Semiconductor Engineering

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

End-to-End Hardware-Driven Graph Preprocessing for Enhanced GNN Performance” was published by researchers at KAIST, Panmnesia ...
SDxCentral

New MLPerf Training Benchmark Results Highlight Hardware and Software Innovations in AI Systems

The MLPerf Training GNN benchmark is used for a node classification task where the goal is to predict a label for each node in a graph. The benchmark uses an R-GAT model and is trained on the 2.2 ...
Hosted on MSN

Graph analysis AI model achieves training up to 95 times faster on a single GPU

Alongside text-based large language models (LLMs), including ChatGPT in industrial fields, GNN (Graph Neural Network)-based graph AI models that analyze unstructured data such as financial ...
Semiconductor Engineering

Predicting Defect Properties In Semiconductors With Graph Neural Networks

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...
Business Wire

New MLPerf Training Benchmark Results Highlight Hardware and Software Innovations in AI Systems

SAN FRANCISCO--(BUSINESS WIRE)--Today, MLCommons ® announced new results for the MLPerf ® Training v4.0 benchmark suite, including first-time results for two benchmarks: LoRA fine-tuning of LLama 2 ...