Characterizing the memory behavior of compiler-parallelized applications

Evan Torrie, Margaret Martonosi, Chau We Tseng, Mary W. Hall

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Compiler-parallelized applications are increasing in importance as moderate-scale 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 standard benchmark suites, we measure statistics such as speedups, synchronization and load imbalance, causes of cache misses, cache line utilization, data traffic, and memory costs. 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.

Original languageEnglish (US)
Pages (from-to)1224-1237
Number of pages14
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number12
StatePublished - 1996

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


  • Cache performance
  • False and true sharing
  • Memory hierarchies
  • Parallelism granularity
  • Parallelizing compilers
  • Shared-memory multiprocessors


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