Architectural support for convolutional neural networks on modern CPUs
Animesh Jain, Michael A. Laurenzano, Gilles Pokam, Jason Mars, Lingjia Tang · 2018
A key focus of recent work in our community has been on devising increasingly sophisticated acceleration devices for deep neural network (DNN) computation, especially for networks driven by convolution layers. Yet, despite the promise of substantial improvements in performance and energy consumption offered by these approaches, general purpose computing is not going away because its traditional well-understood programming model and continued wide deployment. Therefore, the question arises as to what can be done, if anything, to evolve conventional CPUs to accommodate efficient deep neural network computation.