Structuring parallel algorithms in an MIMD, shared memory environment
Parallel Computing
An overview for the PTRAN analysis system for multiprocessing
Journal of Parallel and Distributed Computing - Special Issue on Languages, Compilers and environments for Parallel Programming
Determining average program execution times and their variance
PLDI '89 Proceedings of the ACM SIGPLAN 1989 Conference on Programming language design and implementation
Structure of Computers and Computations
Structure of Computers and Computations
Compiling nested data-parallel programs for shared-memory multiprocessors
ACM Transactions on Programming Languages and Systems (TOPLAS)
Compiler optimizations for eliminating barrier synchronization
PPOPP '95 Proceedings of the fifth ACM SIGPLAN symposium on Principles and practice of parallel programming
Unified compilation techniques for shared and distributed address space machines
ICS '95 Proceedings of the 9th international conference on Supercomputing
Register-sensitive selection, duplication, and sequencing of instructions
ICS '01 Proceedings of the 15th international conference on Supercomputing
Eliminating Barrier Synchronization for Compiler-Parallelized Codes on Software DSMs
International Journal of Parallel Programming
Compile-time Synchronization Optimizations for Software DSMs
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Language Extensions in Support of Compiler Parallelization
Languages and Compilers for Parallel Computing
Efficient, portable implementation of asynchronous multi-place programs
Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming
Reducing task creation and termination overhead in explicitly parallel programs
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
A Transformation Framework for Optimizing Task-Parallel Programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
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Today, two styles of scientific parallel programming prevail. In the SPMD style, all processors execute the same program, with sequential code executed redundantly and parallel code executed cooperatively. In the fork-join style, a sequential thread of control spawns multiple threads to execute a portion of the code concurrently. In this paper we describe an automatic method for approaching the efficiency of SPMD-style execution for programs written in the more structured fork-join style.