Performance and energy evaluation of data prefetching on intel Xeon Phi

Abstract

There is an urgent need to evaluate the existing parallelism and data locality-oriented techniques on emerging manycore machines using multithreaded applications. Data prefetching is a well-known latency hiding technique that comes with various hardware- and software-based implementations in almost all commercial machines. A well-tuned prefetcher can reduce the observed data access latencies significantly by bringing the soonto- be-requested data into the cache ahead of time, eventually improving application execution time. Motivated by this, we present in this paper a detailed performance and power characterization of software (compiler-guided) and hardware data prefetching on an Intel Xeon Phi-based system. Our main contributions are (i) an analysis of the interactions between hardware and software prefetching, showing how hardware prefetching can throttle itself in response to software; (ii) results on the power and energy behavior of prefetching, showing how performance and energy gains outweigh the increased power cost of prefetching; and (iii) an evaluation of the use of intrinsic prefetch instructions to prefetch for applications with difficult-to-detect access patterns.