Fine Grain Cache Partitioning Using Per-Instruction Working Blocks

Jason Jong Kyu Park, Yongjun Park, Scott Mahlke

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


A traditional least-recently used (LRU) cache replacement policy fails to achieve the performance of the optimal replacement policy when cache blocks with diverse reuse characteristics interfere with each other. When multiple applications share a cache, it is often partitioned among the applications because cache blocks show similar reuse characteristics within each application. In this paper, we extend the idea to a single application by viewing a cache as a shared resource between individual memory instructions. To that end, we propose Instruction-based LRU (ILRU), a fine grain cache partitioning that way-partitions individual cache sets based on per-instruction working blocks, which are cache blocks required by an instruction to satisfy all the reuses within a set. In ILRU, a memory instruction steals a block from another only when it requires more blocks than it currently has. Otherwise, a memory instruction victimizes among the cache blocks inserted by itself. Experiments show that ILRU can improve the cache performance in all levels of cache, reducing the number of misses by an average of 7.0% for L1, 9.1% for L2, and 8.7% for L3, which results in a geometric mean performance improvement of 5.3%. ILRU for a three-level cache hierarchy imposes a modest 1.3% storage overhead over the total cache size.

Original languageEnglish
Article number7429315
Pages (from-to)305-316
Number of pages12
JournalParallel Architectures and Compilation Techniques - Conference Proceedings, PACT
Publication statusPublished - 2015
Event24th International Conference on Parallel Architecture and Compilation, PACT 2015 - San Francisco, United States
Duration: 2015 Oct 182015 Oct 21

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture


Dive into the research topics of 'Fine Grain Cache Partitioning Using Per-Instruction Working Blocks'. Together they form a unique fingerprint.

Cite this