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Evaluation of Sparse LU Factorization and Triangular Solution on Multicore Platforms

机译:多核平台上的稀疏LU分解和三角解的评估

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摘要

The Chip Multiprocessor (CMP) will be the basic building block for computer systems ranging from laptops to supercomputers. New software developments at all levels are needed to fully utilize these systems. In this work, we evaluate performance of different high-performance sparse LU factorization and triangular solution algorithms on several representative multicore machines. We include both pthreads and MPI implementations in this study, and found that the pthreads implementation consistently delivers good performance and a left-looking algorithm is usually superior.
机译:芯片多处理器(CMP)将成为从笔记本电脑到超级计算机的计算机系统的基本构建块。为了充分利用这些系统,需要各个级别的新软件开发。在这项工作中,我们评估了几种高性能多核机器上不同的高性能稀疏LU分解和三角解算法的性能。在本研究中,我们同时包含了pthread和MPI实现,并且发现pthreads实现始终提供良好的性能,并且左眼算法通常更好。

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