Non-linear array data dependence test
Data dependence analysis is the most essential process while parallelizing a sequential program. Most current data dependence tests cannot handle array subscripts that are non-linear expressions. In this paper, we present a new parallelization algorithm, called non-linear array subscripts (NLA) test...
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| Published in: | The Journal of systems and software Vol. 57; no. 2; pp. 145 - 154 |
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| Format: | Journal Article |
| Language: | English |
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New York
Elsevier Inc
15.06.2001
Elsevier Sequoia S.A |
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| ISSN: | 0164-1212, 1873-1228 |
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| Abstract | Data dependence analysis is the most essential process while parallelizing a sequential program. Most current data dependence tests cannot handle array subscripts that are non-linear expressions. In this paper, we present a new parallelization algorithm, called non-linear array subscripts (NLA) test, to deal with non-linear or complex array subscripts. In this scheme, the iterations subject to loop-carried dependence are scheduled into different wavefronts, while the iterations with no loop-carried dependence are assigned into the same wavefront. Based on the wavefront information, the original loop is then transformed into parallel code. Our experimental results on shared-memory parallel machines HP SPP2000 and ALR Quad6 prove the high effectiveness of the NLA test. |
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| AbstractList | Data dependence analysis is the most essential process while parallelizing a sequential program. Most current data dependence tests cannot handle array subscripts that are non-linear expressions. In this paper, we present a new parallelization algorithm, called non-linear array subscripts (NLA) test, to deal with non-linear or complex array subscripts. In this scheme, the iterations subject to loop-carried dependence are scheduled into different wavefronts, while the iterations with no loop-carried dependence are assigned into the same wavefront. Based on the wavefront information, the original loop is then transformed into parallel code. Our experimental results on shared-memory parallel machines HP SPP2000 and ALR Quad6 prove the high effectiveness of the NLA test. Data dependence analysis is the most essential process while parallelizing a sequential program. Most current data dependence tests cannot handle array subscripts that are non-linear expressions. In this paper, we present a new parallelization algorithm, called non-linear array subscripts (NLA) test, to deal with non-linear or complex array subscripts. In this scheme, the iterations subject to loop-carried dependence are scheduled into different wavefronts, while the iterations with no loop-carried dependence are assigned into the same wavefront. Based on the wavefront information, the original loop is then transformed into parallel code. Our experimental results on shared-memory parallel machines HP SPP2000 and ALR Quad6 prove the high effectiveness of the NLA test. copyright 2001 Elsevier Science Inc. Data dependence analysis is the most essential process while parallelizing a sequential program. Most current data dependence tests cannot handle array subscripts that are non-linear expressions. This paper presents a new parallelization algorithm, called non-linear array subscripts (NLA) test, to deal with non-linear or complex array subscripts. In this scheme, the iterations subject to loop-carried dependence are scheduled into different wavefronts, while the iterations with no loop-carried dependence are assigned into the same wavefront. Based on the wavefront information, the original loop is then transformed into parallel code. The experimental results on shared-memory parallel machines HP SPP2000 and ALR Quad6 prove the high effectiveness of the NLA test. |
| Author | Huang, Tsung-Chuan Yang, Cheng-Ming |
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| Keywords | Data dependence test Parallelizing compiler Non-linear array subscripts |
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| SubjectTerms | Algorithms Arrays Data dependence test Non-linear array subscripts Parallel processing Parallelizing compiler Sequential scheduling Studies |
| Title | Non-linear array data dependence test |
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