CPE: An Energy-Efficient Edge-Device Training with Multi-dimensional Compression Mechanism

Abstract

Recently, the edge-device DNN training has become of high importance, while the computation and access energy consumption of are too large. This paper proposes a CPE (Compress Process Element) with three characteristics. Firstly, CPE has a method of Reordering and Reusing Data (RRD) by controlling the output to reorder data. Secondly, CPE owns a Multi-directional Redundant Skip (MRS) mechanism, which anticipates all zeros and duplicate fields in advance. Thirdly, CPE contains a scheme to transform The Calculation Format (TCF), which transforms the input into another form. Evaluated with 28nm CMOS process, using CPE achieves 2.02 × energy reduction and offer 1.73 × speed up outperforming state-of-the-art trainable processor GANPU.