Prompt Report on Exa-Scale HPL-AI Benchmark

Our performance benchmark of HPL-AI on the supercomputer Fugaku was awarded in the 55th top500 at ISC20. The effective performance was 1.42 EFlop/s, and the world's first achievement to exceed the wall of exascale in a floating-point arithmetic benchmark. Due to the novelty of HPL-AI, there are few guidelines for large systems and several drawbacks to the large-scale benchmark. It is not enough to replace FP64 operations solely to those on FP32 or FP16. At the least, we need thoughtful numerical analysis for lower-precision arithmetic and introduction of optimization techniques on extensive computing such as on Fugaku. In the poster, we give some comments on the accuracy, implementation, performance improvement, and report on the Exa-scale benchmark on Fugaku.