A tensor product formulation of Strassen's matrix multiplication algorithm with memory reduction

A programming methodology based on tensor products has been used for designing and implementing block recursive algorithms for parallel and vector multiprocessors. A previous tensor product formulation of Strassen's matrix multiplication algorithm requires working arrays of size O(7/sup n/) for...

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Veröffentlicht in:Parallel Processing Symposium, 7th International (IPPS '93 S. 582 - 588
Hauptverfasser: Kumar, B., Huang, C.-H., Johnson, R.W., Sadayappan, P.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE Comput. Soc. Press 1993
Schlagworte:
Algorithm design and analysis
Cloud computing
Computerized monitoring
Information science
Linear algebra
NIST
Parallel machines
Parallel programming
Tensile stress
Vectors
ISBN:9780818634420, 0818634421
Online-Zugang:Volltext
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Zusammenfassung:A programming methodology based on tensor products has been used for designing and implementing block recursive algorithms for parallel and vector multiprocessors. A previous tensor product formulation of Strassen's matrix multiplication algorithm requires working arrays of size O(7/sup n/) for multiplying 2/sup n/*2/sup n/ matrices. The authors present a modified tensor product formulation of Strassen's algorithm in which the size of working arrays can be reduced to O(4/sup n/). The modified formulation exhibits sufficient parallel and vector operations for efficient implementation. Performance results on the Cray Y-MP are presented.< >
ISBN:9780818634420
0818634421
DOI:10.1109/IPPS.1993.262814