GPU NTC Process Variation Compensation With Voltage Stacking

Abstract

Near Threshold Computing (NTC) has the potential to significantly improve efficiency in high throughput architectures like GPGPUs. Nevertheless, NTC is more sensitive to process variation (PV) as it complicates power delivery. We propose GPU Stacking, a novel method based on voltage stacking, to manage the effects of PV and improve the power delivery simultaneously. To evaluate our methodology, we first explore the design space of GPGPUs in the NTC to find a suitable baseline configuration and then apply GPU Stacking to mitigate the effects of PV. When comparing with an equivalent NTC GPGPU without process variation management, we achieve 37% more performance on average. When considering high production volume, our approach shifts all the chips closer to the nominal non-process variation case, delivering on average (across chips) ≈ 80% of the performance of nominal NTC GPGPU, whereas when not using our technique, chips would have ≈ 50% of the nominal performance. We also show that our approach can be applied on top of multi-frequency domain designs, improving the overall performance.

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