Pilot Register File: Energy Efficient Partitioned Register File for GPUs
Mohammad Abdel-Majeed, Alireza Shafaei, Hyeran Jeon, Massoud Pedram, Murali Annavaram · 2017
GPU adoption for general purpose computing has been accelerating. To support a large number of concurrently active threads, GPUs are provisioned with a very large register file (RF). The RF power consumption is a critical concern. One option to reduce the power consumption dramatically is to use near-threshold voltage(NTV) to operate the RF. However, operating MOSFET devices at NTV is fraught with stability and reliability concerns. The adoption of FinFET devices in chip industry is providing a promising path to operate the RF at NTV while satisfactorily tackling the stability and reliability concerns. However, the fundamental problem of NTV operation, namely slow access latency, remains. To tackle this challenge in this paper we propose to build a partitioned RF using FinFET technology. The partitioned RF design exploits our observation that applications exhibit strong preference to utilize a small subset of their registers. One way to exploit this behavior is to cache the RF content as has been proposed in recent works. However, caching leads to unnecessary area overheads since a fraction of the RF must be replicated. Furthermore, we show that caching is not efficient as we increase the number of issued instructions per cycle, which is the expected trend in GPU designs. The proposed partitioned RF splits the registers into two partitions: the highly accessed registers are stored in a small RF that switches between high and low power modes. We use the FinFET's back gate control to provide low overhead switching between the two power modes. The remaining registers are stored in a large RF partition that always operates at NTV. The assignment of the registers to the two partitions will be based on statistics collected by the a hybrid profiling technique that combines the compiler based profiling and the pilot warp profiling technique proposed in this paper. The partitioned FinFET RF is able to save 39% and 54% of the RF leakage and the dynamic energy, respectively, and suffers less than 2% performance overhead.