Affiliation:
1. Department of Electrical Engineering, School of Internet of Things (IoT) Engineering, Jiangnan University 1 , Wuxi, Jiangsu 214122, China
2. Institute of Advanced Technology, Jiangnan University 2 , Wuxi, Jiangsu 214122, China
Abstract
With the rapid development of portable computing devices and users’ demand for high-quality graphics rendering, embedded Graphics Processing Units (GPU) systems for graphics processing are increasingly turning into a key component of computer architecture to enhance computability. The cache system based on traditional static random access memory (SRAM) plays a crucial role in GPUs. But high leakage, low lifetime and poor integration problems deeply plague the science and engineering field. In the paper, a novel magnetic random access memory (MRAM) based cache architecture of GPU systems is proposed for highly efficient graphics processing and computing accelerating, with the merits of high speed, long endurance, strong interference resistance, and ultra-low power consumption. Spin transfer torque-MRAM and spin orbit torque-MRAM are utilized in off-chip and on-chip caches, respectively. A controller design scheme with prefetching modules and optimized cache coherency protocols are adopted. After testing and evaluating with multiple loads, neural network models and datasets, the simulation results show that the proposed system can achieve up to 28%, 56%, and 66.45% optimizations mostly in terms of speed, energy and leakage power, respectively.
Funder
National Natural Science Foundation of China