The core degree based tag reduction on chip multiprocessor to balance energy saving and performance overhead

Long Zheng, Mianxiong Dong, Hai Jin, Minyi Guo, Song Guo, Xuping Tu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)


Tag reduction is an approach to save energy of the cache system in a processor. Our previous work described that it can save more energy on a Chip Multiprocessor (CMP) than on a single-core processor. In this paper, we further investigate the problem on balancing energy saving and performance overhead when tag reduction is used for the low power Chip Multiprocessor (CMP). We first introduce the core degree concept which is defined as the number of cores that tag reduction can use for each thread. We then propose a core degree based tag approach that is to optimize the core degree such that the best balance of energy and performance can be achieved. In particular, as the basis for such optimization, the theoretical upper bounds of the energy savings and performance overhead are decided as function of the core degree. In our experiments, we use a 16-core CMP for example. In order to obtain the energy consumption and performance overhead with various core degrees, we construct an experimental environment, which is based on the Linux operating system. With the experimental environment, benchmarks of SPEC CPU2006 are used to evaluate our core degree based tag reduction. Finally, the experimental results show that the most desired balance of energy saving and performance overhead is achieved when core degree is set to 6.
Original languageEnglish
Title of host publicationNetwork and Parallel Computing - IFIP International Conference, NPC 2010, Proceedings
Number of pages15
Publication statusPublished - 12 Nov 2010
Externally publishedYes
EventIFIP International Conference on Network and Parallel Computing, NPC 2010 - Zhengzhou, China
Duration: 13 Sep 201015 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6289 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceIFIP International Conference on Network and Parallel Computing, NPC 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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