Abstract
Optimizing a parallel program is often difficult. This is true, in particular, for inexperienced programmers who lack the knowledge and intuition of advanced parallel programmers. We have developed a framework that addresses this problem by automating the analysis of static program information and performance data, and offering active suggestions to programmers. Our tool enables experts to transfer programming experience to new users. It complements today’s parallelizing compilers in that it helps to tune the performance of a compiler-optimized parallel program. To show its applicability, we present two case studies that utilize this system. By simply following the suggestions of our system, we were able to reduce the execution time of benchmark programs by as much as 39%.
Original language | English |
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Title of host publication | Languages and Compilers for Parallel Computing - 13th International Workshop, LCPC 2000, Revised Papers |
Editors | Jeanne Ferrante, Samuel P. Midkiff, Jose E. Moreira, Manish Gupta, Siddhartha Chatterjee, Jan Prins, William Pugh, Chau-Wen Tseng |
Publisher | Springer Verlag |
Pages | 274-288 |
Number of pages | 15 |
ISBN (Print) | 3540428623, 9783540455745 |
DOIs | |
Publication status | Published - 2001 |
Externally published | Yes |
Event | 13th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2000 - Yorktown Heights, United States Duration: 2000 Aug 10 → 2000 Aug 12 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 2017 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Other
Other | 13th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2000 |
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Country/Territory | United States |
City | Yorktown Heights |
Period | 00/8/10 → 00/8/12 |
Bibliographical note
Publisher Copyright:© Springer-Verlag Berlin Heidelberg 2001.
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science