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arXiv · 2009.11224

Applying the Roofline model for Deep Learning performance optimizations

Jacek Czaja·Michal Gallus·Joanna Wozna·Adam Grygielski·Luo Tao
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Abstract

In this paper We present a methodology for creating Roofline models automatically for Non-Unified Memory Access (NUMA) using Intel Xeon as an example. Finally, we present an evaluation of highly efficient deep learning primitives as implemented in the Intel oneDNN Library.

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Jacek Czaja, Michal Gallus, Joanna Wozna, Adam Grygielski, Luo Tao. 2020-09-23. Applying the Roofline model for Deep Learning performance optimizations. https://arxiv.org/abs/2009.11224

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