A practical automatic polyhedral parallelizer and locality optimizer
Document Type
Conference Proceeding
Publication Date
12-12-2008
Abstract
We present the design and implementation of an automatic polyhedral source-to-source transformation framework that can optimize regular programs (sequences of possibly imperfectly nested loops) for parallelism and locality simultaneously. Through this work, we show the practicality of analytical model-driven automatic transformation in the polyhedral model far beyond what is possible by current production compilers. Unlike previous works, our approach is an end-to-end fully automatic one driven by an integer linear optimization framework that takes an explicit view of finding good ways of tiling for parallelism and locality using affine transformations. The framework has been implemented into a tool to automatically generate OpenMP parallel code from C program sections. Experimental results from the tool show very high speedups for local and parallel execution on multi-cores over state-of-the-art compiler frameworks from the research community as well as the best native production compilers. The system also enables the easy use of powerful empirical/iterative optimization for general arbitrarily nested loop sequences. copyright © 2008 ACM.
Publication Source (Journal or Book title)
Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)
First Page
101
Last Page
113
Recommended Citation
Bondhugula, U., Hartono, A., Ramanujam, J., & Sadayappan, P. (2008). A practical automatic polyhedral parallelizer and locality optimizer. Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 101-113. https://doi.org/10.1145/1375581.1375595