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Applying the Roofline model for Deep Learning performance optimizations
Published 23 Sep 2020 in cs.DC, cs.AI, and cs.PF | (2009.11224v1)
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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