Memory referencing behavior in compiler-parallelized applications

Compiler-parallelized applications are increasing in importance as moderatescale multiprocessors become common. This paper evaluates how features of advanced memory systems (e.g., longer cache lines) impact memory system behavior for applications amenable to compiler parallelization. Using full-sized input data sets and applications taken from the SPEC, NAS, PERFECT, and RICEPS benchmark suites, we measure statistics such as speedups, memory costs, causes of cache misses, cache line utilization, and data traffic. This exploration allows us to draw several conclusions. First, we find that larger granularity parallelism often correlates with good memory system behavior, good overall performance, and high speedup in these applications. Second, we show that when long (512 byte) cache lines are used, many of these applications suffer from false sharing and low cache line utilization. Third, we identify some of the common artifacts in compiler-parallelized codes that can lead to false sharing or other types of poor memory system performance, and we suggest methods for improving them. Overall, this study offers both an important snapshot of the behavior of applications compiled by state-of-the-art compilers, as well as an increased understanding of the interplay between cache line size, program granularity, and memory performance in moderate-scale multiprocessors.