Towards Energy-Efficient CGRAs via Stochastic Computing

Abstract

Stochastic computing (SC) is a promising computing paradigm for low-power and low-cost applications with the added benefit of high error tolerance. Meanwhile, Coarse-Grained Re-configurable Architecture (CGRA) is also a promising platform for domain-specific applications for its combination of energy efficiency and flexibility. Intuitively, introducing SC to CGRA would synergistically reinforce the strengths of both paradigms. Accordingly, this paper proposes an SC-based CGRA by replacing the exact multiplication in traditional CGRA with an SC-based multiplication, where the problem of accuracy and latency are both improved using parallel stochastic sequence generators and leading zero shifters. In addition, with the flexible connections among PEs, the high-accuracy operation can be easily achieved by combing neighbor PEs without switching costs like power-gating. Compared to the state-of-the-art approximate computing design of CGRA, our proposed CGRA has 16% more energy reduction and 34% energy efficiency improvement while keeping high configuration flexibility.