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The Algorithm of Multiple Relatively Robust Representations for Multi-core Processors

机译:多核处理器的多个相对鲁棒表示算法

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摘要

The algorithm of Multiple Relatively Robust Representations (MRRR or MR~3) computes k eigenvalues and eigenvectors of a symmetric tridiagonal matrix in O(nk) arithmetic operations. Large problems can be effectively tackled with existing distributed-memory parallel implementations of MRRR; small and medium size problems can instead make use of LAPACK's routine xSTEMR. However, xSTEMR is optimized for single-core CPUs, and does not take advantage of today's multi-core and future many-core architectures. In this paper we discuss some of the issues and trade-offs arising in the design of MR3-SMP, an algorithm for multi-core CPUs and SMP systems. Experiments on application matrices indicate that MR3-SMP is both faster and obtains better speedups than all the tridiagonal eigensolvers included in LAPACK and Intel's Math Kernel Library (MKL).
机译:多重相对鲁棒表示(MRRR或MR〜3)算法在O(nk)算术运算中计算对称三对角矩阵的k个特征值和特征向量。现有的MRRR分布式内存并行实现可以有效解决大问题;中小型问题可以改用LAPACK的例行xSTEMR。但是,xSTEMR针对单核CPU进行了优化,并没有利用当今的多核和未来的多核架构。在本文中,我们讨论了在MR3-SMP(一种用于多核CPU和SMP系统的算法)的设计中出现的一些问题和权衡。在应用矩阵上进行的实验表明,与LAPACK和英特尔数学内核库(MKL)中包含的所有三对角本征求解器相比,MR3-SMP不仅速度更快,而且速度更快。

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