Parallel matrix transpose algorithms on distributed memory concurrent computers

This paper describes parallel matrix transpose algorithms on distributed memory concurrent processors. We assume that the matrix is distributed over a P/spl times/Q processor template with a block scattered data distribution. P, Q, and the block size can be arbitrary, so the algorithms have wide app...

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Published in:Proceedings of the Scalable Parallel Libraries Conference , October 6-8, 1993, Mississippi State, Mississippi pp. 245 - 252
Main Authors: Jaeyoung Choi, Dongarra, J.J., Walker, D.W.
Format: Conference Proceeding
Language:English
Published: IEEE Comput. Soc. Press 1993
Subjects:
Application software
Computer architecture
Concurrent computing
Distributed computing
Laboratories
Lifting equipment
Linear algebra
Matrix decomposition
Packaging
Scattering
ISBN:0818649801, 9780818649806
Online Access:Get full text
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Abstract This paper describes parallel matrix transpose algorithms on distributed memory concurrent processors. We assume that the matrix is distributed over a P/spl times/Q processor template with a block scattered data distribution. P, Q, and the block size can be arbitrary, so the algorithms have wide applicability. The algorithms make use of non-blocking, point-to-point communication between processors. The use of nonblocking communication allows a processor to overlap the messages that it sends to different processors, thereby avoiding unnecessary synchronization. Combined with the matrix multiplication routine, C=A/spl middot/B, the algorithms are used to compute parallel multiplications of transposed matrices, C=A/sup T//spl middot/B/sup T/, in the PUMMA package. Details of the parallel implementation of the algorithms are given, and results are presented for runs on the Intel Touchstone Delta computer.< >
AbstractList This paper describes parallel matrix transpose algorithms on distributed memory concurrent processors. We assume that the matrix is distributed over a P/spl times/Q processor template with a block scattered data distribution. P, Q, and the block size can be arbitrary, so the algorithms have wide applicability. The algorithms make use of non-blocking, point-to-point communication between processors. The use of nonblocking communication allows a processor to overlap the messages that it sends to different processors, thereby avoiding unnecessary synchronization. Combined with the matrix multiplication routine, C=A/spl middot/B, the algorithms are used to compute parallel multiplications of transposed matrices, C=A/sup T//spl middot/B/sup T/, in the PUMMA package. Details of the parallel implementation of the algorithms are given, and results are presented for runs on the Intel Touchstone Delta computer.< >
Author Jaeyoung Choi
Dongarra, J.J.
Walker, D.W.
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  surname: Walker
  fullname: Walker, D.W.
  organization: Math. Sci. Sect., Oak Ridge Nat. Lab., TN, USA
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Snippet This paper describes parallel matrix transpose algorithms on distributed memory concurrent processors. We assume that the matrix is distributed over a P/spl...
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StartPage 245
SubjectTerms Application software
Computer architecture
Concurrent computing
Distributed computing
Laboratories
Lifting equipment
Linear algebra
Matrix decomposition
Packaging
Scattering
Title Parallel matrix transpose algorithms on distributed memory concurrent computers
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