Data Allocation Optimization for Hybrid Scratch Pad Memory With SRAM and Nonvolatile Memory

Embedded systems normally have a tight energy budget. Since the on-chip cache typically consumes 25%-50% of the processor's area and energy consumption, scratch pad memory (SPM), which is a software-controlled on-chip memory, has been widely adopted in many embedded systems due to its smaller area and lower power consumption. However, as the speed of the CMOS transistors increases along with density, leakage power consumption is becoming a critical issue for memory components with a large number of transistors. In this paper, we propose a novel hybrid SPM which consists of static random-access memory (SRAM) and nonvolatile memory (NVM) to take advantage of the ultralow leakage power and high density of latter. A novel dynamic data management algorithm is also proposed to make use of the full potential of NVM. According to the experimental results, with the help of the proposed algorithm, the novel hybrid SPM architecture can reduce the memory access time by 18.17%, the dynamic energy by 24.29%, and the leakage power by 37.34% compared with a baseline pure SRAM SPM with the same area.