稀疏矩阵向量乘法(SMV)在三种并行编程范式中的建模之争

A. Sameh, T. El-Ghazawi, Y. Yesha
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引用次数: 0

摘要

我们使用LoPC模型,该模型受到LogP/PG和BSP模型的启发,但考虑到并行编程模型中消息处理资源的争用,从而得出执行成本的一般估计。我们对三种主要的编程模型:消息传递、共享内存和分布式共享内存进行了成本估算分析。我们分析了用这些编程模型编写的具有不规则接收端发起同步通信的典型应用程序SMV乘法。将此应用程序的LoPC估计值与SGI O2000多处理器机器上实际经验计算的运行时测量值进行比较,结果表明LoPC估计值相当准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling contention of sparse-matrix-vector multiplication (SMV) in three parallel programming paradigms
We makes use of the LoPC model, which is inspired by both the LogP/PG and BSP models but accounts for contention for message processing resources in parallel programming models to derive a general estimate of execution cost. We carry out this cost estimate analysis for three dominate programming models: message passing, shared memory and distributed shared memory. We analyze a typical application SMV multiplication written in these programming models with irregular receiver-initiated synchronous communication. The LoPC estimate for this application is shown to be reasonably accurate when compared against measured values of runtime of actual empirical computations on an SGI O2000 multiprocessor machine.
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