基于numa的多核细粒度并行化框架

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum Pub Date : 2013-05-20 DOI:10.1109/IPDPSW.2013.204

C. Rossignon, P. Hénon, Olivier Aumage, Samuel Thibault

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引用次数: 4

摘要

针对在多核架构上处理细粒度并行化时经常遇到的两个问题，提出了一些解决方案:使用适合硬件的任务粒度来表达算法，以及最小化由于非均匀内存访问而造成的时间损失。为了评估我们的工作的好处，我们提出了一些关于稀疏线性系统迭代求解器的细粒度并行化的实验，并与英特尔TBB方法进行了一些比较。

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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A NUMA-Aware Fine Grain Parallelization Framework for Multi-core Architecture

We present some solutions to handle two problems commonly encountered when dealing with fine grain parallelization on multi-core architecture: Expressing algorithms using a task grain size suitable for the hardware and minimizing the time penalty due to Non Uniform Memory Accesses. To evaluate the benefit of our work we present some experiments on the fine grain parallelization of an iterative solver for sparse linear systems with some comparisons with the Intel TBB approach.

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2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum

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