Abstract-As technology keeps scaling down, hardware variability, such as process variations (PV) and negative bias temperature instability (NBTI), emerges as a growing challenge in the modern GPGPUs (general-purpose computing on graphics processing units). PV induces significant delay variations statically, while NBTI dynamically slows down the GPGPUs. Each computing core (i.e., streaming multiprocessor) in GPGPUs supports thousands of simultaneously active threads, and requires a large register file. Such a sizable register file is very sensitive to the hardware variability, and becomes one of the major units in determining the core frequency. In this study, we propose a set of techniques that mitigate both the PV and NBTI impacts on GPGPUs register file. In order to mitigate the susceptibility to PV, we first develop a novel mechanism that classifies registers into fast and slow categories in the highly-banked register architecture to maximize the frequency improvement. We then leverage the unique features in GPGPU applications to effectively tolerate the extra access delay to the slow registers. Moreover, we propose to dynamically balance the utilization across registers to further tolerate the NBTI degradation. Our experimental results show that our proposed techniques optimize GPGPUs performance by 22 percent on average under both PV and NBTI effects.
Tan et al. REF classify register banks into fast and slow according to their access time.
Mitigating the Impact of Hardware Variability for GPGPUs Register File
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Computer Science