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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
ROOM:393-94-95
ABSTRACT:
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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