Mosaic: Exploiting the spatial locality of process variation to reduce refresh energy in on-chip eDRAM modules

TLDR

EDRAM cells require frequent refreshes that consume significant energy, yet retention times vary widely and current systems conservatively refresh all cells at a high rate. This work proposes an alternative approach to reduce refresh energy. By modeling retention properties with Mosaic, exploiting spatial correlation, the authors partition the eDRAM into tiles, profile each tile’s retention, and program tile‑specific refresh rates in the cache controller. Mosaic achieves a 20× reduction in refreshes for large eDRAM modules, effectively eliminating refresh as a major energy source.

Abstract

EDRAM cells require periodic refresh, which ends up consuming substantial energy for large last-level caches. In practice, it is well known that different eDRAM cells can exhibit very different charge-retention properties. Unfortunately, current systems pessimistically assume worst-case retention times, and end up refreshing all the cells at a conservatively-high rate. In this paper, we propose an alternative approach. We use known facts about the factors that determine the retention properties of cells to build a new model of eDRAM retention times. The model is called Mosaic. The model shows that the retention times of cells in large eDRAM modules exhibit spatial correlation. Therefore, we logically divide the eDRAM module into regions or tiles, profile the retention properties of each tile, and program their refresh requirements in small counters in the cache controller. With this architecture, also called Mosaic, we refresh each tile at a different rate. The result is a 20x reduction in the number of refreshes in large eDRAM modules - practically eliminating refresh as a source of energy consumption.