Quantitative analysis of the emerging multi-core workload memory behavior
Zhizhong Tang · Journal of Tsinghua University(Science and Technology) · 2011
Workload characterization is a key leading job for the design of last-level caches(LLCs) on multi-core processors.This paper analyzes the memory behavior of emerging RMS(recognition,mining,and synthesis) workloads for future multi-core processors,including the working set sizes,data sharing behavior,and spatial data locality,which shows that these RMS workloads are memory intensive,with large working-set sizes,a significant amount of data sharing,and strong strided access patterns.The LLC design space was then explored for multi-threaded RMS workloads and the potential architectural choices were discussed for future multi-core cache design based on the observations.The experimental results show that large DRAM caches can effectively satisfy the cache requirement caused by large working sets with a 128 MB DRAM cache significantly reducing the average L1 miss penalty by 18%;that the shared cache provides better performance than the private cache at the LLC level with a 8 MB shared cache improving the cache performance by 25% compared with a private cache with the same size in total;and that stride based hardware prefetching mechanism provides significant performance improvement by 25%.Consequently,a memory hierarchy is given with a 128 MB DRAM cache,an 8 MB on-die SRAM shared cache,and an 8-entry stride prefetcher for the RMS workloads.