期刊
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
卷 31, 期 1, 页码 60-78出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/1055531.1055534
关键词
algorithms; theory; performance; linear algebra; dense systems; linear least squares
This article discusses the high-performance parallel implementation of the computation, and updating of QR factorizations of dense matrices, including problems large enough to require out-of-core computation, where the matrix is stored on disk. The algorithms, presented here are scalable both in problem size and as the number of processors increases. Implementation using the Parallel Linear Algebra Package (PLAPACK) and the Parallel Out-of-Core Linear Algebra Package (POOCLAPACK) is discussed. The methods are shown to attain excellent performance, in some cases attaining roughly 80% of the realizable peak of the architectures on which the experiments were performed.
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