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Conference Papers Year : 2016

Opening Polyhedral Compiler's Black Box

Abstract

While compilers offer a fair trade-off between productivity and executable performance in single-threaded execution, their optimizations remain fragile when addressing compute-intensive code for parallel architectures with deep memory hierarchies. Moreover, these optimizations operate as black boxes, impenetrable for the user, leaving them with no alternative to time-consuming and error-prone manual optimization in cases where an imprecise cost model or a weak analysis resulted in a bad optimization decision. To address this issue, we propose a technique allowing to automatically translate an arbitrary polyhedral optimization, used internally by loop-level optimization frameworks of several modern compilers, into a sequence of comprehensible syntactic transformations as long as this optimization focuses on scheduling loop iterations. With our approach, we open the black box of the polyhedral frameworks enabling users to examine, refine, replay and even design complex optimizations semi-automatically in partnership with the compiler.
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Dates and versions

hal-01253322 , version 1 (18-03-2016)

Identifiers

  • HAL Id : hal-01253322 , version 1

Cite

Lénaïc Bagnères, Oleksandr Zinenko, Stéphane Huot, Cédric Bastoul. Opening Polyhedral Compiler's Black Box. CGO 2016 - 14th Annual IEEE/ACM International Symposium on Code Generation and Optimization, Mar 2016, Barcelona, Spain. ⟨hal-01253322⟩
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