Efficient and exact data dependence analysis
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
A practical algorithm for exact array dependence analysis
Communications of the ACM
Eliminating false data dependences using the Omega test
PLDI '92 Proceedings of the ACM SIGPLAN 1992 conference on Programming language design and implementation
Simplifying polynomial constraints over integers to make dependence analysis more precise
Simplifying polynomial constraints over integers to make dependence analysis more precise
Detecting coarse-grain parallelism using an interprocedural parallelizing compiler
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
The Banerjee-Wolfe and GCD tests on exact data dependence information
Journal of Parallel and Distributed Computing
Constraint-based array dependence analysis
ACM Transactions on Programming Languages and Systems (TOPLAS)
Nonlinear and Symbolic Data Dependence Testing
IEEE Transactions on Parallel and Distributed Systems
Monotonic evolution: an alternative to induction variable substitution for dependence analysis
ICS '01 Proceedings of the 15th international conference on Supercomputing
Symbolic Analysis for Parallelizing Compilers
Symbolic Analysis for Parallelizing Compilers
Optimizing Supercompilers for Supercomputers
Optimizing Supercompilers for Supercomputers
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
An Efficient Data Dependence Analysis for Parallelizing Compilers
IEEE Transactions on Parallel and Distributed Systems
The I Test: An Improved Dependence Test for Automatic Parallelization and Vectorization
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
The impact of data dependence analysis on compilation and program parallelization
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
A unified framework for nonlinear dependence testing and symbolic analysis
Proceedings of the 18th annual international conference on Supercomputing
An empirical evaluation of chains of recurrences for array dependence testing
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
Tight analysis of the performance potential of thread speculation using spec CPU 2006
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
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Scientific source code for high performance computers is extremely complex containing irregular control structures with complicated expressions. This complexity makes it difficult for compilers to analyze the code and perform optimizations. In particular with regard to program parallelization, complex expressions are often not taken intro consideration during the data dependence analysis phase. In this work we propose new data dependence analysis techniques to handle such complex instances of the dependence problem and increase program parallelization. Our method is based on a set of polynomial time techniques that can prove or disprove dependences in the presence of non-linear expressions, complex loop bounds, arrays with coupled subscripts, and if-statement constraints. In addition our algorithm can produce accurate and complete direction vector information enabling the compiler to apply further transformations..To validate our method we performed an experimental evaluation and comparison against the ITest, the Omega test and the Range test in the Perfect and SPEC benchmarks. The experimental results indicate that our dependence analysis tool is efficient and more effective in program parallelization than the other dependence tests. The improved parallelization of key loops results into higher speedups and better program execution performance in several benchmarks.