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Computer Science > Distributed, Parallel, and Cluster Computing

Title: Performance of H-Matrix-Vector Multiplication with Floating Point Compression

Abstract: Matrix-vector multiplication forms the basis of many iterative solution algorithms and as such is an important algorithm also for hierarchical matrices. However, due to its low computational intensity, its performance is typically limited by the available memory bandwidth. By optimizing the storage representation of the data within such matrices, this limitation can be lifted and the performance increased. This applies not only to hierarchical matrices but for also for other low-rank approximation schemes, e.g. block low-rank matrices.
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Mathematical Software (cs.MS)
MSC classes: 65Y05, 65Y20, 68W10, 68W25, 68P30
Cite as: arXiv:2405.03456 [cs.DC]
  (or arXiv:2405.03456v1 [cs.DC] for this version)

Submission history

From: Ronald Kriemann [view email]
[v1] Mon, 6 May 2024 13:29:14 GMT (73kb,D)

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