Data Communication Prediction Model in Multiprocessors based on Robust Estimation 


Vol. 12,  No. 3, pp. 243-252, Jun.  2005
10.3745/KIPSTA.2005.12.3.243


PDF
  Abstract

This paper introduces a noble modeling technique to build data communication prediction models in multiprocessors, using Least-Squares and Robust Estimation methods. A set of sample communication rates are collected by using a few small input data sets into workload programs. By applying estimation methods to these samples, we can build analytic models that precisely estimate communication rates for huge input data sets. The primary advantage is that, since the models depend only on data set size not on the specifications of target systems or workloads, they can be utilized to various systems and applications. In addition, the fact that the algorithmic behavioral characteristics of workloads are reflected into the models entitles them to model diverse other performance metrics. In this paper, we built models for cache miss rates which are the main causes of data communication in shared memory multiprocessor systems. The results present excellent prediction error rates; below 1% for five cases out of 12, and about 3% for the rest cases.

  Statistics
  Cite this article

[IEEE Style]

J. H. Jun and K. W. Lee, "Data Communication Prediction Model in Multiprocessors based on Robust Estimation," The KIPS Transactions:PartA, vol. 12, no. 3, pp. 243-252, 2005. DOI: 10.3745/KIPSTA.2005.12.3.243.

[ACM Style]

Jang Hwan Jun and Kang Woo Lee. 2005. Data Communication Prediction Model in Multiprocessors based on Robust Estimation. The KIPS Transactions:PartA, 12, 3, (2005), 243-252. DOI: 10.3745/KIPSTA.2005.12.3.243.

Forms

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)

Old Journals

Indexing

All publications of TKIPS is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.

TKIPS is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).

Related Journals