Data dependence and its application to parallel processing
International Journal of Parallel Programming
Measuring Parallelism in Computation-Intensive Scientific/Engineering Applications
IEEE Transactions on Computers
On the accuracy of the Banerjee test
Journal of Parallel and Distributed Computing - Special issue on shared-memory multiprocessors
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
Evaluation of programs and parallelizing compilers using dynamic analysis techniques
Evaluation of programs and parallelizing compilers using dynamic analysis techniques
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Gated SSA-based demand-driven symbolic analysis for parallelizing compilers
ICS '95 Proceedings of the 9th international conference on Supercomputing
Data dependence analysis on multi-dimensional array references
ICS '89 Proceedings of the 3rd international conference on Supercomputing
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
The range test: a dependence test for symbolic, non-linear expressions
Proceedings of the 1994 ACM/IEEE conference on Supercomputing
Automatic Detection of Parallelism: A Grand Challenge for High-Performance Computing
IEEE Parallel & Distributed Technology: Systems & Technology
The Power Test for Data Dependence
IEEE Transactions on Parallel and Distributed Systems
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
Constraint-based array dependence analysis
ACM Transactions on Programming Languages and Systems (TOPLAS)
An Interleaving Transformation for Parallelizing Reductions for Distributed-Memory Parallel Machines
The Journal of Supercomputing
Demand-Driven Interprocedural Array Property Analysis
LCPC '99 Proceedings of the 12th International Workshop on Languages and Compilers for Parallel Computing
Partitioning Loops with Variable Dependence Distances
ICPP '00 Proceedings of the Proceedings of the 2000 International Conference on Parallel Processing
IEEE Transactions on Parallel and Distributed Systems
Proceedings of the 20th annual international conference on Supercomputing
Graph transformation and designing parallel sparse matrix algorithms beyond data dependence analysis
Scientific Programming - Distributed Computing and Applications
An exact data dependence testing method for quadratic expressions
Information Sciences: an International Journal
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
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
The Journal of Supercomputing
ISPA'05 Proceedings of the Third international conference on Parallel and Distributed Processing and Applications
A static data dependence analysis approach for software pipelining
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Coping with data dependencies of multi-dimensional array references
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Programmable data dependencies and placements
DAMP '12 Proceedings of the 7th workshop on Declarative aspects and applications of multicore programming
Impact of array data flow analysis on the design of energy-efficient circuits
PATMOS'06 Proceedings of the 16th international conference on Integrated Circuit and System Design: power and Timing Modeling, Optimization and Simulation
Dynafuse: dynamic dependence analysis for FPGA pipeline fusion and locality optimizations
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
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Data dependence analysis techniques are the main component of today's strategies for automatic detection of parallelism. Parallelism detection strategies are being incorporated in commercial compilers with increasing frequency because of the widespread use of processors capable of exploiting instruction-level parallelism and the growing importance of multiprocessors. An assessment of the accuracy of data dependence tests is therefore of great importance for compiler writers and researchers. The tests evaluated in this study include the generalized greatest common divisor test, three variants of Banerjee's test, and the Omega test. Their effectiveness was measured with respect to the Perfect Benchmarks and the linear algebra libraries, EISPACK and LAPACK. Two methods were applied, one using only compile-time information for the analysis, and the second using information gathered during program execution. The results indicate that Banerjee's test is for all practical purposes as accurate as the more complex Omega test in detecting parallelism. However, the Omega test is quite effective in proving the existence of dependences, in contrast with Banerjee's test, which can only disprove, or break dependences. The capability of the Omega test of proving dependences could have a significant impact on several compiler algorithms not considered in this study.