US Patent Issued to The George Washington University on Dec. 9 for "SGCNAX: a scalable graph convolutional neural network accelerator with workload balancing" (Virginia Inventors)

ALEXANDRIA, Va., Dec. 9 -- United States Patent no. 12,493,779, issued on Dec. 9, was assigned to The George Washington University (Washington).

"SGCNAX: a scalable graph convolutional neural network accelerator with workload balancing" was invented by Jiajun Li (Arlington, Va.) and Ahmed Louri (Vienna, Va.).

According to the abstract* released by the U.S. Patent & Trademark Office: "We introduce SGCNAX, a scalable GCN accelerator architecture for the high-performance and energy-efficient acceleration of GCNs. Unlike prior GCN accelerators that either employ limited loop optimization techniques, or determine the design variables based on random sampling, we systematically explore the loop optimization techniques for GCN acceleration and p...