A practical algorithm for exact array dependence analysis
Communications of the ACM
Static and Dynamic Evaluation of Data Dependence Analysis Techniques
IEEE Transactions on Parallel and Distributed Systems
Nonlinear and Symbolic Data Dependence Testing
IEEE Transactions on Parallel and Distributed Systems
Parallel Computing
Data dependence analysis for array references
Journal of Systems and Software
Efficient and precise array access analysis
ACM Transactions on Programming Languages and Systems (TOPLAS)
Dependence Analysis
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
A multi-dimensional version of the I test
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
Performance Analysis of Parallelizing Compilers on the Perfect Benchmarks Programs
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
IEEE Transactions on Parallel and Distributed Systems
Hybrid analysis: static & dynamic memory reference analysis
International Journal of Parallel Programming
Interprocedural Probabilistic Pointer Analysis
IEEE Transactions on Parallel and Distributed Systems
A compiler for exploiting nested parallelism in OpenMP programs
Parallel Computing - OpenMp
Optimizing data permutations for SIMD devices
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
Predecessor/successor approach for high-performance run-time wavefront scheduling
Information Sciences: an International Journal
| Hi-index | 0.07 |
Optimizing compilers relies on program analysis techniques to detect data dependence between program statements. Data dependence testing is a basic step in detecting loop-level parallelism in numerical program. Most studies indicate that data dependence tests cannot handle nonlinear-expression array subscripts. This study presents an exact dependence test that can handle quadratic expression array subscripts precisely. The proposed method detects whether a quadratic equation is monotonically increasing or decreasing, and then reduces the integer solution interval of each variable by repeated projection. When the effective solution interval for any variable shrinks to empty, no integer solutions exist for this quadratic equation; otherwise, all integer solutions can be found, implying that parallelism of a loop can be exploited.