A pilot study to compare programming effort for two parallel programming models
Writing software for the current generation of parallel systems requires significant programmer effort, and the community is seeking alternatives that reduce effort while still achieving good performance. Measure the effect of parallel programming models (message-passing vs. PRAM-like) on programmer...
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| Veröffentlicht in: | The Journal of systems and software Jg. 81; H. 11; S. 1920 - 1930 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Elsevier Inc
01.11.2008
Elsevier Sequoia S.A |
| Schlagworte: | |
| ISSN: | 0164-1212, 1873-1228 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Writing software for the current generation of parallel systems requires significant programmer effort, and the community is seeking alternatives that reduce effort while still achieving good performance.
Measure the effect of parallel programming models (message-passing vs. PRAM-like) on programmer effort.
One group of subjects implemented sparse-matrix dense-vector multiplication using message-passing (MPI), and a second group solved the same problem using a PRAM-like model (XMTC). The subjects were students in two graduate-level classes: one class was taught MPI and the other was taught XMTC.
Development time, program correctness.
Mean XMTC development time was 4.8
h less than mean MPI development time (95% confidence interval, 2.0–7.7), a 46% reduction. XMTC programs were more likely to be correct, but the difference in correctness rates was not statistically significant (
p
=
.16).
XMTC solutions for this particular problem required less effort than MPI equivalents, but further studies are necessary which examine different types of problems and different levels of programmer experience. |
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| Bibliographie: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 |
| ISSN: | 0164-1212 1873-1228 |
| DOI: | 10.1016/j.jss.2007.12.798 |