Advanced compiler optimizations for supercomputers
Communications of the ACM - Special issue on parallelism
The program dependence graph and its use in optimization
ACM Transactions on Programming Languages and Systems (TOPLAS)
Automatic decomposition of scientific programs for parallel execution
POPL '87 Proceedings of the 14th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Loop distribution with arbitrary control flow
Proceedings of the 1990 ACM/IEEE conference on Supercomputing
Automatic selection of high-order transformations in the IBM XL FORTRAN compilers
IBM Journal of Research and Development - Special issue: performance analysis and its impact on design
Conversion of control dependence to data dependence
POPL '83 Proceedings of the 10th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
the NESTOR Library: A Tool for Implementing FORTRAN Source Transformations
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
Parallelism exposure and exploitation in programs
Parallelism exposure and exploitation in programs
Improving the performance of virtual memory computers.
Improving the performance of virtual memory computers.
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We consider the problem of distribution of loops with control dependences, involving if and do control structures. More precisely, we study how to control the number of temporary arrays that have to be introduced to store conditionals. We show that the traditional superposition of the data dependence graph and of the control dependence graph is not adequate, and we introduce a new representation, the mixed dependence graph. This allows us to develop a distribution algorithm that is parameterized by the maximal allowed dimensions of temporary arrays.