SimiEncode: A Similarity-based Encoding Scheme to Improve Performance and Lifetime of Non-Volatile Main Memory

Abstract

Non-Volatile Memories (NVMs) have shown tremendous potential to be the next generation of main memory, yet they are still seriously hampered by the high write latency and limited endurance. In this paper, we first unveil via realworld benchmark analysis that the words within the same cache line showcase a high degree of similarity. We therefore present SimiEncode, a low-overhead and effective Similarity-based Encoding approach. SimiEncode relieves writes to NVMs by (1) generating a mask word with minimized differences to the words within a cache line, (2) encoding each word with the associated mask word by simple XOR operations, and (3) writing a single tag bit to indicate the resulting zero word after encoding. Our prototype implementation of SimiEncode and extensive evaluations driven by 15 state-of-the-art benchmarks demonstrate that, compared with existing approaches, SimiEncode significantly prolongs the lifetime and improves the performance. Importantly, SimiEncode is orthogonal to and can be easily incorporated into existing bit flipping optimizations.