Software Data Spreading: Leveraging Distributed Caches to Improve Single Thread Performance
Single thread performance remains an important consideration even for multicore, multiprocessor systems. As a result, techniques for improving single thread performance using multiple cores have received considerable attention. This work describes a technique, software data spreading, that leverages the cache capacity of extra cores and extra sockets rather than their computational resources. Software data spreading is a software-only technique that uses compiler-directed thread migration to aggregate cache capacity across cores and chips and improve performance. This paper describes an automated scheme that applies data spreading to various types of loops. Experiments with a set of SPEC2000, SPEC2006, NAS, and microbenchmark workloads show that data spreading can provide speedup of over 2, averaging 17% for the SPEC and NAS applications on two systems. In addition, despite using more cores for the same computation, data spreading actually saves power since it reduces access to DRAM.
performance languages chip multiprocessors compilers single-thread performance