科技报告详细信息
Highly scalable linear solvers on thousands of processors. | |
Domino, Stefan Paul (Sandia National Laboratories, Albuquerque, NM) ; Karlin, Ian (University of Colorado at Boulder, Boulder, CO) ; Siefert, Christopher (Sandia National Laboratories, Albuquerque, NM) ; Hu, Jonathan Joseph ; Robinson, Allen Conrad (Sandia Na | |
关键词: ALGORITHMS; PARALLEL PROCESSING; SYNCHRONIZATION; A CODES; DATA TRANSMISSION; | |
DOI : 10.2172/993900 RP-ID : SAND2009-6197 PID : OSTI ID: 993900 Others : TRN: US201101%%115 |
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学科分类:数学(综合) | |
美国|英语 | |
来源: SciTech Connect | |
【 摘 要 】
In this report we summarize research into new parallel algebraic multigrid (AMG) methods. We first provide a introduction to parallel AMG. We then discuss our research in parallel AMG algorithms for very large scale platforms. We detail significant improvements in the AMG setup phase to a matrix-matrix multiplication kernel. We present a smoothed aggregation AMG algorithm with fewer communication synchronization points, and discuss its links to domain decomposition methods. Finally, we discuss a multigrid smoothing technique that utilizes two message passing layers for use on multicore processors.
【 预 览 】
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RO201705170001169LZ | 855KB | download |