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Hierarchical Roofline Analysis: How to Collect Data using Performance Tools on Intel CPUs and NVIDIA GPUs

Charlene Yang
National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720, USA
arXiv:2009.02449 [cs.DC], (5 Sep 2020)

@misc{yang2020hierarchical,

   title={Hierarchical Roofline Analysis: How to Collect Data using Performance Tools on Intel CPUs and NVIDIA GPUs},

   author={Charlene Yang},

   year={2020},

   eprint={2009.02449},

   archivePrefix={arXiv},

   primaryClass={cs.DC}

}

This paper surveys a range of methods to collect necessary performance data on Intel CPUs and NVIDIA GPUs for hierarchical Roofline analysis. As of mid-2020, two vendor performance tools, Intel Advisor and NVIDIA Nsight Compute, have integrated Roofline analysis into their supported feature set. This paper fills the gap for when these tools are not available, or when users would like a more customized workflow for certain analysis. Specifically, we will discuss how to use Intel Advisor, RRZE LIKWID, Intel SDE and Intel Amplifier on Intel architectures, and nvprof, Nsight Compute metrics, and Nsight Compute section files on NVIDIA architectures. These tools will be used to collect information for as many memory/cache levels in the memory hierarchy as possible in order to provide insights into application’s data reuse and cache locality characteristics.
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