China Stretches Another AI Framework To Exascale

The nexus of traditional high performance computing and artificial intelligence is a fact, not a theory, and the exascale-class machinery installed in the United States, Europe, China, and Japan will be a showcase for how these two powerful simulation and analytical prediction techniques can be brought together in many different ways. A year ago, we wrote about some benchmarks done in China with the Tianhe-3 exascale prototype supercomputer running on custom native many-core Armv8-based Phytium 2000 processors. Now comes yet another research paper from more than a dozen scientists from multiple universities in China laying out a hybrid AI-HPC framework on the next-generation exascale Sunway system, the follow-on to the Sunway "TaihuLight" supercomputer that now sits at number four on the Top500 list of the world's fastest systems, combined with innovative neural network designs and deep learning principles to enable researchers to solve massive and highly complex problems. This effort referred to above is distinct from the BaGuaLu machine learning model that we covered back in March, which spanned 37.44 million cores and that juggled 14.5 trillion parameters. In this new AI-HPC mashup run on OceanLight, the challenge was what is called quantum many-body problems, which occur when large numbers of microscopic particles interact with each other, creating a quantum entanglement and resulting in a range of physical phenomena.