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Modeling contention of sparse-matrix-vector multiplication (SMV) in three parallel programming paradigms

机译:三种并行编程范例中的稀疏矩阵向量乘法(SMV)竞争模型

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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.
机译:我们利用了LoPC模型,该模型受LogP / PG和BSP模型的启发,但考虑了并行编程模型中消息处理资源的争用,以得出执行成本的一般估计。我们对三种主要的编程模型进行了成本估算分析:消息传递,共享内存和分布式共享内存。我们分析了在这些编程模型中编写的典型应用SMV乘法,并使用不规则的接收器启动的同步通信。与SGI O2000多处理器机器上的实际经验计算的运行时间的测量值进行比较时,该应用程序的LoPC估计值显示出合理的准确性。

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