Scanning polyhedra with DO loops
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
Communication optimization and code generation for distributed memory machines
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
Loop nest scheduling and transformations
Environments and tools for parallel scientific computing
Communication-free hyperplane partitioning of nested loops
Journal of Parallel and Distributed Computing
Improving locality and parallelism in nested loops
Improving locality and parallelism in nested loops
Some efficient solutions to the affine scheduling problem: I. One-dimensional time
International Journal of Parallel Programming
The Omega Library interface guide
The Omega Library interface guide
Maximizing parallelism and minimizing synchronization with affine transforms
Proceedings of the 24th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Generation of Efficient Nested Loops from Polyhedra
International Journal of Parallel Programming - Special issue on instruction-level parallelism and parallelizing compilation, part 2
Enabling unimodular transformations
Proceedings of the 1994 ACM/IEEE conference on Supercomputing
An Exact Method for Analysis of Value-based Array Data Dependences
Proceedings of the 6th International Workshop on Languages and Compilers for Parallel Computing
Communication-Free Parallelization via Affine Transformations
LCPC '94 Proceedings of the 7th International Workshop on Languages and Compilers for Parallel Computing
Extracting synchronization-free threads in perfectly nested loops using the omega project software
SEPADS'05 Proceedings of the 4th WSEAS International Conference on Software Engineering, Parallel & Distributed Systems
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A technique, permitting us to find synchronization-free parallelism in non-uniform loops, is presented. It is based on finding affine space partition mappings. The main advantage of this technique is that it allows us to form constraints for finding mappings directly in a linear form while known techniques result in building non-linear constraints which should next be linearized. After finding affine space partition mappings, well-known code generation approaches can be applied to expose loop parallelism. The technique is illustrated with two examples.