# A Time Leap Challenge for SAT Solving

arXiv: https://arxiv.org/abs/2008.02215 · HTML: https://mlsanity.com/paper/2008.02215/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Aug 2020.

## Built on by (most cited first, 6 of 6)

- [Algorithmic progress in language models](https://mlsanity.com/paper/2403.05812/) (2024)
- [Algorithmic progress in computer vision](https://mlsanity.com/paper/2212.05153/) (2022)
- [Measuring Progress in Deep Reinforcement Learning Sample Efficiency](https://mlsanity.com/paper/2102.04881/) (2021)
- [Treewidth-aware Reductions of Normal ASP to SAT -- Is Normal ASP Harder than SAT after All?](https://mlsanity.com/paper/2210.03553/) (2022)
- [Design of quantum optical experiments with logic artificial intelligence](https://mlsanity.com/paper/2109.13273/) (2021)
- [Solving MaxSAT with Matrix Multiplication](https://mlsanity.com/paper/2311.02101/) (2023)

## Abstract (arXiv)

We compare the impact of hardware advancement and algorithm advancement for SAT solving over the last two decades. In particular, we compare 20-year-old SAT-solvers on new computer hardware with modern SAT-solvers on 20-year-old hardware. Our findings show that the progress on the algorithmic side has at least as much impact as the progress on the hardware side.