OCMAS: Online Page Clustering for Multibank Scratchpad Memory

Scratchpad memory (SPM), a software-controlled on-chip memory, is being increasingly used in embedded systems to reduce on-chip memory energy consumption. To further reduce energy consumption, multibank SPM architecture is proposed. In multibank SPM, each bank can be accessed independently, and unused banks can enter the low power mode, thus reducing leakage energy. However, if both frequently and infrequently used data exist in the same bank, the bank will not be able to enter the low power mode, resulting in less energy reduction. To address this issue, we propose online page clustering for multibank SPM (OCMAS) to reduce the leakage energy in multibank SPM. OCMAS groups SPM pages with similar access frequencies into the same bank, allowing banks containing infrequently used data to stay in low power mode longer. We also propose a method to dynamically adjust the thresholds for determining cold pages (pages that contain infrequently used data), so banks that contain cold pages can enter the low power mode with a shorter idle timeout. Compared to conventional timeout-based, periodic drowsy, and bank-based methods, OCMAS can reduce the energy delay product by up to 37.67% (18.14% on average), 39.53% (22.38% on average), and 132.32% (23.34% on average) in 32 KB 4-bank SPM, by up to 25.33% (15.71% on average), 29.87% (15.92% on average), and 72.25% (22.64% on average) in 32 KB 8-bank SPM, by up to 28.99% (13.45% on average), 30.71% (14.74% on average), and 96.67% (19.94% on average) in 16 KB 4-bank SPM, and by up to 30.18% (10.05% on average), 32.13% (11.62% on average), and 65.56% (16.2% on average) in 16 KB 8-bank SPM. The area overhead is approximately 0.72%, which is insignificant.