Loop transformations: Convexity, pruning and optimization

Document Type

Conference Proceeding

Publication Date

12-1-2010

Abstract

High-level loop transformations are a key instrument in mapping computational kernels to effectively exploit resources in modern processor architectures. However, determining appropriate compositions of loop transformations to achieve this remains a significantly challenging task; current compilers may achieve significantly lower performance than hand-optimized programs. To address this fundamental challenge, we first present a convex characterization of all distinct, semantics-preserving, multidimensional affine transformations. We then bring together algebraic, algorithmic, and performance analysis results to design a tractable optimization algorithm over this highly expressive space. The framework has been implemented and validated experimentally on a representative set of benchmarks run on state-of-the-art multi-core platforms. Copyright © 2011 ACM.

Publication Source (Journal or Book title)

Conference Record of the Annual ACM Symposium on Principles of Programming Languages

First Page

549

Last Page

561

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