TOKYO, June 16, 2021 — Preferred Networks, Inc. (PFN) has significantly increased the computational speed for practical deep learning workloads using its new specialized compiler for MN-Core, a deep learning processor co-developed by PFN and Kobe University. The maximum computational speed was more than six times higher than PFN’s previous system that does not use MN-Core.
PFN will present the highly efficient and scalable deep learning approach made possible by the new compiler at the 2021 Symposia on VLSI Technology and Circuits.
The new compiler can compile workloads on PyTorch, PFN’s primary deep learning framework, for fast execution on MN-Core without any major changes. PFN’s tests showed that the computations using MN-Core and the new compiler were more than six times faster for image recognition and nearly three times faster for graph processing than MN-2, PFN’s previous generation of supercomputer equipped with general-purpose GPUs. PFN sees the new capability as a competitive advantage in its research and development as deep learning datasets and models grow increasingly large and complex.
More technical details of the achievement are available on the PFN tech blog at: https://tech.preferred.jp/en/blog/mncore-compiler-1/
MN-Core powers MN-3, PFN’s latest generation of supercomputer that started operation in May 2020 and topped the Green500 list of the world’s most energy-efficient supercomputers in June 2020. PFN has developed its software stack to maximize the potential of its hardware for deep learning, including MN-Core and MN-3.
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. https://www.preferred.jp/en/
Source: Preferred Networks