Accuracy analysis of machine learning-based performance modeling for microprocessors

Yoshihiro Tanaka, Keitaro Oka, Takatsugu Ono, Koji Inoue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper analyzes accuracy of performance models generated by machine learning-based empirical modeling methodology. Although the accuracy strongly depends on the quality of learning procedure, it is not clear what kind of learning algorithms and training data set (or feature) should be used. This paper inclusively explores the learning space of processor performance modeling as a case study. We focus on static architectural parameters as training data set such as cache size and clock frequency. Experimental results show that a tree-based non-linear regression modeling is superior to a stepwise linear regression modeling. Another observation is that clock frequency is the most important feature to improve prediction accuracy.

Original languageEnglish
Title of host publicationProceedings of the 2016 4th International Japan-Egypt Conference on Electronic, Communication and Computers, JEC-ECC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages83-86
Number of pages4
ISBN (Electronic)9781467389365
DOIs
Publication statusPublished - Jul 21 2016
Event4th International Japan-Egypt Conference on Electronic, Communication and Computers, JEC-ECC 2016 - Cairo, Egypt
Duration: May 31 2016Jun 2 2016

Publication series

NameProceedings of the 2016 4th International Japan-Egypt Conference on Electronic, Communication and Computers, JEC-ECC 2016

Other

Other4th International Japan-Egypt Conference on Electronic, Communication and Computers, JEC-ECC 2016
CountryEgypt
CityCairo
Period5/31/166/2/16

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Computer Science Applications

Cite this

Tanaka, Y., Oka, K., Ono, T., & Inoue, K. (2016). Accuracy analysis of machine learning-based performance modeling for microprocessors. In Proceedings of the 2016 4th International Japan-Egypt Conference on Electronic, Communication and Computers, JEC-ECC 2016 (pp. 83-86). [7518973] (Proceedings of the 2016 4th International Japan-Egypt Conference on Electronic, Communication and Computers, JEC-ECC 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/JEC-ECC.2016.7518973