Data dependence and its application to parallel processing
International Journal of Parallel Programming
The Omega test: a fast and practical integer programming algorithm for dependence analysis
Proceedings of the 1991 ACM/IEEE conference on Supercomputing
A practical algorithm for exact array dependence analysis
Communications of the ACM
Delinearization: an efficient way to break multiloop dependence equations
PLDI '92 Proceedings of the ACM SIGPLAN 1992 conference on Programming language design and implementation
Nonlinear and Symbolic Data Dependence Testing
IEEE Transactions on Parallel and Distributed Systems
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
Interactive Parallel Programming using the ParaScope Editor
IEEE Transactions on Parallel and Distributed Systems
Interprocedural symbolic analysis
Interprocedural symbolic analysis
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Traditional data dependence testing algorithms have become very accurate and efficient for simple subscript expressions, but they cannot handle symbolic expressions because of the complexity of data-flow and lack of the semantic information of variables in programs. In this paper, a range-based testing and query approach, called DDTQ, is proposed to eliminate data dependence between array references with symbolic subscripts. DDTQ firstly extracts data dependence information from the symbolic subscripts, a testing algorithm is then used to disprove the dependence based on the ranges of expressions. The assumed dependence that cannot be handled by the disprover will be converted into simple questions by a question engine so that the compiler can solve them by user interaction in a friendly way. The experiment on perfect benchmarks indicates that DDTQ is effective in improving the parallelizing capability of the compiler.