Asynchronous Approach to Memory Management in Sparse Multifrontal Methods on Multiprocessors

作     者：Alexander Kalinkin Konstantin Arturov 

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.