Interprocedural dependence analysis and parallelization
SIGPLAN '86 Proceedings of the 1986 SIGPLAN symposium on Compiler construction
Data dependence and its application to parallel processing
International Journal of Parallel Programming
Compilation of Haskell array comprehensions for scientific computing
PLDI '90 Proceedings of the ACM SIGPLAN 1990 conference on Programming language design and implementation
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Compiling crystal for distributed-memory machines
Compiling crystal for distributed-memory machines
An Efficient Data Dependence Analysis for Parallelizing Compilers
IEEE Transactions on Parallel and Distributed Systems
A Loop Transformation Theory and an Algorithm to Maximize Parallelism
IEEE Transactions on Parallel and Distributed Systems
The Power Test for Data Dependence
IEEE Transactions on Parallel and Distributed Systems
Doany: Not Just Another Parallel Loop
Proceedings of the 5th International Workshop on Languages and Compilers for Parallel Computing
Semantics and Implementation of a Generalized forall Statement for Parallel Languages
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
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We have developed a framework for analyzing the behavior and relations of various sequential and parallel control constructs, which we can nest in a very general way. A simple yet powerful scheme defines the order of data accesses in a program, and provides a well-founded semantic structure for nested constructs. When defining parallel languages or extensions to current languages, designers can use this framework to define how each new feature interacts with the language's other features. Because our approach is based on well-known dependence analysis techniques, it is practical for compiler implementation. It determines which behavior the compiler and system must preserve while allowing aggressive automatic optimization. Instead of being confined to a single programming paradigm, programmers can use the most appropriate constructs for the application, and the compiler can transform and optimize the program for different parallel or sequential architectures.