Computing infrastructure for problem solving with deep learning
Preferred Networks (PFN)’s core technologies, especially deep learning, require enormous computing power. To perform a vast number of computations in an efficient way, we currently operate our own computer clusters, more commonly known as supercomputers. Our computer clusters are named MN followed by a series number: MN-1, MN-2 and MN-3.
MN-3 is PFN’s first computer cluster that uses MN-Core, a highly efficient custom processor co-developed by PFN and Kobe University specifically for use in deep learning. MN-3 started operating in May 2020.
In the Green500 list of the world’s most energy-efficient supercomputers, MN-3 ranked:
- #1 at 21.11 Gflops/W in June 2020
- #2 (#1 among Level-3 measured systems) at 26.04 Gflops/W in November 2020
MN-2 is the first GPU cluster built and managed solely by PFN. MN-2 started operating in July 2019.
MN-1 is a GPU computer cluster that NTT Communications operates exclusively for PFN. The MN-1 cluster has two generations: MN-1 operating since September 2017 and MN-1b operating since July 2018.
PFN’s MN-3 Deep Learning Supercomputer Achieves Energy Efficiency of 39.38 GFlops/W, Tops Green500 for Third Time
PFN’s MN-3 Tops Green500 List of World’s Most Energy-Efficient Supercomputers for Second Time