Algorithm-based diskless checkpointing for fault tolerant matrix operations

J. Plank, Youngbae Kim, J. Dongarra
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引用次数: 79

Abstract

The paper is an exploration of diskless checkpointing for distributed scientific computations. With the widespread use of the "network of workstations" (NOW) platform for distributed computing, long-running scientific computations need to tolerate the changing and often faulty nature of NOW environments. We present high-performance implementations of several algorithms for distributed scientific computing, including Cholesky factorization, LU factorization, QR factorization, and preconditioned conjugate gradient. These implementations are able to run on PVM networks of at least N processors, and can complete with low overhead as long as any N processors remain functional. We discuss the details of how the algorithms are tuned for fault-tolerance, and present the performance results on a PVM network of SUN workstations, and on the IBM SP2.<>
基于算法的容错矩阵操作无磁盘检查点
本文是对分布式科学计算的无磁盘检查点的探索。随着分布式计算“工作站网络”(NOW)平台的广泛使用,长期运行的科学计算需要容忍NOW环境的变化和经常出错的性质。我们提出了几种分布式科学计算算法的高性能实现,包括Cholesky分解、LU分解、QR分解和预条件共轭梯度。这些实现能够在至少有N个处理器的PVM网络上运行,并且只要任何N个处理器保持正常工作,就可以以低开销完成。我们将详细讨论如何调优算法以实现容错性,并给出在SUN工作站的PVM网络和IBM SP2. b>上的性能结果
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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