SwiftGPU: Fostering Energy Efficiency in a Near-Threshold GPU Through a Tactical Performance Boost
2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
Association for Computing Machinery
National Science Foundation
In this paper, we investigate the challenges of preserving energy-efficiency in a Near-Threshold Computing (NTC) GPU. Two key factors can significantly undermine the efficacy of GPUs at NTC: (a) elongated delays at NTC make the GPU applications severely sensitive toMulti-cycle Latency Datapaths (MLDs) within the GPU pipeline; and (b) process variation (PV) at NTC induces a substantial performance variance. To address these emerging challenges, we propose SwiftGPU - -an energyefficient GPU design paradigm at NTC. SwiftGPU dynamically adjusts the degree of parallelization, and the speed of the MLDs within each stream core of the GPU. The proposed scheme achieves an average of∼15% improvement in energy-efficiency over an ideal PV-free GPU, operating at the Super-Threshold regime. SwiftGPU incurs marginal area, wire-length and power overheads of 0.65%, 2.6% and 3.7%, respectively.
Prabal Basu, Hu Chen, Shamik Saha, Koushik Chakraborty and Sanghamitra Roy, SwiftGPU: Fostering Energy Efficiency in a Near-Threshold GPU Through Tactical Performance Boost. IEEE/ACM Design Automation Conference (DAC), pp. -6, June 2016, Austin, Texas.