PFN’s MN-3 Tops Green500 List of World’s Most Energy-Efficient Supercomputers for Second Time
- July 1, 2021
- Graduate School of Science
- Collaborations
TOKYO – June 28, 2021 – Preferred Networks, Inc. (PFN) and Kobe University announced today that MN-3, PFN’s deep learning supercomputer, has achieved an energy efficiency of 29.70 gigaflops-per-watt (Gflops/W) and topped the latest Green500 list of the world’s most energy-efficient supercomputers for the second time since June 2020. The new achievement exceeds MN-3’s previous record of 26.04 Gflops/W. in the November 2020 Green500 list by 14.05%.
Powered by MN-Core™, a highly efficient custom processor co-developed by PFN and Kobe University specifically for use in deep learning, MN-3 started operation in May 2020 on a trial basis. Drawing on its software development expertise, PFN continuously improved MN-3’s software stack for higher efficiency and computing performance.
The system used for MN-3’s performance measurement consisted of 32 nodes and 128 MN-Core processors. PFN has made improvements to the software as well as the computer system as a whole to boost energy efficiency, which resulted in a 10.25% increase in computing performance and a 14.05% increase in energy efficiency compared with the November 2020 record. MN-3’s latest energy efficiency record is 40.7% higher than the June 2020 record when MN-3 topped the Green500 list for the first time with the same MN-Core processor. This achievement highlights PFN's software expertise that made maximal use of MN-Core and MN-3's potential.
In addition to improving the HPL (High-Performance Linpack) performance, PFN has made significant progress in MN-3’s computing performance for practical deep learning workloads with a specialized compiler for MN-Core. PFN plans to continue improving hardware and software for MN-Core and MN-3 for their use in research and development for autonomous driving, robotics, drug discovery and more.
The comparison of systems used for measurement and their respective performance are as follows.
|
| June 2021 (new) | November 2020 | June 2020 |
| Nodes | 32 | 40 | |
| MN-Core processors | 128 | 160 | |
| CPU cores | 1,536 Intel Xeon cores | 1,920 Intel Xeon cores | |
| Peak performance (theoretical) | 3.138 Pflops | 3.92 Pflops | |
| HPL benchmark | 1.822 Pflops | 1.653 Pflops | 1.621 Pflops |
| Energy efficiency | 29.70 Gflops/W | 26.04 Gflops/W | 21.11 Gflops/W |
| Green500 ranking | #1 | #2 | #1 |
About Preferred Networks
Preferred Networks (PFN) was established in March 2014 with the goal to develop practical, real-world applications of deep learning, robotics and other latest technologies. PFN is currently focused on three priority areas – transportation systems, manufacturing and bio-healthcare – and also exploring the use of deep learning in personal robots, plant optimization, materials discovery, sports analytics and entertainment. In 2015, PFN developed Chainer™, the open-source deep learning framework. PFN’s MN-3 supercomputer, which is equipped with the MN-Core™ processor dedicated for deep learning, topped the Green500 list in June 2020 and June 2021.
Chainer™ and MN-Core™ are the trademarks or the registered trademarks of Preferred Networks, Inc. in Japan and elsewhere.