DocumentCode :
2053276
Title :
A general data dependence analysis to nested loop using integer interval theory
Author :
Zhou, Jing ; Zeng, Guosun
Author_Institution :
Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai
fYear :
2006
fDate :
25-29 April 2006
Abstract :
Many dependence tests have been proposed for loop parallelization in the case of arrays with linear subscripts, but little work has been done on the arrays with non-linear subscripts, which sometimes occur in parallel benchmarks and scientific and engineering applications. This paper focuses on array subscripts coupled integer power index variables. We attempt to use the integer interval theory to solve the above difficult dependence test problem. Some "interval solution" rules for polynomial equations have been proposed in this paper. Furthermore, based on the proposed rules, we present a novel approach to loop dependence analysis, which is termed the polynomial variable interval test or PVI-test, and also develop a related algorithm. Some case studies show that the PVI-test is effective and efficient. Compared to the VI test, the PVI-test makes significant improvement, and is therefore a more general scheme of dependence test
Keywords :
polynomials; program compilers; program control structures; array subscripts; data dependence analysis; integer interval theory; integer power index variables; interval solution rule; loop dependence analysis; loop parallelization; nested loop; parallel benchmarks; polynomial equations; polynomial variable interval test; Computer science; Concurrent computing; Data analysis; Data engineering; Equations; Page description languages; Performance analysis; Polynomials; Testing; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International
Conference_Location :
Rhodes Island
Print_ISBN :
1-4244-0054-6
Type :
conf
DOI :
10.1109/IPDPS.2006.1639725
Filename :
1639725
Link To Document :
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