Applying the Roofline model for Deep Learning performance optimizations
Jacek Czaja, Michal Gallus, Joanna Woźna, Adam Grygielski, Tao, Luo · arXiv (Cornell University) · 2020
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.