并行预处理Krylov方法的实验研究

D. Baxter, J. Saltz, M. Schultz, S. Eisenstat, K. Crowley
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引用次数: 43

摘要

高性能多处理器体系结构在处理器数量以及同步和通信的延迟成本方面都有所不同。为了在给定架构上获得针对给定问题的良好性能,充分的并行化、良好的负载平衡和适当的粒度选择是必不可少的。我们讨论了PCGPAK并行版本在共享内存架构和超多维数据集上的实现。我们的并行实现足够高效,可以让我们在Encore multiax /320的16个处理器上完成测试问题的解决方案,这是Cray X/MP单个头部所需时间的一小倍,尽管multiax处理器的峰值性能甚至没有接近超级计算机的范围。我们说明了我们的方法在一些油藏工程和数学模型问题上的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An experimental study of methods for parallel preconditioned Krylov methods
High performance multiprocessor architectures differ both in the number of processors, and in the delay costs for synchronization and communication. In order to obtain good performance on a given architecture for a given problem, adequate parallelization, good balance of load and an appropriate choice of granularity are essential. We discuss the implementation of parallel version of PCGPAK for both shared memory architectures and hypercubes. Our parallel implementation is sufficiently efficient to allow us to complete the solution of our test problems on 16 processors of the Encore Multimax/320 in an amount of time that is a small multiple of that required by a single head of a Cray X/MP, despite the fact that the peak performance of the Multimax processors is not even close to the supercomputer range. We illustrate the effectiveness of our approach on a number of model problems from reservoir engineering and mathematics.
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