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    A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

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    Type
    Article
    Authors
    Rosen, Paul
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2013-07-01
    Online Publication Date
    2013-07-01
    Print Publication Date
    2013-06
    Permanent link to this record
    http://hdl.handle.net/10754/597436
    
    Metadata
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    Abstract
    We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.
    Citation
    Rosen P (2013) A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels. Computer Graphics Forum 32: 161–170. Available: http://dx.doi.org/10.1111/cgf.12103.
    Sponsors
    We thank Kristi Potter for her feedback. This work was supported by DOE NETL and KAUST award KUS-C1-016-04.
    Publisher
    Wiley
    Journal
    Computer Graphics Forum
    DOI
    10.1111/cgf.12103
    ae974a485f413a2113503eed53cd6c53
    10.1111/cgf.12103
    Scopus Count
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