By Topic

Multi-level partitioning and scheduling under local memory constraint

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
$31 $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

3 Author(s)
Qingyan Wang ; Dept. of Comput. Sci. & Eng., Notre Dame Univ., IN, USA ; Passos, N.L. ; Sha, E.H.

Massive uniform nested loops are broadly used in scientific and DSP applications. Due to the large amount of data handled by such applications the optimization of data accesses by fully utilizing the local memory and minimizing communication overhead is important in order to improve the overall system performance. Most of the traditional partition strategies do not consider the effect of data access on the computational performance. In this study, multilevel partitioning method based on a static data scheduling technique known as carrot-hole data scheduling, is proposed to control the data traffic between different levels of memory. Based on this data schedule, optimal partition vector scheduling vector and the partition size are chosen in such a way to minimize communication overhead. Non-homogeneous size partitions are the final result of the partition scheme which produces a significant performance improvement. Experiments show that by using this technique local cache misses are significantly reduced as compared to results obtained from traditional methods

Published in:

Parallel and Distributed Processing, 1995. Proceedings. Seventh IEEE Symposium on

Date of Conference:

25-28 Oct 1995