Supporting irregular distributions in FORTRAN 90D/HPF compilers
Supporting irregular distributions in FORTRAN 90D/HPF compilers
Efficient support for irregular applications on distributed-memory machines
PPOPP '95 Proceedings of the fifth ACM SIGPLAN symposium on Principles and practice of parallel programming
Software—Practice & Experience
Compiler and run-time support for irregular computations
Compiler and run-time support for irregular computations
Scheduling loops with partial loop-carried dependencies
Parallel Computing - special issue on parallel computing for irregular applications
Parallel Algorithms for Matrix Computations
Parallel Algorithms for Matrix Computations
Computer Solution of Large Sparse Positive Definite
Computer Solution of Large Sparse Positive Definite
Distributed Memory Compiler Design For Sparse Problems
IEEE Transactions on Computers
Exploiting spatial regularity in irregular iterative applications
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Contribution to Better Handling of Irregular Problems in HPF2
Euro-Par '98 Proceedings of the 4th International Euro-Par Conference on Parallel Processing
A Mapping and Scheduling Algorithm for Parallel Sparse Fan-In Numerical Factorization
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
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In this paper, we study one kind of irregular computation on distributed arrays, the irregular prefix operation, that is currently not well taken into account by the standard data-parallel language HPF2. We show a parallel implementation that efficiently takes advantage of the independent computations arising in this irregular operation. Our approach is based on the use of a directive which characterizes an irregular prefix operation and on inspector/executor support, implemented in the CoLuMBO library, which optimizes the execution by using an asynchronous communication scheme and then communication/ computation overlap. We validate our contribution with results achieved on IBM SP2 for basic experiments and for a sparse Cholesky factorization algorithm applied to real size problems.