Conference Paper

Automatic Transformations for Communication-Minimized Parallelization and Locality Optimization in the Polyhedral Model.

DOI: 10.1007/978-3-540-78791-4_9 Conference: Compiler Construction, 17th International Conference, CC 2008, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2008, Budapest, Hungary, March 29 - April 6, 2008. Proceedings
Source: DBLP

ABSTRACT The polyhedral model provides powerful abstractions to optimize loop nests with regular accesses. Affine transformations in this model capture a com- plex sequence of execution-reordering loop transformations that can improve per- formance by parallelization as well as locality enhancement. Although a signifi- cant body of research has addressed affine scheduling and partitioning, the prob- lemofautomaticallyfindinggoodaffinetransformsforcommunication-optimized coarse-grained parallelization together with locality optimization for the general case of arbitrarily-nested loop sequences remains a challenging problem. We propose an automatic transformation framework to optimize arbitrarily- nested loop sequences with affine dependences for parallelism and locality si- multaneously. The approach finds good tiling hyperplanes by embedding a pow- erful and versatile cost function into an Integer Linear Programming formulation. These tiling hyperplanes are used for communication-minimized coarse-grained parallelization as well as for locality optimization. The approach enables the min- imization of inter-tile communication volume in the processor space, and mini- mization of reuse distances for local execution at each node. Programs requir- ing one-dimensional versus multi-dimensional time schedules (with scheduling- based approaches) are all handled with the same algorithm. Synchronization-free parallelism, permutable loops or pipelined parallelism at various levels can be detected. Preliminary studies of the framework show promising results.

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May 23, 2014