Probabilistic Directed Writebacks for Exclusive Caches.

Energy is an increasingly important consideration in memory system design. Caches improve energy efficiency by decreasing execution time and reducing the number of main memory accesses, but they suffer from known inefficiencies: the last-level cache (LLC) tends to have a high miss ratio while simultaneously storing many blocks that are never referenced. Because these blocks are not referenced before eviction, we can write them directly to memory rather than to the LLC. To do so, we must predict which blocks will not be referenced. Previous approaches rely on additional state at the LLC and/or extra communication. We show that by predicting working set size per program counter (PC), we can decide which blocks have low probability of being referenced. Our approach relies on the insight that it is possible to makes this prediction based solely on the address stream as seen by the level-one data cache (L1D), eliminating the need to store or communicate PC values between levels of the cache hierarchy. We require no modifications to the LLC. Our approach uses Flajolet andMartin's probabilistic counting to keep the state small: two additional bits per L1D block, with an additional 6KB prediction table. This approach yields a large reduction in number of LLC writebacks: 25% fewer for SPEC on average, 80% fewer for graph500, and 67% fewer for an in-memory hash table.