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    Theory and practice of classical matrix-matrix multiplication for hierarchical memory architectures

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    SMITH-DISSERTATION-2017.pdf (951.7Kb)
    Date
    2018-01-23
    Author
    Smith, Tyler Michael
    0000-0003-2502-2946
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    Abstract
    Matrix-matrix multiplication is perhaps the most important operation used as a basic building block in dense linear algebra. A computer with a hierarchical memory architectures has memory that is organized in layers, with small and fast memories close to the processor, and big and slow memories further away from it. Classical matrix-matrix multiplication is an operation particularly suited for such architectures, as it exhibits a large degree of data reuse, so expensive data movements can be amortized over a lot of computation. This dissertation advances the theory of how to optimally reuse data during matrix-matrix multiplication on hierarchical memory architectures, and it uses this understanding to develop new practical algorithms for matrix-matrix multiplication that exhibit improved properties related to data movement.
    Department
    Computer Sciences
    Subject
    Linear algebra
    Scientific computing
    High-performance
    Matrix
    I/O complexity
    URI
    http://hdl.handle.net/2152/63352
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