Program’s Performance Profiling Optimization for Guiding Static Cache Partitioning

How to coordinate the core’s utilizing of cache resource is a key issue for shared cache multi-core processors. The current methods used in cache replacement may cause performance interference between the programs simultaneously running on the cores. Static cache partitioning techniques divide the shared cache into exclusive regions for programs to address the interference problem. In order to allocate the cache space with appropriate size to programs, performance profiling is needed to collect program’s performance under a variety of cache capacities, which has to run program multi-pass, one pass for each cache capacity. The enormous overhead of profiling prevents the static partitioning method from practical use. This paper presents a performance profiling optimization which needs only single-pass run. Phase analysis is used to identify program’s phases to eliminate redundant profiling for the same phases and unnecessary profiling in some cache capacities where program’s performance behavior is insensitive. Then the program’s overall performance under different capacities could be estimated with phases. Experimental results show that the overhead of this method is only 7%, while using it to guide partitioning can get 8% performance improvement than with no partitioning, and only 1% decline compared with the multi-pass profiling guided partitioning.