Titlebook: Scientific Computing on Supercomputers III; Jozef T. Devreese,Piet E. Camp Book 1992 Springer Science+Business Media New York 1992 Transpu

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High Performance Numerically Intensive Applications on Distributed Memory Parallel Computers,gical integrity. In other cases, it may be necessary to modify existing techniques, or even to devise completely new methods, in order to exploit the advantages of large scale parallelism. The study and implementation of parallel methods for the simulation of physical phenomena is now an area of rap

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Parallel Discrete Event Simulation: Opportunities and Pitfalls,t is shown that the traditional sequential simulation algorithm cannot be parallellized, in order to take advantage of opportunities offered by parallel computer architectures. It will be indicated that in order to obtain a performance gain in terms of the only realistic benchmark possible, a sequen

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Simulating Compressible Flow on a Distributed Memory Machine,uid flow, has seen considerable advances. From this work has emerged the high resolution Total Variation Diminishing (TVD) schemes, which are capable of producing sharp shock waves without introducing spurious oscillations. The drawback with these schemes has been that they are difficult to vectoris

RLS898

Principles of Code Optimization on CONVEX-C230,de has to be written in “sequential” standard FORTRAN. The FORTRAN-xx to come provides rather efficient vectorization means, which are used throughout these notes, and which are readily translated in standard FORTRAN-77, in such a way that the autovectorizer recognizes the vector structure of the co

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Antwerp (UIA), Antwerpen, Belgium. It was the sixth in a series of workshops, the fIrst of which took place in 1984. The principal aim of these workshops is to present the state of the art in scientific large-scale and high speed-computation. Computational science has developed into a third methodo

curriculum

Parallel Computational Fluid Dynamics on a Meiko Transputer System with Express in Comparison to iPf a solver for the Euler equations and we present and analyze the performance and the parallel efficiency of the code..Both for the benchmarks and the Euler solver we compare the timings obtained with Express on the Meiko system with those obtained on the Intel iPSC/2 and iPSC/860 parallel computers.

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Preconditioned Conjugate Gradients on the PUMA Architecture,int communication implemented in hardware. The method is then re-formulated to facilitate overlapping of communication and computation and a further timing model developed. The timing models are compared and some conclusions drawn.

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