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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Psarris, K. Kyriakopoulos, K. |
| Copyright Year | 1999 |
| Description | Author affiliation: Div. of Comput. Sci., Texas Univ., San Antonio, TX, USA (Psarris, K.) |
| Abstract | Data dependence analysis is a fundamental step in an optimizing compiler. The results of the analysis enable the compiler to identify code fragments that can be executed in parallel. A number of data dependence tests have been proposed in the literature. In each test there are different tradeoffs between accuracy and efficiency. In this paper we present an experimental evaluation of several data dependence tests, including the Banerjee test, the I-Test and the Omega test. We compare these tests in terms of accuracy and efficiency. We run various experiments using the Perfect Club Benchmarks and the scientific libraries Eispack, Linpack and Lapack. Several observations and conclusions are derived from the experimental results, which are displayed and analyzed in this paper. |
| Starting Page | 264 |
| Ending Page | 273 |
| File Size | 139615 |
| Page Count | 10 |
| File Format | |
| ISBN | 0769504256 |
| ISSN | 1089795X |
| DOI | 10.1109/PACT.1999.807571 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1999-10-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Testing Data analysis Program processors Computer science Read only memory Parallel processing Constraint optimization Optimizing compilers Load management Data mining |
| Content Type | Text |
| Resource Type | Article |
| Subject | Theoretical Computer Science Hardware and Architecture Software |
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