A Scheme to Enforce Data Dependence on Large Multiprocessor Systems
IEEE Transactions on Software Engineering
Run-Time Parallelization and Scheduling of Loops
IEEE Transactions on Computers
A practical algorithm for exact array dependence analysis
Communications of the ACM
Array privatization for parallel execution of loops
ICS '92 Proceedings of the 6th international conference on Supercomputing
Improving the performance of runtime parallelization
PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
ICS '94 Proceedings of the 8th international conference on Supercomputing
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
A scalable method for run-time loop parallelization
International Journal of Parallel Programming
Simplification of array access patterns for compiler optimizations
PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
Loop Parallelization
Parallel Programming with Polaris
Computer
Performance Analysis of Parallelizing Compilers on the Perfect Benchmarks Programs
IEEE Transactions on Parallel and Distributed Systems
Data Dependence and Data-Flow Analysis of Arrays
Proceedings of the 5th International Workshop on Languages and Compilers for Parallel Computing
Polaris: Improving the Effectiveness of Parallelizing Compilers
LCPC '94 Proceedings of the 7th International Workshop on Languages and Compilers for Parallel Computing
Parallelizing while loops for multiprocessor systems
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Run-time parallelization: A framework for parallel computation
Run-time parallelization: A framework for parallel computation
Implementation of Sensitivity Analysis for Automatic Parallelization
Languages and Compilers for Parallel Computing
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Current parallelizing compilers cannot identify a significant fraction of parallelizable loops because they have complex or statically insufficiently defined access patterns. We advocate a novel framework for the identification of parallel loops. It speculatively executes a loop as a doall and applies a fully parallel data dependence test to check for any unsatisfied data dependencies; if the test fails, then the loop is re-executed serially. We will present the principles of the design and implementation of a compiler that employs both run-time and static techniques to parallelize dynamic applications. Run-time optimizations always represent a tradeoff between a speculated potential benefit and a certain (sure) overhead that must be paid. We will introduce techniques that take advantage of classic compiler methods to reduce the cost of run-time optimization thus tilting the outcome of speculation in favor of significant performance gains. Experimental results from the PERFECT, SPEC and NCSA Benchmark suites show that these techniques yield speedups not obtainable by any other known method.