DocumentCode :
2711370
Title :
An Empirical Study of the I Test for Exact Data Dependence
Author :
Psarris, Kleanthis ; Pande, Santosh
Volume :
3
fYear :
1994
fDate :
15-19 Aug. 1994
Firstpage :
92
Lastpage :
96
Abstract :
Parallelizing Compilers rely upon subscript analysis to detect data dependences between pairs of array references inside loop nests. The most widely used approximate subscript analysis tests are the GCD test and the Banerjee test. In an earlier work we proposed the I test, an improved subscript analysis test. The I test extends the accuracy of a combination of the GCD test and the Banerjee test. It is also able to provide exact data dependence information at no additional computation cost. In the present work we perform an empirical study on the Perfect Club benchmarks to demonstrate the effectiveness and practical importance of the I Test. We compare its performance with that of the GCD test and the Banerjee test. We show that the I test is always an exact test in practice.
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing, 1994. ICPP 1994 Volume 3. International Conference on
Conference_Location :
North Carolina, USA
ISSN :
0190-3918
Print_ISBN :
0-8493-2493-9
Type :
conf
DOI :
10.1109/ICPP.1994.55
Filename :
5727837
Link To Document :
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