Supercompilers for parallel and vector computers
Supercompilers for parallel and vector computers
A static performance estimator to guide data partitioning decisions
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
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 optimization and code generation for distributed memory machines
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
Automatic data partitioning on distributed memory multicomputers
Automatic data partitioning on distributed memory multicomputers
An integrated compilation and performance analysis environment for data parallel programs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Automatic data layout for high performance Fortran
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Loop Transformations for Restructuring Compilers: The Foundations
Loop Transformations for Restructuring Compilers: The Foundations
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
Compile-Time Techniques for Data Distribution in Distributed Memory Machines
IEEE Transactions on Parallel and Distributed Systems
Communication-Free Data Allocation Techniques for Parallelizing Compilers on Multicomputers
IEEE Transactions on Parallel and Distributed Systems
Compile-Time Estimation of Communication Costs on Multicomputers
IPPS '92 Proceedings of the 6th International Parallel Processing Symposium
Solving Alignment Using Elementary Linear Algebra
LCPC '94 Proceedings of the 7th International Workshop on Languages and Compilers for Parallel Computing
Improving Performance of Multi-Dimensional Array Redistribution on Distributed Memory Machines
HIPS '98 Proceedings of the High-Level Parallel Programming Models and Supportive Environments
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In this chapter, we propose a linear data distribution technique, which extends the traditional BLOCK or CYCLIC distribution for intra-dimension as in HPF, to permit partitioning the array elements along slant lines. The array distribution patterns are determined by analyzing the array subscript references in loop nests. If the data are distributed along the slant lines, then we show the conversion algorithm between global address and local address, and the conversion algorithm from global iteration space to local iteration space.