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Multilinear algebra and parallel programming

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Abstract

We discuss a programming methodology based on the use of multilinear algebra to design and implement parallel algorithms for linear computations. In particular, we review techniques for implementing expressions involving the tensor product. We then show how the tensor product can be used to formulate Strassen's matrix multiplication algorithm. We report on our experience using this formulation and these techniques to implement a parallel version of Strassen's matrix multiplication algorithm on the Encore Multimax.

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Author information

Authors and Affiliations

  1. Center for Large Scale Computation, The City University of New York, 10036, New York, NY, USA

    R. W. Johnson

  2. Department of Computer and Information Science, The Ohio State University, 43210, Columbus, OH, USA

    C. H. Huang & J. R. Johnson

Authors
  1. R. W. Johnson
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  2. C. H. Huang
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  3. J. R. Johnson
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Additional information

Supported in part by Defense Advanced Research Projects Agency DARPA Order No. 6674, monitored by AFOSR under contract No. F49620-89-C-0020.

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Johnson, R.W., Huang, C.H. & Johnson, J.R. Multilinear algebra and parallel programming. J Supercomput 5, 189–217 (1991). https://doi.org/10.1007/BF00127843

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