BingoCGN, a scalable and effective chart semantic network accelerator that makes it possible for reasoning of real-time, massive charts via chart dividing, has actually been created by scientists at the Institute of Scientific Research Tokyo, Japan. This innovation structure uses an ingenious cross-partition message quantization method and an unique training formula to dramatically decrease memory needs and boost computational and power performance.
发布者：Dr.Durant，转转请注明出处：https://robotalks.cn/new-framework-reduces-memory-usage-and-boosts-energy-efficiency-for-large-scale-ai-graph-analysis-2/
