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SwiftGPU: Fostering energy efficiency in a near-threshold GPU through a tactical performance boost

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 to Multi-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 energy-efficient 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.