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Late Breaking Results: Differential and Massively Parallel Sampling of SAT Formulas

Published: 07 November 2024 Publication History

Abstract

Diverse solutions to the Boolean satisfiability (SAT) problem are essential for thorough testing and verification of software and hardware designs, ensuring reliability and applicability to real-world scenarios. We introduce a novel differentiable sampling method, called DiffSampler, which employs gradient descent (GD) to learn diverse solutions to the SAT problem. By formulating SAT as a supervised multi-output regression task and minimizing its loss function using GD, our approach enables performing the learning operations in parallel, leading to GPU-accelerated sampling and comparable run time performance w.r.t. heuristic samplers. We demonstrate that DiffSampler can generate diverse uniform-like solutions similar to conventional samplers.

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M. Soos et al., "Tinted, detached, and lazy cnf-xor solving and its applications to counting and sampling," in Proceedings of International Conference on Computer-Aided Verification (CAV), 2020.
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R. Dutra et al., "Efficient sampling of sat solutions for testing," in Proc. of the International Conference on Software Engineering, 2018.
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C. Costa, "Parallelization of sat algorithms on gpus," Technical report, INESC-ID, Technical University of Lisbon, Tech. Rep., 2013.
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M. Osama et al., "Sat solving with gpu accelerated inprocessing," in International Conference on Tools and Algorithms for the Construction and Analysis of Systems. Springer, 2021, pp. 133--151.
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J. Gu, "Global optimization for satisfiability (sat) problem," IEEE Trans. on Knowledge and Data Engineering, vol. 6, no. 3, pp. 361--381, 1994.
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T. Sato et al., "Matsat: a matrix-based differentiable sat solver," arXiv preprint arXiv:2108.06481, 2021.
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Y. Pote et al., "On scalable testing of samplers," in Advances in Neural Information Processing Systems (NeurIPS), 2022.

Cited By

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  • (2025)DEMOTIC: A Differentiable Sampler for Multi-Level Digital CircuitsProceedings of the 30th Asia and South Pacific Design Automation Conference10.1145/3658617.3697760(1328-1335)Online publication date: 20-Jan-2025

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cover image ACM Conferences
DAC '24: Proceedings of the 61st ACM/IEEE Design Automation Conference
June 2024
2159 pages
ISBN:9798400706011
DOI:10.1145/3649329
This work is licensed under a Creative Commons Attribution-ShareAlike International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 07 November 2024

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DAC '24
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DAC '24: 61st ACM/IEEE Design Automation Conference
June 23 - 27, 2024
CA, San Francisco, USA

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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View all
  • (2025)DEMOTIC: A Differentiable Sampler for Multi-Level Digital CircuitsProceedings of the 30th Asia and South Pacific Design Automation Conference10.1145/3658617.3697760(1328-1335)Online publication date: 20-Jan-2025

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