The optimization of short sequences of loop-free fixed-point x86_64 code sequences is an important problem in high-performance computing. Unfortunately, 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 programs, we are able to generate aggressively optimized versions of a given target program. Beginning from binaries compiled by gcc -O0, we are able to produce provably correct code sequences that either match or outperform the code produced by gcc -O3, and in some cases expert hand-written assembly.
The University of Wisconsin-Madison is seeking a CRT/.NET Developer within the School of Business. Find complete details by reading Position Vacancy Listing (PVL) #79080 on the website of the Office of Human Resources. To ensure consideration, applicants must apply by July 7, 2014.