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Author Schkufza, Eric ♦ Sharma, Rahul ♦ Aiken, Alex
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract The optimization of short sequences of loop-free, fixed-point assembly code sequences is an important problem in high-performance computing. However, the competing constraints of transformation correctness and performance improvement often force even special purpose compilers to produce sub-optimal code. We show that by encoding these constraints as terms in a cost function, and using a Markov Chain Monte Carlo sampler to rapidly explore the space of all possible code sequences, we are able to generate aggressively optimized versions of a given target code sequence. Beginning from binaries compiled by 11vm --O0, we are able to produce provably correct code sequences that either match or outperform the code produced by qcc --O3, icc --O3, and in some cases expert handwritten assembly.
Description Affiliation: Stanford University, Stanford, CA (Schkufza, Eric; Sharma, Rahul; Aiken, Alex)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 59
Issue Number 2
Page Count 9
Starting Page 114
Ending Page 122


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Source: ACM Digital Library