Performance Evaluation of the Eigen Exa Eigensolver on Oakleaf-FX: Tridiagonalization Versus Pentadiagonalization
Performance Evaluation of the Eigen Exa Eigensolver on Oakleaf-FX: Tridiagonalization Versus Pentadiagonalization
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Oakleaf-FX 上 Eigen Exa Eigensolver 的性能评估：三对角化与五对角化
DOI：
10.1109/ipdpsw.2015.128
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Toshiyuki Imamura
中科院分区：
文献类型：
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作者：
Takeshi Fukaya;Toshiyuki Imamura
真实的对称稠密特征值问题的求解是矩阵计算的基本问题之一。到目前为止，已经开发了几个新的高性能本征解算器的PETA和postPETA规模的系统。其中之一，本征Exa本征求解器，已在日本开发。Eigen Exa提供了两个例程：基于传统三对角化的eigens和通过五对角矩阵采用新方法的eigensx。最近，我们使用Oak leaf-FX超级计算机系统的4，800个节点对Eigen Exa进行了详细的性能评估。在本文中，我们报告的结果，我们的评估，这主要是集中在调查两个例程之间的差异。结果清楚地表明了本征值x相对于本征值的优点和缺点，这将有助于进一步提高本征值Exa的性能。所得到的结果也预计是有用的其他并行稠密矩阵计算，除了本征值问题。
The solution of real symmetric dense Eigen value problems is one of the fundamental matrix computations. To date, several new high-performance Eigen solvers have been developed for peta and postpeta scale systems. One of these, the Eigen Exa Eigen solver, has been developed in Japan. Eigen Exa provides two routines: eigens, which is based on traditional tridiagonalization, and eigensx, which employs a new method via a pentadiagonal matrix. Recently, we conducted a detailed performance evaluation of Eigen Exa by using 4,800 nodes of the Oak leaf-FX supercomputer system. In this paper, we report the results of our evaluation, which is mainly focused on investigating the differences between the two routines. The results clearly indicate both the advantages and disadvantages of eigensx over eigens, which will contribute to further performance improvement of Eigen Exa. The obtained results are also expected to be useful for other parallel dense matrix computations, in addition to Eigen value problems.
开发超越千万亿级超级计算机系统的高性能特征求解器
DOI：
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发表时间：
2010
期刊：
影响因子：
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作者：
Imamura;T.;Yamada;S.;Machida;M.
通讯作者：
M.