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Parallel computation in atmospheric chemical modeling

PARALLEL COMPUTING 1996年第1期22卷 111-130页

作者： Dabdub, D Seinfeld, JH CALTECH DEPT CHEM ENGNPASADENACA 91125

The porting of atmospheric chemical dynamic models to massively parallel computers presents interesting computational challenges. Strategies for the parallelization of the transport and chemistry operators of atmospheric models are outlined. The use of parallel buffers to perform input/output operations is described. Results are given for implementation of the CIT urban air pollution model on distributed memory multiple instruction/multiple data (MIMD) machines ranging from a cluster of workstations to a 512 node Intel Paragon. A speed-up factor of 94.9 is achieved when the I/O, transport, and chemistry portions of the model are performed in parallel using 256 nodes of the Intel Paragon.

关键词： atmospheric models air quality modeling parallel I/O distributed memory multiprocessors workstation cluster

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ASYNCHRONOUS MULTILEVEL ADAPTIVE METHODS FOR SOLVING PARTIAL-DIFFERENTIAL EQUATIONS ON multiprocessors - BASIC IDEAS

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PARALLEL COMPUTING 1989年第2期12卷 131-144页

作者： HART, L MCCORMICK, S UNIV COLORADO COMP MATH GRPDENVERCO 80204

Several mesh refinement methods exists for solving partial differential equations that make efficient use of local grids on scalar computers. On distributed memory multiprocessors, such methods benefit from their tendency to create multiple refinement regions, yet they suffer from the sequential way that the levels of refinement are treated. The asynchronous fast adaptive composite grid method (AFAC) is developed here as a method that can process refinement levels in parallel while maintaining full multilevel convergence speeds. In the present paper, we develop a simple two-level AFAC theory and provide estimates of its asymptotic convergence factors as it applies to very large scale examples. In a companion paper, we report on extensive timing results for AFAC, implemented on an Intel iPSC hypercube.

关键词： asynchronous FAC distributed memory multiprocessors Fast adaptive composite grid method (FAC) partial differential equations

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Parallel reduction of banded matrices to bidiagonal form

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PARALLEL COMPUTING 1996年第1期22卷 1-18页

作者： Lang, BN ETH ZURICH ZURICH SWITZERLAND FORSCHUNGSZENTRUM JULICH FORSCHUNGSZENTRUM ZENT INST ANGEW MATH JULICH GERMANY

A parallel algorithm for reducing banded matrices to bidiagonal form is presented. In contrast to the rotation-based ''standard approach'', our algorithm is based on Householder transforms, therefore exhibiting considerably higher data locality (BLAS level 2 instead of level 1). The update of the transformation matrices which involves the vast majority of the operations can even be blocked to allow the use of level 3 BLAS. Thus, our algorithm will outperform the standard method on a serial computer with a distinct memory hierarchy. In addition, the algorithm can be efficiently implemented in a distributed memory environment, as is demonstrated by numerical results on the Intel Paragon.

关键词： linear algebra singular value decomposition BLAS hierarchy distributed memory multiprocessors banded matrices parallel reduction

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Mapping affine loop nests

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PARALLEL COMPUTING 1996年第10期22卷 1373-1397页

作者： Dion, M Robert, Y ECOLE NORMALE SUPER LYON URA CNRS 1398 LAB LIP F-69364 LYON 07 FRANCE

This paper deals with the problem of aligning data and computations when mapping affine loop nests onto distributed memory Parallel Computers (DMPCs). We formulate the problem by introducing a new graph, the access graph, to model affine communications (with rectangular access matrices) more adequately than with the previously introduced tool, the communication graph. We show that maximizing the number of local communications in the access graph is an NP-complete problem in the strong sense and we present several heuristics based upon the access graph for mapping affine loop nests onto DMPCs.

关键词： affine mapping problem distributed memory multiprocessors loop nests communication graphs heuristics

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Parallel computation of the correlation dimension from a time series

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PARALLEL COMPUTING 1999年第6期25卷 639-666页

作者： Corana, A Consiglio Nazl Ricerche Ist Circuiti Elettronici I-16149 Genoa Italy

A parallel algorithm is presented for computing the Correlation Dimension (D-2) from a time series generated by a dynamical system, using the method of correlation integrals. Three versions are discussed: the first computes all distances between points in the phase space, whereas the second and third compute only distances less than a threshold epsilon;the third version in particular is very powerful since it employs a box-assisted approach and linked lists for a fast search of neighboring points. The parallelization is designed for coarse-grained multiprocessor systems with distributed memory and is accomplished using a message passing model and partitioning points evenly among processors. Uniform implementation and computational analysis allow a clear comparison of the three versions. The algorithms, tested on the Transtech PARAstation multiprocessor, are well balanced, give a linear speed-up and show a good scalability. The third version is particularly suitable for fast processing of very long time series and allows the estimation of D-2 even for medium- and high-dimensional systems, where an extremely large number of points is needed. The algorithms can be adapted with few modifications to the computation of the generalized dimensions D-q, and they can also be useful in other applications involving the efficient computation of distances between points in a large set. More generally, the computational framework can be used in similar problems involving long-range interactions. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： nonlinear time series analysis Correlation Dimension computation of distances long-range interactions box-assisted parallel algorithms distributed memory multiprocessors message passing

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Parallel computing of diatomic molecular rarefied gas flows

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PARALLEL COMPUTING 1997年第9期23卷 1249-1260页

作者： Matsumoto, Y Tokumasu, T Department of Mechanical Engineering The University of Tokyo Hongo Bunkyo-ku Tokyo 113 Japan

A parallel algorithm for direct simulation Monte Carlo calculation of diatomic molecular rarefied gas flows is presented. For reliable simulation of such flow, an efficient molecular collision model is required. Using the molecular dynamics method, the collision of N-2 molecules is simulated. For this molecular dynamics simulation, the parameter decomposition method is applied for parallel computing. By using these results, the statistical collision model of diatomic molecule is constructed. For validation this model is applied to the direct simulation Monte Carlo method to simulate the energy distribution at equilibrium condition and the structure of normal shock wave. For this DSMC calculation, the domain decomposition is applied. It is shown that the collision process of diatomic molecules can be calculated precisely and the parallel algorithm can be efficiently implemented on the parallel computer. (C) 1997 Elsevier Science B.V.

关键词： rarefied gas flows molecular collision model direct simulation Monte Carlo method parameter decomposition method domain decomposition load balance distributed memory multiprocessors

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A PARALLEL SOLVER FOR TRIDIAGONAL LINEAR-SYSTEMS FOR distributed memory PARALLEL COMPUTERS

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PARALLEL COMPUTING 1991年第9期17卷 1017-1023页

作者： BRUGNANO, L Dipartimento di Matematica Trav. 200 Re David 70125 Bari Italy

The solution of linear tridiagonal systems is a very common problem in Numerical Analysis. Many algorithms are known for solving such linear systems on vector and parallel computers [3,4,6-9]. In this paper a new para... 详细信息

关键词： LINEAR ALGEBRA TRIDIAGONAL LINEAR SYSTEMS distributed memory multiprocessors TRANSPUTER NETWORKS TIMING RESULTS

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PARALLEL MATRIX TRANSPOSE ALGORITHMS ON distributed-memory CONCURRENT COMPUTERS

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PARALLEL COMPUTING 1995年第9期21卷 1387-1405页

作者： CHOI, JY DONGARRA, JJ WALKER, DW OAK RIDGE NATL LAB MATH SCI SECT OAK RIDGE TN 37831 USA UNIV TENNESSEE DEPT COMP SCI KNOXVILLE TN 37996 USA

This paper describes parallel matrix transpose algorithms on distributed memory concurrent processors. We assume that the matrix is distributed over a P X Q processor template with a block cyclic data distribution. P, Q, and the block size can be arbitrary, so the algorithms have wide applicability. The communication schemes of the algorithms are determined by the greatest common divisor (GCD) of P and e. If P and Q are relatively prime, the matrix transpose algorithm involves complete exchange communication. If P and P are not relatively prime, processors are divided into GCD groups and the communication operations are overlapped for different groups of processors. Processors transpose GCD wrapped diagonal blocks simultaneously, and the matrix can be transposed with LCM/GCD steps, where LCM is the least common multiple of P and Q. The algorithms make use of non-blocking, point-to-point communication between processors. The use of nonblocking communication allows a processor to overlap the messages that it sends to different processors, thereby avoiding unnecessary synchronization. Combined with the matrix muliplication routine, C = A . B, the algorithms are used to compute parallel multiplications of transposed matrices, C = A(T) . B-T, in the PUMMA package [5]. Details of the parallel implementation of the algorithms are given, and results are presented for runs on the Intel Touchstone Delta computer.

关键词： LINEAR ALGEBRA MATRIX TRANSPOSE ALGORITHM distributed memory multiprocessors POINT-TO-POINT COMMUNICATION INTEL TOUCHSTONE DELTA

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EXPERIENCES WITH REENGINEERING AND PARALLELIZING A HIGH-T(C) SUPERCONDUCTIVITY CODE

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PARALLEL COMPUTING 1994年第3期20卷 399-407页

作者： KLEIS, U SINGER, JM MORGENSTERN, I HUSSLEIN, T MATUTTIS, HG UNIV REGENSBURG DEPT PHYSD-93053 REGENSBURGGERMANY

Motivated by experiments on high-T(c) superconducting compounds and made possible by the power of present day supercomputers, a number of researchers have used the Quantum Monte Carlo method to gain more insight into Hubbard-like many particle models. We used the Projector Quantum Monte Carlo method (PQMC) [1,2] as a computational technique for studying the physical properties of many-electron and quantum-spin systems. This review gives a survey of the algorithms and techniques as well as of the methods to implement the PQMC scheme on modem parallel computers like the Intel Hypercube or IBM RS/6000 workstation clusters. In order to study systems of larger size or with more complex interactions, increasingly large amounts of computational power are required. Although based on one particular algorithm, we believe that our results should interest simulators with quite different algorithms and other parallel architectures as well.

关键词： distributed memory multiprocessors Hubbard model Parallelization strategy Performance results Projector Quantum Monte Carlo method

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A SCALABLE SCHEDULING SCHEME FOR FUNCTIONAL PARALLELISM ON distributed-memory MULTIPROCESSOR SYSTEMS

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 1995年第4期6卷 388-399页

作者： PANDE, S AGRAWAL, DP MAUNEY, J N CAROLINA STATE UNIV DEPT ELECT & COMP ENGNRALEIGHNC 27695

We attempt a new variant of the scheduling problem by investigating the scalability of the schedule length with the required number of processors, by performing scheduling partially at compile time and partially at run time. Assuming infinite number of processors, the compile time schedule is found using anew concept of the threshold of a task that quantifies a trade-off between the schedule-length and the degree of parallelism, The schedule is found to minimize either the schedule length dr the number of required processors and it satisfies: A feasibility, condition which guarantees that the schedule delay of a task from its earliest start time is below the threshold, and An optimality condition which uses a merit function to decide the best task-processor match for a set of tasks competing for a given processor. At run time, the tasks re merged producing a schedule for a smaller number of available processors,This allows the program to be scaled down to the processors actually available at run time, Usefulness of this scheduling heuristic has been demonstrated by. incorporating the scheduler in the compiler backend for targeting Sisal (Streams and Iterations in a Single Assignment Language) on iPSC/860.

关键词： COMPILE TIME SCHEDULING DATA-FLOW GRAPHS distributed memory multiprocessors FUNCTIONAL PARALLELISM RUNTIME SCHEDULING SCALING SCHEDULE LENGTH

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