Taming Process Variations in CNFET for Efficient Last Level Cache Design

TL;DR

This paper proposes variation-aware cache designs for CNFET-based last level caches, significantly reducing latency and energy consumption by addressing process variations and optimizing cache layout and data placement.

Contribution

It introduces VASA and VAWA cache architectures tailored for CNFET layouts, incorporating data shuffling and page mapping to mitigate process variation effects.

Findings

Reduced average access latency by up to 45%.

Improved overall performance by up to 9%.

Lowered energy consumption by up to 8%.

Abstract

Carbon nanotube field-effect transistors (CNFET) emerge as a promising alternative to CMOS transistors for the much higher speed and energy efficiency, which makes the technology particularly suitable for building the energy-hungry last level cache (LLC). However, the process variations (PVs) in CNFET caused by the imperfect fabrication lead to large timing variation and the worst-case timing dramatically limits the LLC operation speed. Particularly, we observe that the CNFET-based cache latency distribution is closely related to the LLC layouts. For the two typical LLC layouts that have the CNT growth direction aligned to the cache way direction and cache set direction respectively, we proposed variation-aware set aligned (VASA) cache and variation-aware way aligned (VAWA) cache in combination with corresponding cache optimizations such as data shuffling and page mapping to enable low-latency cache for frequently used data. According to our experiments, the optimized LLC reduces the average access latency by 32% and 45% compared to the baseline designs on the two different CNFET layouts respectively while it improves the overall performance by 6\% and 9\% and reduces the energy consumption by 4% and 8% respectively. In addition, with both the architecture induced latency variation and PV incurred latency variation considered in a unified model, we extended the VAWA and VASA cache design for the CNFET-based NUCA and the proposed NUCA achieves both significant performance improvement and energy saving compared to the straightforward variation-aware NUCA.