Scheduling the Computations of a Loop Nest with Respect to a Given Mapping

Authors:
Alain Darte;Claude G. Diderich;Marc Gengler;Frédéric Vivien
Affiliations:
-;-;-;-
Venue:
Euro-Par '00 Proceedings from the 6th International Euro-Par Conference on Parallel Processing
Year:
2000

Citing 10
Cited 1

Automatic translation of FORTRAN programs to vector form

ACM Transactions on Programming Languages and Systems (TOPLAS)
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
Some efficient solutions to the affine scheduling problem: I. One-dimensional time

International Journal of Parallel Programming
Maximizing parallelism and minimizing synchronization with affine transforms

Proceedings of the 24th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Optimal fine and medium grain parallelism detection in polyhedral reduced dependence graphs

International Journal of Parallel Programming
A Loop Transformation Theory and an Algorithm to Maximize Parallelism

IEEE Transactions on Parallel and Distributed Systems
Compile-Time Techniques for Data Distribution in Distributed Memory Machines

IEEE Transactions on Parallel and Distributed Systems
Mapping affine loop nests: new results

HPCN Europe '95 Proceedings of the International Conference and Exhibition on High-Performance Computing and Networking
Solving Alignment Using Elementary Linear Algebra

LCPC '94 Proceedings of the 7th International Workshop on Languages and Compilers for Parallel Computing
The Alignment Problem in a Linear Algebra Framework

HICSS '97 Proceedings of the 30th Hawaii International Conference on System Sciences: Software Technology and Architecture - Volume 1

A Constraint Optimization Framework for Mapping a Digital Signal Processing Application onto a Parallel Architecture

CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming

Quantified Score

Hi-index	0.00

Visualization

Abstract

When parallelizing loop nests for distributed memory parallel computers, we have to specify when the different computations are carried out (computation scheduling), where they are carried out (computation mapping), and where the data are stored (data mapping). We show that even the "best" scheduling and mapping functions can lead to a sequential execution when combined, if they are independently chosen. We characterize when combined scheduling and mapping functions actually lead to a parallel execution. We present an algorithm which computes a scheduling compatible with a given computation mapping, if such a schedule exists.