CuMAPz: A tool to analyze memory access patterns in CUDA

  title={CuMAPz: A tool to analyze memory access patterns in CUDA},
  author={Yooseong Kim and Aviral Shrivastava},
  journal={2011 48th ACM/EDAC/IEEE Design Automation Conference (DAC)},
CUDA programming model provides a simple interface to program on GPUs, but tuning GPGPU applications for high performance is still quite challenging. Programmers need to consider several architectural details, and small changes in source code, especially on memory access pattern, affect performance significantly. This paper presents CuMAPz, a tool to compare the memory performance of a CUDA program. CuMAPz can help programmers explore different ways of using shared and global memories, and… CONTINUE READING
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Publications referenced by this paper.
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An integrated GPU power and performance model

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