program where the characteristics of the algorithm and the target architecture critically influence the development of such an implementation.

Advanced mathematical on-line analysis in nuclear experiments. Usage of parallel computing CUDA routines in standard root analysis

NASA Astrophysics Data System (ADS)

Grzeszczuk, A.; Kowalski, S.

2015-04-01

Compute Unified Device Architecture (CUDA) is a parallel computing platform developed by Nvidia for increase speed of graphics by usage of parallel mode for processes calculation. The success of this solution has opened technology General-Purpose Graphic Processor Units (GPGPUs) for applications not coupled with graphics. The GPGPUs system can be applying as effective tool for reducing huge number of data for pulse shape analysis measures, by on-line recalculation or by very quick system of compression. The simplified structure of CUDA system and model of programming based on example Nvidia GForce GTX580 card are presented by our poster contribution in stand-alone version and as ROOT application.

MPF: A portable message passing facility for shared memory multiprocessors

NASA Technical Reports Server (NTRS)

Malony, Allen D.; Reed, Daniel A.; Mcguire, Patrick J.

1987-01-01

The design, implementation, and performance evaluation of a message passing facility (MPF) for shared memory multiprocessors are presented. The MPF is based on a message passing model conceptually similar to conversations. Participants (parallel processors) can enter or leave a conversation at any time. The message passing primitives for this model are implemented as a portable library of C function calls. The MPF is currently operational on a Sequent Balance 21000, and several parallel applications were developed and tested. Several simple benchmark programs are presented to establish interprocess communication performance for common patterns of interprocess communication. Finally, performance figures are presented for two parallel applications, linear systems solution, and iterative solution of partial differential equations.

Parallel simulations of Grover's algorithm for closest match search in neutron monitor data

NASA Astrophysics Data System (ADS)

Kussainov, Arman; White, Yelena

We are studying the parallel implementations of Grover's closest match search algorithm for neutron monitor data analysis. This includes data formatting, and matching quantum parameters to a conventional structure of a chosen programming language and selected experimental data type. We have employed several workload distribution models based on acquired data and search parameters. As a result of these simulations, we have an understanding of potential problems that may arise during configuration of real quantum computational devices and the way they could run tasks in parallel. The work was supported by the Science Committee of the Ministry of Science and Education of the Republic of Kazakhstan Grant #2532/GF3.

WFIRST: Science from the Guest Investigator and Parallel Observation Programs

NASA Astrophysics Data System (ADS)

Postman, Marc; Nataf, David; Furlanetto, Steve; Milam, Stephanie; Robertson, Brant; Williams, Ben; Teplitz, Harry; Moustakas, Leonidas; Geha, Marla; Gilbert, Karoline; Dickinson, Mark; Scolnic, Daniel; Ravindranath, Swara; Strolger, Louis; Peek, Joshua; Marc Postman

2018-01-01

The Wide Field InfraRed Survey Telescope (WFIRST) mission will provide an extremely rich archival dataset that will enable a broad range of scientific investigations beyond the initial objectives of the proposed key survey programs. The scientific impact of WFIRST will thus be significantly expanded by a robust Guest Investigator (GI) archival research program. We will present examples of GI research opportunities ranging from studies of the properties of a variety of Solar System objects, surveys of the outer Milky Way halo, comprehensive studies of cluster galaxies, to unique and new constraints on the epoch of cosmic re-ionization and the assembly of galaxies in the early universe.WFIRST will also support the acquisition of deep wide-field imaging and slitless spectroscopic data obtained in parallel during campaigns with the coronagraphic instrument (CGI). These parallel wide-field imager (WFI) datasets can provide deep imaging data covering several square degrees at no impact to the scheduling of the CGI program. A competitively selected program of well-designed parallel WFI observation programs will, like the GI science above, maximize the overall scientific impact of WFIRST. We will give two examples of parallel observations that could be conducted during a proposed CGI program centered on a dozen nearby stars.

Parallelized direct execution simulation of message-passing parallel programs

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

Design of object-oriented distributed simulation classes

NASA Technical Reports Server (NTRS)

Schoeffler, James D. (Principal Investigator)

1995-01-01

Distributed simulation of aircraft engines as part of a computer aided design package is being developed by NASA Lewis Research Center for the aircraft industry. The project is called NPSS, an acronym for 'Numerical Propulsion Simulation System'. NPSS is a flexible object-oriented simulation of aircraft engines requiring high computing speed. It is desirable to run the simulation on a distributed computer system with multiple processors executing portions of the simulation in parallel. The purpose of this research was to investigate object-oriented structures such that individual objects could be distributed. The set of classes used in the simulation must be designed to facilitate parallel computation. Since the portions of the simulation carried out in parallel are not independent of one another, there is the need for communication among the parallel executing processors which in turn implies need for their synchronization. Communication and synchronization can lead to decreased throughput as parallel processors wait for data or synchronization signals from other processors. As a result of this research, the following have been accomplished. The design and implementation of a set of simulation classes which result in a distributed simulation control program have been completed. The design is based upon MIT 'Actor' model of a concurrent object and uses 'connectors' to structure dynamic connections between simulation components. Connectors may be dynamically created according to the distribution of objects among machines at execution time without any programming changes. Measurements of the basic performance have been carried out with the result that communication overhead of the distributed design is swamped by the computation time of modules unless modules have very short execution times per iteration or time step. An analytical performance model based upon queuing network theory has been designed and implemented. Its application to realistic configurations has not been carried out.

Design of Object-Oriented Distributed Simulation Classes

NASA Technical Reports Server (NTRS)

Schoeffler, James D.

1995-01-01

Distributed simulation of aircraft engines as part of a computer aided design package being developed by NASA Lewis Research Center for the aircraft industry. The project is called NPSS, an acronym for "Numerical Propulsion Simulation System". NPSS is a flexible object-oriented simulation of aircraft engines requiring high computing speed. It is desirable to run the simulation on a distributed computer system with multiple processors executing portions of the simulation in parallel. The purpose of this research was to investigate object-oriented structures such that individual objects could be distributed. The set of classes used in the simulation must be designed to facilitate parallel computation. Since the portions of the simulation carried out in parallel are not independent of one another, there is the need for communication among the parallel executing processors which in turn implies need for their synchronization. Communication and synchronization can lead to decreased throughput as parallel processors wait for data or synchronization signals from other processors. As a result of this research, the following have been accomplished. The design and implementation of a set of simulation classes which result in a distributed simulation control program have been completed. The design is based upon MIT "Actor" model of a concurrent object and uses "connectors" to structure dynamic connections between simulation components. Connectors may be dynamically created according to the distribution of objects among machines at execution time without any programming changes. Measurements of the basic performance have been carried out with the result that communication overhead of the distributed design is swamped by the computation time of modules unless modules have very short execution times per iteration or time step. An analytical performance model based upon queuing network theory has been designed and implemented. Its application to realistic configurations has not been carried out.

Using Coarrays to Parallelize Legacy Fortran Applications: Strategy and Case Study

DOE PAGES

Radhakrishnan, Hari; Rouson, Damian W. I.; Morris, Karla; ...

2015-01-01

This paper summarizes a strategy for parallelizing a legacy Fortran 77 program using the object-oriented (OO) and coarray features that entered Fortran in the 2003 and 2008 standards, respectively. OO programming (OOP) facilitates the construction of an extensible suite of model-verification and performance tests that drive the development. Coarray parallel programming facilitates a rapid evolution from a serial application to a parallel application capable of running on multicore processors and many-core accelerators in shared and distributed memory. We delineate 17 code modernization steps used to refactor and parallelize the program and study the resulting performance. Our initial studies were donemore » using the Intel Fortran compiler on a 32-core shared memory server. Scaling behavior was very poor, and profile analysis using TAU showed that the bottleneck in the performance was due to our implementation of a collective, sequential summation procedure. We were able to improve the scalability and achieve nearly linear speedup by replacing the sequential summation with a parallel, binary tree algorithm. We also tested the Cray compiler, which provides its own collective summation procedure. Intel provides no collective reductions. With Cray, the program shows linear speedup even in distributed-memory execution. We anticipate similar results with other compilers once they support the new collective procedures proposed for Fortran 2015.« less

A GaAs vector processor based on parallel RISC microprocessors

NASA Astrophysics Data System (ADS)

Misko, Tim A.; Rasset, Terry L.

A vector processor architecture based on the development of a 32-bit microprocessor using gallium arsenide (GaAs) technology has been developed. The McDonnell Douglas vector processor (MVP) will be fabricated completely from GaAs digital integrated circuits. The MVP architecture includes a vector memory of 1 megabyte, a parallel bus architecture with eight processing elements connected in parallel, and a control processor. The processing elements consist of a reduced instruction set CPU (RISC) with four floating-point coprocessor units and necessary memory interface functions. This architecture has been simulated for several benchmark programs including complex fast Fourier transform (FFT), complex inner product, trigonometric functions, and sort-merge routine. The results of this study indicate that the MVP can process a 1024-point complex FFT at a speed of 112 microsec (389 megaflops) while consuming approximately 618 W of power in a volume of approximately 0.1 ft-cubed.

A Family of ACO Routing Protocols for Mobile Ad Hoc Networks.

PubMed

Rupérez Cañas, Delfín; Sandoval Orozco, Ana Lucila; García Villalba, Luis Javier; Kim, Tai-Hoon

2017-05-22

In this work, an ACO routing protocol for mobile ad hoc networks based on AntHocNet is specified. As its predecessor, this new protocol, called AntOR, is hybrid in the sense that it contains elements from both reactive and proactive routing. Specifically, it combines a reactive route setup process with a proactive route maintenance and improvement process. Key aspects of the AntOR protocol are the disjoint-link and disjoint-node routes, separation between the regular pheromone and the virtual pheromone in the diffusion process and the exploration of routes, taking into consideration the number of hops in the best routes. In this work, a family of ACO routing protocols based on AntOR is also specified. These protocols are based on protocol successive refinements. In this work, we also present a parallelized version of AntOR that we call PAntOR. Using programming multiprocessor architectures based on the shared memory protocol, PAntOR allows running tasks in parallel using threads. This parallelization is applicable in the route setup phase, route local repair process and link failure notification. In addition, a variant of PAntOR that consists of having more than one interface, which we call PAntOR-MI (PAntOR-Multiple Interface), is specified. This approach parallelizes the sending of broadcast messages by interface through threads.

Load Forecasting Based Distribution System Network Reconfiguration -- A Distributed Data-Driven Approach

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

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load prediction and benefit the network reconfiguration. Because of the nonconvexity of the three-phase balanced optimal power flow, a second-order cone program (SOCP) based approach is used to relax the optimal power flow problem. Then, the alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the limited number of the switches and the increasing computation capability, themore » proposed network reconfiguration is solved in a parallel way. The numerical results demonstrate the feasible and effectiveness of the proposed approach.« less

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

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.

Performance Implications of Synchronization Support for Parallel FORTRAN Programs

DTIC Science & Technology

1991-06-17

applications we used in this study are BDNA and FLO52. BDNA is a molecular dy- I namics simulator for biomolecules in water and it uses ordinary...parallelism structures and loop granularity. In the BDNA program, most of the parallel loops are not nested and the iterations are 200-1000 instructions long...are of concern. The BDNA curve in Figure 21 shows that for this program only 17% of all 32 I I 100 BDNA -4 FLO52 -I 80 3 CumuilatQe percentage of3

Selective, Embedded, Just-In-Time Specialization (SEJITS): Portable Parallel Performance from Sequential, Productive, Embedded Domain-Specific Languages

DTIC Science & Technology

2012-12-01

identity operation SIMD Single instruction, multiple datastream parallel computing Scala A byte-compiled programming language featuring dynamic type...Specific Languages 5a. CONTRACT NUMBER FA8750-10-1-0191 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 61101E 6. AUTHOR(S) Armando Fox 5d...application performance, but usually must rely on efficiency programmers who are experts in explicit parallel programming to achieve it. Since such efficiency

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 Greenwich, to reduce potential errors made by users. Earlier tests on NAS Benchmarks and ARC3D have demonstrated good success of this tool. In this study, we have applied CAPO to parallelize three large applications in the area of computational fluid dynamics (CFD): OVERFLOW, TLNS3D and INS3D. These codes are widely used for solving Navier-Stokes equations with complicated boundary conditions and turbulence model in multiple zones. Each one comprises of from 50K to 1,00k lines of FORTRAN77. As an example, CAPO took 77 hours to complete the data dependence analysis of OVERFLOW on a workstation (SGI, 175MHz, R10K processor). A fair amount of effort was spent on correcting false dependencies due to lack of necessary knowledge during the analysis. Even so, CAPO provides an easy way for user to interact with the parallelization process. The OpenMP version was generated within a day after the analysis was completed. Due to sequential algorithms involved, code sections in TLNS3D and INS3D need to be restructured by hand to produce more efficient parallel codes. An included figure shows preliminary test results of the generated OVERFLOW with several test cases in single zone. The MPI data points for the small test case were taken from a handcoded MPI version. As we can see, CAPO's version has achieved 18 fold speed up on 32 nodes of the SGI O2K. For the small test case, it outperformed the MPI version. These results are very encouraging, but further work is needed. For example, although CAPO attempts to place directives on the outer- most parallel loops in an interprocedural framework, it does not insert directives based on the best manual strategy. In particular, it lacks the support of parallelization at the multi-zone level. Future work will emphasize on the development of methodology to work in a multi-zone level and with a hybrid approach. Development of tools to perform more complicated code transformation is also needed.

An engineering approach to automatic programming

NASA Technical Reports Server (NTRS)

Rubin, Stuart H.

1990-01-01

An exploratory study of the automatic generation and optimization of symbolic programs using DECOM - a prototypical requirement specification model implemented in pure LISP was undertaken. It was concluded, on the basis of this study, that symbolic processing languages such as LISP can support a style of programming based upon formal transformation and dependent upon the expression of constraints in an object-oriented environment. Such languages can represent all aspects of the software generation process (including heuristic algorithms for effecting parallel search) as dynamic processes since data and program are represented in a uniform format.

Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

PubMed

Bellucci, Michael A; Coker, David F

2011-07-28

We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

Concepts of Concurrent Programming

DTIC Science & Technology

1990-04-01

to the material presented. Carriero89 Carriero, N., and Gelernter, D. " How to Write Parallel Programs : A Guide to the Perplexed." ACM...between the architectures on which programs can be executed and the application domains from which problems are drawn. Our goal is to show how programs ...Sept. 1989), 251-510. Abstract: There are four papers: 1. Programming Languages for Distributed Computing Systems (52); 2. How to Write Parallel

NavP: Structured and Multithreaded Distributed Parallel Programming

NASA Technical Reports Server (NTRS)

Pan, Lei; Xu, Jingling

2006-01-01

This slide presentation reviews some of the issues around distributed parallel programming. It compares and contrast two methods of programming: Single Program Multiple Data (SPMD) with the Navigational Programming (NAVP). It then reviews the distributed sequential computing (DSC) method and the methodology of NavP. Case studies are presented. It also reviews the work that is being done to enable the NavP system.

Concurrent Collections (CnC): A new approach to parallel programming

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

Knobe, Kathleen

2010-05-07

A common approach in designing parallel languages is to provide some high level handles to manipulate the use of the parallel platform. This exposes some aspects of the target platform, for example, shared vs. distributed memory. It may expose some but not all types of parallelism, for example, data parallelism but not task parallelism. This approach must find a balance between the desire to provide a simple view for the domain expert and provide sufficient power for tuning. This is hard for any given architecture and harder if the language is to apply to a range of architectures. Either simplicitymore » or power is lost. Instead of viewing the language design problem as one of providing the programmer with high level handles, we view the problem as one of designing an interface. On one side of this interface is the programmer (domain expert) who knows the application but needs no knowledge of any aspects of the platform. On the other side of the interface is the performance expert (programmer or program) who demands maximal flexibility for optimizing the mapping to a wide range of target platforms (parallel / serial, shared / distributed, homogeneous / heterogeneous, etc.) but needs no knowledge of the domain. Concurrent Collections (CnC) is based on this separation of concerns. The talk will present CnC and its benefits. About the speaker. Kathleen Knobe has focused throughout her career on parallelism especially compiler technology, runtime system design and language design. She worked at Compass (aka Massachusetts Computer Associates) from 1980 to 1991 designing compilers for a wide range of parallel platforms for Thinking Machines, MasPar, Alliant, Numerix, and several government projects. In 1991 she decided to finish her education. After graduating from MIT in 1997, she joined Digital Equipment’s Cambridge Research Lab (CRL). She stayed through the DEC/Compaq/HP mergers and when CRL was acquired and absorbed by Intel. She currently works in the Software and Services Group / Technology Pathfinding and Innovation.« less

Concurrent Collections (CnC): A new approach to parallel programming

ScienceCinema

Knobe, Kathleen

2018-04-16

A common approach in designing parallel languages is to provide some high level handles to manipulate the use of the parallel platform. This exposes some aspects of the target platform, for example, shared vs. distributed memory. It may expose some but not all types of parallelism, for example, data parallelism but not task parallelism. This approach must find a balance between the desire to provide a simple view for the domain expert and provide sufficient power for tuning. This is hard for any given architecture and harder if the language is to apply to a range of architectures. Either simplicity or power is lost. Instead of viewing the language design problem as one of providing the programmer with high level handles, we view the problem as one of designing an interface. On one side of this interface is the programmer (domain expert) who knows the application but needs no knowledge of any aspects of the platform. On the other side of the interface is the performance expert (programmer or program) who demands maximal flexibility for optimizing the mapping to a wide range of target platforms (parallel / serial, shared / distributed, homogeneous / heterogeneous, etc.) but needs no knowledge of the domain. Concurrent Collections (CnC) is based on this separation of concerns. The talk will present CnC and its benefits. About the speaker. Kathleen Knobe has focused throughout her career on parallelism especially compiler technology, runtime system design and language design. She worked at Compass (aka Massachusetts Computer Associates) from 1980 to 1991 designing compilers for a wide range of parallel platforms for Thinking Machines, MasPar, Alliant, Numerix, and several government projects. In 1991 she decided to finish her education. After graduating from MIT in 1997, she joined Digital Equipment’s Cambridge Research Lab (CRL). She stayed through the DEC/Compaq/HP mergers and when CRL was acquired and absorbed by Intel. She currently works in the Software and Services Group / Technology Pathfinding and Innovation.

High Performance Programming Using Explicit Shared Memory Model on Cray T3D1

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Saini, Subhash; Grassi, Charles

1994-01-01

The Cray T3D system is the first-phase system in Cray Research, Inc.'s (CRI) three-phase massively parallel processing (MPP) program. This system features a heterogeneous architecture that closely couples DEC's Alpha microprocessors and CRI's parallel-vector technology, i.e., the Cray Y-MP and Cray C90. An overview of the Cray T3D hardware and available programming models is presented. Under Cray Research adaptive Fortran (CRAFT) model four programming methods (data parallel, work sharing, message-passing using PVM, and explicit shared memory model) are available to the users. However, at this time data parallel and work sharing programming models are not available to the user community. The differences between standard PVM and CRI's PVM are highlighted with performance measurements such as latencies and communication bandwidths. We have found that the performance of neither standard PVM nor CRI s PVM exploits the hardware capabilities of the T3D. The reasons for the bad performance of PVM as a native message-passing library are presented. This is illustrated by the performance of NAS Parallel Benchmarks (NPB) programmed in explicit shared memory model on Cray T3D. In general, the performance of standard PVM is about 4 to 5 times less than obtained by using explicit shared memory model. This degradation in performance is also seen on CM-5 where the performance of applications using native message-passing library CMMD on CM-5 is also about 4 to 5 times less than using data parallel methods. The issues involved (such as barriers, synchronization, invalidating data cache, aligning data cache etc.) while programming in explicit shared memory model are discussed. Comparative performance of NPB using explicit shared memory programming model on the Cray T3D and other highly parallel systems such as the TMC CM-5, Intel Paragon, Cray C90, IBM-SP1, etc. is presented.

Providing a parallel and distributed capability for JMASS using SPEEDES

NASA Astrophysics Data System (ADS)

Valinski, Maria; Driscoll, Jonathan; McGraw, Robert M.; Meyer, Bob

2002-07-01

The Joint Modeling And Simulation System (JMASS) is a Tri-Service simulation environment that supports engineering and engagement-level simulations. As JMASS is expanded to support other Tri-Service domains, the current set of modeling services must be expanded for High Performance Computing (HPC) applications by adding support for advanced time-management algorithms, parallel and distributed topologies, and high speed communications. By providing support for these services, JMASS can better address modeling domains requiring parallel computationally intense calculations such clutter, vulnerability and lethality calculations, and underwater-based scenarios. A risk reduction effort implementing some HPC services for JMASS using the SPEEDES (Synchronous Parallel Environment for Emulation and Discrete Event Simulation) Simulation Framework has recently concluded. As an artifact of the JMASS-SPEEDES integration, not only can HPC functionality be brought to the JMASS program through SPEEDES, but an additional HLA-based capability can be demonstrated that further addresses interoperability issues. The JMASS-SPEEDES integration provided a means of adding HLA capability to preexisting JMASS scenarios through an implementation of the standard JMASS port communication mechanism that allows players to communicate.

New Parallel Algorithms for Landscape Evolution Model

NASA Astrophysics Data System (ADS)

Jin, Y.; Zhang, H.; Shi, Y.

2017-12-01

Most landscape evolution models (LEM) developed in the last two decades solve the diffusion equation to simulate the transportation of surface sediments. This numerical approach is difficult to parallelize due to the computation of drainage area for each node, which needs huge amount of communication if run in parallel. In order to overcome this difficulty, we developed two parallel algorithms for LEM with a stream net. One algorithm handles the partition of grid with traditional methods and applies an efficient global reduction algorithm to do the computation of drainage areas and transport rates for the stream net; the other algorithm is based on a new partition algorithm, which partitions the nodes in catchments between processes first, and then partitions the cells according to the partition of nodes. Both methods focus on decreasing communication between processes and take the advantage of massive computing techniques, and numerical experiments show that they are both adequate to handle large scale problems with millions of cells. We implemented the two algorithms in our program based on the widely used finite element library deal.II, so that it can be easily coupled with ASPECT.

On program restructuring, scheduling, and communication for parallel processor systems

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

Polychronopoulos, Constantine D.

1986-08-01

This dissertation discusses several software and hardware aspects of program execution on large-scale, high-performance parallel processor systems. The issues covered are program restructuring, partitioning, scheduling and interprocessor communication, synchronization, and hardware design issues of specialized units. All this work was performed focusing on a single goal: to maximize program speedup, or equivalently, to minimize parallel execution time. Parafrase, a Fortran restructuring compiler was used to transform programs in a parallel form and conduct experiments. Two new program restructuring techniques are presented, loop coalescing and subscript blocking. Compile-time and run-time scheduling schemes are covered extensively. Depending on the program construct, thesemore » algorithms generate optimal or near-optimal schedules. For the case of arbitrarily nested hybrid loops, two optimal scheduling algorithms for dynamic and static scheduling are presented. Simulation results are given for a new dynamic scheduling algorithm. The performance of this algorithm is compared to that of self-scheduling. Techniques for program partitioning and minimization of interprocessor communication for idealized program models and for real Fortran programs are also discussed. The close relationship between scheduling, interprocessor communication, and synchronization becomes apparent at several points in this work. Finally, the impact of various types of overhead on program speedup and experimental results are presented.« less

Randomized, Controlled Trial of CBT Training for PTSD Providers

DTIC Science & Technology

2016-10-29

trial and comparative effectiveness study is to design, implement and evaluate a cost effective, web based self paced training program to provide skills...without web -centered supervision, may provide an effective means to train increasing numbers of mental health providers in relevant, evidence-based...in equal numbers to three parallel intervention condition: a) Web -based training plus web -centered supervision; b) Web - based training alone; and c

Simple and flexible SAS and SPSS programs for analyzing lag-sequential categorical data.

PubMed

O'Connor, B P

1999-11-01

This paper describes simple and flexible programs for analyzing lag-sequential categorical data, using SAS and SPSS. The programs read a stream of codes and produce a variety of lag-sequential statistics, including transitional frequencies, expected transitional frequencies, transitional probabilities, adjusted residuals, z values, Yule's Q values, likelihood ratio tests of stationarity across time and homogeneity across groups or segments, transformed kappas for unidirectional dependence, bidirectional dependence, parallel and nonparallel dominance, and significance levels based on both parametric and randomization tests.

Computational strategy for the solution of large strain nonlinear problems using the Wilkins explicit finite-difference approach

NASA Technical Reports Server (NTRS)

Hofmann, R.

1980-01-01

The STEALTH code system, which solves large strain, nonlinear continuum mechanics problems, was rigorously structured in both overall design and programming standards. The design is based on the theoretical elements of analysis while the programming standards attempt to establish a parallelism between physical theory, programming structure, and documentation. These features have made it easy to maintain, modify, and transport the codes. It has also guaranteed users a high level of quality control and quality assurance.

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

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

Before They Can Speak, They Must Know.

ERIC Educational Resources Information Center

Cromie, William J.; Edson, Lee

1984-01-01

Intelligent relationships with people are among the goals for tomorrow's computers. Knowledge-based systems used and being developed to achieve these goals are discussed. Automatic learning, producing inferences, parallelism, program languages, friendly machines, computer vision, and biomodels are among the topics considered. (JN)

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce

PubMed Central

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network’s initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data. PMID:27304987

Modelling parallel programs and multiprocessor architectures with AXE

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Fineman, Charles E.

1991-01-01

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

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.

Fine-grained parallelism accelerating for RNA secondary structure prediction with pseudoknots based on FPGA.

PubMed

Xia, Fei; Jin, Guoqing

2014-06-01

PKNOTS is a most famous benchmark program and has been widely used to predict RNA secondary structure including pseudoknots. It adopts the standard four-dimensional (4D) dynamic programming (DP) method and is the basis of many variants and improved algorithms. Unfortunately, the O(N(6)) computing requirements and complicated data dependency greatly limits the usefulness of PKNOTS package with the explosion in gene database size. In this paper, we present a fine-grained parallel PKNOTS package and prototype system for accelerating RNA folding application based on FPGA chip. We adopted a series of storage optimization strategies to resolve the "Memory Wall" problem. We aggressively exploit parallel computing strategies to improve computational efficiency. We also propose several methods that collectively reduce the storage requirements for FPGA on-chip memory. To the best of our knowledge, our design is the first FPGA implementation for accelerating 4D DP problem for RNA folding application including pseudoknots. The experimental results show a factor of more than 50x average speedup over the PKNOTS-1.08 software running on a PC platform with Intel Core2 Q9400 Quad CPU for input RNA sequences. However, the power consumption of our FPGA accelerator is only about 50% of the general-purpose micro-processors.

Flexbar 3.0 - SIMD and multicore parallelization.

PubMed

Roehr, Johannes T; Dieterich, Christoph; Reinert, Knut

2017-09-15

High-throughput sequencing machines can process many samples in a single run. For Illumina systems, sequencing reads are barcoded with an additional DNA tag that is contained in the respective sequencing adapters. The recognition of barcode and adapter sequences is hence commonly needed for the analysis of next-generation sequencing data. Flexbar performs demultiplexing based on barcodes and adapter trimming for such data. The massive amounts of data generated on modern sequencing machines demand that this preprocessing is done as efficiently as possible. We present Flexbar 3.0, the successor of the popular program Flexbar. It employs now twofold parallelism: multi-threading and additionally SIMD vectorization. Both types of parallelism are used to speed-up the computation of pair-wise sequence alignments, which are used for the detection of barcodes and adapters. Furthermore, new features were included to cover a wide range of applications. We evaluated the performance of Flexbar based on a simulated sequencing dataset. Our program outcompetes other tools in terms of speed and is among the best tools in the presented quality benchmark. https://github.com/seqan/flexbar. johannes.roehr@fu-berlin.de or knut.reinert@fu-berlin.de. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Instrumentation, performance visualization, and debugging tools for multiprocessors

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Fineman, Charles E.; Hontalas, Philip J.

1991-01-01

The need for computing power has forced a migration from serial computation on a single processor to parallel processing on multiprocessor architectures. However, without effective means to monitor (and visualize) program execution, debugging, and tuning parallel programs becomes intractably difficult as program complexity increases with the number of processors. Research on performance evaluation tools for multiprocessors is being carried out at ARC. Besides investigating new techniques for instrumenting, monitoring, and presenting the state of parallel program execution in a coherent and user-friendly manner, prototypes of software tools are being incorporated into the run-time environments of various hardware testbeds to evaluate their impact on user productivity. Our current tool set, the Ames Instrumentation Systems (AIMS), incorporates features from various software systems developed in academia and industry. The execution of FORTRAN programs on the Intel iPSC/860 can be automatically instrumented and monitored. Performance data collected in this manner can be displayed graphically on workstations supporting X-Windows. We have successfully compared various parallel algorithms for computational fluid dynamics (CFD) applications in collaboration with scientists from the Numerical Aerodynamic Simulation Systems Division. By performing these comparisons, we show that performance monitors and debuggers such as AIMS are practical and can illuminate the complex dynamics that occur within parallel programs.

SCELib2: the new revision of SCELib, the parallel computational library of molecular properties in the single center approach

NASA Astrophysics Data System (ADS)

Sanna, N.; Morelli, G.

2004-09-01

In this paper we present the new version of the SCELib program (CPC Catalogue identifier ADMG) a full numerical implementation of the Single Center Expansion (SCE) method. The physics involved is that of producing the SCE description of molecular electronic densities, of molecular electrostatic potentials and of molecular perturbed potentials due to a point negative or positive charge. This new revision of the program has been optimized to run in serial as well as in parallel execution mode, to support a larger set of molecular symmetries and to permit the restart of long-lasting calculations. To measure the performance of this new release, a comparative study has been carried out on the most powerful computing architectures in serial and parallel runs. The results of the calculations reported in this paper refer to real cases medium to large molecular systems and they are reported in full details to benchmark at best the parallel architectures the new SCELib code will run on. Program summaryTitle of program: SCELib2 Catalogue identifier: ADGU Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADGU Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Reference to previous versions: Comput. Phys. Commun. 128 (2) (2000) 139 (CPC catalogue identifier: ADMG) Does the new version supersede the original program?: Yes Computer for which the program is designed and others on which it has been tested: HP ES45 and rx2600, SUN ES4500, IBM SP and any single CPU workstation based on Alpha, SPARC, POWER, Itanium2 and X86 processors Installations: CASPUR, local Operating systems under which the program has been tested: HP Tru64 V5.X, SUNOS V5.8, IBM AIX V5.X, Linux RedHat V8.0 Programming language used: C Memory required to execute with typical data: 10 Mwords. Up to 2000 Mwords depending on the molecular system and runtime parameters No. of bits in a word: 64 No. of processors used: 1 to 32 Has the code been vectorized or parallelized?: Yes No. of bytes in distributed program, including test data, etc.: 3 798 507 No. of lines in distributed program, including test data, etc.: 187 226 Distribution format: tar.gz Nature of physical problem: In this set of codes an efficient procedure is implemented to describe the wavefunction and related molecular properties of a polyatomic molecular system within the Single Center of Expansion (SCE) approximation. The resulting SCE wavefunction, electron density, electrostatic and exchange/correlation potentials can then be used via a proper Application Programming Interface (API) to describe the target molecular system which can be employed in electron-molecule scattering calculations. The molecular properties expanded over a single center turn out to also be of more general application and some possible uses in quantum chemistry, biomodelling and drug design are also outlined. Method of solution: The polycentre Hartee-Fock solution for a molecule of arbitrary geometry, based on linear combination of Gaussian-Type Orbital (GTO), is expanded over a single center, typically the Center Of Mass (C.O.M.), by means of a Gauss-Legendre/Chebyschev quadrature over the θ, φ angular coordinates. The resulting SCE numerical wavefunction is then used to calculate the one-particle electron density, the electrostatic potential and two different models for the correlation/polarization potentials induced by the impinging electron, which have the correct asymptotic behaviour for the leading dipole molecular polarizabilities. Restrictions on the complexity of the problem: Depending on the molecular system under study and on the operating conditions the program may or may not fit into available RAM memory. In this case a feature of the program is to memory map a disk file in order to efficiently access the memory data through a disk device. Typical running time: The execution time strongly depends on the molecular target description and on the hardware/OS chosen, it is directly proportional to the ( r, θ, φ) grid size and to the number of angular basis functions used. Thus, from the program printout of the main arrays memory occupancy, the user can approximately derive the expected computer time needed for a given calculation executed in serial mode. For parallel executions the overall efficiency must be further taken into account, and this depends on the no. of processors used as well as on the parallel architecture chosen, so a simple general law is at present not determinable. Unusual features of the program: The code has been engineered to use dynamical, runtime determined, global parameters with the aim to have all the data fitted in the RAM memory. Some unusual circumstances, e.g., when using large values of those parameters, may cause the program to run with unexpected performance reductions due to runtime bottlenecks like those caused by memory swap operations which strongly depend on the hardware used. In such cases, a parallel execution of the code is generally sufficient to fix the problem since the data size is partitioned over the available processors. When a suitable parallel system is not available for execution, a mechanism of memory mapped file can be used; with this option on, all the available memory will be used as a buffer for a disk file which contains the whole data set, thus having a better throughput with respect to the traditional swapping/paging of the Unix OS.

Parallelization and checkpointing of GPU applications through program transformation

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

Solano-Quinde, Lizandro Damian

2012-01-01

GPUs have emerged as a powerful tool for accelerating general-purpose applications. The availability of programming languages that makes writing general-purpose applications for running on GPUs tractable have consolidated GPUs as an alternative for accelerating general purpose applications. Among the areas that have benefited from GPU acceleration are: signal and image processing, computational fluid dynamics, quantum chemistry, and, in general, the High Performance Computing (HPC) Industry. In order to continue to exploit higher levels of parallelism with GPUs, multi-GPU systems are gaining popularity. In this context, single-GPU applications are parallelized for running in multi-GPU systems. Furthermore, multi-GPU systems help to solvemore » the GPU memory limitation for applications with large application memory footprint. Parallelizing single-GPU applications has been approached by libraries that distribute the workload at runtime, however, they impose execution overhead and are not portable. On the other hand, on traditional CPU systems, parallelization has been approached through application transformation at pre-compile time, which enhances the application to distribute the workload at application level and does not have the issues of library-based approaches. Hence, a parallelization scheme for GPU systems based on application transformation is needed. Like any computing engine of today, reliability is also a concern in GPUs. GPUs are vulnerable to transient and permanent failures. Current checkpoint/restart techniques are not suitable for systems with GPUs. Checkpointing for GPU systems present new and interesting challenges, primarily due to the natural differences imposed by the hardware design, the memory subsystem architecture, the massive number of threads, and the limited amount of synchronization among threads. Therefore, a checkpoint/restart technique suitable for GPU systems is needed. The goal of this work is to exploit higher levels of parallelism and to develop support for application-level fault tolerance in applications using multiple GPUs. Our techniques reduce the burden of enhancing single-GPU applications to support these features. To achieve our goal, this work designs and implements a framework for enhancing a single-GPU OpenCL application through application transformation.« less

Japanese project aims at supercomputer that executes 10 gflops

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

Burskey, D.

1984-05-03

Dubbed supercom by its multicompany design team, the decade-long project's goal is an engineering supercomputer that can execute 10 billion floating-point operations/s-about 20 times faster than today's supercomputers. The project, guided by Japan's Ministry of International Trade and Industry (MITI) and the Agency of Industrial Science and Technology encompasses three parallel research programs, all aimed at some angle of the superconductor. One program should lead to superfast logic and memory circuits, another to a system architecture that will afford the best performance, and the last to the software that will ultimately control the computer. The work on logic and memorymore » chips is based on: GAAS circuit; Josephson junction devices; and high electron mobility transistor structures. The architecture will involve parallel processing.« less

A practical guide to replica-exchange Wang—Landau simulations

NASA Astrophysics Data System (ADS)

Vogel, Thomas; Li, Ying Wai; Landau, David P.

2018-04-01

This paper is based on a series of tutorial lectures about the replica-exchange Wang-Landau (REWL) method given at the IX Brazilian Meeting on Simulational Physics (BMSP 2017). It provides a practical guide for the implementation of the method. A complete example code for a model system is available online. In this paper, we discuss the main parallel features of this code after a brief introduction to the REWL algorithm. The tutorial section is mainly directed at users who have written a single-walker Wang–Landau program already but might have just taken their first steps in parallel programming using the Message Passing Interface (MPI). In the last section, we answer “frequently asked questions” from users about the implementation of REWL for different scientific problems.

Towards the integration of medical informatics education for clinicians into the medical curriculum.

PubMed

Lungeanu, Diana; Tractenberg, Rochelle E; Bersan, Otilia S; Mihalas, George I

2009-01-01

In the context of an existing first year, one-semester mandatory course of medical informatics (MI) for medical students, we tested an interactive teaching approach in parallel with the traditional academic program. After six semesters (at the beginning of the clinical stage) we collected feedback from the former students in the two parallel programs (with anonymous questionnaires comprising both subjectively-rated items and open-ended questions). We conclude that an introductory course on information and communication technology and information skills can be useful at the beginning of the medical curriculum, while an interactive, problem-based-learning-type MI course should be included during the clinical stage. Early development of these skills, and their use/utility across the curriculum, are important aspects of integrating MI education into clinical training.

GraphReduce: Processing Large-Scale Graphs on Accelerator-Based Systems

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

Sengupta, Dipanjan; Song, Shuaiwen; Agarwal, Kapil

2015-11-15

Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the host andmore » device.« less

Parallel computation with the force

NASA Technical Reports Server (NTRS)

Jordan, H. F.

1985-01-01

A methodology, called the force, supports the construction of programs to be executed in parallel by a force of processes. The number of processes in the force is unspecified, but potentially very large. The force idea is embodied in a set of macros which produce multiproceossor FORTRAN code and has been studied on two shared memory multiprocessors of fairly different character. The method has simplified the writing of highly parallel programs within a limited class of parallel algorithms and is being extended to cover a broader class. The individual parallel constructs which comprise the force methodology are discussed. Of central concern are their semantics, implementation on different architectures and performance implications.

The Use of a Microcomputer Based Array Processor for Real Time Laser Velocimeter Data Processing

NASA Technical Reports Server (NTRS)

Meyers, James F.

1990-01-01

The application of an array processor to laser velocimeter data processing is presented. The hardware is described along with the method of parallel programming required by the array processor. A portion of the data processing program is described in detail. The increase in computational speed of a microcomputer equipped with an array processor is illustrated by comparative testing with a minicomputer.

Nonlinear relaxation algorithms for circuit simulation

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

Saleh, R.A.

Circuit simulation is an important Computer-Aided Design (CAD) tool in the design of Integrated Circuits (IC). However, the standard techniques used in programs such as SPICE result in very long computer-run times when applied to large problems. In order to reduce the overall run time, a number of new approaches to circuit simulation were developed and are described. These methods are based on nonlinear relaxation techniques and exploit the relative inactivity of large circuits. Simple waveform-processing techniques are described to determine the maximum possible speed improvement that can be obtained by exploiting this property of large circuits. Three simulation algorithmsmore » are described, two of which are based on the Iterated Timing Analysis (ITA) method and a third based on the Waveform-Relaxation Newton (WRN) method. New programs that incorporate these techniques were developed and used to simulate a variety of industrial circuits. The results from these simulations are provided. The techniques are shown to be much faster than the standard approach. In addition, a number of parallel aspects of these algorithms are described, and a general space-time model of parallel-task scheduling is developed.« less

Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures

NASA Technical Reports Server (NTRS)

Biegel, Bryan A. (Technical Monitor); Jost, G.; Jin, H.; Labarta J.; Gimenez, J.; Caubet, J.

2003-01-01

Parallel programming paradigms include process level parallelism, thread level parallelization, and multilevel parallelism. This viewgraph presentation describes a detailed performance analysis of these paradigms for Shared Memory Architecture (SMA). This analysis uses the Paraver Performance Analysis System. The presentation includes diagrams of a flow of useful computations.

Methodologies and systems for heterogeneous concurrent computing

NASA Technical Reports Server (NTRS)

Sunderam, V. S.

1994-01-01

Heterogeneous concurrent computing is gaining increasing acceptance as an alternative or complementary paradigm to multiprocessor-based parallel processing as well as to conventional supercomputing. While algorithmic and programming aspects of heterogeneous concurrent computing are similar to their parallel processing counterparts, system issues, partitioning and scheduling, and performance aspects are significantly different. In this paper, we discuss critical design and implementation issues in heterogeneous concurrent computing, and describe techniques for enhancing its effectiveness. In particular, we highlight the system level infrastructures that are required, aspects of parallel algorithm development that most affect performance, system capabilities and limitations, and tools and methodologies for effective computing in heterogeneous networked environments. We also present recent developments and experiences in the context of the PVM system and comment on ongoing and future work.

Simulating electron wave dynamics in graphene superlattices exploiting parallel processing advantages

NASA Astrophysics Data System (ADS)

Rodrigues, Manuel J.; Fernandes, David E.; Silveirinha, Mário G.; Falcão, Gabriel

2018-01-01

This work introduces a parallel computing framework to characterize the propagation of electron waves in graphene-based nanostructures. The electron wave dynamics is modeled using both "microscopic" and effective medium formalisms and the numerical solution of the two-dimensional massless Dirac equation is determined using a Finite-Difference Time-Domain scheme. The propagation of electron waves in graphene superlattices with localized scattering centers is studied, and the role of the symmetry of the microscopic potential in the electron velocity is discussed. The computational methodologies target the parallel capabilities of heterogeneous multi-core CPU and multi-GPU environments and are built with the OpenCL parallel programming framework which provides a portable, vendor agnostic and high throughput-performance solution. The proposed heterogeneous multi-GPU implementation achieves speedup ratios up to 75x when compared to multi-thread and multi-core CPU execution, reducing simulation times from several hours to a couple of minutes.

76 FR 62808 - Pilot Program for Parallel Review of Medical Products

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-11

... voluntary participation in the pilot program, as well as the guiding principles the Agencies intend to... 57045), parallel review is intended to reduce the time between FDA marketing approval and CMS national...

Algorithms and programming tools for image processing on the MPP

NASA Technical Reports Server (NTRS)

Reeves, A. P.

1985-01-01

Topics addressed include: data mapping and rotational algorithms for the Massively Parallel Processor (MPP); Parallel Pascal language; documentation for the Parallel Pascal Development system; and a description of the Parallel Pascal language used on the MPP.

A Parallel Vector Machine for the PM Programming Language

NASA Astrophysics Data System (ADS)

Bellerby, Tim

2016-04-01

PM is a new programming language which aims to make the writing of computational geoscience models on parallel hardware accessible to scientists who are not themselves expert parallel programmers. It is based around the concept of communicating operators: language constructs that enable variables local to a single invocation of a parallelised loop to be viewed as if they were arrays spanning the entire loop domain. This mechanism enables different loop invocations (which may or may not be executing on different processors) to exchange information in a manner that extends the successful Communicating Sequential Processes idiom from single messages to collective communication. Communicating operators avoid the additional synchronisation mechanisms, such as atomic variables, required when programming using the Partitioned Global Address Space (PGAS) paradigm. Using a single loop invocation as the fundamental unit of concurrency enables PM to uniformly represent different levels of parallelism from vector operations through shared memory systems to distributed grids. This paper describes an implementation of PM based on a vectorised virtual machine. On a single processor node, concurrent operations are implemented using masked vector operations. Virtual machine instructions operate on vectors of values and may be unmasked, masked using a Boolean field, or masked using an array of active vector cell locations. Conditional structures (such as if-then-else or while statement implementations) calculate and apply masks to the operations they control. A shift in mask representation from Boolean to location-list occurs when active locations become sufficiently sparse. Parallel loops unfold data structures (or vectors of data structures for nested loops) into vectors of values that may additionally be distributed over multiple computational nodes and then split into micro-threads compatible with the size of the local cache. Inter-node communication is accomplished using standard OpenMP and MPI. Performance analyses of the PM vector machine, demonstrating its scaling properties with respect to domain size and the number of processor nodes will be presented for a range of hardware configurations. The PM software and language definition are being made available under unrestrictive MIT and Creative Commons Attribution licenses respectively: www.pm-lang.org.

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.

Program Correctness, Verification and Testing for Exascale (Corvette)

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

Sen, Koushik; Iancu, Costin; Demmel, James W

The goal of this project is to provide tools to assess the correctness of parallel programs written using hybrid parallelism. There is a dire lack of both theoretical and engineering know-how in the area of finding bugs in hybrid or large scale parallel programs, which our research aims to change. In the project we have demonstrated novel approaches in several areas: 1. Low overhead automated and precise detection of concurrency bugs at scale. 2. Using low overhead bug detection tools to guide speculative program transformations for performance. 3. Techniques to reduce the concurrency required to reproduce a bug using partialmore » program restart/replay. 4. Techniques to provide reproducible execution of floating point programs. 5. Techniques for tuning the floating point precision used in codes.« less

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.

Parallelization of NAS Benchmarks for Shared Memory Multiprocessors

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry C.; Saini, Subhash (Technical Monitor)

1998-01-01

This paper presents our experiences of parallelizing the sequential implementation of NAS benchmarks using compiler directives on SGI Origin2000 distributed shared memory (DSM) system. Porting existing applications to new high performance parallel and distributed computing platforms is a challenging task. Ideally, a user develops a sequential version of the application, leaving the task of porting to new generations of high performance computing systems to parallelization tools and compilers. Due to the simplicity of programming shared-memory multiprocessors, compiler developers have provided various facilities to allow the users to exploit parallelism. Native compilers on SGI Origin2000 support multiprocessing directives to allow users to exploit loop-level parallelism in their programs. Additionally, supporting tools can accomplish this process automatically and present the results of parallelization to the users. We experimented with these compiler directives and supporting tools by parallelizing sequential implementation of NAS benchmarks. Results reported in this paper indicate that with minimal effort, the performance gain is comparable with the hand-parallelized, carefully optimized, message-passing implementations of the same benchmarks.

GASPRNG: GPU accelerated scalable parallel random number generator library

NASA Astrophysics Data System (ADS)

Gao, Shuang; Peterson, Gregory D.

2013-04-01

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

Exploiting Symmetry on Parallel Architectures.

NASA Astrophysics Data System (ADS)

Stiller, Lewis Benjamin

1995-01-01

This thesis describes techniques for the design of parallel programs that solve well-structured problems with inherent symmetry. Part I demonstrates the reduction of such problems to generalized matrix multiplication by a group-equivariant matrix. Fast techniques for this multiplication are described, including factorization, orbit decomposition, and Fourier transforms over finite groups. Our algorithms entail interaction between two symmetry groups: one arising at the software level from the problem's symmetry and the other arising at the hardware level from the processors' communication network. Part II illustrates the applicability of our symmetry -exploitation techniques by presenting a series of case studies of the design and implementation of parallel programs. First, a parallel program that solves chess endgames by factorization of an associated dihedral group-equivariant matrix is described. This code runs faster than previous serial programs, and discovered it a number of results. Second, parallel algorithms for Fourier transforms for finite groups are developed, and preliminary parallel implementations for group transforms of dihedral and of symmetric groups are described. Applications in learning, vision, pattern recognition, and statistics are proposed. Third, parallel implementations solving several computational science problems are described, including the direct n-body problem, convolutions arising from molecular biology, and some communication primitives such as broadcast and reduce. Some of our implementations ran orders of magnitude faster than previous techniques, and were used in the investigation of various physical phenomena.

A set of parallel, implicit methods for a reconstructed discontinuous Galerkin method for compressible flows on 3D hybrid grids

DOE PAGES

Xia, Yidong; Luo, Hong; Frisbey, Megan; ...

2014-07-01

A set of implicit methods are proposed for a third-order hierarchical WENO reconstructed discontinuous Galerkin method for compressible flows on 3D hybrid grids. An attractive feature in these methods are the application of the Jacobian matrix based on the P1 element approximation, resulting in a huge reduction of memory requirement compared with DG (P2). Also, three approaches -- analytical derivation, divided differencing, and automatic differentiation (AD) are presented to construct the Jacobian matrix respectively, where the AD approach shows the best robustness. A variety of compressible flow problems are computed to demonstrate the fast convergence property of the implemented flowmore » solver. Furthermore, an SPMD (single program, multiple data) programming paradigm based on MPI is proposed to achieve parallelism. The numerical results on complex geometries indicate that this low-storage implicit method can provide a viable and attractive DG solution for complicated flows of practical importance.« less

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

NASA Astrophysics Data System (ADS)

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

1995-03-01

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

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

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

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

1995-04-01

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

Parallelization and automatic data distribution for nuclear reactor simulations

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

Liebrock, L.M.

1997-07-01

Detailed attempts at realistic nuclear reactor simulations currently take many times real time to execute on high performance workstations. Even the fastest sequential machine can not run these simulations fast enough to ensure that the best corrective measure is used during a nuclear accident to prevent a minor malfunction from becoming a major catastrophe. Since sequential computers have nearly reached the speed of light barrier, these simulations will have to be run in parallel to make significant improvements in speed. In physical reactor plants, parallelism abounds. Fluids flow, controls change, and reactions occur in parallel with only adjacent components directlymore » affecting each other. These do not occur in the sequentialized manner, with global instantaneous effects, that is often used in simulators. Development of parallel algorithms that more closely approximate the real-world operation of a reactor may, in addition to speeding up the simulations, actually improve the accuracy and reliability of the predictions generated. Three types of parallel architecture (shared memory machines, distributed memory multicomputers, and distributed networks) are briefly reviewed as targets for parallelization of nuclear reactor simulation. Various parallelization models (loop-based model, shared memory model, functional model, data parallel model, and a combined functional and data parallel model) are discussed along with their advantages and disadvantages for nuclear reactor simulation. A variety of tools are introduced for each of the models. Emphasis is placed on the data parallel model as the primary focus for two-phase flow simulation. Tools to support data parallel programming for multiple component applications and special parallelization considerations are also discussed.« less

ORCA Project: Research on high-performance parallel computer programming environments. Final report, 1 Apr-31 Mar 90

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

Snyder, L.; Notkin, D.; Adams, L.

1990-03-31

This task relates to research on programming massively parallel computers. Previous work on the Ensamble concept of programming was extended and investigation into nonshared memory models of parallel computation was undertaken. Previous work on the Ensamble concept defined a set of programming abstractions and was used to organize the programming task into three distinct levels; Composition of machine instruction, composition of processes, and composition of phases. It was applied to shared memory models of computations. During the present research period, these concepts were extended to nonshared memory models. During the present research period, one Ph D. thesis was completed, onemore » book chapter, and six conference proceedings were published.« less

Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

NASA Technical Reports Server (NTRS)

Sun, Xian-He

1997-01-01

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

The parallel programming of voluntary and reflexive saccades.

PubMed

Walker, Robin; McSorley, Eugene

2006-06-01

A novel two-step paradigm was used to investigate the parallel programming of consecutive, stimulus-elicited ('reflexive') and endogenous ('voluntary') saccades. The mean latency of voluntary saccades, made following the first reflexive saccades in two-step conditions, was significantly reduced compared to that of voluntary saccades made in the single-step control trials. The latency of the first reflexive saccades was modulated by the requirement to make a second saccade: first saccade latency increased when a second voluntary saccade was required in the opposite direction to the first saccade, and decreased when a second saccade was required in the same direction as the first reflexive saccade. A second experiment confirmed the basic effect and also showed that a second reflexive saccade may be programmed in parallel with a first voluntary saccade. The results support the view that voluntary and reflexive saccades can be programmed in parallel on a common motor map.

GLAD: a system for developing and deploying large-scale bioinformatics grid.

PubMed

Teo, Yong-Meng; Wang, Xianbing; Ng, Yew-Kwong

2005-03-01

Grid computing is used to solve large-scale bioinformatics problems with gigabytes database by distributing the computation across multiple platforms. Until now in developing bioinformatics grid applications, it is extremely tedious to design and implement the component algorithms and parallelization techniques for different classes of problems, and to access remotely located sequence database files of varying formats across the grid. In this study, we propose a grid programming toolkit, GLAD (Grid Life sciences Applications Developer), which facilitates the development and deployment of bioinformatics applications on a grid. GLAD has been developed using ALiCE (Adaptive scaLable Internet-based Computing Engine), a Java-based grid middleware, which exploits the task-based parallelism. Two bioinformatics benchmark applications, such as distributed sequence comparison and distributed progressive multiple sequence alignment, have been developed using GLAD.

Incremental Parallelization of Non-Data-Parallel Programs Using the Charon Message-Passing Library

NASA Technical Reports Server (NTRS)

VanderWijngaart, Rob F.

2000-01-01

Message passing is among the most popular techniques for parallelizing scientific programs on distributed-memory architectures. The reasons for its success are wide availability (MPI), efficiency, and full tuning control provided to the programmer. A major drawback, however, is that incremental parallelization, as offered by compiler directives, is not generally possible, because all data structures have to be changed throughout the program simultaneously. Charon remedies this situation through mappings between distributed and non-distributed data. It allows breaking up the parallelization into small steps, guaranteeing correctness at every stage. Several tools are available to help convert legacy codes into high-performance message-passing programs. They usually target data-parallel applications, whose loops carrying most of the work can be distributed among all processors without much dependency analysis. Others do a full dependency analysis and then convert the code virtually automatically. Even more toolkits are available that aid construction from scratch of message passing programs. None, however, allows piecemeal translation of codes with complex data dependencies (i.e. non-data-parallel programs) into message passing codes. The Charon library (available in both C and Fortran) provides incremental parallelization capabilities by linking legacy code arrays with distributed arrays. During the conversion process, non-distributed and distributed arrays exist side by side, and simple mapping functions allow the programmer to switch between the two in any location in the program. Charon also provides wrapper functions that leave the structure of the legacy code intact, but that allow execution on truly distributed data. Finally, the library provides a rich set of communication functions that support virtually all patterns of remote data demands in realistic structured grid scientific programs, including transposition, nearest-neighbor communication, pipelining, gather/scatter, and redistribution. At the end of the conversion process most intermediate Charon function calls will have been removed, the non-distributed arrays will have been deleted, and virtually the only remaining Charon functions calls are the high-level, highly optimized communications. Distribution of the data is under complete control of the programmer, although a wide range of useful distributions is easily available through predefined functions. A crucial aspect of the library is that it does not allocate space for distributed arrays, but accepts programmer-specified memory. This has two major consequences. First, codes parallelized using Charon do not suffer from encapsulation; user data is always directly accessible. This provides high efficiency, and also retains the possibility of using message passing directly for highly irregular communications. Second, non-distributed arrays can be interpreted as (trivial) distributions in the Charon sense, which allows them to be mapped to truly distributed arrays, and vice versa. This is the mechanism that enables incremental parallelization. In this paper we provide a brief introduction of the library and then focus on the actual steps in the parallelization process, using some representative examples from, among others, the NAS Parallel Benchmarks. We show how a complicated two-dimensional pipeline-the prototypical non-data-parallel algorithm- can be constructed with ease. To demonstrate the flexibility of the library, we give examples of the stepwise, efficient parallel implementation of nonlocal boundary conditions common in aircraft simulations, as well as the construction of the sequence of grids required for multigrid.

78 FR 76628 - Pilot Program for Parallel Review of Medical Products; Extension of the Duration of the Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-18

...The Food and Drug Administration (FDA) and the Centers for Medicare and Medicaid Services (CMS) (the Agencies) are announcing the extension of the ``Pilot Program for Parallel Review of Medical Products.'' The Agencies have decided to continue the program as currently designed for an additional period of 2 years from the date of publication of this notice.

Models@Home: distributed computing in bioinformatics using a screensaver based approach.

PubMed

Krieger, Elmar; Vriend, Gert

2002-02-01

Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.

Computing Gröbner and Involutive Bases for Linear Systems of Difference Equations

NASA Astrophysics Data System (ADS)

Yanovich, Denis

2018-02-01

The computation of involutive bases and Gröbner bases for linear systems of difference equations is solved and its importance for physical and mathematical problems is discussed. The algorithm and issues concerning its implementation in C are presented and calculation times are compared with the competing programs. The paper ends with consideration on the parallel version of this implementation and its scalability.

Integrated Task and Data Parallel Programming

NASA Technical Reports Server (NTRS)

Grimshaw, A. S.

1998-01-01

This research investigates the combination of task and data parallel language constructs within a single programming language. There are an number of applications that exhibit properties which would be well served by such an integrated language. Examples include global climate models, aircraft design problems, and multidisciplinary design optimization problems. Our approach incorporates data parallel language constructs into an existing, object oriented, task parallel language. The language will support creation and manipulation of parallel classes and objects of both types (task parallel and data parallel). Ultimately, the language will allow data parallel and task parallel classes to be used either as building blocks or managers of parallel objects of either type, thus allowing the development of single and multi-paradigm parallel applications. 1995 Research Accomplishments In February I presented a paper at Frontiers 1995 describing the design of the data parallel language subset. During the spring I wrote and defended my dissertation proposal. Since that time I have developed a runtime model for the language subset. I have begun implementing the model and hand-coding simple examples which demonstrate the language subset. I have identified an astrophysical fluid flow application which will validate the data parallel language subset. 1996 Research Agenda Milestones for the coming year include implementing a significant portion of the data parallel language subset over the Legion system. Using simple hand-coded methods, I plan to demonstrate (1) concurrent task and data parallel objects and (2) task parallel objects managing both task and data parallel objects. My next steps will focus on constructing a compiler and implementing the fluid flow application with the language. Concurrently, I will conduct a search for a real-world application exhibiting both task and data parallelism within the same program. Additional 1995 Activities During the fall I collaborated with Andrew Grimshaw and Adam Ferrari to write a book chapter which will be included in Parallel Processing in C++ edited by Gregory Wilson. I also finished two courses, Compilers and Advanced Compilers, in 1995. These courses complete my class requirements at the University of Virginia. I have only my dissertation research and defense to complete.

Integrated Task And Data Parallel Programming: Language Design

NASA Technical Reports Server (NTRS)

Grimshaw, Andrew S.; West, Emily A.

1998-01-01

his research investigates the combination of task and data parallel language constructs within a single programming language. There are an number of applications that exhibit properties which would be well served by such an integrated language. Examples include global climate models, aircraft design problems, and multidisciplinary design optimization problems. Our approach incorporates data parallel language constructs into an existing, object oriented, task parallel language. The language will support creation and manipulation of parallel classes and objects of both types (task parallel and data parallel). Ultimately, the language will allow data parallel and task parallel classes to be used either as building blocks or managers of parallel objects of either type, thus allowing the development of single and multi-paradigm parallel applications. 1995 Research Accomplishments In February I presented a paper at Frontiers '95 describing the design of the data parallel language subset. During the spring I wrote and defended my dissertation proposal. Since that time I have developed a runtime model for the language subset. I have begun implementing the model and hand-coding simple examples which demonstrate the language subset. I have identified an astrophysical fluid flow application which will validate the data parallel language subset. 1996 Research Agenda Milestones for the coming year include implementing a significant portion of the data parallel language subset over the Legion system. Using simple hand-coded methods, I plan to demonstrate (1) concurrent task and data parallel objects and (2) task parallel objects managing both task and data parallel objects. My next steps will focus on constructing a compiler and implementing the fluid flow application with the language. Concurrently, I will conduct a search for a real-world application exhibiting both task and data parallelism within the same program m. Additional 1995 Activities During the fall I collaborated with Andrew Grimshaw and Adam Ferrari to write a book chapter which will be included in Parallel Processing in C++ edited by Gregory Wilson. I also finished two courses, Compilers and Advanced Compilers, in 1995. These courses complete my class requirements at the University of Virginia. I have only my dissertation research and defense to complete.

Automatic Management of Parallel and Distributed System Resources

NASA Technical Reports Server (NTRS)

Yan, Jerry; Ngai, Tin Fook; Lundstrom, Stephen F.

1990-01-01

Viewgraphs on automatic management of parallel and distributed system resources are presented. Topics covered include: parallel applications; intelligent management of multiprocessing systems; performance evaluation of parallel architecture; dynamic concurrent programs; compiler-directed system approach; lattice gaseous cellular automata; and sparse matrix Cholesky factorization.

Machine Learning Based Online Performance Prediction for Runtime Parallelization and Task Scheduling

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

Li, J; Ma, X; Singh, K

2008-10-09

With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as well as developing next-generation software requires assistance from hardware, compilers and runtime systems to exploit parallelism transparently within applications. These systems must decompose applications into tasks that can be executed in parallel and then schedule those tasks to minimize load imbalance. However, many systems lack a priori knowledge about the execution time of all tasks to perform effective load balancing with low scheduling overhead. In this paper, we approach this fundamental problem using machine learning techniques first to generatemore » performance models for all tasks and then applying those models to perform automatic performance prediction across program executions. We also extend an existing scheduling algorithm to use generated task cost estimates for online task partitioning and scheduling. We implement the above techniques in the pR framework, which transparently parallelizes scripts in the popular R language, and evaluate their performance and overhead with both a real-world application and a large number of synthetic representative test scripts. Our experimental results show that our proposed approach significantly improves task partitioning and scheduling, with maximum improvements of 21.8%, 40.3% and 22.1% and average improvements of 15.9%, 16.9% and 4.2% for LMM (a real R application) and synthetic test cases with independent and dependent tasks, respectively.« less

Graphics-Based Parallel Programming Tools

DTIC Science & Technology

1991-09-01

mean "beyond" (as in " paranormal "). emphasizing the fact that the editor supports the specification of not just single graphs, but entire graph...conflicting dependencies: all processes see the three steps in the same order and all interprocess communication happens within a step. 6 Not all abstract

Describing, using 'recognition cones'. [parallel-series model with English-like computer program

NASA Technical Reports Server (NTRS)

Uhr, L.

1973-01-01

A parallel-serial 'recognition cone' model is examined, taking into account the model's ability to describe scenes of objects. An actual program is presented in an English-like language. The concept of a 'description' is discussed together with possible types of descriptive information. Questions regarding the level and the variety of detail are considered along with approaches for improving the serial representations of parallel systems.

A Family of ACO Routing Protocols for Mobile Ad Hoc Networks

PubMed Central

Rupérez Cañas, Delfín; Sandoval Orozco, Ana Lucila; García Villalba, Luis Javier; Kim, Tai-hoon

2017-01-01

In this work, an ACO routing protocol for mobile ad hoc networks based on AntHocNet is specified. As its predecessor, this new protocol, called AntOR, is hybrid in the sense that it contains elements from both reactive and proactive routing. Specifically, it combines a reactive route setup process with a proactive route maintenance and improvement process. Key aspects of the AntOR protocol are the disjoint-link and disjoint-node routes, separation between the regular pheromone and the virtual pheromone in the diffusion process and the exploration of routes, taking into consideration the number of hops in the best routes. In this work, a family of ACO routing protocols based on AntOR is also specified. These protocols are based on protocol successive refinements. In this work, we also present a parallelized version of AntOR that we call PAntOR. Using programming multiprocessor architectures based on the shared memory protocol, PAntOR allows running tasks in parallel using threads. This parallelization is applicable in the route setup phase, route local repair process and link failure notification. In addition, a variant of PAntOR that consists of having more than one interface, which we call PAntOR-MI (PAntOR-Multiple Interface), is specified. This approach parallelizes the sending of broadcast messages by interface through threads. PMID:28531159

Advanced space system concepts and their orbital support needs (1980 - 2000). Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Bekey, I.; Mayer, H. L.; Wolfe, M. G.

1976-01-01

The likely system concepts which might be representative of NASA and DoD space programs in the 1980-2000 time period were studied along with the programs' likely needs for major space transportation vehicles, orbital support vehicles, and technology developments which could be shared by the military and civilian space establishments in that time period. Such needs could then be used by NASA as an input in determining the nature of its long-range development plan. The approach used was to develop a list of possible space system concepts (initiatives) in parallel with a list of needs based on consideration of the likely environments and goals of the future. The two lists thus obtained represented what could be done, regardless of need; and what should be done, regardless of capability, respectively. A set of development program plans for space application concepts was then assembled, matching needs against capabilities, and the requirements of the space concepts for support vehicles, transportation, and technology were extracted. The process was pursued in parallel for likely military and civilian programs, and the common support needs thus identified.

Effects of a Prototype Internet Dissonance-Based Eating Disorder Prevention Program at 1- and 2-Year Follow-up

PubMed Central

Stice, Eric; Durant, Shelley; Rohde, Paul; Shaw, Heather

2014-01-01

Objective A group-based eating disorder prevention program wherein young women explore the costs of pursuing the thin ideal reduces eating disorder risk factors and symptoms. However, it can be challenging to identify school clinicians to effectively deliver the intervention. The present study compares the effects of a new Internet-based version of this prevention program, which could facilitate dissemination, to the group-based program and to educational video and educational brochure control conditions at 1- and 2-year follow-up. Method Female college students with body dissatisfaction (N = 107; M age = 21.6 SD = 6.6) were randomized to these four conditions. Results Internet participants showed reductions in eating disorder risk factors and symptoms relative to the two control conditions at 1- and 2-year follow-up (M d = .34 and .17 respectively), but the effects were smaller than parallel comparisons for the group participants (M d = .48 and .43 respectively). Yet the Internet intervention produced large weight gain prevention effects relative to the two control conditions at 1- and 2-year follow-up (M d = .80 and .73 respectively), which were larger than the parallel effects for the group intervention (M d = .19 and .47 respectively). Conclusions Although the effects for the Internet versus group intervention were similar at posttest, results suggest that the effects faded more quickly for the Internet intervention. However, the Internet intervention produced large weight gain prevention effects, implying that it might be useful for simultaneously preventing eating disordered behavior and unhealthy weight gain. PMID:25020152

Eigensolver for a Sparse, Large Hermitian Matrix

NASA Technical Reports Server (NTRS)

Tisdale, E. Robert; Oyafuso, Fabiano; Klimeck, Gerhard; Brown, R. Chris

2003-01-01

A parallel-processing computer program finds a few eigenvalues in a sparse Hermitian matrix that contains as many as 100 million diagonal elements. This program finds the eigenvalues faster, using less memory, than do other, comparable eigensolver programs. This program implements a Lanczos algorithm in the American National Standards Institute/ International Organization for Standardization (ANSI/ISO) C computing language, using the Message Passing Interface (MPI) standard to complement an eigensolver in PARPACK. [PARPACK (Parallel Arnoldi Package) is an extension, to parallel-processing computer architectures, of ARPACK (Arnoldi Package), which is a collection of Fortran 77 subroutines that solve large-scale eigenvalue problems.] The eigensolver runs on Beowulf clusters of computers at the Jet Propulsion Laboratory (JPL).

Hybrid MPI+OpenMP Programming of an Overset CFD Solver and Performance Investigations

NASA Technical Reports Server (NTRS)

Djomehri, M. Jahed; Jin, Haoqiang H.; Biegel, Bryan (Technical Monitor)

2002-01-01

This report describes a two level parallelization of a Computational Fluid Dynamic (CFD) solver with multi-zone overset structured grids. The approach is based on a hybrid MPI+OpenMP programming model suitable for shared memory and clusters of shared memory machines. The performance investigations of the hybrid application on an SGI Origin2000 (O2K) machine is reported using medium and large scale test problems.

Parallelization of elliptic solver for solving 1D Boussinesq model

NASA Astrophysics Data System (ADS)

Tarwidi, D.; Adytia, D.

2018-03-01

In this paper, a parallel implementation of an elliptic solver in solving 1D Boussinesq model is presented. Numerical solution of Boussinesq model is obtained by implementing a staggered grid scheme to continuity, momentum, and elliptic equation of Boussinesq model. Tridiagonal system emerging from numerical scheme of elliptic equation is solved by cyclic reduction algorithm. The parallel implementation of cyclic reduction is executed on multicore processors with shared memory architectures using OpenMP. To measure the performance of parallel program, large number of grids is varied from 28 to 214. Two test cases of numerical experiment, i.e. propagation of solitary and standing wave, are proposed to evaluate the parallel program. The numerical results are verified with analytical solution of solitary and standing wave. The best speedup of solitary and standing wave test cases is about 2.07 with 214 of grids and 1.86 with 213 of grids, respectively, which are executed by using 8 threads. Moreover, the best efficiency of parallel program is 76.2% and 73.5% for solitary and standing wave test cases, respectively.

Support for Debugging Automatically Parallelized Programs

NASA Technical Reports Server (NTRS)

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

2001-01-01

We describe a system that simplifies the process of debugging programs produced by computer-aided parallelization tools. The system uses relative debugging techniques to compare serial and parallel executions in order to show where the computations begin to differ. If the original serial code is correct, errors due to parallelization will be isolated by the comparison. One of the primary goals of the system is to minimize the effort required of the user. To that end, the debugging system uses information produced by the parallelization tool to drive the comparison process. In particular the debugging system relies on the parallelization tool to provide information about where variables may have been modified and how arrays are distributed across multiple processes. User effort is also reduced through the use of dynamic instrumentation. This allows us to modify the program execution without changing the way the user builds the executable. The use of dynamic instrumentation also permits us to compare the executions in a fine-grained fashion and only involve the debugger when a difference has been detected. This reduces the overhead of executing instrumentation.

Relative Debugging of Automatically Parallelized Programs

NASA Technical Reports Server (NTRS)

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

2002-01-01

We describe a system that simplifies the process of debugging programs produced by computer-aided parallelization tools. The system uses relative debugging techniques to compare serial and parallel executions in order to show where the computations begin to differ. If the original serial code is correct, errors due to parallelization will be isolated by the comparison. One of the primary goals of the system is to minimize the effort required of the user. To that end, the debugging system uses information produced by the parallelization tool to drive the comparison process. In particular, the debugging system relies on the parallelization tool to provide information about where variables may have been modified and how arrays are distributed across multiple processes. User effort is also reduced through the use of dynamic instrumentation. This allows us to modify, the program execution with out changing the way the user builds the executable. The use of dynamic instrumentation also permits us to compare the executions in a fine-grained fashion and only involve the debugger when a difference has been detected. This reduces the overhead of executing instrumentation.

Paralex: An Environment for Parallel Programming in Distributed Systems

DTIC Science & Technology

1991-12-07

distributed systems is coni- parable to assembly language programming for traditional sequential systems - the user must resort to low-level primitives ...to accomplish data encoding/decoding, communication, remote exe- cution, synchronization , failure detection and recovery. It is our belief that... synchronization . Finally, composing parallel programs by interconnecting se- quential computations allows automatic support for heterogeneity and fault tolerance

mm_par2.0: An object-oriented molecular dynamics simulation program parallelized using a hierarchical scheme with MPI and OPENMP

NASA Astrophysics Data System (ADS)

Oh, Kwang Jin; Kang, Ji Hoon; Myung, Hun Joo

2012-02-01

We have revised a general purpose parallel molecular dynamics simulation program mm_par using the object-oriented programming. We parallelized the revised version using a hierarchical scheme in order to utilize more processors for a given system size. The benchmark result will be presented here. New version program summaryProgram title: mm_par2.0 Catalogue identifier: ADXP_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXP_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2 390 858 No. of bytes in distributed program, including test data, etc.: 25 068 310 Distribution format: tar.gz Programming language: C++ Computer: Any system operated by Linux or Unix Operating system: Linux Classification: 7.7 External routines: We provide wrappers for FFTW [1], Intel MKL library [2] FFT routine, and Numerical recipes [3] FFT, random number generator, and eigenvalue solver routines, SPRNG [4] random number generator, Mersenne Twister [5] random number generator, space filling curve routine. Catalogue identifier of previous version: ADXP_v1_0 Journal reference of previous version: Comput. Phys. Comm. 174 (2006) 560 Does the new version supersede the previous version?: Yes Nature of problem: Structural, thermodynamic, and dynamical properties of fluids and solids from microscopic scales to mesoscopic scales. Solution method: Molecular dynamics simulation in NVE, NVT, and NPT ensemble, Langevin dynamics simulation, dissipative particle dynamics simulation. Reasons for new version: First, object-oriented programming has been used, which is known to be open for extension and closed for modification. It is also known to be better for maintenance. Second, version 1.0 was based on atom decomposition and domain decomposition scheme [6] for parallelization. However, atom decomposition is not popular due to its poor scalability. On the other hand, domain decomposition scheme is better for scalability. It still has a limitation in utilizing a large number of cores on recent petascale computers due to the requirement that the domain size is larger than the potential cutoff distance. To go beyond such a limitation, a hierarchical parallelization scheme has been adopted in this new version and implemented using MPI [7] and OPENMP [8]. Summary of revisions: (1) Object-oriented programming has been used. (2) A hierarchical parallelization scheme has been adopted. (3) SPME routine has been fully parallelized with parallel 3D FFT using volumetric decomposition scheme [9]. K.J.O. thanks Mr. Seung Min Lee for useful discussion on programming and debugging. Running time: Running time depends on system size and methods used. For test system containing a protein (PDB id: 5DHFR) with CHARMM22 force field [10] and 7023 TIP3P [11] waters in simulation box having dimension 62.23 Å×62.23 Å×62.23 Å, the benchmark results are given in Fig. 1. Here the potential cutoff distance was set to 12 Å and the switching function was applied from 10 Å for the force calculation in real space. For the SPME [12] calculation, K, K, and K were set to 64 and the interpolation order was set to 4. To do the fast Fourier transform, we used Intel MKL library. All bonds including hydrogen atoms were constrained using SHAKE/RATTLE algorithms [13,14]. The code was compiled using Intel compiler version 11.1 and mvapich2 version 1.5. Fig. 2 shows performance gains from using CUDA-enabled version [15] of mm_par for 5DHFR simulation in water on Intel Core2Quad 2.83 GHz and GeForce GTX 580. Even though mm_par2.0 is not ported yet for GPU, its performance data would be useful to expect mm_par2.0 performance on GPU. Timing results for 1000 MD steps. 1, 2, 4, and 8 in the figure mean the number of OPENMP threads. Timing results for 1000 MD steps from double precision simulation on CPU, single precision simulation on GPU, and double precision simulation on GPU.

Exploring Asynchronous Many-Task Runtime Systems toward Extreme Scales

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

Knight, Samuel; Baker, Gavin Matthew; Gamell, Marc

2015-10-01

Major exascale computing reports indicate a number of software challenges to meet the dramatic change of system architectures in near future. While several-orders-of-magnitude increase in parallelism is the most commonly cited of those, hurdles also include performance heterogeneity of compute nodes across the system, increased imbalance between computational capacity and I/O capabilities, frequent system interrupts, and complex hardware architectures. Asynchronous task-parallel programming models show a great promise in addressing these issues, but are not yet fully understood nor developed su ciently for computational science and engineering application codes. We address these knowledge gaps through quantitative and qualitative exploration of leadingmore » candidate solutions in the context of engineering applications at Sandia. In this poster, we evaluate MiniAero code ported to three leading candidate programming models (Charm++, Legion and UINTAH) to examine the feasibility of these models that permits insertion of new programming model elements into an existing code base.« less

A Tensor Product Formulation of Strassen's Matrix Multiplication Algorithm with Memory Reduction

DOE PAGES

Kumar, B.; Huang, C. -H.; Sadayappan, P.; ...

1995-01-01

In this article, we present a program generation strategy of Strassen's matrix multiplication algorithm using a programming methodology based on tensor product formulas. In this methodology, block recursive programs such as the fast Fourier Transforms and Strassen's matrix multiplication algorithm are expressed as algebraic formulas involving tensor products and other matrix operations. Such formulas can be systematically translated to high-performance parallel/vector codes for various architectures. In this article, we present a nonrecursive implementation of Strassen's algorithm for shared memory vector processors such as the Cray Y-MP. A previous implementation of Strassen's algorithm synthesized from tensor product formulas required working storagemore » of size O(7 n ) for multiplying 2 n × 2 n matrices. We present a modified formulation in which the working storage requirement is reduced to O(4 n ). The modified formulation exhibits sufficient parallelism for efficient implementation on a shared memory multiprocessor. Performance results on a Cray Y-MP8/64 are presented.« less

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

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.

An intelligent allocation algorithm for parallel processing

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.

1988-01-01

The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.

Real-Time Monitoring of Scada Based Control System for Filling Process

NASA Astrophysics Data System (ADS)

Soe, Aung Kyaw; Myint, Aung Naing; Latt, Maung Maung; Theingi

2008-10-01

This paper is a design of real-time monitoring for filling system using Supervisory Control and Data Acquisition (SCADA). The monitoring of production process is described in real-time using Visual Basic.Net programming under Visual Studio 2005 software without SCADA software. The software integrators are programmed to get the required information for the configuration screens. Simulation of components is expressed on the computer screen using parallel port between computers and filling devices. The programs of real-time simulation for the filling process from the pure drinking water industry are provided.

A software platform for continuum modeling of ion channels based on unstructured mesh

NASA Astrophysics Data System (ADS)

Tu, B.; Bai, S. Y.; Chen, M. X.; Xie, Y.; Zhang, L. B.; Lu, B. Z.

2014-01-01

Most traditional continuum molecular modeling adopted finite difference or finite volume methods which were based on a structured mesh (grid). Unstructured meshes were only occasionally used, but an increased number of applications emerge in molecular simulations. To facilitate the continuum modeling of biomolecular systems based on unstructured meshes, we are developing a software platform with tools which are particularly beneficial to those approaches. This work describes the software system specifically for the simulation of a typical, complex molecular procedure: ion transport through a three-dimensional channel system that consists of a protein and a membrane. The platform contains three parts: a meshing tool chain for ion channel systems, a parallel finite element solver for the Poisson-Nernst-Planck equations describing the electrodiffusion process of ion transport, and a visualization program for continuum molecular modeling. The meshing tool chain in the platform, which consists of a set of mesh generation tools, is able to generate high-quality surface and volume meshes for ion channel systems. The parallel finite element solver in our platform is based on the parallel adaptive finite element package PHG which wass developed by one of the authors [1]. As a featured component of the platform, a new visualization program, VCMM, has specifically been developed for continuum molecular modeling with an emphasis on providing useful facilities for unstructured mesh-based methods and for their output analysis and visualization. VCMM provides a graphic user interface and consists of three modules: a molecular module, a meshing module and a numerical module. A demonstration of the platform is provided with a study of two real proteins, the connexin 26 and hemolysin ion channels.

A GPU-paralleled implementation of an enhanced face recognition algorithm

NASA Astrophysics Data System (ADS)

Chen, Hao; Liu, Xiyang; Shao, Shuai; Zan, Jiguo

2013-03-01

Face recognition algorithm based on compressed sensing and sparse representation is hotly argued in these years. The scheme of this algorithm increases recognition rate as well as anti-noise capability. However, the computational cost is expensive and has become a main restricting factor for real world applications. In this paper, we introduce a GPU-accelerated hybrid variant of face recognition algorithm named parallel face recognition algorithm (pFRA). We describe here how to carry out parallel optimization design to take full advantage of many-core structure of a GPU. The pFRA is tested and compared with several other implementations under different data sample size. Finally, Our pFRA, implemented with NVIDIA GPU and Computer Unified Device Architecture (CUDA) programming model, achieves a significant speedup over the traditional CPU implementations.

A high-speed linear algebra library with automatic parallelism

NASA Technical Reports Server (NTRS)

Boucher, Michael L.

1994-01-01

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

MOTIVES INFLUENCING NEEDS TO ACHIEVE IN VOCATIONAL EDUCATION.

ERIC Educational Resources Information Center

HELTZEL, FRANCES B.

THIS RESEARCH SOUGHT TO MEASURE M TIVATION UNDERLYING ACHIEVEMENT-ORIENTED BEHAVIOR AT THE SECONDARY LEVEL, SPECIFICALLY OF STUDENTS IN VOCATIONAL PROGRAMS. PARALLEL INSTRUMENTS OF 42 ITEMS WERE CONSTRUCTED TO MEASURE MOTIVE FOR STRIVING, BASED ON MASLOW'S HIERARCHY OF NEED FOR SECURITY, BELONGINGNESS, ESTEEM, AND SELF-ACTUALIZATION. STRENGTH OF…

Putting time into proof outlines

NASA Technical Reports Server (NTRS)

Schneider, Fred B.; Bloom, Bard; Marzullo, Keith

1991-01-01

A logic for reasoning about timing of concurrent programs is presented. The logic is based on proof outlines and can handle maximal parallelism as well as resource-constrained execution environments. The correctness proof for a mutual exclusion protocol that uses execution timings in a subtle way illustrates the logic in action.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

NASA Astrophysics Data System (ADS)

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

PubMed Central

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value. PMID:27905520

GraphReduce: Large-Scale Graph Analytics on Accelerator-Based HPC Systems

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

Sengupta, Dipanjan; Agarwal, Kapil; Song, Shuaiwen

2015-09-30

Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of both edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the hostmore » and the device.« less

Parallel and patterned optogenetic manipulation of neurons in the brain slice using a DMD-based projector.

PubMed

Sakai, Seiichiro; Ueno, Kenichi; Ishizuka, Toru; Yawo, Hiromu

2013-01-01

Optical manipulation technologies greatly advanced the understanding of the neuronal network and its dysfunctions. To achieve patterned and parallel optical switching, we developed a microscopic illumination system using a commercial DMD-based projector and a software program. The spatiotemporal patterning of the system was evaluated using acute slices of the hippocampus. The neural activity was optically manipulated, positively by the combination of channelrhodopsin-2 (ChR2) and blue light, and negatively by the combination of archaerhodopsin-T (ArchT) and green light. It is suggested that our projector-managing optical system (PMOS) would effectively facilitate the optogenetic analyses of neurons and their circuits. Copyright © 2012 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Dual and parallel postdoctoral training programs: implications for the osteopathic medical profession.

PubMed

Burkhart, Diane N; Lischka, Terri A

2011-04-01

Students in colleges of osteopathic medicine have several options when considering postdoctoral training programs. In addition to training programs approved solely by the American Osteopathic Association or accredited solely by the Accreditation Council for Graduate Medical Education (ACGME), students can pursue programs accredited by both organizations (ie, dually accredited programs) or osteopathic programs that occur side-by-side with ACGME programs (ie, parallel programs). In the present article, we report on the availability and growth of these 2 training options and describe their benefits and drawbacks for trainees and the osteopathic medical profession as a whole.

A Comparison of Parallel and Integrated Models for Implementation of Routine HIV Screening in a Large, Urban Emergency Department.

PubMed

Hankin, Abigail; Freiman, Heather; Copeland, Brittney; Travis, Natasha; Shah, Bijal

2016-01-01

This study compared two approaches for implementation of non-targeted HIV screening in the emergency department (ED): (1) designated HIV counselors screening in parallel with ED care and (2) nurse-based screening integrated into patient triage. A retrospective analysis was performed to compare parallel and integrated screening models using data from the first 12 months of each program. Data for the parallel screening model were extracted from information collected by HIV test counselors and the electronic medical record (EMR). Integrated screening model data were extracted from the EMR and supplemented by data collected by HIV social workers during patient interaction. For both programs, data included demographics, HIV test offer, test acceptance or declination, and test result. A Z-test between two proportions was performed to compare screening frequencies and results. During the first 12 months of parallel screening, approximately 120,000 visits were made to the ED, with 3,816 (3%) HIV tests administered and 65 (2%) new diagnoses of HIV infection. During the first 12 months of integrated screening, 111,738 patients were triaged in the ED, with 16,329 (15%) patients tested and 190 (1%) new diagnoses. Integrated screening resulted in an increased frequency of HIV screening compared with parallel screening (0.15 tests per ED patient visit vs. 0.03 tests per ED patient visit, p<0.001) and an increase in the absolute number of new diagnoses (190 vs. 65), representing a slight decrease in the proportion of new diagnoses (1% vs. 2%, p=0.007). Non-targeted, integrated HIV screening, with test offer and order by ED nurses during patient triage, is feasible and resulted in an increased frequency of HIV screening and a threefold increase in the absolute number of newly identified HIV-positive patients.

Adaptation of an Evidence-Based Arthritis Program for Breast Cancer Survivors on Aromatase Inhibitor Therapy Who Experience Joint Pain

PubMed Central

Callahan, Leigh F.; Rini, Christine; Altpeter, Mary; Hackney, Betsy; Schecher, Arielle; Wilson, Anne; Muss, Hyman B.

2015-01-01

Adding aromatase inhibitors (AIs) to adjuvant treatment of postmenopausal women with hormone-receptor–positive breast cancer significantly reduces cancer recurrence. A common side effect of AIs is noninflammatory joint pain and stiffness (arthralgia) similar to arthritis symptoms. An evidence-based walking program developed by the Arthritis Foundation — Walk With Ease (WWE) — reduces arthritis-related joint symptoms. We hypothesized that WWE may also reduce AI-associated arthralgia. However, the potential for different barriers and facilitators to physical activity for these 2 patient populations suggested a need to adapt WWE before testing it with breast cancer survivors. We conducted qualitative research with 46 breast cancer survivors to explore program modification and inform the development of materials for an adapted program (Walk With Ease-Breast Cancer). Our process parallels the National Cancer Institute’s Research-Tested Intervention Programs (RTIPs) guidelines for adapting evidence-based programs for cancer populations. Findings resulted in a customized 8-page brochure to supplement existing WWE materials. PMID:26068412

Parallel Implementation of Numerical Solution of Few-Body Problem Using Feynman's Continual Integrals

NASA Astrophysics Data System (ADS)

Naumenko, Mikhail; Samarin, Viacheslav

2018-02-01

Modern parallel computing algorithm has been applied to the solution of the few-body problem. The approach is based on Feynman's continual integrals method implemented in C++ programming language using NVIDIA CUDA technology. A wide range of 3-body and 4-body bound systems has been considered including nuclei described as consisting of protons and neutrons (e.g., 3,4He) and nuclei described as consisting of clusters and nucleons (e.g., 6He). The correctness of the results was checked by the comparison with the exactly solvable 4-body oscillatory system and experimental data.

Performance Comparison of HPF and MPI Based NAS Parallel Benchmarks

NASA Technical Reports Server (NTRS)

Saini, Subhash

1997-01-01

Compilers supporting High Performance Form (HPF) features first appeared in late 1994 and early 1995 from Applied Parallel Research (APR), Digital Equipment Corporation, and The Portland Group (PGI). IBM introduced an HPF compiler for the IBM RS/6000 SP2 in April of 1996. Over the past two years, these implementations have shown steady improvement in terms of both features and performance. The performance of various hardware/ programming model (HPF and MPI) combinations will be compared, based on latest NAS Parallel Benchmark results, thus providing a cross-machine and cross-model comparison. Specifically, HPF based NPB results will be compared with MPI based NPB results to provide perspective on performance currently obtainable using HPF versus MPI or versus hand-tuned implementations such as those supplied by the hardware vendors. In addition, we would also present NPB, (Version 1.0) performance results for the following systems: DEC Alpha Server 8400 5/440, Fujitsu CAPP Series (VX, VPP300, and VPP700), HP/Convex Exemplar SPP2000, IBM RS/6000 SP P2SC node (120 MHz), NEC SX-4/32, SGI/CRAY T3E, and SGI Origin2000. We would also present sustained performance per dollar for Class B LU, SP and BT benchmarks.

Changes in health indicators related to health promotion and microcredit programs in the Dominican Republic.

PubMed

Dohn, Anita L; Chávez, Andrea; Dohn, Michael N; Saturria, Luis; Pimentel, Carlos

2004-03-01

To assess the impact of health promotion programs and microcredit programs on three communities in the Dominican Republic. One community had only the health promotion program, one community had only the microcredit program, and one community had both a health promotion program and a microcredit program. This pilot project examined the hypothesis that the largest changes in 11 health indicators that were studied would be in the community with both a health promotion program and a microcredit program, that there would be intermediate changes in the community with only a health promotion program, and that the smallest changes would be in the community with only a microcredit program. The health promotion programs used community volunteers to address two major concerns: (1) the prevalent causes of mortality among children under 5 years of age and (2) women's health (specifically breast and cervical cancer screening). The microcredit program made small loans to individuals to start or expand small businesses. Outcome measures were based on comparisons for 11 health indicators from baseline community surveys (27 households surveyed in each of the three communities, done in December 2000 and January 2001) and from follow-up surveys (also 27 households surveyed in each of the three communities, in June and July 2002, after the health promotion program had been operating for about 13 months). Households were randomly chosen during both the baseline and follow-up surveys, without regard to their involvement in the microcredit or health promotion programs. The health indicators improved in all three communities. However, the degree of change was different among the communities (P < 0.001). The community with parallel microcredit and health promotion programs had the largest changes for 10 of the 11 health indicators. Multisector development is known to be important on a macroeconomic scale. The results of this pilot project support the view that multisector development is also important on a microeconomic level, given that the parallel microcredit and health promotion programs resulted in greater change in the measured health indicators than either program alone. As far as we authors know, this is the first published study to quantify changes in health indicators related to parallel health promotion and microcredit programs as compared to control communities with only a health promotion program or a microcredit program.

Expressing Parallelism with ROOT

NASA Astrophysics Data System (ADS)

Piparo, D.; Tejedor, E.; Guiraud, E.; Ganis, G.; Mato, P.; Moneta, L.; Valls Pla, X.; Canal, P.

2017-10-01

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.

Expressing Parallelism with ROOT

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

Piparo, D.; Tejedor, E.; Guiraud, E.

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module inmore » Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.« less

Verification and Planning Based on Coinductive Logic Programming

NASA Technical Reports Server (NTRS)

Bansal, Ajay; Min, Richard; Simon, Luke; Mallya, Ajay; Gupta, Gopal

2008-01-01

Coinduction is a powerful technique for reasoning about unfounded sets, unbounded structures, infinite automata, and interactive computations [6]. Where induction corresponds to least fixed point's semantics, coinduction corresponds to greatest fixed point semantics. Recently coinduction has been incorporated into logic programming and an elegant operational semantics developed for it [11, 12]. This operational semantics is the greatest fix point counterpart of SLD resolution (SLD resolution imparts operational semantics to least fix point based computations) and is termed co- SLD resolution. In co-SLD resolution, a predicate goal p( t) succeeds if it unifies with one of its ancestor calls. In addition, rational infinite terms are allowed as arguments of predicates. Infinite terms are represented as solutions to unification equations and the occurs check is omitted during the unification process. Coinductive Logic Programming (Co-LP) and Co-SLD resolution can be used to elegantly perform model checking and planning. A combined SLD and Co-SLD resolution based LP system forms the common basis for planning, scheduling, verification, model checking, and constraint solving [9, 4]. This is achieved by amalgamating SLD resolution, co-SLD resolution, and constraint logic programming [13] in a single logic programming system. Given that parallelism in logic programs can be implicitly exploited [8], complex, compute-intensive applications (planning, scheduling, model checking, etc.) can be executed in parallel on multi-core machines. Parallel execution can result in speed-ups as well as in larger instances of the problems being solved. In the remainder we elaborate on (i) how planning can be elegantly and efficiently performed under real-time constraints, (ii) how real-time systems can be elegantly and efficiently model- checked, as well as (iii) how hybrid systems can be verified in a combined system with both co-SLD and SLD resolution. Implementations of co-SLD resolution as well as preliminary implementations of the planning and verification applications have been developed [4]. Co-LP and Model Checking: The vast majority of properties that are to be verified can be classified into safety properties and liveness properties. It is well known within model checking that safety properties can be verified by reachability analysis, i.e, if a counter-example to the property exists, it can be finitely determined by enumerating all the reachable states of the Kripke structure.

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

NASA Technical Reports Server (NTRS)

Dennis, Jack B.

1989-01-01

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

Exploiting loop level parallelism in nonprocedural dataflow programs

NASA Technical Reports Server (NTRS)

Gokhale, Maya B.

1987-01-01

Discussed are how loop level parallelism is detected in a nonprocedural dataflow program, and how a procedural program with concurrent loops is scheduled. Also discussed is a program restructuring technique which may be applied to recursive equations so that concurrent loops may be generated for a seemingly iterative computation. A compiler which generates C code for the language described below has been implemented. The scheduling component of the compiler and the restructuring transformation are described.

Tolerant (parallel) Programming

NASA Technical Reports Server (NTRS)

DiNucci, David C.; Bailey, David H. (Technical Monitor)

1997-01-01

In order to be truly portable, a program must be tolerant of a wide range of development and execution environments, and a parallel program is just one which must be tolerant of a very wide range. This paper first defines the term "tolerant programming", then describes many layers of tools to accomplish it. The primary focus is on F-Nets, a formal model for expressing computation as a folded partial-ordering of operations, thereby providing an architecture-independent expression of tolerant parallel algorithms. For implementing F-Nets, Cooperative Data Sharing (CDS) is a subroutine package for implementing communication efficiently in a large number of environments (e.g. shared memory and message passing). Software Cabling (SC), a very-high-level graphical programming language for building large F-Nets, possesses many of the features normally expected from today's computer languages (e.g. data abstraction, array operations). Finally, L2(sup 3) is a CASE tool which facilitates the construction, compilation, execution, and debugging of SC programs.

Resolutions of the Coulomb operator: VIII. Parallel implementation using the modern programming language X10.

PubMed

Limpanuparb, Taweetham; Milthorpe, Josh; Rendell, Alistair P

2014-10-30

Use of the modern parallel programming language X10 for computing long-range Coulomb and exchange interactions is presented. By using X10, a partitioned global address space language with support for task parallelism and the explicit representation of data locality, the resolution of the Ewald operator can be parallelized in a straightforward manner including use of both intranode and internode parallelism. We evaluate four different schemes for dynamic load balancing of integral calculation using X10's work stealing runtime, and report performance results for long-range HF energy calculation of large molecule/high quality basis running on up to 1024 cores of a high performance cluster machine. Copyright © 2014 Wiley Periodicals, Inc.

Exploring types of play in an adapted robotics program for children with disabilities.

PubMed

Lindsay, Sally; Lam, Ashley

2018-04-01

Play is an important occupation in a child's development. Children with disabilities often have fewer opportunities to engage in meaningful play than typically developing children. The purpose of this study was to explore the types of play (i.e., solitary, parallel and co-operative) within an adapted robotics program for children with disabilities aged 6-8 years. This study draws on detailed observations of each of the six robotics workshops and interviews with 53 participants (21 children, 21 parents and 11 programme staff). Our findings showed that four children engaged in solitary play, where all but one showed signs of moving towards parallel play. Six children demonstrated parallel play during all workshops. The remainder of the children had mixed play types play (solitary, parallel and/or co-operative) throughout the robotics workshops. We observed more parallel and co-operative, and less solitary play as the programme progressed. Ten different children displayed co-operative behaviours throughout the workshops. The interviews highlighted how staff supported children's engagement in the programme. Meanwhile, parents reported on their child's development of play skills. An adapted LEGO ® robotics program has potential to develop the play skills of children with disabilities in moving from solitary towards more parallel and co-operative play. Implications for rehabilitation Educators and clinicians working with children who have disabilities should consider the potential of LEGO ® robotics programs for developing their play skills. Clinicians should consider how the extent of their involvement in prompting and facilitating children's engagement and play within a robotics program may influence their ability to interact with their peers. Educators and clinicians should incorporate both structured and unstructured free-play elements within a robotics program to facilitate children's social development.

Parallelized CCHE2D flow model with CUDA Fortran on Graphics Process Units

USDA-ARS?s Scientific Manuscript database

This paper presents the CCHE2D implicit flow model parallelized using CUDA Fortran programming technique on Graphics Processing Units (GPUs). A parallelized implicit Alternating Direction Implicit (ADI) solver using Parallel Cyclic Reduction (PCR) algorithm on GPU is developed and tested. This solve...

Programming scheme based optimization of hybrid 4T-2R OxRAM NVSRAM

NASA Astrophysics Data System (ADS)

Majumdar, Swatilekha; Kingra, Sandeep Kaur; Suri, Manan

2017-09-01

In this paper, we present a novel single-cycle programming scheme for 4T-2R NVSRAM, exploiting pulse engineered input signals. OxRAM devices based on 3 nm thick bi-layer active switching oxide and 90 nm CMOS technology node were used for all simulations. The cell design is implemented for real-time non-volatility rather than last-bit, or power-down non-volatility. Detailed analysis of the proposed single-cycle, parallel RRAM device programming scheme is presented in comparison to the two-cycle sequential RRAM programming used for similar 4T-2R NVSRAM bit-cells. The proposed single-cycle programming scheme coupled with the 4T-2R architecture leads to several benefits such as- possibility of unconventional transistor sizing, 50% lower latency, 20% improvement in SNM and ∼20× reduced energy requirements, when compared against two-cycle programming approach.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

A Methodolgy, Based on Analytical Modeling, for the Design of Parallel and Distributed Architectures for Relational Database Query Processors.

DTIC Science & Technology

1987-12-01

Application Programs Intelligent Disk Database Controller Manangement System Operating System Host .1’ I% Figure 2. Intelligent Disk Controller Application...8217. /- - • Database Control -% Manangement System Disk Data Controller Application Programs Operating Host I"" Figure 5. Processor-Per- Head data. Therefore, the...However. these ad- ditional properties have been proven in classical set and relation theory [75]. These additional properties are described here

The role of life skills promotion in substance abuse prevention: a mediation analysis.

PubMed

Bühler, Anneke; Schröder, Elke; Silbereisen, Rainer K

2008-08-01

Research has shown that life skills programs are the most effective single activity in school-based substance abuse prevention. However, little is known about the processes through which they are effective. This study examines whether an evidence-based prevention program targeting general competence is effective through the promotion of knowledge about life skills and enhanced related behaviors. Based on a sample of 442 fifth graders participating in a quasi-experimental prevention study, as expected, mediation analyses revealed that increased knowledge about life skills paralleled an increase in students' distant attitudes toward alcohol and nicotine use. Unexpectedly, behaviors manifesting enhanced life skills were found not only among program participants who remained experimental/non-smokers or stopped smoking but also among smokers. In general, findings suggest that favorable prevention outcomes may be influenced through building knowledge about general life skills. The notion of uniform mechanisms of effectiveness in prevention programs is discussed.

Real-time stereo matching using orthogonal reliability-based dynamic programming.

PubMed

Gong, Minglun; Yang, Yee-Hong

2007-03-01

A novel algorithm is presented in this paper for estimating reliable stereo matches in real time. Based on the dynamic programming-based technique we previously proposed, the new algorithm can generate semi-dense disparity maps using as few as two dynamic programming passes. The iterative best path tracing process used in traditional dynamic programming is replaced by a local minimum searching process, making the algorithm suitable for parallel execution. Most computations are implemented on programmable graphics hardware, which improves the processing speed and makes real-time estimation possible. The experiments on the four new Middlebury stereo datasets show that, on an ATI Radeon X800 card, the presented algorithm can produce reliable matches for 60% approximately 80% of pixels at the rate of 10 approximately 20 frames per second. If needed, the algorithm can be configured for generating full density disparity maps.

Multiprocessor smalltalk: Implementation, performance, and analysis

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

Pallas, J.I.

1990-01-01

Multiprocessor Smalltalk demonstrates the value of object-oriented programming on a multiprocessor. Its implementation and analysis shed light on three areas: concurrent programming in an object oriented language without special extensions, implementation techniques for adapting to multiprocessors, and performance factors in the resulting system. Adding parallelism to Smalltalk code is easy, because programs already use control abstractions like iterators. Smalltalk's basic control and concurrency primitives (lambda expressions, processes and semaphores) can be used to build parallel control abstractions, including parallel iterators, parallel objects, atomic objects, and futures. Language extensions for concurrency are not required. This implementation demonstrates that it is possiblemore » to build an efficient parallel object-oriented programming system and illustrates techniques for doing so. Three modification tools-serialization, replication, and reorganization-adapted the Berkeley Smalltalk interpreter to the Firefly multiprocessor. Multiprocessor Smalltalk's performance shows that the combination of multiprocessing and object-oriented programming can be effective: speedups (relative to the original serial version) exceed 2.0 for five processors on all the benchmarks; the median efficiency is 48%. Analysis shows both where performance is lost and how to improve and generalize the experimental results. Changes in the interpreter to support concurrency add at most 12% overhead; better access to per-process variables could eliminate much of that. Changes in the user code to express concurrency add as much as 70% overhead; this overhead could be reduced to 54% if blocks (lambda expressions) were reentrant. Performance is also lost when the program cannot keep all five processors busy.« less

A portable approach for PIC on emerging architectures

NASA Astrophysics Data System (ADS)

Decyk, Viktor

2016-03-01

A portable approach for designing Particle-in-Cell (PIC) algorithms on emerging exascale computers, is based on the recognition that 3 distinct programming paradigms are needed. They are: low level vector (SIMD) processing, middle level shared memory parallel programing, and high level distributed memory programming. In addition, there is a memory hierarchy associated with each level. Such algorithms can be initially developed using vectorizing compilers, OpenMP, and MPI. This is the approach recommended by Intel for the Phi processor. These algorithms can then be translated and possibly specialized to other programming models and languages, as needed. For example, the vector processing and shared memory programming might be done with CUDA instead of vectorizing compilers and OpenMP, but generally the algorithm itself is not greatly changed. The UCLA PICKSC web site at http://www.idre.ucla.edu/ contains example open source skeleton codes (mini-apps) illustrating each of these three programming models, individually and in combination. Fortran2003 now supports abstract data types, and design patterns can be used to support a variety of implementations within the same code base. Fortran2003 also supports interoperability with C so that implementations in C languages are also easy to use. Finally, main codes can be translated into dynamic environments such as Python, while still taking advantage of high performing compiled languages. Parallel languages are still evolving with interesting developments in co-Array Fortran, UPC, and OpenACC, among others, and these can also be supported within the same software architecture. Work supported by NSF and DOE Grants.

Parallel transformation of K-SVD solar image denoising algorithm

NASA Astrophysics Data System (ADS)

Liang, Youwen; Tian, Yu; Li, Mei

2017-02-01

The images obtained by observing the sun through a large telescope always suffered with noise due to the low SNR. K-SVD denoising algorithm can effectively remove Gauss white noise. Training dictionaries for sparse representations is a time consuming task, due to the large size of the data involved and to the complexity of the training algorithms. In this paper, an OpenMP parallel programming language is proposed to transform the serial algorithm to the parallel version. Data parallelism model is used to transform the algorithm. Not one atom but multiple atoms updated simultaneously is the biggest change. The denoising effect and acceleration performance are tested after completion of the parallel algorithm. Speedup of the program is 13.563 in condition of using 16 cores. This parallel version can fully utilize the multi-core CPU hardware resources, greatly reduce running time and easily to transplant in multi-core platform.

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.

Scalable computing for evolutionary genomics.

PubMed

Prins, Pjotr; Belhachemi, Dominique; Möller, Steffen; Smant, Geert

2012-01-01

Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis of multiple hypotheses and scenarios takes too long on a single desktop computer. In this chapter, we discuss techniques for scaling computations through parallelization of calculations, after giving a quick overview of advanced programming techniques. Unfortunately, parallel programming is difficult and requires special software design. The alternative, especially attractive for legacy software, is to introduce poor man's parallelization by running whole programs in parallel as separate processes, using job schedulers. Such pipelines are often deployed on bioinformatics computer clusters. Recent advances in PC virtualization have made it possible to run a full computer operating system, with all of its installed software, on top of another operating system, inside a "box," or virtual machine (VM). Such a VM can flexibly be deployed on multiple computers, in a local network, e.g., on existing desktop PCs, and even in the Cloud, to create a "virtual" computer cluster. Many bioinformatics applications in evolutionary biology can be run in parallel, running processes in one or more VMs. Here, we show how a ready-made bioinformatics VM image, named BioNode, effectively creates a computing cluster, and pipeline, in a few steps. This allows researchers to scale-up computations from their desktop, using available hardware, anytime it is required. BioNode is based on Debian Linux and can run on networked PCs and in the Cloud. Over 200 bioinformatics and statistical software packages, of interest to evolutionary biology, are included, such as PAML, Muscle, MAFFT, MrBayes, and BLAST. Most of these software packages are maintained through the Debian Med project. In addition, BioNode contains convenient configuration scripts for parallelizing bioinformatics software. Where Debian Med encourages packaging free and open source bioinformatics software through one central project, BioNode encourages creating free and open source VM images, for multiple targets, through one central project. BioNode can be deployed on Windows, OSX, Linux, and in the Cloud. Next to the downloadable BioNode images, we provide tutorials online, which empower bioinformaticians to install and run BioNode in different environments, as well as information for future initiatives, on creating and building such images.

A package of Linux scripts for the parallelization of Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Badal, Andreu; Sempau, Josep

2006-09-01

Despite the fact that fast computers are nowadays available at low cost, there are many situations where obtaining a reasonably low statistical uncertainty in a Monte Carlo (MC) simulation involves a prohibitively large amount of time. This limitation can be overcome by having recourse to parallel computing. Most tools designed to facilitate this approach require modification of the source code and the installation of additional software, which may be inconvenient for some users. We present a set of tools, named clonEasy, that implement a parallelization scheme of a MC simulation that is free from these drawbacks. In clonEasy, which is designed to run under Linux, a set of "clone" CPUs is governed by a "master" computer by taking advantage of the capabilities of the Secure Shell (ssh) protocol. Any Linux computer on the Internet that can be ssh-accessed by the user can be used as a clone. A key ingredient for the parallel calculation to be reliable is the availability of an independent string of random numbers for each CPU. Many generators—such as RANLUX, RANECU or the Mersenne Twister—can readily produce these strings by initializing them appropriately and, hence, they are suitable to be used with clonEasy. This work was primarily motivated by the need to find a straightforward way to parallelize PENELOPE, a code for MC simulation of radiation transport that (in its current 2005 version) employs the generator RANECU, which uses a combination of two multiplicative linear congruential generators (MLCGs). Thus, this paper is focused on this class of generators and, in particular, we briefly present an extension of RANECU that increases its period up to ˜5×10 and we introduce seedsMLCG, a tool that provides the information necessary to initialize disjoint sequences of an MLCG to feed different CPUs. This program, in combination with clonEasy, allows to run PENELOPE in parallel easily, without requiring specific libraries or significant alterations of the sequential code. Program summary 1Title of program:clonEasy Catalogue identifier:ADYD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYD_v1_0 Program obtainable from:CPC Program Library, Queen's University of Belfast, Northern Ireland Computer for which the program is designed and others in which it is operable:Any computer with a Unix style shell (bash), support for the Secure Shell protocol and a FORTRAN compiler Operating systems under which the program has been tested:Linux (RedHat 8.0, SuSe 8.1, Debian Woody 3.1) Compilers:GNU FORTRAN g77 (Linux); g95 (Linux); Intel Fortran Compiler 7.1 (Linux) Programming language used:Linux shell (bash) script, FORTRAN 77 No. of bits in a word:32 No. of lines in distributed program, including test data, etc.:1916 No. of bytes in distributed program, including test data, etc.:18 202 Distribution format:tar.gz Nature of the physical problem:There are many situations where a Monte Carlo simulation involves a huge amount of CPU time. The parallelization of such calculations is a simple way of obtaining a relatively low statistical uncertainty using a reasonable amount of time. Method of solution:The presented collection of Linux scripts and auxiliary FORTRAN programs implement Secure Shell-based communication between a "master" computer and a set of "clones". The aim of this communication is to execute a code that performs a Monte Carlo simulation on all the clones simultaneously. The code is unique, but each clone is fed with a different set of random seeds. Hence, clonEasy effectively permits the parallelization of the calculation. Restrictions on the complexity of the program:clonEasy can only be used with programs that produce statistically independent results using the same code, but with a different sequence of random numbers. Users must choose the initialization values for the random number generator on each computer and combine the output from the different executions. A FORTRAN program to combine the final results is also provided. Typical running time:The execution time of each script largely depends on the number of computers that are used, the actions that are to be performed and, to a lesser extent, on the network connexion bandwidth. Unusual features of the program:Any computer on the Internet with a Secure Shell client/server program installed can be used as a node of a virtual computer cluster for parallel calculations with the sequential source code. The simplicity of the parallelization scheme makes the use of this package a straightforward task, which does not require installing any additional libraries. Program summary 2Title of program:seedsMLCG Catalogue identifier:ADYE_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYE_v1_0 Program obtainable from:CPC Program Library, Queen's University of Belfast, Northern Ireland Computer for which the program is designed and others in which it is operable:Any computer with a FORTRAN compiler Operating systems under which the program has been tested:Linux (RedHat 8.0, SuSe 8.1, Debian Woody 3.1), MS Windows (2000, XP) Compilers:GNU FORTRAN g77 (Linux and Windows); g95 (Linux); Intel Fortran Compiler 7.1 (Linux); Compaq Visual Fortran 6.1 (Windows) Programming language used:FORTRAN 77 No. of bits in a word:32 Memory required to execute with typical data:500 kilobytes No. of lines in distributed program, including test data, etc.:492 No. of bytes in distributed program, including test data, etc.:5582 Distribution format:tar.gz Nature of the physical problem:Statistically independent results from different runs of a Monte Carlo code can be obtained using uncorrelated sequences of random numbers on each execution. Multiplicative linear congruential generators (MLCG), or other generators that are based on them such as RANECU, can be adapted to produce these sequences. Method of solution:For a given MLCG, the presented program calculates initialization values that produce disjoint, consecutive sequences of pseudo-random numbers. The calculated values initiate the generator in distant positions of the random number cycle and can be used, for instance, on a parallel simulation. The values are found using the formula S=(aS)MODm, which gives the random value that will be generated after J iterations of the MLCG. Restrictions on the complexity of the program:The 32-bit length restriction for the integer variables in standard FORTRAN 77 limits the produced seeds to be separated a distance smaller than 2 31, when the distance J is expressed as an integer value. The program allows the user to input the distance as a power of 10 for the purpose of efficiently splitting the sequence of generators with a very long period. Typical running time:The execution time depends on the parameters of the used MLCG and the distance between the generated seeds. The generation of 10 6 seeds separated 10 12 units in the sequential cycle, for one of the MLCGs found in the RANECU generator, takes 3 s on a 2.4 GHz Intel Pentium 4 using the g77 compiler.

Parallel Robot for Lower Limb Rehabilitation Exercises.

PubMed

Rastegarpanah, Alireza; Saadat, Mozafar; Borboni, Alberto

2016-01-01

The aim of this study is to investigate the capability of a 6-DoF parallel robot to perform various rehabilitation exercises. The foot trajectories of twenty healthy participants have been measured by a Vicon system during the performing of four different exercises. Based on the kinematics and dynamics of a parallel robot, a MATLAB program was developed in order to calculate the length of the actuators, the actuators' forces, workspace, and singularity locus of the robot during the performing of the exercises. The calculated length of the actuators and the actuators' forces were used by motion analysis in SolidWorks in order to simulate different foot trajectories by the CAD model of the robot. A physical parallel robot prototype was built in order to simulate and execute the foot trajectories of the participants. Kinect camera was used to track the motion of the leg's model placed on the robot. The results demonstrate the robot's capability to perform a full range of various rehabilitation exercises.

Parallel Robot for Lower Limb Rehabilitation Exercises

PubMed Central

Saadat, Mozafar; Borboni, Alberto

2016-01-01

The aim of this study is to investigate the capability of a 6-DoF parallel robot to perform various rehabilitation exercises. The foot trajectories of twenty healthy participants have been measured by a Vicon system during the performing of four different exercises. Based on the kinematics and dynamics of a parallel robot, a MATLAB program was developed in order to calculate the length of the actuators, the actuators' forces, workspace, and singularity locus of the robot during the performing of the exercises. The calculated length of the actuators and the actuators' forces were used by motion analysis in SolidWorks in order to simulate different foot trajectories by the CAD model of the robot. A physical parallel robot prototype was built in order to simulate and execute the foot trajectories of the participants. Kinect camera was used to track the motion of the leg's model placed on the robot. The results demonstrate the robot's capability to perform a full range of various rehabilitation exercises. PMID:27799727

Parallel Computation of the Regional Ocean Modeling System (ROMS)

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

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

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 ofmore » 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.« less

Large-scale parallel genome assembler over cloud computing environment.

PubMed

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering.

PubMed

Slepoy, A; Peters, M D; Thompson, A P

2007-11-30

Molecular dynamics and other molecular simulation methods rely on a potential energy function, based only on the relative coordinates of the atomic nuclei. Such a function, called a force field, approximately represents the electronic structure interactions of a condensed matter system. Developing such approximate functions and fitting their parameters remains an arduous, time-consuming process, relying on expert physical intuition. To address this problem, a functional programming methodology was developed that may enable automated discovery of entirely new force-field functional forms, while simultaneously fitting parameter values. The method uses a combination of genetic programming, Metropolis Monte Carlo importance sampling and parallel tempering, to efficiently search a large space of candidate functional forms and parameters. The methodology was tested using a nontrivial problem with a well-defined globally optimal solution: a small set of atomic configurations was generated and the energy of each configuration was calculated using the Lennard-Jones pair potential. Starting with a population of random functions, our fully automated, massively parallel implementation of the method reproducibly discovered the original Lennard-Jones pair potential by searching for several hours on 100 processors, sampling only a minuscule portion of the total search space. This result indicates that, with further improvement, the method may be suitable for unsupervised development of more accurate force fields with completely new functional forms. Copyright (c) 2007 Wiley Periodicals, Inc.

The novel implicit LU-SGS parallel iterative method based on the diffusion equation of a nuclear reactor on a GPU cluster

NASA Astrophysics Data System (ADS)

Zhang, Jilin; Sha, Chaoqun; Wu, Yusen; Wan, Jian; Zhou, Li; Ren, Yongjian; Si, Huayou; Yin, Yuyu; Jing, Ya

2017-02-01

GPU not only is used in the field of graphic technology but also has been widely used in areas needing a large number of numerical calculations. In the energy industry, because of low carbon, high energy density, high duration and other characteristics, the development of nuclear energy cannot easily be replaced by other energy sources. Management of core fuel is one of the major areas of concern in a nuclear power plant, and it is directly related to the economic benefits and cost of nuclear power. The large-scale reactor core expansion equation is large and complicated, so the calculation of the diffusion equation is crucial in the core fuel management process. In this paper, we use CUDA programming technology on a GPU cluster to run the LU-SGS parallel iterative calculation against the background of the diffusion equation of the reactor. We divide one-dimensional and two-dimensional mesh into a plurality of domains, with each domain evenly distributed on the GPU blocks. A parallel collision scheme is put forward that defines the virtual boundary of the grid exchange information and data transmission by non-stop collision. Compared with the serial program, the experiment shows that GPU greatly improves the efficiency of program execution and verifies that GPU is playing a much more important role in the field of numerical calculations.

Evolution and coevolution of developmental programs

NASA Astrophysics Data System (ADS)

Jacob, Christian

1999-09-01

The developmental processes of single organisms, such as growth and structure formation, can be described by parallel rewrite systems in the form of Lindenmayer systems, which also allow one to generate geometrical structures in 3D space using turtle interpretation. We present examples of L-systems for growth programs of plant-like structures. Evolution-based programming techniques are applied to design L-systems by Genetic L-system Programming (GLP), demonstrating how developmental programs for plants, exhibiting specific morphogenetic properties can be interactively bred or automatically evolved. Finally, we demonstrate coevolutionary effects among plant populations consisting of different species, interacting with each other, competing for resources like sunlight and nutrients, and evolving successful reproduction strategies in their specific environments.

Method for resource control in parallel environments using program organization and run-time support

NASA Technical Reports Server (NTRS)

Ekanadham, Kattamuri (Inventor); Moreira, Jose Eduardo (Inventor); Naik, Vijay Krishnarao (Inventor)

2001-01-01

A system and method for dynamic scheduling and allocation of resources to parallel applications during the course of their execution. By establishing well-defined interactions between an executing job and the parallel system, the system and method support dynamic reconfiguration of processor partitions, dynamic distribution and redistribution of data, communication among cooperating applications, and various other monitoring actions. The interactions occur only at specific points in the execution of the program where the aforementioned operations can be performed efficiently.

Method for resource control in parallel environments using program organization and run-time support

NASA Technical Reports Server (NTRS)

Ekanadham, Kattamuri (Inventor); Moreira, Jose Eduardo (Inventor); Naik, Vijay Krishnarao (Inventor)

1999-01-01

A system and method for dynamic scheduling and allocation of resources to parallel applications during the course of their execution. By establishing well-defined interactions between an executing job and the parallel system, the system and method support dynamic reconfiguration of processor partitions, dynamic distribution and redistribution of data, communication among cooperating applications, and various other monitoring actions. The interactions occur only at specific points in the execution of the program where the aforementioned operations can be performed efficiently.

XMOS XC-2 Development Board for Mechanical Control and Data Collection

NASA Technical Reports Server (NTRS)

Jarnot, Robert F.; Bowden, William J.

2011-01-01

The scanning microwave limb sounder (SMLS) will use technological improvements in low-noise mixers to provide precise data on the Earth s atmospheric composition with high spatial resolution. This project focuses on the design and implementation of a realtime control system needed for airborne engineering tests of the SMLS. The system must coordinate the actuation of optical components using four motors with encoder readback, while collecting synchronized telemetric data from a GPS receiver and 3-axis gyrometric system. A graphical user interface for testing the control system was also designed using Python. Although the system could have been implemented with an FPGA(fieldprogrammable gate array)-based setup, a processor development kit manufactured by XMOS was chosen. The XMOS architecture allows parallel execution of multiple tasks on separate threads, making it ideal for this application. It is easily programmed using XC (a subset of C). The necessary communication interfaces were implemented in software, including Ethernet, with significant cost and time reduction compared to an FPGA-based approach. A simple approach to control the chopper, calibration mirror, and gimbal for the airborne SMLS was needed. The XMOS board allows for multiple threads and real-time data acquisition. The XC-2 development kit is an attractive choice for synchronized, real-time, event-driven applications. The XMOS is based on the transputer microprocessor architecture developed for parallel computing, which is being revamped in this new platform. The XMOS device has multiple cores capable of running parallel applications on separate threads. The threads communicate with each other via user-defined channels capable of transmitting data within the device. XMOS provides a C-based development environment using XC, which eliminates the need for custom tool kits associated with FPGA programming. The XC-2 has four cores and necessary hardware for Ethernet I/O.

Semantic Language Extensions for Implicit Parallel Programming

DTIC Science & Technology

2013-09-01

mobile CPU interacts with a GPU on the same device and a cloud based backend at a remote location presents endless possibilities for solving com...for his contribution to the compiler infrastructure . His creativity in solving research problems and expertise in architecting and implementing...92 5.5.1 Frontend . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 5.5.2 Backend

Parallel community climate model: Description and user`s guide

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

Drake, J.B.; Flanery, R.E.; Semeraro, B.D.

This report gives an overview of a parallel version of the NCAR Community Climate Model, CCM2, implemented for MIMD massively parallel computers using a message-passing programming paradigm. The parallel implementation was developed on an Intel iPSC/860 with 128 processors and on the Intel Delta with 512 processors, and the initial target platform for the production version of the code is the Intel Paragon with 2048 processors. Because the implementation uses a standard, portable message-passing libraries, the code has been easily ported to other multiprocessors supporting a message-passing programming paradigm. The parallelization strategy used is to decompose the problem domain intomore » geographical patches and assign each processor the computation associated with a distinct subset of the patches. With this decomposition, the physics calculations involve only grid points and data local to a processor and are performed in parallel. Using parallel algorithms developed for the semi-Lagrangian transport, the fast Fourier transform and the Legendre transform, both physics and dynamics are computed in parallel with minimal data movement and modest change to the original CCM2 source code. Sequential or parallel history tapes are written and input files (in history tape format) are read sequentially by the parallel code to promote compatibility with production use of the model on other computer systems. A validation exercise has been performed with the parallel code and is detailed along with some performance numbers on the Intel Paragon and the IBM SP2. A discussion of reproducibility of results is included. A user`s guide for the PCCM2 version 2.1 on the various parallel machines completes the report. Procedures for compilation, setup and execution are given. A discussion of code internals is included for those who may wish to modify and use the program in their own research.« less

WaveJava: Wavelet-based network computing

NASA Astrophysics Data System (ADS)

Ma, Kun; Jiao, Licheng; Shi, Zhuoer

1997-04-01

Wavelet is a powerful theory, but its successful application still needs suitable programming tools. Java is a simple, object-oriented, distributed, interpreted, robust, secure, architecture-neutral, portable, high-performance, multi- threaded, dynamic language. This paper addresses the design and development of a cross-platform software environment for experimenting and applying wavelet theory. WaveJava, a wavelet class library designed by the object-orient programming, is developed to take advantage of the wavelets features, such as multi-resolution analysis and parallel processing in the networking computing. A new application architecture is designed for the net-wide distributed client-server environment. The data are transmitted with multi-resolution packets. At the distributed sites around the net, these data packets are done the matching or recognition processing in parallel. The results are fed back to determine the next operation. So, the more robust results can be arrived quickly. The WaveJava is easy to use and expand for special application. This paper gives a solution for the distributed fingerprint information processing system. It also fits for some other net-base multimedia information processing, such as network library, remote teaching and filmless picture archiving and communications.

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.

The Goddard Space Flight Center Program to develop parallel image processing systems

NASA Technical Reports Server (NTRS)

Schaefer, D. H.

1972-01-01

Parallel image processing which is defined as image processing where all points of an image are operated upon simultaneously is discussed. Coherent optical, noncoherent optical, and electronic methods are considered parallel image processing techniques.

Applying graph partitioning methods in measurement-based dynamic load balancing

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

Bhatele, Abhinav; Fourestier, Sebastien; Menon, Harshitha

Load imbalance leads to an increasing waste of resources as an application is scaled to more and more processors. Achieving the best parallel efficiency for a program requires optimal load balancing which is a NP-hard problem. However, finding near-optimal solutions to this problem for complex computational science and engineering applications is becoming increasingly important. Charm++, a migratable objects based programming model, provides a measurement-based dynamic load balancing framework. This framework instruments and then migrates over-decomposed objects to balance computational load and communication at runtime. This paper explores the use of graph partitioning algorithms, traditionally used for partitioning physical domains/meshes, formore » measurement-based dynamic load balancing of parallel applications. In particular, we present repartitioning methods developed in a graph partitioning toolbox called SCOTCH that consider the previous mapping to minimize migration costs. We also discuss a new imbalance reduction algorithm for graphs with irregular load distributions. We compare several load balancing algorithms using microbenchmarks on Intrepid and Ranger and evaluate the effect of communication, number of cores and number of objects on the benefit achieved from load balancing. New algorithms developed in SCOTCH lead to better performance compared to the METIS partitioners for several cases, both in terms of the application execution time and fewer number of objects migrated.« less

Parallel Volunteer Learning during Youth Programs

ERIC Educational Resources Information Center

Lesmeister, Marilyn K.; Green, Jeremy; Derby, Amy; Bothum, Candi

2012-01-01

Lack of time is a hindrance for volunteers to participate in educational opportunities, yet volunteer success in an organization is tied to the orientation and education they receive. Meeting diverse educational needs of volunteers can be a challenge for program managers. Scheduling a Volunteer Learning Track for chaperones that is parallel to a…

Embedding global and collective in a torus network with message class map based tree path selection

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

Chen, Dong; Coteus, Paul W.; Eisley, Noel A.

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computermore » program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.« less

Parallel, stochastic measurement of molecular surface area.

PubMed

Juba, Derek; Varshney, Amitabh

2008-08-01

Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering. We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.

Mechanism to support generic collective communication across a variety of programming models

DOEpatents

Almasi, Gheorghe [Ardsley, NY; Dozsa, Gabor [Ardsley, NY; Kumar, Sameer [White Plains, NY

2011-07-19

A system and method for supporting collective communications on a plurality of processors that use different parallel programming paradigms, in one aspect, may comprise a schedule defining one or more tasks in a collective operation, an executor that executes the task, a multisend module to perform one or more data transfer functions associated with the tasks, and a connection manager that controls one or more connections and identifies an available connection. The multisend module uses the available connection in performing the one or more data transfer functions. A plurality of processors that use different parallel programming paradigms can use a common implementation of the schedule module, the executor module, the connection manager and the multisend module via a language adaptor specific to a parallel programming paradigm implemented on a processor.

The TeraShake Computational Platform for Large-Scale Earthquake Simulations

NASA Astrophysics Data System (ADS)

Cui, Yifeng; Olsen, Kim; Chourasia, Amit; Moore, Reagan; Maechling, Philip; Jordan, Thomas

Geoscientific and computer science researchers with the Southern California Earthquake Center (SCEC) are conducting a large-scale, physics-based, computationally demanding earthquake system science research program with the goal of developing predictive models of earthquake processes. The computational demands of this program continue to increase rapidly as these researchers seek to perform physics-based numerical simulations of earthquake processes for larger meet the needs of this research program, a multiple-institution team coordinated by SCEC has integrated several scientific codes into a numerical modeling-based research tool we call the TeraShake computational platform (TSCP). A central component in the TSCP is a highly scalable earthquake wave propagation simulation program called the TeraShake anelastic wave propagation (TS-AWP) code. In this chapter, we describe how we extended an existing, stand-alone, wellvalidated, finite-difference, anelastic wave propagation modeling code into the highly scalable and widely used TS-AWP and then integrated this code into the TeraShake computational platform that provides end-to-end (initialization to analysis) research capabilities. We also describe the techniques used to enhance the TS-AWP parallel performance on TeraGrid supercomputers, as well as the TeraShake simulations phases including input preparation, run time, data archive management, and visualization. As a result of our efforts to improve its parallel efficiency, the TS-AWP has now shown highly efficient strong scaling on over 40K processors on IBM’s BlueGene/L Watson computer. In addition, the TSCP has developed into a computational system that is useful to many members of the SCEC community for performing large-scale earthquake simulations.

Programming with Intervals

NASA Astrophysics Data System (ADS)

Matsakis, Nicholas D.; Gross, Thomas R.

Intervals are a new, higher-level primitive for parallel programming with which programmers directly construct the program schedule. Programs using intervals can be statically analyzed to ensure that they do not deadlock or contain data races. In this paper, we demonstrate the flexibility of intervals by showing how to use them to emulate common parallel control-flow constructs like barriers and signals, as well as higher-level patterns such as bounded-buffer producer-consumer. We have implemented intervals as a publicly available library for Java and Scala.

Classification of hyperspectral imagery using MapReduce on a NVIDIA graphics processing unit (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ramirez, Andres; Rahnemoonfar, Maryam

2017-04-01

A hyperspectral image provides multidimensional figure rich in data consisting of hundreds of spectral dimensions. Analyzing the spectral and spatial information of such image with linear and non-linear algorithms will result in high computational time. In order to overcome this problem, this research presents a system using a MapReduce-Graphics Processing Unit (GPU) model that can help analyzing a hyperspectral image through the usage of parallel hardware and a parallel programming model, which will be simpler to handle compared to other low-level parallel programming models. Additionally, Hadoop was used as an open-source version of the MapReduce parallel programming model. This research compared classification accuracy results and timing results between the Hadoop and GPU system and tested it against the following test cases: the CPU and GPU test case, a CPU test case and a test case where no dimensional reduction was applied.

User's guide of TOUGH2-EGS-MP: A Massively Parallel Simulator with Coupled Geomechanics for Fluid and Heat Flow in Enhanced Geothermal Systems VERSION 1.0

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

Xiong, Yi; Fakcharoenphol, Perapon; Wang, Shihao

2013-12-01

TOUGH2-EGS-MP is a parallel numerical simulation program coupling geomechanics with fluid and heat flow in fractured and porous media, and is applicable for simulation of enhanced geothermal systems (EGS). TOUGH2-EGS-MP is based on the TOUGH2-MP code, the massively parallel version of TOUGH2. In TOUGH2-EGS-MP, the fully-coupled flow-geomechanics model is developed from linear elastic theory for thermo-poro-elastic systems and is formulated in terms of mean normal stress as well as pore pressure and temperature. Reservoir rock properties such as porosity and permeability depend on rock deformation, and the relationships between these two, obtained from poro-elasticity theories and empirical correlations, are incorporatedmore » into the simulation. This report provides the user with detailed information on the TOUGH2-EGS-MP mathematical model and instructions for using it for Thermal-Hydrological-Mechanical (THM) simulations. The mathematical model includes the fluid and heat flow equations, geomechanical equation, and discretization of those equations. In addition, the parallel aspects of the code, such as domain partitioning and communication between processors, are also included. Although TOUGH2-EGS-MP has the capability for simulating fluid and heat flows coupled with geomechanical effects, it is up to the user to select the specific coupling process, such as THM or only TH, in a simulation. There are several example problems illustrating applications of this program. These example problems are described in detail and their input data are presented. Their results demonstrate that this program can be used for field-scale geothermal reservoir simulation in porous and fractured media with fluid and heat flow coupled with geomechanical effects.« less

On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics

PubMed Central

Calcagno, Cristina; Coppo, Mario

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed. PMID:25050327

Data Acquisition System for Multi-Frequency Radar Flight Operations Preparation

NASA Technical Reports Server (NTRS)

Leachman, Jonathan

2010-01-01

A three-channel data acquisition system was developed for the NASA Multi-Frequency Radar (MFR) system. The system is based on a commercial-off-the-shelf (COTS) industrial PC (personal computer) and two dual-channel 14-bit digital receiver cards. The decimated complex envelope representations of the three radar signals are passed to the host PC via the PCI bus, and then processed in parallel by multiple cores of the PC CPU (central processing unit). The innovation is this parallelization of the radar data processing using multiple cores of a standard COTS multi-core CPU. The data processing portion of the data acquisition software was built using autonomous program modules or threads, which can run simultaneously on different cores. A master program module calculates the optimal number of processing threads, launches them, and continually supplies each with data. The benefit of this new parallel software architecture is that COTS PCs can be used to implement increasingly complex processing algorithms on an increasing number of radar range gates and data rates. As new PCs become available with higher numbers of CPU cores, the software will automatically utilize the additional computational capacity.

PREMER: a Tool to Infer Biological Networks.

PubMed

Villaverde, Alejandro F; Becker, Kolja; Banga, Julio R

2017-10-04

Inferring the structure of unknown cellular networks is a main challenge in computational biology. Data-driven approaches based on information theory can determine the existence of interactions among network nodes automatically. However, the elucidation of certain features - such as distinguishing between direct and indirect interactions or determining the direction of a causal link - requires estimating information-theoretic quantities in a multidimensional space. This can be a computationally demanding task, which acts as a bottleneck for the application of elaborate algorithms to large-scale network inference problems. The computational cost of such calculations can be alleviated by the use of compiled programs and parallelization. To this end we have developed PREMER (Parallel Reverse Engineering with Mutual information & Entropy Reduction), a software toolbox that can run in parallel and sequential environments. It uses information theoretic criteria to recover network topology and determine the strength and causality of interactions, and allows incorporating prior knowledge, imputing missing data, and correcting outliers. PREMER is a free, open source software tool that does not require any commercial software. Its core algorithms are programmed in FORTRAN 90 and implement OpenMP directives. It has user interfaces in Python and MATLAB/Octave, and runs on Windows, Linux and OSX (https://sites.google.com/site/premertoolbox/).

On designing multicore-aware simulators for systems biology endowed with OnLine statistics.

PubMed

Aldinucci, Marco; Calcagno, Cristina; Coppo, Mario; Damiani, Ferruccio; Drocco, Maurizio; Sciacca, Eva; Spinella, Salvatore; Torquati, Massimo; Troina, Angelo

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

A Fault Oblivious Extreme-Scale Execution Environment

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

McKie, Jim

The FOX project, funded under the ASCR X-stack I program, developed systems software and runtime libraries for a new approach to the data and work distribution for massively parallel, fault oblivious application execution. Our work was motivated by the premise that exascale computing systems will provide a thousand-fold increase in parallelism and a proportional increase in failure rate relative to today’s machines. To deliver the capability of exascale hardware, the systems software must provide the infrastructure to support existing applications while simultaneously enabling efficient execution of new programming models that naturally express dynamic, adaptive, irregular computation; coupled simulations; and massivemore » data analysis in a highly unreliable hardware environment with billions of threads of execution. Our OS research has prototyped new methods to provide efficient resource sharing, synchronization, and protection in a many-core compute node. We have experimented with alternative task/dataflow programming models and shown scalability in some cases to hundreds of thousands of cores. Much of our software is in active development through open source projects. Concepts from FOX are being pursued in next generation exascale operating systems. Our OS work focused on adaptive, application tailored OS services optimized for multi → many core processors. We developed a new operating system NIX that supports role-based allocation of cores to processes which was released to open source. We contributed to the IBM FusedOS project, which promoted the concept of latency-optimized and throughput-optimized cores. We built a task queue library based on distributed, fault tolerant key-value store and identified scaling issues. A second fault tolerant task parallel library was developed, based on the Linda tuple space model, that used low level interconnect primitives for optimized communication. We designed fault tolerance mechanisms for task parallel computations employing work stealing for load balancing that scaled to the largest existing supercomputers. Finally, we implemented the Elastic Building Blocks runtime, a library to manage object-oriented distributed software components. To support the research, we won two INCITE awards for time on Intrepid (BG/P) and Mira (BG/Q). Much of our work has had impact in the OS and runtime community through the ASCR Exascale OS/R workshop and report, leading to the research agenda of the Exascale OS/R program. Our project was, however, also affected by attrition of multiple PIs. While the PIs continued to participate and offer guidance as time permitted, losing these key individuals was unfortunate both for the project and for the DOE HPC community.« less

Multi-cluster processor operating only select number of clusters during each phase based on program statistic monitored at predetermined intervals

DOEpatents

Balasubramonian, Rajeev [Sandy, UT; Dwarkadas, Sandhya [Rochester, NY; Albonesi, David [Ithaca, NY

2009-02-10

In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied dynamically. At the start of each program phase, the configuration option for an interval is run to determine the optimal configuration, which is used until the next phase change is detected. The optimum instruction interval is determined by starting with a minimum interval and doubling it until a low stability factor is reached.

File concepts for parallel I/O

NASA Technical Reports Server (NTRS)

Crockett, Thomas W.

1989-01-01

The subject of input/output (I/O) was often neglected in the design of parallel computer systems, although for many problems I/O rates will limit the speedup attainable. The I/O problem is addressed by considering the role of files in parallel systems. The notion of parallel files is introduced. Parallel files provide for concurrent access by multiple processes, and utilize parallelism in the I/O system to improve performance. Parallel files can also be used conventionally by sequential programs. A set of standard parallel file organizations is proposed, organizations are suggested, using multiple storage devices. Problem areas are also identified and discussed.

Program For Parallel Discrete-Event Simulation

NASA Technical Reports Server (NTRS)

Beckman, Brian C.; Blume, Leo R.; Geiselman, John S.; Presley, Matthew T.; Wedel, John J., Jr.; Bellenot, Steven F.; Diloreto, Michael; Hontalas, Philip J.; Reiher, Peter L.; Weiland, Frederick P.

1991-01-01

User does not have to add any special logic to aid in synchronization. Time Warp Operating System (TWOS) computer program is special-purpose operating system designed to support parallel discrete-event simulation. Complete implementation of Time Warp mechanism. Supports only simulations and other computations designed for virtual time. Time Warp Simulator (TWSIM) subdirectory contains sequential simulation engine interface-compatible with TWOS. TWOS and TWSIM written in, and support simulations in, C programming language.

LLMapReduce: Multi-Lingual Map-Reduce for Supercomputing Environments

DTIC Science & Technology

2015-11-20

1990s. Popularized by Google [36] and Apache Hadoop [37], map-reduce has become a staple technology of the ever- growing big data community...Lexington, MA, U.S.A Abstract— The map-reduce parallel programming model has become extremely popular in the big data community. Many big data ...to big data users running on a supercomputer. LLMapReduce dramatically simplifies map-reduce programming by providing simple parallel programming

Creating a Parallel Version of VisIt for Microsoft Windows

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

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

2011-12-07

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

Debugging Fortran on a shared memory machine

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

Allen, T.R.; Padua, D.A.

1987-01-01

Debugging on a parallel processor is more difficult than debugging on a serial machine because errors in a parallel program may introduce nondeterminism. The approach to parallel debugging presented here attempts to reduce the problem of debugging on a parallel machine to that of debugging on a serial machine by automatically detecting nondeterminism. 20 refs., 6 figs.

Parallel computation and the basis system

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

Smith, G.R.

1993-05-01

A software package has been written that can facilitate efforts to develop powerful, flexible, and easy-to use programs that can run in single-processor, massively parallel, and distributed computing environments. Particular attention has been given to the difficulties posed by a program consisting of many science packages that represent subsystems of a complicated, coupled system. Methods have been found to maintain independence of the packages by hiding data structures without increasing the communications costs in a parallel computing environment. Concepts developed in this work are demonstrated by a prototype program that uses library routines from two existing software systems, Basis andmore » Parallel Virtual Machine (PVM). Most of the details of these libraries have been encapsulated in routines and macros that could be rewritten for alternative libraries that possess certain minimum capabilities. The prototype software uses a flexible master-and-slaves paradigm for parallel computation and supports domain decomposition with message passing for partitioning work among slaves. Facilities are provided for accessing variables that are distributed among the memories of slaves assigned to subdomains. The software is named PROTOPAR.« less

The Automated Instrumentation and Monitoring System (AIMS) reference manual

NASA Technical Reports Server (NTRS)

Yan, Jerry; Hontalas, Philip; Listgarten, Sherry

1993-01-01

Whether a researcher is designing the 'next parallel programming paradigm,' another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of execution traces can help computer designers and software architects to uncover system behavior and to take advantage of specific application characteristics and hardware features. A software tool kit that facilitates performance evaluation of parallel applications on multiprocessors is described. The Automated Instrumentation and Monitoring System (AIMS) has four major software components: a source code instrumentor which automatically inserts active event recorders into the program's source code before compilation; a run time performance-monitoring library, which collects performance data; a trace file animation and analysis tool kit which reconstructs program execution from the trace file; and a trace post-processor which compensate for data collection overhead. Besides being used as prototype for developing new techniques for instrumenting, monitoring, and visualizing parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware test beds to evaluate their impact on user productivity. Currently, AIMS instrumentors accept FORTRAN and C parallel programs written for Intel's NX operating system on the iPSC family of multi computers. A run-time performance-monitoring library for the iPSC/860 is included in this release. We plan to release monitors for other platforms (such as PVM and TMC's CM-5) in the near future. Performance data collected can be graphically displayed on workstations (e.g. Sun Sparc and SGI) supporting X-Windows (in particular, Xl IR5, Motif 1.1.3).

Tensor contraction engine: Abstraction and automated parallel implementation of configuration-interaction, coupled-cluster, and many-body perturbation theories

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

Hirata, So

2003-11-20

We develop a symbolic manipulation program and program generator (Tensor Contraction Engine or TCE) that automatically derives the working equations of a well-defined model of second-quantized many-electron theories and synthesizes efficient parallel computer programs on the basis of these equations. Provided an ansatz of a many-electron theory model, TCE performs valid contractions of creation and annihilation operators according to Wick's theorem, consolidates identical terms, and reduces the expressions into the form of multiple tensor contractions acted by permutation operators. Subsequently, it determines the binary contraction order for each multiple tensor contraction with the minimal operation and memory cost, factorizes commonmore » binary contractions (defines intermediate tensors), and identifies reusable intermediates. The resulting ordered list of binary tensor contractions, additions, and index permutations is translated into an optimized program that is combined with the NWChem and UTChem computational chemistry software packages. The programs synthesized by TCE take advantage of spin symmetry, Abelian point-group symmetry, and index permutation symmetry at every stage of calculations to minimize the number of arithmetic operations and storage requirement, adjust the peak local memory usage by index range tiling, and support parallel I/O interfaces and dynamic load balancing for parallel executions. We demonstrate the utility of TCE through automatic derivation and implementation of parallel programs for various models of configuration-interaction theory (CISD, CISDT, CISDTQ), many-body perturbation theory [MBPT(2), MBPT(3), MBPT(4)], and coupled-cluster theory (LCCD, CCD, LCCSD, CCSD, QCISD, CCSDT, and CCSDTQ).« less

Parallel eigenanalysis of finite element models in a completely connected architecture

NASA Technical Reports Server (NTRS)

Akl, F. A.; Morel, M. R.

1989-01-01

A parallel algorithm is presented for the solution of the generalized eigenproblem in linear elastic finite element analysis, (K)(phi) = (M)(phi)(omega), where (K) and (M) are of order N, and (omega) is order of q. The concurrent solution of the eigenproblem is based on the multifrontal/modified subspace method and is achieved in a completely connected parallel architecture in which each processor is allowed to communicate with all other processors. The algorithm was successfully implemented on a tightly coupled multiple-instruction multiple-data parallel processing machine, Cray X-MP. A finite element model is divided into m domains each of which is assumed to process n elements. Each domain is then assigned to a processor or to a logical processor (task) if the number of domains exceeds the number of physical processors. The macrotasking library routines are used in mapping each domain to a user task. Computational speed-up and efficiency are used to determine the effectiveness of the algorithm. The effect of the number of domains, the number of degrees-of-freedom located along the global fronts and the dimension of the subspace on the performance of the algorithm are investigated. A parallel finite element dynamic analysis program, p-feda, is documented and the performance of its subroutines in parallel environment is analyzed.

Parallel computer vision

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

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

Parallel Performance of a Combustion Chemistry Simulation

DOE PAGES

Skinner, Gregg; Eigenmann, Rudolf

1995-01-01

We used a description of a combustion simulation's mathematical and computational methods to develop a version for parallel execution. The result was a reasonable performance improvement on small numbers of processors. We applied several important programming techniques, which we describe, in optimizing the application. This work has implications for programming languages, compiler design, and software engineering.

Algorithms and programming tools for image processing on the MPP, part 2

NASA Technical Reports Server (NTRS)

Reeves, Anthony P.

1986-01-01

A number of algorithms were developed for image warping and pyramid image filtering. Techniques were investigated for the parallel processing of a large number of independent irregular shaped regions on the MPP. In addition some utilities for dealing with very long vectors and for sorting were developed. Documentation pages for the algorithms which are available for distribution are given. The performance of the MPP for a number of basic data manipulations was determined. From these results it is possible to predict the efficiency of the MPP for a number of algorithms and applications. The Parallel Pascal development system, which is a portable programming environment for the MPP, was improved and better documentation including a tutorial was written. This environment allows programs for the MPP to be developed on any conventional computer system; it consists of a set of system programs and a library of general purpose Parallel Pascal functions. The algorithms were tested on the MPP and a presentation on the development system was made to the MPP users group. The UNIX version of the Parallel Pascal System was distributed to a number of new sites.

Scalable Unix commands for parallel processors : a high-performance implementation.

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

Ong, E.; Lusk, E.; Gropp, W.

2001-06-22

We describe a family of MPI applications we call the Parallel Unix Commands. These commands are natural parallel versions of common Unix user commands such as ls, ps, and find, together with a few similar commands particular to the parallel environment. We describe the design and implementation of these programs and present some performance results on a 256-node Linux cluster. The Parallel Unix Commands are open source and freely available.

Parallel language constructs for tensor product computations on loosely coupled architectures

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Van Rosendale, John

1989-01-01

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

Report from the MPP Working Group to the NASA Associate Administrator for Space Science and Applications

NASA Technical Reports Server (NTRS)

Fischer, James R.; Grosch, Chester; Mcanulty, Michael; Odonnell, John; Storey, Owen

1987-01-01

NASA's Office of Space Science and Applications (OSSA) gave a select group of scientists the opportunity to test and implement their computational algorithms on the Massively Parallel Processor (MPP) located at Goddard Space Flight Center, beginning in late 1985. One year later, the Working Group presented its report, which addressed the following: algorithms, programming languages, architecture, programming environments, the way theory relates, and performance measured. The findings point to a number of demonstrated computational techniques for which the MPP architecture is ideally suited. For example, besides executing much faster on the MPP than on conventional computers, systolic VLSI simulation (where distances are short), lattice simulation, neural network simulation, and image problems were found to be easier to program on the MPP's architecture than on a CYBER 205 or even a VAX. The report also makes technical recommendations covering all aspects of MPP use, and recommendations concerning the future of the MPP and machines based on similar architectures, expansion of the Working Group, and study of the role of future parallel processors for space station, EOS, and the Great Observatories era.

Role of HPC in Advancing Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.

2004-01-01

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

A CS1 pedagogical approach to parallel thinking

NASA Astrophysics Data System (ADS)

Rague, Brian William

Almost all collegiate programs in Computer Science offer an introductory course in programming primarily devoted to communicating the foundational principles of software design and development. The ACM designates this introduction to computer programming course for first-year students as CS1, during which methodologies for solving problems within a discrete computational context are presented. Logical thinking is highlighted, guided primarily by a sequential approach to algorithm development and made manifest by typically using the latest, commercially successful programming language. In response to the most recent developments in accessible multicore computers, instructors of these introductory classes may wish to include training on how to design workable parallel code. Novel issues arise when programming concurrent applications which can make teaching these concepts to beginning programmers a seemingly formidable task. Student comprehension of design strategies related to parallel systems should be monitored to ensure an effective classroom experience. This research investigated the feasibility of integrating parallel computing concepts into the first-year CS classroom. To quantitatively assess student comprehension of parallel computing, an experimental educational study using a two-factor mixed group design was conducted to evaluate two instructional interventions in addition to a control group: (1) topic lecture only, and (2) topic lecture with laboratory work using a software visualization Parallel Analysis Tool (PAT) specifically designed for this project. A new evaluation instrument developed for this study, the Perceptions of Parallelism Survey (PoPS), was used to measure student learning regarding parallel systems. The results from this educational study show a statistically significant main effect among the repeated measures, implying that student comprehension levels of parallel concepts as measured by the PoPS improve immediately after the delivery of any initial three-week CS1 level module when compared with student comprehension levels just prior to starting the course. Survey results measured during the ninth week of the course reveal that performance levels remained high compared to pre-course performance scores. A second result produced by this study reveals no statistically significant interaction effect between the intervention method and student performance as measured by the evaluation instrument over three separate testing periods. However, visual inspection of survey score trends and the low p-value generated by the interaction analysis (0.062) indicate that further studies may verify improved concept retention levels for the lecture w/PAT group.

PISCES 2 users manual

NASA Technical Reports Server (NTRS)

Pratt, Terrence W.

1987-01-01

PISCES 2 is a programming environment and set of extensions to Fortran 77 for parallel programming. It is intended to provide a basis for writing programs for scientific and engineering applications on parallel computers in a way that is relatively independent of the particular details of the underlying computer architecture. This user's manual provides a complete description of the PISCES 2 system as it is currently implemented on the 20 processor Flexible FLEX/32 at NASA Langley Research Center.

Highly efficient and exact method for parallelization of grid-based algorithms and its implementation in DelPhi

PubMed Central

Li, Chuan; Li, Lin; Zhang, Jie; Alexov, Emil

2012-01-01

The Gauss-Seidel method is a standard iterative numerical method widely used to solve a system of equations and, in general, is more efficient comparing to other iterative methods, such as the Jacobi method. However, standard implementation of the Gauss-Seidel method restricts its utilization in parallel computing due to its requirement of using updated neighboring values (i.e., in current iteration) as soon as they are available. Here we report an efficient and exact (not requiring assumptions) method to parallelize iterations and to reduce the computational time as a linear/nearly linear function of the number of CPUs. In contrast to other existing solutions, our method does not require any assumptions and is equally applicable for solving linear and nonlinear equations. This approach is implemented in the DelPhi program, which is a finite difference Poisson-Boltzmann equation solver to model electrostatics in molecular biology. This development makes the iterative procedure on obtaining the electrostatic potential distribution in the parallelized DelPhi several folds faster than that in the serial code. Further we demonstrate the advantages of the new parallelized DelPhi by computing the electrostatic potential and the corresponding energies of large supramolecular structures. PMID:22674480

First experience with particle-in-cell plasma physics code on ARM-based HPC systems

NASA Astrophysics Data System (ADS)

Sáez, Xavier; Soba, Alejandro; Sánchez, Edilberto; Mantsinen, Mervi; Mateo, Sergi; Cela, José M.; Castejón, Francisco

2015-09-01

In this work, we will explore the feasibility of porting a Particle-in-cell code (EUTERPE) to an ARM multi-core platform from the Mont-Blanc project. The used prototype is based on a system-on-chip Samsung Exynos 5 with an integrated GPU. It is the first prototype that could be used for High-Performance Computing (HPC), since it supports double precision and parallel programming languages.

Code Parallelization with CAPO: A User Manual

NASA Technical Reports Server (NTRS)

Jin, Hao-Qiang; Frumkin, Michael; Yan, Jerry; Biegel, Bryan (Technical Monitor)

2001-01-01

A software tool has been developed to assist the parallelization of scientific codes. This tool, CAPO, extends an existing parallelization toolkit, CAPTools developed at the University of Greenwich, to generate OpenMP parallel codes for shared memory architectures. This is an interactive toolkit to transform a serial Fortran application code to an equivalent parallel version of the software - in a small fraction of the time normally required for a manual parallelization. We first discuss the way in which loop types are categorized and how efficient OpenMP directives can be defined and inserted into the existing code using the in-depth interprocedural analysis. The use of the toolkit on a number of application codes ranging from benchmark to real-world application codes is presented. This will demonstrate the great potential of using the toolkit to quickly parallelize serial programs as well as the good performance achievable on a large number of toolkit to quickly parallelize serial programs as well as the good performance achievable on a large number of processors. The second part of the document gives references to the parameters and the graphic user interface implemented in the toolkit. Finally a set of tutorials is included for hands-on experiences with this toolkit.

Management Trainee Program of Turkish Airlines: Global Distance Education

ERIC Educational Resources Information Center

Karasar, Sahin; Öztürk, Ömer Faruk

2014-01-01

It has always been a contested task to try to present a scientific base for the concept of "management." The concept of management, which has always been of great importance to the institutions and organizations, has gone through periodical changes both in terms of its structure and scope, and improved in a parallel fashion as the time…

Pedagogy, Praxis and Purpose in Education. Routledge Research in Education Policy and Politics

ERIC Educational Resources Information Center

Mulcahy, C. M.; Mulcahy, D. E.; Mulcahy, D. G.

2014-01-01

Recent years have shown the growth of federal legislation and programs having a profound impact on educational policy and practice, and a decline in reliance on broadly based educational justifications. Paralleling this development has been the emergence of well-endowed and influential private foundations, and an increase in corporate influence in…

Preconditioned implicit solvers for the Navier-Stokes equations on distributed-memory machines

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Liou, Meng-Sing; Dyson, Rodger W.

1994-01-01

The GMRES method is parallelized, and combined with local preconditioning to construct an implicit parallel solver to obtain steady-state solutions for the Navier-Stokes equations of fluid flow on distributed-memory machines. The new implicit parallel solver is designed to preserve the convergence rate of the equivalent 'serial' solver. A static domain-decomposition is used to partition the computational domain amongst the available processing nodes of the parallel machine. The SPMD (Single-Program Multiple-Data) programming model is combined with message-passing tools to develop the parallel code on a 32-node Intel Hypercube and a 512-node Intel Delta machine. The implicit parallel solver is validated for internal and external flow problems, and is found to compare identically with flow solutions obtained on a Cray Y-MP/8. A peak computational speed of 2300 MFlops/sec has been achieved on 512 nodes of the Intel Delta machine,k for a problem size of 1024 K equations (256 K grid points).

Implementation of a parallel protein structure alignment service on cloud.

PubMed

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.

Paradigms and strategies for scientific computing on distributed memory concurrent computers

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

Foster, I.T.; Walker, D.W.

1994-06-01

In this work we examine recent advances in parallel languages and abstractions that have the potential for improving the programmability and maintainability of large-scale, parallel, scientific applications running on high performance architectures and networks. This paper focuses on Fortran M, a set of extensions to Fortran 77 that supports the modular design of message-passing programs. We describe the Fortran M implementation of a particle-in-cell (PIC) plasma simulation application, and discuss issues in the optimization of the code. The use of two other methodologies for parallelizing the PIC application are considered. The first is based on the shared object abstraction asmore » embodied in the Orca language. The second approach is the Split-C language. In Fortran M, Orca, and Split-C the ability of the programmer to control the granularity of communication is important is designing an efficient implementation.« less

Implementation of a Parallel Protein Structure Alignment Service on Cloud

PubMed Central

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform. PMID:23671842

Programming a hillslope water movement model on the MPP

NASA Technical Reports Server (NTRS)

Devaney, J. E.; Irving, A. R.; Camillo, P. J.; Gurney, R. J.

1987-01-01

A physically based numerical model was developed of heat and moisture flow within a hillslope on a parallel architecture computer, as a precursor to a model of a complete catchment. Moisture flow within a catchment includes evaporation, overland flow, flow in unsaturated soil, and flow in saturated soil. Because of the empirical evidence that moisture flow in unsaturated soil is mainly in the vertical direction, flow in the unsaturated zone can be modeled as a series of one dimensional columns. This initial version of the hillslope model includes evaporation and a single column of one dimensional unsaturated zone flow. This case has already been solved on an IBM 3081 computer and is now being applied to the massively parallel processor architecture so as to make the extension to the one dimensional case easier and to check the problems and benefits of using a parallel architecture machine.

Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.

PubMed

Peker, Musa; Şen, Baha; Gürüler, Hüseyin

2015-02-01

The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.

Accelerated Adaptive MGS Phase Retrieval

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs.

PubMed

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-05-28

Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4-15.9 times faster, while Unphased jobs performed 1.1-18.6 times faster compared to the accumulated computation duration. Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance.

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs

PubMed Central

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-01-01

Background Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Results Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4–15.9 times faster, while Unphased jobs performed 1.1–18.6 times faster compared to the accumulated computation duration. Conclusion Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance. PMID:18541045

CESDIS

NASA Technical Reports Server (NTRS)

1994-01-01

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

PIPS-SBB: A Parallel Distributed-Memory Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs

DOE PAGES

Munguia, Lluis-Miquel; Oxberry, Geoffrey; Rajan, Deepak

2016-05-01

Stochastic mixed-integer programs (SMIPs) deal with optimization under uncertainty at many levels of the decision-making process. When solved as extensive formulation mixed- integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPS-SBB: a distributed-memory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPS-SBB to improve furthermore » as more functionality is added in the future.« less

A design methodology for portable software on parallel computers

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Parallel Logic Programming and Parallel Systems Software and Hardware

DTIC Science & Technology

1989-07-29

Conference, Dallas TX. January 1985. (55) [Rous75] Roussel, P., "PROLOG: Manuel de Reference et d’Uilisation", Group d’ Intelligence Artificielle , Universite d...completed. Tools were provided for software development using artificial intelligence techniques. Al software for massively parallel architectures was...using artificial intelligence tech- niques. Al software for massively parallel architectures was started. 1. Introduction We describe research conducted

Virtual earthquake engineering laboratory with physics-based degrading materials on parallel computers

NASA Astrophysics Data System (ADS)

Cho, In Ho

For the last few decades, we have obtained tremendous insight into underlying microscopic mechanisms of degrading quasi-brittle materials from persistent and near-saintly efforts in laboratories, and at the same time we have seen unprecedented evolution in computational technology such as massively parallel computers. Thus, time is ripe to embark on a novel approach to settle unanswered questions, especially for the earthquake engineering community, by harmoniously combining the microphysics mechanisms with advanced parallel computing technology. To begin with, it should be stressed that we placed a great deal of emphasis on preserving clear meaning and physical counterparts of all the microscopic material models proposed herein, since it is directly tied to the belief that by doing so, the more physical mechanisms we incorporate, the better prediction we can obtain. We departed from reviewing representative microscopic analysis methodologies, selecting out "fixed-type" multidirectional smeared crack model as the base framework for nonlinear quasi-brittle materials, since it is widely believed to best retain the physical nature of actual cracks. Microscopic stress functions are proposed by integrating well-received existing models to update normal stresses on the crack surfaces (three orthogonal surfaces are allowed to initiate herein) under cyclic loading. Unlike the normal stress update, special attention had to be paid to the shear stress update on the crack surfaces, due primarily to the well-known pathological nature of the fixed-type smeared crack model---spurious large stress transfer over the open crack under nonproportional loading. In hopes of exploiting physical mechanism to resolve this deleterious nature of the fixed crack model, a tribology-inspired three-dimensional (3d) interlocking mechanism has been proposed. Following the main trend of tribology (i.e., the science and engineering of interacting surfaces), we introduced the base fabric of solid particle-soft matrix to explain realistic interlocking over rough crack surfaces, and the adopted Gaussian distribution feeds random particle sizes to the entire domain. Validation against a well-documented rough crack experiment reveals promising accuracy of the proposed 3d interlocking model. A consumed energy-based damage model has been proposed for the weak correlation between the normal and shear stresses on the crack surfaces, and also for describing the nature of irrecoverable damage. Since the evaluation of the consumed energy is directly linked to the microscopic deformation, which can be efficiently tracked on the crack surfaces, the proposed damage model is believed to provide a more physical interpretation than existing damage mechanics, which fundamentally stem from mathematical derivation with few physical counterparts. Another novel point of the present work lies in the topological transition-based "smart" steel bar model, notably with evolving compressive buckling length. We presented a systematic framework of information flow between the key ingredients of composite materials (i.e., steel bar and its surrounding concrete elements). The smart steel model suggested can incorporate smooth transition during reversal loading, tensile rupture, early buckling after reversal from excessive tensile loading, and even compressive buckling. Especially, the buckling length is made to evolve according to the damage states of the surrounding elements of each bar, while all other dominant models leave the length unchanged. What lies behind all the aforementioned novel attempts is, of course, the problem-optimized parallel platform. In fact, the parallel computing in our field has been restricted to monotonic shock or blast loading with explicit algorithm which is characteristically feasible to be parallelized. In the present study, efficient parallelization strategies for the highly demanding implicit nonlinear finite element analysis (FEA) program for real-scale reinforced concrete (RC) structures under cyclic loading are proposed. Quantitative comparison of state-of-the-art parallel strategies, in terms of factorization, had been carried out, leading to the problem-optimized solver, which is successfully embracing the penalty method and banded nature. Particularly, the penalty method employed imparts considerable smoothness to the global response, which yields a practical superiority of the parallel triangular system solver over other advanced solvers such as parallel preconditioned conjugate gradient method. Other salient issues on parallelization are also addressed. The parallel platform established offers unprecedented access to simulations of real-scale structures, giving new understanding about the physics-based mechanisms adopted and probabilistic randomness at the entire system level. Particularly, the platform enables bold simulations of real-scale RC structures exposed to cyclic loading---H-shaped wall system and 4-story T-shaped wall system. The simulations show the desired capability of accurate prediction of global force-displacement responses, postpeak softening behavior, and compressive buckling of longitudinal steel bars. It is fascinating to see that intrinsic randomness of the 3d interlocking model appears to cause "localized" damage of the real-scale structures, which is consistent with reported observations in different fields such as granular media. Equipped with accuracy, stability and scalability as demonstrated so far, the parallel platform is believed to serve as a fertile ground for the introducing of further physical mechanisms into various research fields as well as the earthquake engineering community. In the near future, it can be further expanded to run in concert with reliable FEA programs such as FRAME3d or OPENSEES. Following the central notion of "multiscale" analysis technique, actual infrastructures exposed to extreme natural hazard can be successfully tackled by this next generation analysis tool---the harmonious union of the parallel platform and a general FEA program. At the same time, any type of experiments can be easily conducted by this "virtual laboratory."

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Efficient Thread Labeling for Monitoring Programs with Nested Parallelism

NASA Astrophysics Data System (ADS)

Ha, Ok-Kyoon; Kim, Sun-Sook; Jun, Yong-Kee

It is difficult and cumbersome to detect data races occurred in an execution of parallel programs. Any on-the-fly race detection techniques using Lamport's happened-before relation needs a thread labeling scheme for generating unique identifiers which maintain logical concurrency information for the parallel threads. NR labeling is an efficient thread labeling scheme for the fork-join program model with nested parallelism, because its efficiency depends only on the nesting depth for every fork and join operation. This paper presents an improved NR labeling, called e-NR labeling, in which every thread generates its label by inheriting the pointer to its ancestor list from the parent threads or by updating the pointer in a constant amount of time and space. This labeling is more efficient than the NR labeling, because its efficiency does not depend on the nesting depth for every fork and join operation. Some experiments were performed with OpenMP programs having nesting depths of three or four and maximum parallelisms varying from 10,000 to 1,000,000. The results show that e-NR is 5 times faster than NR labeling and 4.3 times faster than OS labeling in the average time for creating and maintaining the thread labels. In average space required for labeling, it is 3.5 times smaller than NR labeling and 3 times smaller than OS labeling.

User-Defined Data Distributions in High-Level Programming Languages

NASA Technical Reports Server (NTRS)

Diaconescu, Roxana E.; Zima, Hans P.

2006-01-01

One of the characteristic features of today s high performance computing systems is a physically distributed memory. Efficient management of locality is essential for meeting key performance requirements for these architectures. The standard technique for dealing with this issue has involved the extension of traditional sequential programming languages with explicit message passing, in the context of a processor-centric view of parallel computation. This has resulted in complex and error-prone assembly-style codes in which algorithms and communication are inextricably interwoven. This paper presents a high-level approach to the design and implementation of data distributions. Our work is motivated by the need to improve the current parallel programming methodology by introducing a paradigm supporting the development of efficient and reusable parallel code. This approach is currently being implemented in the context of a new programming language called Chapel, which is designed in the HPCS project Cascade.

Block-Parallel Data Analysis with DIY2

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

Morozov, Dmitriy; Peterka, Tom

DIY2 is a programming model and runtime for block-parallel analytics on distributed-memory machines. Its main abstraction is block-structured data parallelism: data are decomposed into blocks; blocks are assigned to processing elements (processes or threads); computation is described as iterations over these blocks, and communication between blocks is defined by reusable patterns. By expressing computation in this general form, the DIY2 runtime is free to optimize the movement of blocks between slow and fast memories (disk and flash vs. DRAM) and to concurrently execute blocks residing in memory with multiple threads. This enables the same program to execute in-core, out-of-core, serial,more » parallel, single-threaded, multithreaded, or combinations thereof. This paper describes the implementation of the main features of the DIY2 programming model and optimizations to improve performance. DIY2 is evaluated on benchmark test cases to establish baseline performance for several common patterns and on larger complete analysis codes running on large-scale HPC machines.« less

Parallel Rendering of Large Time-Varying Volume Data

NASA Technical Reports Server (NTRS)

Garbutt, Alexander E.

2005-01-01

Interactive visualization of large time-varying 3D volume datasets has been and still is a great challenge to the modem computational world. It stretches the limits of the memory capacity, the disk space, the network bandwidth and the CPU speed of a conventional computer. In this SURF project, we propose to develop a parallel volume rendering program on SGI's Prism, a cluster computer equipped with state-of-the-art graphic hardware. The proposed program combines both parallel computing and hardware rendering in order to achieve an interactive rendering rate. We use 3D texture mapping and a hardware shader to implement 3D volume rendering on each workstation. We use SGI's VisServer to enable remote rendering using Prism's graphic hardware. And last, we will integrate this new program with ParVox, a parallel distributed visualization system developed at JPL. At the end of the project, we Will demonstrate remote interactive visualization using this new hardware volume renderer on JPL's Prism System using a time-varying dataset from selected JPL applications.

Solving Partial Differential Equations in a data-driven multiprocessor environment

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

Gaudiot, J.L.; Lin, C.M.; Hosseiniyar, M.

1988-12-31

Partial differential equations can be found in a host of engineering and scientific problems. The emergence of new parallel architectures has spurred research in the definition of parallel PDE solvers. Concurrently, highly programmable systems such as data-how architectures have been proposed for the exploitation of large scale parallelism. The implementation of some Partial Differential Equation solvers (such as the Jacobi method) on a tagged token data-flow graph is demonstrated here. Asynchronous methods (chaotic relaxation) are studied and new scheduling approaches (the Token No-Labeling scheme) are introduced in order to support the implementation of the asychronous methods in a data-driven environment.more » New high-level data-flow language program constructs are introduced in order to handle chaotic operations. Finally, the performance of the program graphs is demonstrated by a deterministic simulation of a message passing data-flow multiprocessor. An analysis of the overhead in the data-flow graphs is undertaken to demonstrate the limits of parallel operations in dataflow PDE program graphs.« less

Visual analysis of inter-process communication for large-scale parallel computing.

PubMed

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

Roofline model toolkit: A practical tool for architectural and program analysis

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

Lo, Yu Jung; Williams, Samuel; Van Straalen, Brian

We present preliminary results of the Roofline Toolkit for multicore, many core, and accelerated architectures. This paper focuses on the processor architecture characterization engine, a collection of portable instrumented micro benchmarks implemented with Message Passing Interface (MPI), and OpenMP used to express thread-level parallelism. These benchmarks are specialized to quantify the behavior of different architectural features. Compared to previous work on performance characterization, these microbenchmarks focus on capturing the performance of each level of the memory hierarchy, along with thread-level parallelism, instruction-level parallelism and explicit SIMD parallelism, measured in the context of the compilers and run-time environments. We also measuremore » sustained PCIe throughput with four GPU memory managed mechanisms. By combining results from the architecture characterization with the Roofline model based solely on architectural specifications, this work offers insights for performance prediction of current and future architectures and their software systems. To that end, we instrument three applications and plot their resultant performance on the corresponding Roofline model when run on a Blue Gene/Q architecture.« less

Multi-GPU parallel algorithm design and analysis for improved inversion of probability tomography with gravity gradiometry data

NASA Astrophysics Data System (ADS)

Hou, Zhenlong; Huang, Danian

2017-09-01

In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.

On Parallelizing Single Dynamic Simulation Using HPC Techniques and APIs of Commercial Software

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

Diao, Ruisheng; Jin, Shuangshuang; Howell, Frederic

Time-domain simulations are heavily used in today’s planning and operation practices to assess power system transient stability and post-transient voltage/frequency profiles following severe contingencies to comply with industry standards. Because of the increased modeling complexity, it is several times slower than real time for state-of-the-art commercial packages to complete a dynamic simulation for a large-scale model. With the growing stochastic behavior introduced by emerging technologies, power industry has seen a growing need for performing security assessment in real time. This paper presents a parallel implementation framework to speed up a single dynamic simulation by leveraging the existing stability model librarymore » in commercial tools through their application programming interfaces (APIs). Several high performance computing (HPC) techniques are explored such as parallelizing the calculation of generator current injection, identifying fast linear solvers for network solution, and parallelizing data outputs when interacting with APIs in the commercial package, TSAT. The proposed method has been tested on a WECC planning base case with detailed synchronous generator models and exhibits outstanding scalable performance with sufficient accuracy.« less

Integrating Cache Performance Modeling and Tuning Support in Parallelization Tools

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

With the resurgence of distributed shared memory (DSM) systems based on cache-coherent Non Uniform Memory Access (ccNUMA) architectures and increasing disparity between memory and processors speeds, data locality overheads are becoming the greatest bottlenecks in the way of realizing potential high performance of these systems. While parallelization tools and compilers facilitate the users in porting their sequential applications to a DSM system, a lot of time and effort is needed to tune the memory performance of these applications to achieve reasonable speedup. In this paper, we show that integrating cache performance modeling and tuning support within a parallelization environment can alleviate this problem. The Cache Performance Modeling and Prediction Tool (CPMP), employs trace-driven simulation techniques without the overhead of generating and managing detailed address traces. CPMP predicts the cache performance impact of source code level "what-if" modifications in a program to assist a user in the tuning process. CPMP is built on top of a customized version of the Computer Aided Parallelization Tools (CAPTools) environment. Finally, we demonstrate how CPMP can be applied to tune a real Computational Fluid Dynamics (CFD) application.

Parallel machine architecture and compiler design facilities

NASA Technical Reports Server (NTRS)

Kuck, David J.; Yew, Pen-Chung; Padua, David; Sameh, Ahmed; Veidenbaum, Alex

1990-01-01

The objective is to provide an integrated simulation environment for studying and evaluating various issues in designing parallel systems, including machine architectures, parallelizing compiler techniques, and parallel algorithms. The status of Delta project (which objective is to provide a facility to allow rapid prototyping of parallelized compilers that can target toward different machine architectures) is summarized. Included are the surveys of the program manipulation tools developed, the environmental software supporting Delta, and the compiler research projects in which Delta has played a role.

The OpenMP Implementation of NAS Parallel Benchmarks and its Performance

NASA Technical Reports Server (NTRS)

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

1999-01-01

As the new ccNUMA architecture became popular in recent years, parallel programming with compiler directives on these machines has evolved to accommodate new needs. In this study, we examine the effectiveness of OpenMP directives for parallelizing the NAS Parallel Benchmarks. Implementation details will be discussed and performance will be compared with the MPI implementation. We have demonstrated that OpenMP can achieve very good results for parallelization on a shared memory system, but effective use of memory and cache is very important.

Monitoring Data-Structure Evolution in Distributed Message-Passing Programs

NASA Technical Reports Server (NTRS)

Sarukkai, Sekhar R.; Beers, Andrew; Woodrow, Thomas S. (Technical Monitor)

1996-01-01

Monitoring the evolution of data structures in parallel and distributed programs, is critical for debugging its semantics and performance. However, the current state-of-art in tracking and presenting data-structure information on parallel and distributed environments is cumbersome and does not scale. In this paper we present a methodology that automatically tracks memory bindings (not the actual contents) of static and dynamic data-structures of message-passing C programs, using PVM. With the help of a number of examples we show that in addition to determining the impact of memory allocation overheads on program performance, graphical views can help in debugging the semantics of program execution. Scalable animations of virtual address bindings of source-level data-structures are used for debugging the semantics of parallel programs across all processors. In conjunction with light-weight core-files, this technique can be used to complement traditional debuggers on single processors. Detailed information (such as data-structure contents), on specific nodes, can be determined using traditional debuggers after the data structure evolution leading to the semantic error is observed graphically.

A Linguistic Model in Component Oriented Programming

NASA Astrophysics Data System (ADS)

Crăciunean, Daniel Cristian; Crăciunean, Vasile

2016-12-01

It is a fact that the component-oriented programming, well organized, can bring a large increase in efficiency in the development of large software systems. This paper proposes a model for building software systems by assembling components that can operate independently of each other. The model is based on a computing environment that runs parallel and distributed applications. This paper introduces concepts as: abstract aggregation scheme and aggregation application. Basically, an aggregation application is an application that is obtained by combining corresponding components. In our model an aggregation application is a word in a language.

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

PubMed

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

2015-06-01

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

Command/response protocols and concurrent software

NASA Technical Reports Server (NTRS)

Bynum, W. L.

1987-01-01

A version of the program to control the parallel jaw gripper is documented. The parallel jaw end-effector hardware and the Intel 8031 processor that is used to control the end-effector are briefly described. A general overview of the controller program is given and a complete description of the program's structure and design are contained. There are three appendices: a memory map of the on-chip RAM, a cross-reference listing of the self-scheduling routines, and a summary of the top-level and monitor commands.

Multiple DNA and protein sequence alignment on a workstation and a supercomputer.

PubMed

Tajima, K

1988-11-01

This paper describes a multiple alignment method using a workstation and supercomputer. The method is based on the alignment of a set of aligned sequences with the new sequence, and uses a recursive procedure of such alignment. The alignment is executed in a reasonable computation time on diverse levels from a workstation to a supercomputer, from the viewpoint of alignment results and computational speed by parallel processing. The application of the algorithm is illustrated by several examples of multiple alignment of 12 amino acid and DNA sequences of HIV (human immunodeficiency virus) env genes. Colour graphic programs on a workstation and parallel processing on a supercomputer are discussed.

Computer programs for adjusting the mechanical properties of 2-inch dimension lumber for changes in moisture content

Treesearch

James W. Evans; Jane K. Evans; David W. Green

1990-01-01

This paper presents computer programs for adjusting the mechanical properties of 2-in. dimension lumber for changes in moisture content. Mechanical properties adjusted are modulus of rupture, ultimate tensile stress parallel to the grain, ultimate compressive stress parallel to the gain, and flexural modulus of elasticity. The models are valid for moisture contents...

GPU-completeness: theory and implications

NASA Astrophysics Data System (ADS)

Lin, I.-Jong

2011-01-01

This paper formalizes a major insight into a class of algorithms that relate parallelism and performance. The purpose of this paper is to define a class of algorithms that trades off parallelism for quality of result (e.g. visual quality, compression rate), and we propose a similar method for algorithmic classification based on NP-Completeness techniques, applied toward parallel acceleration. We will define this class of algorithm as "GPU-Complete" and will postulate the necessary properties of the algorithms for admission into this class. We will also formally relate his algorithmic space and imaging algorithms space. This concept is based upon our experience in the print production area where GPUs (Graphic Processing Units) have shown a substantial cost/performance advantage within the context of HPdelivered enterprise services and commercial printing infrastructure. While CPUs and GPUs are converging in their underlying hardware and functional blocks, their system behaviors are clearly distinct in many ways: memory system design, programming paradigms, and massively parallel SIMD architecture. There are applications that are clearly suited to each architecture: for CPU: language compilation, word processing, operating systems, and other applications that are highly sequential in nature; for GPU: video rendering, particle simulation, pixel color conversion, and other problems clearly amenable to massive parallelization. While GPUs establishing themselves as a second, distinct computing architecture from CPUs, their end-to-end system cost/performance advantage in certain parts of computation inform the structure of algorithms and their efficient parallel implementations. While GPUs are merely one type of architecture for parallelization, we show that their introduction into the design space of printing systems demonstrate the trade-offs against competing multi-core, FPGA, and ASIC architectures. While each architecture has its own optimal application, we believe that the selection of architecture can be defined in terms of properties of GPU-Completeness. For a welldefined subset of algorithms, GPU-Completeness is intended to connect the parallelism, algorithms and efficient architectures into a unified framework to show that multiple layers of parallel implementation are guided by the same underlying trade-off.

Class and Home Problems: Modeling of an Industrial Anaerobic Digester: A Case Study for Undergraduate Students

ERIC Educational Resources Information Center

Durruty, Ignacio; Ayude, María A.

2014-01-01

The case study discussed in this work is used at the chemical reaction engineering course, offered in fifth-year of the chemical engineering undergraduate program at National University of Mar del Plata (UNMdP). A serial-parallel reaction system based on the anaerobic degradation of particulate-containing potato processing wastewater is presented.…

A real-time implementation of an advanced sensor failure detection, isolation, and accommodation algorithm

NASA Technical Reports Server (NTRS)

Delaat, J. C.; Merrill, W. C.

1983-01-01

A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.

Massively parallel simulator of optical coherence tomography of inhomogeneous turbid media.

PubMed

Malektaji, Siavash; Lima, Ivan T; Escobar I, Mauricio R; Sherif, Sherif S

2017-10-01

An accurate and practical simulator for Optical Coherence Tomography (OCT) could be an important tool to study the underlying physical phenomena in OCT such as multiple light scattering. Recently, many researchers have investigated simulation of OCT of turbid media, e.g., tissue, using Monte Carlo methods. The main drawback of these earlier simulators is the long computational time required to produce accurate results. We developed a massively parallel simulator of OCT of inhomogeneous turbid media that obtains both Class I diffusive reflectivity, due to ballistic and quasi-ballistic scattered photons, and Class II diffusive reflectivity due to multiply scattered photons. This Monte Carlo-based simulator is implemented on graphic processing units (GPUs), using the Compute Unified Device Architecture (CUDA) platform and programming model, to exploit the parallel nature of propagation of photons in tissue. It models an arbitrary shaped sample medium as a tetrahedron-based mesh and uses an advanced importance sampling scheme. This new simulator speeds up simulations of OCT of inhomogeneous turbid media by about two orders of magnitude. To demonstrate this result, we have compared the computation times of our new parallel simulator and its serial counterpart using two samples of inhomogeneous turbid media. We have shown that our parallel implementation reduced simulation time of OCT of the first sample medium from 407 min to 92 min by using a single GPU card, to 12 min by using 8 GPU cards and to 7 min by using 16 GPU cards. For the second sample medium, the OCT simulation time was reduced from 209 h to 35.6 h by using a single GPU card, and to 4.65 h by using 8 GPU cards, and to only 2 h by using 16 GPU cards. Therefore our new parallel simulator is considerably more practical to use than its central processing unit (CPU)-based counterpart. Our new parallel OCT simulator could be a practical tool to study the different physical phenomena underlying OCT, or to design OCT systems with improved performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Mobile and replicated alignment of arrays in data-parallel programs

NASA Technical Reports Server (NTRS)

Chatterjee, Siddhartha; Gilbert, John R.; Schreiber, Robert

1993-01-01

When a data-parallel language like FORTRAN 90 is compiled for a distributed-memory machine, aggregate data objects (such as arrays) are distributed across the processor memories. The mapping determines the amount of residual communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: first, an alignment that maps all the objects to an abstract template, and then a distribution that maps the template to the processors. We solve two facets of the problem of finding alignments that reduce residual communication: we determine alignments that vary in loops, and objects that should have replicated alignments. We show that loop-dependent mobile alignment is sometimes necessary for optimum performance, and we provide algorithms with which a compiler can determine good mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself (via spread operations) or can be used to improve performance. We propose an algorithm based on network flow that determines which objects to replicate so as to minimize the total amount of broadcast communication in replication. This work on mobile and replicated alignment extends our earlier work on determining static alignment.

A biologically inspired neural network for dynamic programming.

PubMed

Francelin Romero, R A; Kacpryzk, J; Gomide, F

2001-12-01

An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems.

Performance evaluation of throughput computing workloads using multi-core processors and graphics processors

NASA Astrophysics Data System (ADS)

Dave, Gaurav P.; Sureshkumar, N.; Blessy Trencia Lincy, S. S.

2017-11-01

Current trend in processor manufacturing focuses on multi-core architectures rather than increasing the clock speed for performance improvement. Graphic processors have become as commodity hardware for providing fast co-processing in computer systems. Developments in IoT, social networking web applications, big data created huge demand for data processing activities and such kind of throughput intensive applications inherently contains data level parallelism which is more suited for SIMD architecture based GPU. This paper reviews the architectural aspects of multi/many core processors and graphics processors. Different case studies are taken to compare performance of throughput computing applications using shared memory programming in OpenMP and CUDA API based programming.

Automated Instrumentation, Monitoring and Visualization of PVM Programs Using AIMS

NASA Technical Reports Server (NTRS)

Mehra, Pankaj; VanVoorst, Brian; Yan, Jerry; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

We present views and analysis of the execution of several PVM (Parallel Virtual Machine) codes for Computational Fluid Dynamics on a networks of Sparcstations, including: (1) NAS Parallel Benchmarks CG and MG; (2) a multi-partitioning algorithm for NAS Parallel Benchmark SP; and (3) an overset grid flowsolver. These views and analysis were obtained using our Automated Instrumentation and Monitoring System (AIMS) version 3.0, a toolkit for debugging the performance of PVM programs. We will describe the architecture, operation and application of AIMS. The AIMS toolkit contains: (1) Xinstrument, which can automatically instrument various computational and communication constructs in message-passing parallel programs; (2) Monitor, a library of runtime trace-collection routines; (3) VK (Visual Kernel), an execution-animation tool with source-code clickback; and (4) Tally, a tool for statistical analysis of execution profiles. Currently, Xinstrument can handle C and Fortran 77 programs using PVM 3.2.x; Monitor has been implemented and tested on Sun 4 systems running SunOS 4.1.2; and VK uses XIIR5 and Motif 1.2. Data and views obtained using AIMS clearly illustrate several characteristic features of executing parallel programs on networked workstations: (1) the impact of long message latencies; (2) the impact of multiprogramming overheads and associated load imbalance; (3) cache and virtual-memory effects; and (4) significant skews between workstation clocks. Interestingly, AIMS can compensate for constant skew (zero drift) by calibrating the skew between a parent and its spawned children. In addition, AIMS' skew-compensation algorithm can adjust timestamps in a way that eliminates physically impossible communications (e.g., messages going backwards in time). Our current efforts are directed toward creating new views to explain the observed performance of PVM programs. Some of the features planned for the near future include: (1) ConfigView, showing the physical topology of the virtual machine, inferred using specially formatted IP (Internet Protocol) packets: and (2) LoadView, synchronous animation of PVM-program execution and resource-utilization patterns.

Parallelizing Compiler Framework and API for Power Reduction and Software Productivity of Real-Time Heterogeneous Multicores

NASA Astrophysics Data System (ADS)

Hayashi, Akihiro; Wada, Yasutaka; Watanabe, Takeshi; Sekiguchi, Takeshi; Mase, Masayoshi; Shirako, Jun; Kimura, Keiji; Kasahara, Hironori

Heterogeneous multicores have been attracting much attention to attain high performance keeping power consumption low in wide spread of areas. However, heterogeneous multicores force programmers very difficult programming. The long application program development period lowers product competitiveness. In order to overcome such a situation, this paper proposes a compilation framework which bridges a gap between programmers and heterogeneous multicores. In particular, this paper describes the compilation framework based on OSCAR compiler. It realizes coarse grain task parallel processing, data transfer using a DMA controller, power reduction control from user programs with DVFS and clock gating on various heterogeneous multicores from different vendors. This paper also evaluates processing performance and the power reduction by the proposed framework on a newly developed 15 core heterogeneous multicore chip named RP-X integrating 8 general purpose processor cores and 3 types of accelerator cores which was developed by Renesas Electronics, Hitachi, Tokyo Institute of Technology and Waseda University. The framework attains speedups up to 32x for an optical flow program with eight general purpose processor cores and four DRP(Dynamically Reconfigurable Processor) accelerator cores against sequential execution by a single processor core and 80% of power reduction for the real-time AAC encoding.

Advanced information processing system: The Army Fault-Tolerant Architecture detailed design overview

NASA Technical Reports Server (NTRS)

Harper, Richard E.; Babikyan, Carol A.; Butler, Bryan P.; Clasen, Robert J.; Harris, Chris H.; Lala, Jaynarayan H.; Masotto, Thomas K.; Nagle, Gail A.; Prizant, Mark J.; Treadwell, Steven

1994-01-01

The Army Avionics Research and Development Activity (AVRADA) is pursuing programs that would enable effective and efficient management of large amounts of situational data that occurs during tactical rotorcraft missions. The Computer Aided Low Altitude Night Helicopter Flight Program has identified automated Terrain Following/Terrain Avoidance, Nap of the Earth (TF/TA, NOE) operation as key enabling technology for advanced tactical rotorcraft to enhance mission survivability and mission effectiveness. The processing of critical information at low altitudes with short reaction times is life-critical and mission-critical necessitating an ultra-reliable/high throughput computing platform for dependable service for flight control, fusion of sensor data, route planning, near-field/far-field navigation, and obstacle avoidance operations. To address these needs the Army Fault Tolerant Architecture (AFTA) is being designed and developed. This computer system is based upon the Fault Tolerant Parallel Processor (FTPP) developed by Charles Stark Draper Labs (CSDL). AFTA is hard real-time, Byzantine, fault-tolerant parallel processor which is programmed in the ADA language. This document describes the results of the Detailed Design (Phase 2 and 3 of a 3-year project) of the AFTA development. This document contains detailed descriptions of the program objectives, the TF/TA NOE application requirements, architecture, hardware design, operating systems design, systems performance measurements and analytical models.

PC-CUBE: A Personal Computer Based Hypercube

NASA Technical Reports Server (NTRS)

Ho, Alex; Fox, Geoffrey; Walker, David; Snyder, Scott; Chang, Douglas; Chen, Stanley; Breaden, Matt; Cole, Terry

1988-01-01

PC-CUBE is an ensemble of IBM PCs or close compatibles connected in the hypercube topology with ordinary computer cables. Communication occurs at the rate of 115.2 K-band via the RS-232 serial links. Available for PC-CUBE is the Crystalline Operating System III (CrOS III), Mercury Operating System, CUBIX and PLOTIX which are parallel I/O and graphics libraries. A CrOS performance monitor was developed to facilitate the measurement of communication and computation time of a program and their effects on performance. Also available are CXLISP, a parallel version of the XLISP interpreter; GRAFIX, some graphics routines for the EGA and CGA; and a general execution profiler for determining execution time spent by program subroutines. PC-CUBE provides a programming environment similar to all hypercube systems running CrOS III, Mercury and CUBIX. In addition, every node (personal computer) has its own graphics display monitor and storage devices. These allow data to be displayed or stored at every processor, which has much instructional value and enables easier debugging of applications. Some application programs which are taken from the book Solving Problems on Concurrent Processors (Fox 88) were implemented with graphics enhancement on PC-CUBE. The applications range from solving the Mandelbrot set, Laplace equation, wave equation, long range force interaction, to WaTor, an ecological simulation.

FX-87 performance measurements: data-flow implementation. Technical report

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

Hammel, R.T.; Gifford, D.K.

1988-11-01

This report documents a series of experiments performed to explore the thesis that the FX-87 effect system permits a compiler to schedule imperative programs (i.e., programs that may contain side-effects) for execution on a parallel computer. The authors analyze how much the FX-87 static effect system can improve the execution times of five benchmark programs on a parallel graph interpreter. Three of their benchmark programs do not use side-effects (factorial, fibonacci, and polynomial division) and thus did not have any effect-induced constraints. Their FX-87 performance was comparable to their performance in a purely functional language. Two of the benchmark programsmore » use side effects (DNA sequence matching and Scheme interpretation) and the compiler was able to use effect information to reduce their execution times by factors of 1.7 to 5.4 when compared with sequential execution times. These results support the thesis that a static effect system is a powerful tool for compilation to multiprocessor computers. However, the graph interpreter we used was based on unrealistic assumptions, and thus our results may not accurately reflect the performance of a practical FX-87 implementation. The results also suggest that conventional loop analysis would complement the FX-87 effect system« less

Work stealing for GPU-accelerated parallel programs in a global address space framework: WORK STEALING ON GPU-ACCELERATED SYSTEMS

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

Arafat, Humayun; Dinan, James; Krishnamoorthy, Sriram

Task parallelism is an attractive approach to automatically load balance the computation in a parallel system and adapt to dynamism exhibited by parallel systems. Exploiting task parallelism through work stealing has been extensively studied in shared and distributed-memory contexts. In this paper, we study the design of a system that uses work stealing for dynamic load balancing of task-parallel programs executed on hybrid distributed-memory CPU-graphics processing unit (GPU) systems in a global-address space framework. We take into account the unique nature of the accelerator model employed by GPUs, the significant performance difference between GPU and CPU execution as a functionmore » of problem size, and the distinct CPU and GPU memory domains. We consider various alternatives in designing a distributed work stealing algorithm for CPU-GPU systems, while taking into account the impact of task distribution and data movement overheads. These strategies are evaluated using microbenchmarks that capture various execution configurations as well as the state-of-the-art CCSD(T) application module from the computational chemistry domain.« less

Work stealing for GPU-accelerated parallel programs in a global address space framework

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

Arafat, Humayun; Dinan, James; Krishnamoorthy, Sriram

Task parallelism is an attractive approach to automatically load balance the computation in a parallel system and adapt to dynamism exhibited by parallel systems. Exploiting task parallelism through work stealing has been extensively studied in shared and distributed-memory contexts. In this paper, we study the design of a system that uses work stealing for dynamic load balancing of task-parallel programs executed on hybrid distributed-memory CPU-graphics processing unit (GPU) systems in a global-address space framework. We take into account the unique nature of the accelerator model employed by GPUs, the significant performance difference between GPU and CPU execution as a functionmore » of problem size, and the distinct CPU and GPU memory domains. We consider various alternatives in designing a distributed work stealing algorithm for CPU-GPU systems, while taking into account the impact of task distribution and data movement overheads. These strategies are evaluated using microbenchmarks that capture various execution configurations as well as the state-of-the-art CCSD(T) application module from the computational chemistry domain« less

"Travelers In The Night" in the Old and New Media

NASA Astrophysics Data System (ADS)

Grauer, Albert D.

2015-11-01

"Travelers in the Night" is a series of 2 minute audio programs based on current research in astronomy and the space sciences.After more than a year of submitting “Travelers In The Night” 2 minute audio pieces to NPR and Community Radio stations with limited success, a parallel effort was initiated by posting the pieces as audio podcasts on Spreaker.com and iTunes.The classic media dispenses programming whose content and schedule is determined by editors and station managers. Riding the wave of new technology, people from every demographic group across the globe are selecting what, when, and how they receive information and entertainment. This change is significant with the Pew Research Center reporting that currently more than 60% of Facebook and Twitter users now get their news and/or links to stories from these sources. What remains constant is the public’s interest in astronomy and space.This poster presents relevant statistics and a discussion of the initial results of these two parallel efforts.

RPython high-level synthesis

NASA Astrophysics Data System (ADS)

Cieszewski, Radoslaw; Linczuk, Maciej

2016-09-01

The development of FPGA technology and the increasing complexity of applications in recent decades have forced compilers to move to higher abstraction levels. Compilers interprets an algorithmic description of a desired behavior written in High-Level Languages (HLLs) and translate it to Hardware Description Languages (HDLs). This paper presents a RPython based High-Level synthesis (HLS) compiler. The compiler get the configuration parameters and map RPython program to VHDL. Then, VHDL code can be used to program FPGA chips. In comparison of other technologies usage, FPGAs have the potential to achieve far greater performance than software as a result of omitting the fetch-decode-execute operations of General Purpose Processors (GPUs), and introduce more parallel computation. This can be exploited by utilizing many resources at the same time. Creating parallel algorithms computed with FPGAs in pure HDL is difficult and time consuming. Implementation time can be greatly reduced with High-Level Synthesis compiler. This article describes design methodologies and tools, implementation and first results of created VHDL backend for RPython compiler.

GPU accelerated particle visualization with Splotch

NASA Astrophysics Data System (ADS)

Rivi, M.; Gheller, C.; Dykes, T.; Krokos, M.; Dolag, K.

2014-07-01

Splotch is a rendering algorithm for exploration and visual discovery in particle-based datasets coming from astronomical observations or numerical simulations. The strengths of the approach are production of high quality imagery and support for very large-scale datasets through an effective mix of the OpenMP and MPI parallel programming paradigms. This article reports our experiences in re-designing Splotch for exploiting emerging HPC architectures nowadays increasingly populated with GPUs. A performance model is introduced to guide our re-factoring of Splotch. A number of parallelization issues are discussed, in particular relating to race conditions and workload balancing, towards achieving optimal performances. Our implementation was accomplished by using the CUDA programming paradigm. Our strategy is founded on novel schemes achieving optimized data organization and classification of particles. We deploy a reference cosmological simulation to present performance results on acceleration gains and scalability. We finally outline our vision for future work developments including possibilities for further optimizations and exploitation of hybrid systems and emerging accelerators.

Malleable architecture generator for FPGA computing

NASA Astrophysics Data System (ADS)

Gokhale, Maya; Kaba, James; Marks, Aaron; Kim, Jang

1996-10-01

The malleable architecture generator (MARGE) is a tool set that translates high-level parallel C to configuration bit streams for field-programmable logic based computing systems. MARGE creates an application-specific instruction set and generates the custom hardware components required to perform exactly those computations specified by the C program. In contrast to traditional fixed-instruction processors, MARGE's dynamic instruction set creation provides for efficient use of hardware resources. MARGE processes intermediate code in which each operation is annotated by the bit lengths of the operands. Each basic block (sequence of straight line code) is mapped into a single custom instruction which contains all the operations and logic inherent in the block. A synthesis phase maps the operations comprising the instructions into register transfer level structural components and control logic which have been optimized to exploit functional parallelism and function unit reuse. As a final stage, commercial technology-specific tools are used to generate configuration bit streams for the desired target hardware. Technology- specific pre-placed, pre-routed macro blocks are utilized to implement as much of the hardware as possible. MARGE currently supports the Xilinx-based Splash-2 reconfigurable accelerator and National Semiconductor's CLAy-based parallel accelerator, MAPA. The MARGE approach has been demonstrated on systolic applications such as DNA sequence comparison.

Massively parallel and linear-scaling algorithm for second-order Møller-Plesset perturbation theory applied to the study of supramolecular wires

NASA Astrophysics Data System (ADS)

Kjærgaard, Thomas; Baudin, Pablo; Bykov, Dmytro; Eriksen, Janus Juul; Ettenhuber, Patrick; Kristensen, Kasper; Larkin, Jeff; Liakh, Dmitry; Pawłowski, Filip; Vose, Aaron; Wang, Yang Min; Jørgensen, Poul

2017-03-01

We present a scalable cross-platform hybrid MPI/OpenMP/OpenACC implementation of the Divide-Expand-Consolidate (DEC) formalism with portable performance on heterogeneous HPC architectures. The Divide-Expand-Consolidate formalism is designed to reduce the steep computational scaling of conventional many-body methods employed in electronic structure theory to linear scaling, while providing a simple mechanism for controlling the error introduced by this approximation. Our massively parallel implementation of this general scheme has three levels of parallelism, being a hybrid of the loosely coupled task-based parallelization approach and the conventional MPI +X programming model, where X is either OpenMP or OpenACC. We demonstrate strong and weak scalability of this implementation on heterogeneous HPC systems, namely on the GPU-based Cray XK7 Titan supercomputer at the Oak Ridge National Laboratory. Using the "resolution of the identity second-order Møller-Plesset perturbation theory" (RI-MP2) as the physical model for simulating correlated electron motion, the linear-scaling DEC implementation is applied to 1-aza-adamantane-trione (AAT) supramolecular wires containing up to 40 monomers (2440 atoms, 6800 correlated electrons, 24 440 basis functions and 91 280 auxiliary functions). This represents the largest molecular system treated at the MP2 level of theory, demonstrating an efficient removal of the scaling wall pertinent to conventional quantum many-body methods.

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

PubMed Central

2011-01-01

Background Mutual information is a measure of similarity between two variables. It has been widely used in various application domains including computational biology, machine learning, statistics, image processing, and financial computing. Previously used simple histogram based mutual information estimators lack the precision in quality compared to kernel based methods. The recently introduced B-spline function based mutual information estimation method is competitive to the kernel based methods in terms of quality but at a lower computational complexity. Results We present a new approach to accelerate the B-spline function based mutual information estimation algorithm with commodity graphics hardware. To derive an efficient mapping onto this type of architecture, we have used the Compute Unified Device Architecture (CUDA) programming model to design and implement a new parallel algorithm. Our implementation, called CUDA-MI, can achieve speedups of up to 82 using double precision on a single GPU compared to a multi-threaded implementation on a quad-core CPU for large microarray datasets. We have used the results obtained by CUDA-MI to infer gene regulatory networks (GRNs) from microarray data. The comparisons to existing methods including ARACNE and TINGe show that CUDA-MI produces GRNs of higher quality in less time. Conclusions CUDA-MI is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant speedup over sequential multi-threaded implementation by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs. PMID:21672264

The language parallel Pascal and other aspects of the massively parallel processor

NASA Technical Reports Server (NTRS)

Reeves, A. P.; Bruner, J. D.

1982-01-01

A high level language for the Massively Parallel Processor (MPP) was designed. This language, called Parallel Pascal, is described in detail. A description of the language design, a description of the intermediate language, Parallel P-Code, and details for the MPP implementation are included. Formal descriptions of Parallel Pascal and Parallel P-Code are given. A compiler was developed which converts programs in Parallel Pascal into the intermediate Parallel P-Code language. The code generator to complete the compiler for the MPP is being developed independently. A Parallel Pascal to Pascal translator was also developed. The architecture design for a VLSI version of the MPP was completed with a description of fault tolerant interconnection networks. The memory arrangement aspects of the MPP are discussed and a survey of other high level languages is given.

Automatic recognition of vector and parallel operations in a higher level language

NASA Technical Reports Server (NTRS)

Schneck, P. B.

1971-01-01

A compiler for recognizing statements of a FORTRAN program which are suited for fast execution on a parallel or pipeline machine such as Illiac-4, Star or ASC is described. The technique employs interval analysis to provide flow information to the vector/parallel recognizer. Where profitable the compiler changes scalar variables to subscripted variables. The output of the compiler is an extension to FORTRAN which shows parallel and vector operations explicitly.

Parallel reduced-instruction-set-computer architecture for real-time symbolic pattern matching

NASA Astrophysics Data System (ADS)

Parson, Dale E.

1991-03-01

This report discusses ongoing work on a parallel reduced-instruction- set-computer (RISC) architecture for automatic production matching. The PRIOPS compiler takes advantage of the memoryless character of automatic processing by translating a program's collection of automatic production tests into an equivalent combinational circuit-a digital circuit without memory, whose outputs are immediate functions of its inputs. The circuit provides a highly parallel, fine-grain model of automatic matching. The compiler then maps the combinational circuit onto RISC hardware. The heart of the processor is an array of comparators capable of testing production conditions in parallel, Each comparator attaches to private memory that contains virtual circuit nodes-records of the current state of nodes and busses in the combinational circuit. All comparator memories hold identical information, allowing simultaneous update for a single changing circuit node and simultaneous retrieval of different circuit nodes by different comparators. Along with the comparator-based logic unit is a sequencer that determines the current combination of production-derived comparisons to try, based on the combined success and failure of previous combinations of comparisons. The memoryless nature of automatic matching allows the compiler to designate invariant memory addresses for virtual circuit nodes, and to generate the most effective sequences of comparison test combinations. The result is maximal utilization of parallel hardware, indicating speed increases and scalability beyond that found for course-grain, multiprocessor approaches to concurrent Rete matching. Future work will consider application of this RISC architecture to the standard (controlled) Rete algorithm, where search through memory dominates portions of matching.

Understanding and Improving High-Performance I/O Subsystems

NASA Technical Reports Server (NTRS)

El-Ghazawi, Tarek A.; Frieder, Gideon; Clark, A. James

1996-01-01

This research program has been conducted in the framework of the NASA Earth and Space Science (ESS) evaluations led by Dr. Thomas Sterling. In addition to the many important research findings for NASA and the prestigious publications, the program has helped orienting the doctoral research program of two students towards parallel input/output in high-performance computing. Further, the experimental results in the case of the MasPar were very useful and helpful to MasPar with which the P.I. has had many interactions with the technical management. The contributions of this program are drawn from three experimental studies conducted on different high-performance computing testbeds/platforms, and therefore presented in 3 different segments as follows: 1. Evaluating the parallel input/output subsystem of a NASA high-performance computing testbeds, namely the MasPar MP- 1 and MP-2; 2. Characterizing the physical input/output request patterns for NASA ESS applications, which used the Beowulf platform; and 3. Dynamic scheduling techniques for hiding I/O latency in parallel applications such as sparse matrix computations. This study also has been conducted on the Intel Paragon and has also provided an experimental evaluation for the Parallel File System (PFS) and parallel input/output on the Paragon. This report is organized as follows. The summary of findings discusses the results of each of the aforementioned 3 studies. Three appendices, each containing a key scholarly research paper that details the work in one of the studies are included.

Computer-Aided Engineering Of Cabling

NASA Technical Reports Server (NTRS)

Billitti, Joseph W.

1989-01-01

Program generates data sheets, drawings, and other information on electrical connections. DFACS program, centered around single data base, has built-in menus providing easy input of, and access to, data for all personnel involved in system, subsystem, and cabling. Enables parallel design of circuit-data sheets and drawings of harnesses. Also recombines raw information to generate automatically various project documents and drawings, including index of circuit-data sheets, list of electrical-interface circuits, lists of assemblies and equipment, cabling trees, and drawings of cabling electrical interfaces and harnesses. Purpose of program to provide engineering community with centralized data base for putting in, and gaining access to, functional definition of system as specified in terms of details of pin connections of end circuits of subsystems and instruments and data on harnessing. Primary objective to provide instantaneous single point of interchange of information, thus avoiding

Marionette

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

Sullivan, M.; Anderson, D.P.

1988-01-01

Marionette is a system for distributed parallel programming in an environment of networked heterogeneous computer systems. It is based on a master/slave model. The master process can invoke worker operations (asynchronous remote procedure calls to single slaves) and context operations (updates to the state of all slaves). The master and slaves also interact through shared data structures that can be modified only by the master. The master and slave processes are programmed in a sequential language. The Marionette runtime system manages slave process creation, propagates shared data structures to slaves as needed, queues and dispatches worker and context operations, andmore » manages recovery from slave processor failures. The Marionette system also includes tools for automated compilation of program binaries for multiple architectures, and for distributing binaries to remote fuel systems. A UNIX-based implementation of Marionette is described.« less

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.

Parallel Computational Protein Design.

PubMed

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

2017-01-01

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 (Gainza et al., Methods Enzymol 523:87, 2013) 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 (Gainza et al., PLoS Comput Biol 8:e1002335, 2012) and DEEPer (Hallen et al., Proteins 81:18-39, 2013) to also consider continuous backbone and side-chain flexibility.

QuBiLS-MIDAS: a parallel free-software for molecular descriptors computation based on multilinear algebraic maps.

PubMed

García-Jacas, César R; Marrero-Ponce, Yovani; Acevedo-Martínez, Liesner; Barigye, Stephen J; Valdés-Martiní, José R; Contreras-Torres, Ernesto

2014-07-05

The present report introduces the QuBiLS-MIDAS software belonging to the ToMoCoMD-CARDD suite for the calculation of three-dimensional molecular descriptors (MDs) based on the two-linear (bilinear), three-linear, and four-linear (multilinear or N-linear) algebraic forms. Thus, it is unique software that computes these tensor-based indices. These descriptors, establish relations for two, three, and four atoms by using several (dis-)similarity metrics or multimetrics, matrix transformations, cutoffs, local calculations and aggregation operators. The theoretical background of these N-linear indices is also presented. The QuBiLS-MIDAS software was developed in the Java programming language and employs the Chemical Development Kit library for the manipulation of the chemical structures and the calculation of the atomic properties. This software is composed by a desktop user-friendly interface and an Abstract Programming Interface library. The former was created to simplify the configuration of the different options of the MDs, whereas the library was designed to allow its easy integration to other software for chemoinformatics applications. This program provides functionalities for data cleaning tasks and for batch processing of the molecular indices. In addition, it offers parallel calculation of the MDs through the use of all available processors in current computers. The studies of complexity of the main algorithms demonstrate that these were efficiently implemented with respect to their trivial implementation. Lastly, the performance tests reveal that this software has a suitable behavior when the amount of processors is increased. Therefore, the QuBiLS-MIDAS software constitutes a useful application for the computation of the molecular indices based on N-linear algebraic maps and it can be used freely to perform chemoinformatics studies. Copyright © 2014 Wiley Periodicals, Inc.

Image Understanding Research and Its Application to Cartography and Computer-Based Analysis of Aerial Imagery

DTIC Science & Technology

1983-05-01

Parallel Computation that Assign Canonical Object-Based Frames of Refer- ence," Proc. 7th it. .nt. Onf. on Artifcial Intellig nce (IJCAI-81), Vol. 2...Perception of Linear Struc- ture in Imaged Data ." TN 276, Artiflci!.a Intelligence Center, SRI International, Feb. 1983. [Fram75] J.P. Frain and E.S...1983 May 1983 D C By: Martin A. Fischler, Program Director S ELECTE Principal Investigator, (415)859-5106 MAY 2 21990 Artificial Intelligence Center

Simulation of an array-based neural net model

NASA Technical Reports Server (NTRS)

Barnden, John A.

1987-01-01

Research in cognitive science suggests that much of cognition involves the rapid manipulation of complex data structures. However, it is very unclear how this could be realized in neural networks or connectionist systems. A core question is: how could the interconnectivity of items in an abstract-level data structure be neurally encoded? The answer appeals mainly to positional relationships between activity patterns within neural arrays, rather than directly to neural connections in the traditional way. The new method was initially devised to account for abstract symbolic data structures, but it also supports cognitively useful spatial analogue, image-like representations. As the neural model is based on massive, uniform, parallel computations over 2D arrays, the massively parallel processor is a convenient tool for simulation work, although there are complications in using the machine to the fullest advantage. An MPP Pascal simulation program for a small pilot version of the model is running.

Accelerating sino-atrium computer simulations with graphic processing units.

PubMed

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

2015-01-01

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

Did we get our money's worth? Bridging economic and behavioral measures of program success in adolescent drug prevention.

PubMed

Griffith, Kevin N; Scheier, Lawrence M

2013-11-08

The recent U.S. Congressional mandate for creating drug-free learning environments in elementary and secondary schools stipulates that education reform rely on accountability, parental and community involvement, local decision making, and use of evidence-based drug prevention programs. By necessity, this charge has been paralleled by increased interest in demonstrating that drug prevention programs net tangible benefits to society. One pressing concern is precisely how to integrate traditional scientific methods of program evaluation with economic measures of "cost efficiency". The languages and methods of each respective discipline don't necessarily converge on how to establish the true benefits of drug prevention. This article serves as a primer for conducting economic analyses of school-based drug prevention programs. The article provides the reader with a foundation in the relevant principles, methodologies, and benefits related to conducting economic analysis. Discussion revolves around how economists value the potential costs and benefits, both financial and personal, from implementing school-based drug prevention programs targeting youth. Application of heterogeneous costing methods coupled with widely divergent program evaluation findings influences the feasibility of these techniques and may hinder utilization of these practices. Determination of cost-efficiency should undoubtedly become one of several markers of program success and contribute to the ongoing debate over health policy.

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

NASA Technical Reports Server (NTRS)

Weed, Richard Allen; Sankar, L. N.

1994-01-01

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

Communication library for run-time visualization of distributed, asynchronous data

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

Rowlan, J.; Wightman, B.T.

1994-04-01

In this paper we present a method for collecting and visualizing data generated by a parallel computational simulation during run time. Data distributed across multiple processes is sent across parallel communication lines to a remote workstation, which sorts and queues the data for visualization. We have implemented our method in a set of tools called PORTAL (for Parallel aRchitecture data-TrAnsfer Library). The tools comprise generic routines for sending data from a parallel program (callable from either C or FORTRAN), a semi-parallel communication scheme currently built upon Unix Sockets, and a real-time connection to the scientific visualization program AVS. Our methodmore » is most valuable when used to examine large datasets that can be efficiently generated and do not need to be stored on disk. The PORTAL source libraries, detailed documentation, and a working example can be obtained by anonymous ftp from info.mcs.anl.gov from the file portal.tar.Z from the directory pub/portal.« less

cellGPU: Massively parallel simulations of dynamic vertex models

NASA Astrophysics Data System (ADS)

Sussman, Daniel M.

2017-10-01

Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program Files doi:http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off-lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/cellGPUdocumentation

Multiprogramming performance degradation - Case study on a shared memory multiprocessor

NASA Technical Reports Server (NTRS)

Dimpsey, R. T.; Iyer, R. K.

1989-01-01

The performance degradation due to multiprogramming overhead is quantified for a parallel-processing machine. Measurements of real workloads were taken, and it was found that there is a moderate correlation between the completion time of a program and the amount of system overhead measured during program execution. Experiments in controlled environments were then conducted to calculate a lower bound on the performance degradation of parallel jobs caused by multiprogramming overhead. The results show that the multiprogramming overhead of parallel jobs consumes at least 4 percent of the processor time. When two or more serial jobs are introduced into the system, this amount increases to 5.3 percent

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

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

Zuo, Wangda; McNeil, Andrew; Wetter, Michael

2011-09-06

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

SPSS and SAS programs for determining the number of components using parallel analysis and velicer's MAP test.

PubMed

O'Connor, B P

2000-08-01

Popular statistical software packages do not have the proper procedures for determining the number of components in factor and principal components analyses. Parallel analysis and Velicer's minimum average partial (MAP) test are validated procedures, recommended widely by statisticians. However, many researchers continue to use alternative, simpler, but flawed procedures, such as the eigenvalues-greater-than-one rule. Use of the proper procedures might be increased if these procedures could be conducted within familiar software environments. This paper describes brief and efficient programs for using SPSS and SAS to conduct parallel analyses and the MAP test.

Neurite, a Finite Difference Large Scale Parallel Program for the Simulation of Electrical Signal Propagation in Neurites under Mechanical Loading

PubMed Central

García-Grajales, Julián A.; Rucabado, Gabriel; García-Dopico, Antonio; Peña, José-María; Jérusalem, Antoine

2015-01-01

With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite—explicit and implicit—were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted. PMID:25680098

GPAW - massively parallel electronic structure calculations with Python-based software.

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

Enkovaara, J.; Romero, N.; Shende, S.

2011-01-01

Electronic structure calculations are a widely used tool in materials science and large consumer of supercomputing resources. Traditionally, the software packages for these kind of simulations have been implemented in compiled languages, where Fortran in its different versions has been the most popular choice. While dynamic, interpreted languages, such as Python, can increase the effciency of programmer, they cannot compete directly with the raw performance of compiled languages. However, by using an interpreted language together with a compiled language, it is possible to have most of the productivity enhancing features together with a good numerical performance. We have used thismore » approach in implementing an electronic structure simulation software GPAW using the combination of Python and C programming languages. While the chosen approach works well in standard workstations and Unix environments, massively parallel supercomputing systems can present some challenges in porting, debugging and profiling the software. In this paper we describe some details of the implementation and discuss the advantages and challenges of the combined Python/C approach. We show that despite the challenges it is possible to obtain good numerical performance and good parallel scalability with Python based software.« less

Data Acquisition with GPUs: The DAQ for the Muon $g$-$2$ Experiment at Fermilab

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

Gohn, W.

Graphical Processing Units (GPUs) have recently become a valuable computing tool for the acquisition of data at high rates and for a relatively low cost. The devices work by parallelizing the code into thousands of threads, each executing a simple process, such as identifying pulses from a waveform digitizer. The CUDA programming library can be used to effectively write code to parallelize such tasks on Nvidia GPUs, providing a significant upgrade in performance over CPU based acquisition systems. The muonmore » $g$-$2$ experiment at Fermilab is heavily relying on GPUs to process its data. The data acquisition system for this experiment must have the ability to create deadtime-free records from 700 $$\\mu$$s muon spills at a raw data rate 18 GB per second. Data will be collected using 1296 channels of $$\\mu$$TCA-based 800 MSPS, 12 bit waveform digitizers and processed in a layered array of networked commodity processors with 24 GPUs working in parallel to perform a fast recording of the muon decays during the spill. The described data acquisition system is currently being constructed, and will be fully operational before the start of the experiment in 2017.« less

Estimation of CO2 reduction by parallel hard-type power hybridization for gasoline and diesel vehicles.

PubMed

Oh, Yunjung; Park, Junhong; Lee, Jong Tae; Seo, Jigu; Park, Sungwook

2017-10-01

The purpose of this study is to investigate possible improvements in ICEVs by implementing fuzzy logic-based parallel hard-type power hybrid systems. Two types of conventional ICEVs (gasoline and diesel) and two types of HEVs (gasoline-electric, diesel electric) were generated using vehicle and powertrain simulation tools and a Matlab-Simulink application programming interface. For gasoline and gasoline-electric HEV vehicles, the prediction accuracy for four types of LDV models was validated by conducting comparative analysis with the chassis dynamometer and OBD test data. The predicted results show strong correlation with the test data. The operating points of internal combustion engines and electric motors are well controlled in the high efficiency region and battery SOC was well controlled within ±1.6%. However, for diesel vehicles, we generated virtual diesel-electric HEV vehicle because there is no available vehicles with similar engine and vehicle specifications with ICE vehicle. Using a fuzzy logic-based parallel hybrid system in conventional ICEVs demonstrated that HEVs showed superior performance in terms of fuel consumption and CO 2 emission in most driving modes. Copyright © 2017 Elsevier B.V. All rights reserved.