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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yonghong Song Zhiyuan Li |
| Copyright Year | 2004 |
| Description | Author affiliation: Sun MicroSysterms Inc., Santa Clara, CA, USA (Yonghong Song) |
| Abstract | Efficient program execution on multiprocessor computers requires both sufficient parallelism and good data locality. Recent research found that, using a combination of loop shifting, loop fusion, and array contraction, one can reduce the memory required to execute a sequence of serial loops, thereby to improve the cache locality. This paper studies how to extend such a memory-reduction scheme to a sequence of DOALL loops, which are executed in parallel on multiprocessors. Two methods are proposed to overcome difficulties caused by loop-carried dependences. Data copy-in is performed to remove anti-dependences between different parallel threads, and computation duplication is performed to remove flow dependences. Experiments performed on a number of benchmark programs show that the proposed technique improves both cache locality and parallel execution speed for the DOALL loops. The scheme achieves an average speedup of 1.41 for 17 programs on a 4-processor SUN machine. |
| Starting Page | 46 |
| Ending Page | 53 |
| File Size | 349168 |
| Page Count | 8 |
| File Format | |
| ISBN | 0769521975 |
| ISSN | 01903918 |
| DOI | 10.1109/ICPP.2004.1327903 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-08-15 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Yarn Concurrent computing Sun Computer networks Parallel processing Intelligent networks Data flow computing |
| Content Type | Text |
| Resource Type | Article |
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