VARIUS-NTV: A microarchitectural model to capture the increased sensitivity of manycores to process variations at near-threshold voltages

Ulya R. Karpuzcu, Krishna B. Kolluru, Nam Sung Kim, Josep Torrellas

2012 · 93 citations · 38 references

Concepts

TL;DR

Near‑threshold computing offers energy efficiency but is more vulnerable to process variations, causing higher power consumption, lower operating frequencies, and increased fault rates compared to conventional super‑threshold computing. This work introduces the first microarchitectural model of process variations specifically for near‑threshold computing. The VARIUS‑NTV model extends the existing VARIUS framework by incorporating a gate‑delay model and NTC‑tailored SRAM cells, modeling SRAM failure modes that arise at low voltages, and accounting for leakage effects, and is evaluated on a simulated 11 nm, 288‑core tiled manycore at both NTC and STC. Evaluation shows that near‑threshold operation exhibits significantly larger frequency and power variations, with the maximum on‑chip tile frequency differing by approximately 2.3× at STC and 3.7× at NTC.

Abstract

Near-Threshold Computing (NTC), where the supply voltage is only slightly higher than the threshold voltage of transistors, is a promising approach to attain energy-efficient computing. Unfortunately, compared to the conventional Super-Threshold Computing (STC), NTC is more sensitive to process variations, which results in higher power consumption and lower frequencies than would otherwise be possible, and potentially a non-negligible fault rate. To help address variations at NTC at the architecture level, this paper presents the first microarchitectural model of process variations for NTC. The model, called VARIUS-NTV, extends the existing VARIUS variation model. Its key aspects include: (i) adopting a gate-delay model and an SRAM cell type that are tailored to NTC, (ii) modeling SRAM failure modes emerging at NTC, and (iii) accounting for the impact of leakage in SRAM models. We evaluate a simulated 11nm, 288-core tiled manycore at both NTC and STC. The results show higher frequency and power variations within the NTC chip. For example, the maximum difference in on-chip tile frequency is ≈2.3× at STC and ≈3.7× at NTC. We also validate our model against an experimental chip.

References

38