activity
20212024
most citediEDA: An Open-Source Intelligent Physical Implementation Toolkit and Library

5 citations · 5 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AR2024

WideSA: A High Array Utilization Mapping Scheme for Uniform Recurrences on the Versal ACAP Architecture

Tuo Dai, Bizhao Shi, Guojie Luo

The Versal Adaptive Compute Acceleration Platform (ACAP) is a new architecture that combines AI Engines (AIEs) with reconfigurable fabric. This architecture offers significant acce…

cs.LG2023

Fast Exact NPN Classification with Influence-aided Canonical Form

Yonghe Zhang, Liwei Ni, Jiaxi Zhang +3

NPN classification has many applications in the synthesis and verification of digital circuits. The canonical-form-based method is the most common approach, designing a canonical f…

cs.AR20235 cited

iEDA: An Open-Source Intelligent Physical Implementation Toolkit and Library

Xingquan Li, Simin Tao, Zengrong Huang +53

Open-source EDA shows promising potential in unleashing EDA innovation and lowering the cost of chip design. This paper presents an open-source EDA project, iEDA, aiming for buildi…

math.OC2023

Per-RMAP: Feasibility-Seeking and Superiorization Methods for Floorplanning with I/O Assignment

Shan Yu, Yair Censor, Ming Jiang +1

The feasibility-seeking approach provides a systematic scheme to manage and solve complex constraints for continuous problems, and we explore it for the floorplanning problems with…

cs.CC2023

Rethinking NPN Classification from Face and Point Characteristics of Boolean Functions

Jiaxi Zhang, Shenggen Zheng, Liwei Ni +2

NPN classification is an essential problem in the design and verification of digital circuits. Most existing works explored variable symmetries and cofactor signatures to develop t…

cs.AI2021

BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matrices

Zhe Zhou, Bizhao Shi, Zhe Zhang +3

In recent years, Graph Neural Networks (GNNs) appear to be state-of-the-art algorithms for analyzing non-euclidean graph data. By applying deep-learning to extract high-level repre…