Theory of linear and integer programming
Theory of linear and integer programming
Automatic decomposition of scientific programs for parallel execution
POPL '87 Proceedings of the 14th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
A data locality optimizing algorithm
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Some efficient solutions to the affine scheduling problem: I. One-dimensional time
International Journal of Parallel Programming
Optimal fine and medium grain parallelism detection in polyhedral reduced dependence graphs
International Journal of Parallel Programming
Parameterized polyhedra and their vertices
International Journal of Parallel Programming
The parallel execution of DO loops
Communications of the ACM
International Journal of Parallel Programming - Special issue on parallel architectures and compilation techniques
Scheduling and Automatic Parallelization
Scheduling and Automatic Parallelization
Application-domain-driven system design for pervasive video processing
Ambient intelligence
Iterative Optimization in the Polyhedral Model: Part I, One-Dimensional Time
Proceedings of the International Symposium on Code Generation and Optimization
AIC'05 Proceedings of the 5th WSEAS International Conference on Applied Informatics and Communications
Iterative optimization in the polyhedral model: part ii, multidimensional time
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Multi-dimensional rankings, program termination, and complexity bounds of flowchart programs
SAS'10 Proceedings of the 17th international conference on Static analysis
Using free scheduling for programming graphic cards
Facing the Multicore-Challenge II
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Feautrier's scheduling algorithm is the most powerful existing algorithm for parallelism detection and extraction. But it has always been known to be suboptimal. However, the question whether it may miss some parallelism because of its design was still open. We show that this is not the case. Therefore, to find more parallelism than this algorithm does, one needs to get rid of some of the hypotheses underlying its framework.