Trash in cache: Detecting eternally silent stores

The gap between processing and storage speeds remains a concern for computer system designers and application developers. This disparity can be bridged in part by eliminating unnecessary stores, thereby reducing the amount of traffic that flows from the processor and first-level caches to the slower components of the storage subsystem. Reducing the "write" traffic can improve program performance, save power, and increase the longevity of storage components that have limited write endurance. Techniques have been proposed and evaluated for identifying various classes of stores that can be silenced. A relatively unexplored class of such stores are those that would write data that is dirty, but dead. Such data appears as if it needs to be written back to memory from cache, yet it can be proven that the application can never subsequently access the data. In this paper, we suggest identifying garbage (trash) in cache, so that the dirty bytes associated with the trash need not be written to memory. We propose and evaluate a simple technique based on reference counting that finds a subset of these "eternally silent" (dead) stores. When applied to popular benchmarks, our results show that a significant fraction of the writes to memory can be silenced based on the impossibility of an application subsequently accessing the data.