Darkmem: fine-grained power management of local memories for accelerators in embedded systems
Christian Pilato, Luca P. Carloni · Asia and South Pacific Design Automation Conference · 2018
SRAM consumes a growing fraction of the static power in heterogeneous SoCs, as embedded memories take 70% to 90% of the area of specialized accelerators. We present Dark-Mem as a comprehensive solution for fine-grained power management of accelerator local memories. The DarkMem methodology optimizes at design time the bank configuration for each given accelerator to maximize power-gating opportunities. The DarkMem microarchitecture dynamically varies the operating mode of each memory bank according to the accelerator workload. In our experiments, DarkMem reduces the SRAM static power by more than 40% on average, which translates into a reduction of the total power by almost 18% on average with less than 1% overhead.