![]() ABCI achieved first place amongst all registered systems in the "DeepCAM" benchmark program as well, also with about half of the system. ![]() The ABCI system delivered 20 times the performance of the other GPU types, while Fugaku delivered 14 times the performance of the other CPU types. The ABCI ranked first in metrics of all registered systems in the "CosmoFlow" benchmark program, with about half of the whole ABCI system ( 4), and Fugaku ranked second with measurement of about 1/10 of the whole system ( 5). MLPerf HPC is a performance competition in two benchmark programs: "CosmoFlow" ( 2), which predicts cosmological parameters, and "DeepCAM" ( 3), which identifies abnormal weather phenomena. The results were presented as MLPerf HPC v0.7 on November 18th (November 19th Japan Time) at the 2020 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC20) event, which is currently being held online. Similarly, about 1/10 of Fugaku was utilized to set a record for CPU-type supercomputers consisting of general-purpose computing devices only, achieving a processing speed 14 times faster than that of other CPU-type systems. That is the highest performance among supercomputers based on GPUs, computing devices specialized in deep learning. Utilizing about half the computing resources of its system, ABCI achieved processing speeds 20 times faster than other GPU-type systems. The MLPerf HPC benchmark measures large-scale machine learning processing on a level requiring supercomputers, and the parties achieved these outcomes leveraging approximately half of the "AI-Bridging Cloud Infrastructure" ("ABCI") supercomputer system, operated by AIST, and about 1/10 of the resources of the supercomputer Fugaku, which is currently under joint development by RIKEN and Fujitsu. Fujitsu, the National Institute of Advanced Industrial Science and Technology (AIST), and RIKEN today announced a performance milestone in supercomputing, achieving the highest performance and claiming the ranking positions on the MLPerf HPC benchmark ( 1).
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