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    Optimizing The Performance of Streaming Numerical Kernels On The IBM Blue Gene/P PowerPC 450

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    Tareq Malas Thesis.pdf
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    Type
    Thesis
    Authors
    Malas, Tareq Majed Yasin cc
    Advisors
    Keyes, David E. cc
    Committee members
    Ahmadia, Aron cc
    Moshkov, Mikhail cc
    Program
    Computer Science
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2011-07
    Permanent link to this record
    http://hdl.handle.net/10754/209374
    
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    Abstract
    Several emerging petascale architectures use energy-efficient processors with vectorized computational units and in-order thread processing. On these architectures the sustained performance of streaming numerical kernels, ubiquitous in the solution of partial differential equations, represents a formidable challenge despite the regularity of memory access. Sophisticated optimization techniques beyond the capabilities of modern compilers are required to fully utilize the Central Processing Unit (CPU). The aim of the work presented here is to improve the performance of streaming numerical kernels on high performance architectures by developing efficient algorithms to utilize the vectorized floating point units. The importance of the development time demands the creation of tools to enable simple yet direct development in assembly to utilize the power-efficient cores featuring in-order execution and multiple-issue units. We implement several stencil kernels for a variety of cached memory scenarios using our Python instruction simulation and generation tool. Our technique simplifies the development of efficient assembly code for the IBM Blue Gene/P supercomputer's PowerPC 450. This enables us to perform high-level design, construction, verification, and simulation on a subset of the CPU's instruction set. Our framework has the capability to implement streaming numerical kernels on current and future high performance architectures. Finally, we present several automatically generated implementations, including a 27-point stencil achieving a 1.7x speedup over the best previously published results.
    Citation
    Malas, T. M. Y. (2011). Optimizing The Performance of Streaming Numerical Kernels On The IBM Blue Gene/P PowerPC 450. KAUST Research Repository. https://doi.org/10.25781/KAUST-02ZS4
    DOI
    10.25781/KAUST-02ZS4
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-02ZS4
    Scopus Count
    Collections
    MS Theses; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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