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Parallel matrix transpose algorithms on distributed memory concurrent computers

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3 Author(s)
Jaeyoung Choi ; Math. Sci. Sect., Oak Ridge Nat. Lab., TN, USA ; J. J. Dongarra ; D. W. Walker

This paper describes parallel matrix transpose algorithms on distributed memory concurrent processors. We assume that the matrix is distributed over a P×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·B, the algorithms are used to compute parallel multiplications of transposed matrices, C=AT·BT , 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

Published in:

Scalable Parallel Libraries Conference, 1993., Proceedings of the

Date of Conference:

6-8 Oct 1993