Efficiently computing static single assignment form and the control dependence graph
ACM Transactions on Programming Languages and Systems (TOPLAS)
Beyond induction variables: detecting and classifying sequences using a demand-driven SSA form
ACM Transactions on Programming Languages and Systems (TOPLAS)
Gated SSA-based demand-driven symbolic analysis for parallelizing compilers
ICS '95 Proceedings of the 9th international conference on Supercomputing
Idiom recognition in the Polaris parallelizing compiler
ICS '95 Proceedings of the 9th international conference on Supercomputing
Detection and global optimization of reduction operations for distributed parallel machines
ICS '96 Proceedings of the 10th international conference on Supercomputing
Array SSA form and its use in parallelization
POPL '98 Proceedings of the 25th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Proceedings of the 14th international conference on Supercomputing
Efficient compiler and run-time support for parallel irregular reductions
Parallel Computing - special issue on parallel computing for irregular applications
Graphics Gems
Parallel Programming with Polaris
Computer
Irregular Assignment Computations on cc-NUMA Multiprocessors
ISHPC '02 Proceedings of the 4th International Symposium on High Performance Computing
Towards Detection of Coarse-Grain Loop-Level Parallelism in Irregular Computations
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
A GSA-based compiler infrastructure to extract parallelism from complex loops
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
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This paper describes a compiler framework that enhances the detection of parallelism in loops with complex irregular computations. The framework is based on the static analysis of the Gated Single Assignment (GSA) program representation. A taxonomy of the strongly connected components (SCCs) that appear in GSA dependence graphs is presented as the basis of our framework. Furthermore, an algorithm for classifying the set of SCCs associated with loops is described. We have implemented a prototype of the SCC classification algorithm using the infrastructure provided by the Polaris parallelizing compiler. Experimental results for a suite of real irregular programs are shown.