On the new SeGaBench benchmark, the strongest of five LLMs recovered compiler-missed optimization semantics and produced validated, speedup-delivering code changes in a large majority of cases.
Minotaur: A SIMD-Oriented Synthesizing Superoptimizer
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
A superoptimizing compiler--one that performs a meaningful search of the program space as part of the optimization process--can find optimization opportunities that are missed by even the best existing optimizing compilers. We created Minotaur: a superoptimizer for LLVM that uses program synthesis to improve its code generation, focusing on integer and floating-point SIMD code. On an Intel Cascade Lake processor, Minotaur achieves an average speedup of 7.3\% on the GNU Multiple Precision library (GMP)'s benchmark suite, with a maximum speedup of 13\%. On SPEC CPU 2017, our superoptimizer produces an average speedup of 1.5\%, with a maximum speedup of 4.5\% for 638.imagick. Every optimization produced by Minotaur has been formally verified, and several optimizations that it has discovered have been implemented in LLVM as a result of our work.
fields
cs.PL 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss?
On the new SeGaBench benchmark, the strongest of five LLMs recovered compiler-missed optimization semantics and produced validated, speedup-delivering code changes in a large majority of cases.