Nature

R-GNN: recurrent graph neural networks for font classification of oracle bone inscriptions

Font classification of oracle bone inscriptions serves as a crucial basis for determining the historical period to which they belong and holds significant importance in reconstructing significant ...
Nature

Using graph neural network and symbolic regression to model disordered systems

The key to modeling disordered systems lies in accurately simulating atomic trajectories, typically achieved through molecular dynamic (MD) simulation. The accuracy of MD simulations depends on the ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
Semiconductor Engineering

An FPGA-based Accelerator Addressing Bottlenecks in GNN Preprocessing (KAIST et al.)

A new technical paper “AutoGNN: End-to-End Hardware-Driven Graph Preprocessing for Enhanced GNN Performance” was published by researchers at KAIST, Panmnesia, Peking University, Hanyang University, ...
Semiconductor Engineering

GNN-Based Pre-Silicon Power Side-Channel Analysis Framework At RTL Level

A technical paper titled “SCAR: Power Side-Channel Analysis at RTL-Level” was published by researchers at University of Texas at Dallas, Technology Innovation Institute and University of Illinois ...