arXiv subjects

Zhang Hu

Publications and source records attributed to Zhang Hu.

3 recordsLinked to original sources

arXiv2026

GNN-based Path-aware multi-view Circuit Learning for Technology Mapping

Traditional technology mapping suffers from systemic inaccuracies in delay estimation due to its reliance on abstract, technology-agnostic delay models that fail to capture the nuanced timing behavior behavior of real post-mapping circuits. To address this fundamental limitation, we introduce GPA(graph neural network (GNN)-based Path-Aware multi-view circuit learning), a novel GNN framework that learns precise, data-driven delay predictions by synergistically fusing three complementary views of circuit structure: And-Inverter Graphs (AIGs)-based functional encoding, post-mapping technology emphasizes critical timing paths. Trained exclusively on real cell delays extracted from critical paths of industrial-grade post-mapping netlists, GPA learns to classify cut delays with unprecedented accuracy, directly informing smarter mapping decisions. Evaluated on the 19 EPFL combinational benchmarks, GPA achieves 19.9%, 2.1% and 4.1% average delay reduction over the conventional heuristics methods (techmap, MCH) and the prior state-of-the-art ML-based approach SLAP, respectively-without compromising area efficiency.

cs.ET↗

arXiv2025

Mixed Structural Choice Operator: Enhancing Technology Mapping with Heterogeneous Representations

The independence of logic optimization and technology mapping poses a significant challenge in achieving high-quality synthesis results. Recent studies have improved optimization outcomes through collaborative optimization of multiple logic representations and have improved structural bias through structural choices. However, these methods still rely on technology-independent optimization and fail to truly resolve structural bias issues. This paper proposes a scalable and efficient framework based on Mixed Structural Choices (MCH). This is a novel heterogeneous mapping method that combines multiple logic representations with technology-aware optimization. MCH flexibly integrates different logic representations and stores candidates for various optimization strategies. By comprehensively evaluating the technology costs of these candidates, it enhances technology mapping and addresses structural bias issues in logic synthesis. Notably, the MCH-based lookup table (LUT) mapping algorithm set new records in the EPFL Best Results Challenge by combining the structural strengths of both And-Inverter Graph (AIG) and XOR-Majority Graph (XMG) logic representations. Additionally, MCH-based ASIC technology mapping achieves a 3.73% area and 8.94% delay reduction (balanced), 20.35% delay reduction (delay-oriented), and 21.02% area reduction (area-oriented), outperforming traditional structural choice methods. Furthermore, MCH-based logic optimization utilizes diverse structures to surpass local optima and achieve better results.

cs.AR↗

arXiv2015

Review paper: Magnetocaloric effects in RTX intermetallic compounds (R = Gd~Tm, T = Fe~Cu and Pd, X = Al and Si)

The ternary intermetallic RTX compounds (R = rare earth, T = transitional metal, X = p-block metal) have been investigated extensively in the past few decades due to their interesting physical properties. Recently, much attention has been paid to the magnetocaloric effect (MCE) of these RTX compounds, especially the ones with heavy rare-earth, for their potential application in low temperature magnetic refrigeration. In this paper, we review the MCE of RTSi and RTAl systems with R = Gd~Tm, T = Fe~Cu and Pd, which are widely investigated in recent years. It is found that these RTX compounds exhibit various crystal structures and magnetic properties, which then result in different MCE. Large MCE has been observed not only in the typical ferromagnetic materials but also in the antiferromagnetic materials. The magnetic properties have been studied in detail to discuss the physical mechanism of large MCE in RTX compounds. Particularly, some RTX compounds, such as ErFeSi, HoCuSi, HoCuAl, etc, exhibit large reversible MCE under low magnetic field change, which suggests that these compounds could be promising materials for magnetic refrigeration in low temperature range.

cond-mat.mtrl-sci↗