By Topic

A performance model and metrics for fine grain parallel computing systems-finding optimal parallelism

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
S. Sekiguchi ; Electrotech. Lab., Tsukuba, Japan ; M. Sato

Parallel computing, and fine grain computing in particular, need criteria to find optimal parallelism. This paper proposes performance models that measure ability to generate and synchronize parallel processes, and to switch control in parallel processing systems. We consider the performance of controlling the number of parallel processes (synchronization capability), the performance of generating parallel processes (generation capability), and the performance of controlling a computing flow of parallel processes (branch capability) in fine grain parallel computing. We also discuss the usefulness of these performance measures, and prove that optimization is possible by measuring the branch capability of instruction level data flow computers. With optimal parallelism, extraction and control of parallel processes is well-balanced, and the balancing point is specified

Published in:

Algorithms & Architectures for Parallel Processing, 1996. ICAPP 96. 1996 IEEE Second International Conference on

Date of Conference:

11-13 Jun 1996