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
Integer Programming for Array Subscript Analysis
IEEE Transactions on Parallel and Distributed Systems
Static and Dynamic Evaluation of Data Dependence Analysis Techniques
IEEE Transactions on Parallel and Distributed Systems
Data dependence analysis on multi-dimensional array references
ICS '89 Proceedings of the 3rd international conference on Supercomputing
Data dependence analysis for array references
Journal of Systems and Software
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
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
The Power Test for Data Dependence
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Data dependence analysis techniques for increased accuracy and extracted parallelism
International Journal of Parallel Programming - Special issue II: The 17th annual international conference on supercomputing (ICS'03)
An Empirical Study of the I Test for Exact Data Dependence
ICPP '94 Proceedings of the 1994 International Conference on Parallel Processing - Volume 03
Hi-index | 0.00 |
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.