A Novel Adaptive Scratchpad Memory Management Strategy

Scratchpad Memory (SPM) is a fast and small software-managed SRAM. Its current extensive uses in embedded processors are motivated by the advantages of power saving, small area and low access time compared with cache. However, existing SPM management methods depend heavily on profiling and compilers. The dependence on compiler also makes embedded applications hard to transplant. This paper presents a novel strategy to manage the scratchpad memory without compiler support. Based on the memory reference locality theory, a hardware random sampling module is adopted to dynamically identify the frequently accessed addresses at runtime. The consequential data movement and address redirection are handled by software operation with the assistance of memory management unit (MMU). We evaluate our method on 10 typical embedded applications and compare the results to a cache reference system. Experimental results show that, on average, our scheme can achieve 33.5% reduction in energy consumption with only slight (<1%) decrease in throughput versus the reference system.