6 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…
MapTune: Advancing ASIC Technology Mapping via Reinforcement Learning Guided Library Tuning
Mingju Liu, Daniel Robinson, Yingjie Li +1
Technology mapping involves mapping logical circuits to a library of cells. Traditionally, the full technology library is used, leading to a large search space and potential overhe…
Differentiable Combinatorial Scheduling at Scale
Mingju Liu, Yingjie Li, Jiaqi Yin +2
This paper addresses the complex issue of resource-constrained scheduling, an NP-hard problem that spans critical areas including chip design and high-performance computing. Tradit…
Verilog-to-PyG -- A Framework for Graph Learning and Augmentation on RTL Designs
Yingjie Li, Mingju Liu, Alan Mishchenko +1
The complexity of modern hardware designs necessitates advanced methodologies for optimizing and analyzing modern digital systems. In recent times, machine learning (ML) methodolog…
DAG-aware Synthesis Orchestration
Yingjie Li, Mingju Liu, Mark Ren +2
The key methodologies of modern logic synthesis techniques are conducted on multi-level technology-independent representations such as And-Inverter-Graphs (AIGs) of the digital log…