Asynchronous Approach to Memory Management in Sparse Multifrontal Methods on Multiprocessors
Asynchronous Approach to Memory Management in Sparse Multifrontal Methods on Multiprocessors作者机构:ZAO Intel/AO Novosibirsk Russia
出 版 物:《Applied Mathematics》 (应用数学(英文))
年 卷 期:2013年第4卷第12期
页 面:33-39页
学科分类:081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:Direct Solver Distributed Data OpenMP and MPI
摘 要:This research covers the Intel? Direct Sparse Solver for Clusters, the software that implements a direct method for solving the Ax = b equation with sparse symmetric matrix A on a cluster. This method, researched by Intel, is based on Cholesky decomposition and could be considered as extension of functionality PARDISO from Intel??MKL. To achieve an efficient work balance on a large number of processes, the so-called “multifrontal approach to Cholesky decomposition is implemented. This software implements parallelization that is based on nodes of the dependency tree and uses MPI, as well as parallelization inside a node of the tree that uses OpenMP directives. The article provides a high-level description of the algorithm to distribute the work between both computational nodes and cores within a single node, and between different computational nodes. A series of experiments shows that this implementation causes no growth of the computational time and decreases the amount of memory needed for the computations.