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Author Pouchet, Louis-Noël ♦ Kong, Martin ♦ Veras, Richard ♦ Stock, Kevin ♦ Franchetti, Franz ♦ Sadayappan, P.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Compiler optimization ♦ Loop transformations ♦ Autotuning ♦ Affine scheduling ♦ Program synthesis
Abstract Data locality and parallelism are critical optimization objectives for performance on modern multi-core machines. Both coarse-grain parallelism (e.g., multi-core) and fine-grain parallelism (e.g., vector SIMD) must be effectively exploited, but despite decades of progress at both ends, current compiler optimization schemes that attempt to address data locality and both kinds of parallelism often fail at one of the three objectives. We address this problem by proposing a 3-step framework, which aims for integrated data locality, multi-core parallelism and SIMD execution of programs. We define the concept of vectorizable codelets, with properties tailored to achieve effective SIMD code generation for the codelets. We leverage the power of a modern high-level transformation framework to restructure a program to expose good ISA-independent vectorizable codelets, exploiting multi-dimensional data reuse. Then, we generate ISA-specific customized code for the codelets, using a collection of lower-level SIMD-focused optimizations. We demonstrate our approach on a collection of numerical kernels that we automatically tile, parallelize and vectorize, exhibiting significant performance improvements over existing compilers.
Description Affiliation: Carnegie Mellon University, Pittsburgh, PA, USA (Veras, Richard; Franchetti, Franz) || Ohio State University, Columbus, OH, USA (Kong, Martin; Stock, Kevin; Sadayappan, P.) || University of California Los Angeles, Los Angeles, CA, USA (Pouchet, Louis-Noël)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1983-05-01
Publisher Place New York
Journal ACM SIGPLAN Notices (SIGP)
Volume Number 48
Issue Number 6
Page Count 12
Starting Page 127
Ending Page 138

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Source: ACM Digital Library