Feedback-Driven Restructuring of Multi-threaded Applications for NUCA Cache Performance in CMPs

Abstract

This paper addresses feedback-directed restructuring techniques tuned to Non Uniform Cache Architectures (NUCA) in CMPs running multi-threaded applications. Access time to NUCA caches depends on the location of the referred block, so the locality and cache mapping of the application influence the overall performance. We show techniques for altering the distribution of applications into the cache space as to achieve improved average memory access time. In CMPs running multi-threaded applications, the aggregated accesses (and locality) of the processors form the actual cache load and pose specific issues. We consider a number of Splash-2 and Parsec benchmarks on an 8 processor system and we show that a relatively simple remapping algorithm is able to improve the average Static-NUCA (SNUCA) cache access time by 5.5% and allows an SNUCA cache to surpass the performance of a more complex dynamic-NUCA (DNUCA) for most benchmarks. Then, we present a more sophisticated remapping algorithm, relying on cache geometry information and on the access distribution statistics from individual processors, that reduces the average cache access time by 10.2% and is very stable across all benchmarks.