|Author||Schkufza, Eric ♦ Sharma, Rahul ♦ Aiken, Alex|
|Source||ACM Digital Library|
|Publisher||Association for Computing Machinery (ACM)|
|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|
|Education Level||UG and PG|
|Learning Resource Type||Article|
|Publisher Place||New York|
|Journal||Communications of the ACM (CACM)|
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