Accelerating Boolean Constraint Propagation for Efficient SAT-Solving on FPGAs
Abstract
We present a hardware-accelerated SAT solver targeting processor/Field Programmable Gate Arrays (FPGA) SoCs. Our solution accelerates the most expensive subroutine of the Davis-Putnam-Logemann-Loveland (DPLL) algorithm, Boolean Constraint Propagation (BCP) through fine-grained FPGA parallelism. Unlike prior state-of-the-art solutions, our solver eliminates costly clause look-up operations by assigning clauses directly to clause processors on the FPGA and dividing large formulas into smaller partitions manageable by FPGA. Partitions are hot-swapped during runtime as required and the supported formula size is limited only by available external memory, not on-chip FPGA memory. We evaluate our solver on a Xilinx Zynq platform with results showing quicker execution time across various formula sizes, subject to formula partitioning strategy. Compared to prior state-of-the-art, we achieve 1.7x and 1.1x speed up on BCP for 2 representative benchmarks and up to 6x total speedup over software-only implementation.
Cite
@article{arxiv.2401.07429,
title = {Accelerating Boolean Constraint Propagation for Efficient SAT-Solving on FPGAs},
author = {Hariprasadh Govindasamy and Babak Esfandiari and Paulo Garcia},
journal= {arXiv preprint arXiv:2401.07429},
year = {2024}
}
Comments
Accepted at ACM GLSVLSI 2024