Optimization Through Recomputation in the Polygedrak Model; Work in progress
M. Jongen, Luc Waeijen, Roel Jordans, L. Jóźwiak, Henk Corporaal · Radboud Repository (Radboud University) · 2018
Many modern (mobile) systems involve memory intensive computations.External memory accesses are costly when it comes to the execution time and energy consumption of a program.To overcome this, we usually apply tiling to improve data locality and data reuse in internal memories.In the research reported in this paper we add the possibility to recompute data rather than storing temporary results, and demonstrate that this can have a positive effect on the overall application performance.To achieve this we represented recomputation in the Polyhedral model by extending Polly.We experimentally verified the effectiveness of recomputation on a pair of Convolutional Neural Network layers, when applying loop tiling, loop fusion, and recompute.