FreshCache: Statically and Dynamically Exploiting Dataless Ways

Abstract

Last level caches (LLCs) account for a substantial fraction of the area and power budget in many modern processors. Two recent trends ? dwindling die yield that falls off sharply with larger chips and increasing static power ? make a strong case for a fresh look at LLC design. Inclusive caches are particularly interesting because many, if not most, commercially successful processors use inclusion to ease coherence at a cost of some data being stale or redundant.

LLC designs can be improved statically (at design time) or dynamically (at runtime). The "static dataless ways," removes the data?but not tag?from some cache ways to save energy and area without complicating inclusive-LLC coherence. A dynamic version ("dynamic dataless ways") could dynamically turn off data, but not tags, effectively adapting the classic selective cache ways idea to save energy in LLC but not area. Our data show that (a) all our benchmarks benefit from dataless ways, but (b) the best number of dataless ways varies by workload. Thus, a pure static dataless design leaves energy-saving opportunity on the table, while a pure dynamic dataless design misses area-saving opportunity. To surpass both pure static and dynamic approaches, we develop the FreshCache LLC design that both statically and dynamically exploits dataless ways, including repurposing a predictor to adapt the number of dynamic dataless ways as well as detailed cache management policies. Results show that FreshCache saves more energy than static dataless ways alone (e.g., 72% vs. 9% of LLC) and more area by dynamic dataless ways only (e.g., 8% vs. 0% of LLC).