# Minotaur: A SIMD-Oriented Synthesizing Superoptimizer

arXiv: https://arxiv.org/abs/2306.00229 · HTML: https://mlsanity.com/paper/2306.00229/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 May 2023.

## Built on by (most cited first, 2 of 2)

- [YFlows: Systematic Dataflow Exploration and Code Generation for Efficient Neural Network Inference using SIMD Architectures on CPUs](https://mlsanity.com/paper/2310.00574/) (2023)
- [Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss?](https://mlsanity.com/paper/2608.03983/) (2026)

## Abstract (arXiv)

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.