Progress of “Plasma and Fusion Cloud” research data platform towards “Open Science”
A new cloud platform to realize the plasma and fusion experimental data ecosystem, named the “Plasma and Fusion Cloud,” has been technically verified on some fundamental issues. Such an enormous amount of diagnostic data requires a high-performance computing (HPC) platform not only for LHD physics data analyses but also for next-generation experiments, such as ITER and JT-60SA. Performance evaluation has been done at NIFS by using the HPC supercomputer “Raijin” and the LHD primary data storage system, both of which are directly connected by the 100 Gbps Ethernet optical link. The test results show that almost a full bandwidth can be used by means of multiple parallel streams. In order to make plasma and fusion diagnostic data “FAIR”, all the LHD’s diagnostic data objects are now under way to be registered with digital object identifiers (DOI) for each acquisition node and plasma pulse. In 2023, more than 1.2 million DOIs were issued for the LHD diagnostic data. Cloud technology is also very promising as a high-performance data computing platform, not only for physics data analyses but also for real-time plasma and plant controls. AWS (Amazon Web Service) S3 cloud storage has accepted a proposal to store all 2.0 peta-byte of compressed LHD physics data for open access, under the AWS Open Data Sponsorship Program (ODP). AWS is also one of the commercial providers of computing clouds in the framework of NII’s Research Data Cloud (RDC) in Japan, allowing LHD data users to increase or decrease the computing power they need on demand. The demonstrations and technical verifications done in this study suggest that a next-generation fusion data research center could be based on cloud technology. • “Plasma and Fusion Cloud” has been technically verified to realize a research data ecosystem • AWS Open Data Sponsorship Program has provided 2 PB free space for LHD data fully open • Direct connection between supercomputer and huge data storage is tested on 100 Gbps Ethernet • 1.2 million DOIs have been issued on LHD diagnostic data, following the FAIR data principle
Authors
- R. Sakamoto (ORCID: https://orcid.org/0000-0002-4453-953X)
- Kenjiro Yamanaka
- Y. Todo (ORCID: https://orcid.org/0000-0001-9323-8285)
- Shigeo Urushidani (ORCID: https://orcid.org/0000-0002-5317-3437)
- Setsuo Imazu
- M. Osakabe (ORCID: https://orcid.org/0000-0001-5220-947X)
- Masaki Ohsuna
- S. Satake (ORCID: https://orcid.org/0000-0002-9387-9987)
- M. Nonomura
- M. Emoto (ORCID: https://orcid.org/0000-0002-0441-6340)
- H. Nakanishi (ORCID: https://orcid.org/0000-0001-6388-4489)
- Takashi Yamamoto (ORCID: https://orcid.org/0000-0001-5888-8901)
- Arimichi Takayama (ORCID: https://orcid.org/0000-0001-8170-7531)
- Masanobu Yoshida
Institutions
- National Institute of Informatics (JP)
- The Graduate University for Advanced Studies, SOKENDAI (JP)
- National Institute for Fusion Science (JP)
Publication Details
- Journal
- Fusion Engineering and Design
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1016/j.fusengdes.2025.114898
- Primary Topic
- Big Data Technologies and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Education, Culture, Sports, Science and Technology
- National Institute of Informatics