4 papers
Differentiable Initialization-Accelerated CPU-GPU Hybrid Combinatorial Scheduling
Mingju Liu, Jiaqi Yin, Alvaro Velasquez +1
This paper presents a hybrid CPU-GPU framework for solving combinatorial scheduling problems formulated as Integer Linear Programming (ILP). While scheduling underpins many optimiz…
GaloisSAT: Differentiable Boolean Satisfiability Solving via Finite Field Algebra
Curie Kim, Carsten Portner, Mingju Liu +6
Boolean satisfiability (SAT) problem, the first problem proven to be NP-complete, has become a fundamental challenge in computational complexity, with widespread applications in op…
A Scalable Lift-and-Project Differentiable Approach For the Maximum Cut Problem
Ismail Alkhouri, Mian Wu, Cunxi Yu +3
We propose a scalable framework for solving the Maximum Cut (MaxCut) problem in large graphs using projected gradient ascent on quadratic objectives. Our approach is differentiable…
TurboSAT: Gradient-Guided Boolean Satisfiability Accelerated on GPU-CPU Hybrid System
Steve Dai, Cunxi Yu, Kalyan Krishnamani +1
While accelerated computing has transformed many domains of computing, its impact on logical reasoning, specifically Boolean satisfiability (SAT), remains limited. State-of-the-art…