Optimizing data scheduling on processor-in-memory arrays

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In the study of PetaFlop project, Processor-in-Memory array was proposed to be a target architecture in achieving 1015 floating point operations per second computing performance. However one of the major obstacles to achieve the fast computing was interprocessor communications, which lengthen the total execution time of an application. A good data scheduling, consisting of finding initial data placement and data movement during the run-time, can give a significant reduction in the total communication cost and the execution time of the application. In this paper, we propose efficient algorithms for the data scheduling problem. Experimental results show the effectiveness of the proposed approaches. Compared with default data distribution methods such as row-wise or column-wise distributions, the average improvement for the tested benchmarks can be up to 30%.

Original languageEnglish
Title of host publicationProceedings of the 1st Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing, IPPS/SPDP 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages57-61
Number of pages5
ISBN (Electronic)0818684038, 9780818684036
DOIs
StatePublished - 1998
Externally publishedYes
Event1st Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing, IPPS/SPDP 1998 - Orlando, United States
Duration: 30 Mar 19983 Apr 1998

Publication series

NameProceedings of the 1st Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing, IPPS/SPDP 1998
Volume1998-March

Conference

Conference1st Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing, IPPS/SPDP 1998
Country/TerritoryUnited States
CityOrlando
Period30/03/983/04/98

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