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Author Lee, Heejo ♦ Kim, Jong ♦ Hong, Sung Je ♦ Lee, Sunggu
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Block Cholesky Factorization ♦ Hierarchical Memory System ♦ Restricted Communication Pattern ♦ Block Sparse Cholesky Factorization ♦ New Task ♦ Distributedmemory System ♦ Computational Unit ♦ Communication Volume ♦ Customary Column-oriented Factorization Method ♦ Factorization Method ♦ Rectangular Sub-blocks ♦ Conventional Parallel Task Model ♦ Algorithm Consi ♦ Distributed-memory Multiprocessor System ♦ Execution Behavior ♦ Block-oriented Sparse Cholesky Factorization ♦ Block Dependency Dag ♦ Load Balance ♦ Sparse Matrix
Description In: Proceedings of 14-th ACM Symposium on Applied Computing
Block-oriented sparse Cholesky factorization decomposes a sparse matrix into rectangular sub-blocks; each block can then be handled as a computational unit in order to increase data reuse in a hierarchical memory system. Also, the factorization method increases the degree of concurrency with the reduction of communication volumes so that it performs more efficiently on a distributed-memory multiprocessor system than the customary column-oriented factorization method. But until now, mapping of blocks to processors has been designed for load balance with restricted communication patterns. In this paper, we represent tasks using a block dependency DAG that shows the execution behavior of block sparse Cholesky factorization in a distributedmemory system. Since the characteristics of tasks for the block Cholesky factorization are different from those of the conventional parallel task model, we propose a new task scheduling algorithm using a block dependency DAG. The proposed algorithm consi...
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2000-01-01