Interprocedural dependence analysis and parallelization
SIGPLAN '86 Proceedings of the 1986 SIGPLAN symposium on Compiler construction
Automatic translation of FORTRAN programs to vector form
ACM Transactions on Programming Languages and Systems (TOPLAS)
Data dependence and its application to parallel processing
International Journal of Parallel Programming
An overview of the PTRAN analysis system for multiprocessing
Proceedings of the 1st International Conference on Supercomputing
On the accuracy of the Banerjee test
Journal of Parallel and Distributed Computing - Special issue on shared-memory multiprocessors
The parallel execution of DO loops
Communications of the ACM
Optimizing Supercompilers for Supercomputers
Optimizing Supercompilers for Supercomputers
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
The I Test: An Improved Dependence Test for Automatic Parallelization and Vectorization
IEEE Transactions on Parallel and Distributed Systems
Control and data dependence for program transformations.
Control and data dependence for program transformations.
Speedup of ordinary programs
Dependence analysis for subscripted variables and its application to program transformations
Dependence analysis for subscripted variables and its application to program transformations
Optimizing supercompilers for supercomputers
Optimizing supercompilers for supercomputers
ICS '98 Proceedings of the 12th international conference on Supercomputing
An Analytical Comparison of the I-Test and Omega Test
LCPC '99 Proceedings of the 12th International Workshop on Languages and Compilers for Parallel Computing
The impact of data dependence analysis on compilation and program parallelization
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
A unified framework for nonlinear dependence testing and symbolic analysis
Proceedings of the 18th annual international conference on Supercomputing
Efficient Techniques for Advanced Data Dependence Analysis
Proceedings of the 14th International Conference on Parallel Architectures and Compilation Techniques
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 evaluation of chains of recurrences for array dependence testing
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
An exact data dependence testing method for quadratic expressions
Information Sciences: an International Journal
One-dimensional I test and direction vector I test with array references by induction variable
International Journal of High Performance Computing and Networking
A multi-dimensional Interval Reduction test
International Journal of High Performance Computing and Networking
A general data dependence analysis for parallelizing compilers
The Journal of Supercomputing
Transformations techniques for extracting parallelism in non-uniform nested loops
WSEAS Transactions on Computers
Affine and unimodular transformations for non-uniform nested loops
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
A general data dependence analysis to nested loop using integer interval theory
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
A static data dependence analysis approach for software pipelining
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
On dependence analysis for SIMD enhanced processors
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
Paragon: collaborative speculative loop execution on GPU and CPU
Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units
Leveraging GPUs using cooperative loop speculation
ACM Transactions on Architecture and Code Optimization (TACO)
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The GCD and Banerjee tests are the standard data dependence tests used to determinewhether a loop may be parallelized/vectorized. In an earlier work, (1991) the authorspresented a new data dependence test, the I test, which extends the accuracy of theGCD and the Banerjee tests. In the original presentation, only the case of generaldependence was considered, i.e., the case of dependence with a direction vector of theform (*,*,...,*). In the present work, the authors generalize the I test to check for datadependence subject to an arbitrary direction vector.