sponsored byIEEEACMThe International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 16-21, 2014

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Oil and Water Can Mix! An Integration of Polyhedral and AST-based Transformations

SESSION: Compiler Analysis and Optimization

EVENT TYPE: Papers, Best Paper Finalists

TIME: 3:30PM - 4:00PM

SESSION CHAIR: Milind Kulkarni

AUTHOR(S):Jun Shirako, Louis-Noel Pouchet, Vivek Sarkar



Optimizing compilers targeting modern multi-core
machines require complex program restructuring to expose the proper
grain of coarse- and fine-grain parallelism and data locality.
The polyhedral compilation model has provided significant advancements
in handling of compositions of loop transformations,
exposing multiple levels of parallelism and improving data
reuse. However, not all program transformations can be expressed in
this model, and some others may actually limit performance because of
the excessively complex loop structures generated.

In this paper, we propose an optimization flow that combines polyhedral
and syntactic/AST-based transformations, leveraging the strengths and
cornering the limitations of each framework. It generates
high-performance code containing well-formed loops which can be
effectively vectorized, while still exposing sufficient
parallelism and data reuse. It combines several transformation stages
using either polyhedral or AST-based transformations, delivering
performance improvements over single-staged polyhedral compilers.

Chair/Author Details:

Milind Kulkarni (Chair) - Purdue University

Jun Shirako - Rice University

Louis-Noel Pouchet - University of California, Los Angeles

Vivek Sarkar - Rice University

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society