Computer
Memory storage patterns in parallel processing
Memory storage patterns in parallel processing
Process decomposition through locality of reference
PLDI '89 Proceedings of the ACM SIGPLAN 1989 Conference on Programming language design and implementation
The DINO parallel programming language
Journal of Parallel and Distributed Computing
The data alignment phase in compiling programs for distributed-memory machines
Journal of Parallel and Distributed Computing
Compiling programs for nonshared memory machines
Compiling programs for nonshared memory machines
Compiling Fortran D for MIMD distributed-memory machines
Communications of the ACM
Global optimizations for parallelism and locality on scalable parallel machines
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
Communication-free hyperplane partitioning of nested loops
Journal of Parallel and Distributed Computing
Evaluating compiler optimizations for Fortran D
Journal of Parallel and Distributed Computing - Special issue on data parallel algorithms and programming
An optimizing Fortran D compiler for MIMD distributed-memory machines
An optimizing Fortran D compiler for MIMD distributed-memory machines
Parallel Computing - Special double issue: SUPRENUM and GENESIS
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
Compiling Global Name-Space Parallel Loops for Distributed Execution
IEEE Transactions on Parallel and Distributed Systems
A Loop Transformation Theory and an Algorithm to Maximize Parallelism
IEEE Transactions on Parallel and Distributed Systems
Compile-Time Techniques for Data Distribution in Distributed Memory Machines
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Communication-Free Data Allocation Techniques for Parallelizing Compilers on Multicomputers
IEEE Transactions on Parallel and Distributed Systems
Communication-Free Parallelization via Affine Transformations
LCPC '94 Proceedings of the 7th International Workshop on Languages and Compilers for Parallel Computing
The Journal of Supercomputing
ISHPC '00 Proceedings of the Third International Symposium on High Performance Computing
IEEE Transactions on Parallel and Distributed Systems
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This paper addresses the problem of communication-free partition of iteration spaces and data spaces along hyperplanes. To finding more possible communication-free hyperplane partitions, we treat statements within a loop body as separate schedulable units. Instead of using the information about data dependence distance or direction vectors, our technique explicitly formulates array references as transformations from statement-iteration spaces to data spaces. Based on these transformations, the necessary and sufficient conditions for communication-free partition along hyperplanes to be feasible have been proposed. This approach can be applied to all programs with an imperfectly nested loop or sequences of imperfectly nested loops, whose array references are affine functions of outer loop indices or loop invariant variables. The proposed approach is more practical than existing methods in finding the data and computation distribution patterns that can cause the processor to execute fully-parallel on multicomputers without any interprocessor communication.