Hierarchical QR Factorization Algorithms for Multi-core Cluster Systems
Hierarchical QR Factorization Algorithms for Multi-core Cluster Systems
This paper describes a new QR factorization algorithm which is especially designed for massively parallel platforms combining parallel distributed multi-core nodes. These platforms make the present and the foreseeable future of high-performance computing. Our new QR factorization algorithm falls in the category of the tile algorithms which naturally enables good data locality for the sequential kernels executed by the cores (high sequential performance), low number of messages in a parallel distributed setting (small latency term), and fine granularity (high parallelism).
FOS: Computer and information sciences, distributed memory, Clustering algorithms, Tiles, granular computing, multicore cluster system, pattern clustering, reduction tree, sequential kernel, matrix decomposition, DAGUE scheduling tool, hierarchical QR factorization algorithm, numerical linear algebra, Algorithm design and analysis, tile algorithm, cluster, distribution layout, petascale platform, interprocessor communication, cache storage, processor scheduling, parallel machines, hierarchical tree, multicore, QR factorization, high-performance computing, hierarchical architecture, Binary trees, Program processors, parallel internode reduction, Multicore processing, multiprocessing systems, Kernel, linear algebra, Computer Science - Distributed, Parallel, and Cluster Computing, tree data structures, data reduction, internode tree, intranode trees, exascale platform, Distributed, Parallel, and Cluster Computing (cs.DC), cache friendliness, parallel distributed multicore node
FOS: Computer and information sciences, distributed memory, Clustering algorithms, Tiles, granular computing, multicore cluster system, pattern clustering, reduction tree, sequential kernel, matrix decomposition, DAGUE scheduling tool, hierarchical QR factorization algorithm, numerical linear algebra, Algorithm design and analysis, tile algorithm, cluster, distribution layout, petascale platform, interprocessor communication, cache storage, processor scheduling, parallel machines, hierarchical tree, multicore, QR factorization, high-performance computing, hierarchical architecture, Binary trees, Program processors, parallel internode reduction, Multicore processing, multiprocessing systems, Kernel, linear algebra, Computer Science - Distributed, Parallel, and Cluster Computing, tree data structures, data reduction, internode tree, intranode trees, exascale platform, Distributed, Parallel, and Cluster Computing (cs.DC), cache friendliness, parallel distributed multicore node
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