mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations
/ Authors
T. Suzumura, Akiyoshi Sugiki, Hiroyuki Takizawa, A. Imakura, Hiroshi Nakamura, K. Taura, T. Kudoh, T. Hanawa, Y. Sekiya, H. Kobayashi
and 23 more authors
Shin Matsushima, Yohei Kuga, Ryo Nakamura, Renhe Jiang, Junya Kawase, Masatoshi Hanai, H. Miyazaki, Tsutomu Ishizaki, Daisuké Shimotoku, Daisuke Miyamoto, Kento Aida, A. Takefusa, T. Kurimoto, K. Sasayama, Naoya Kitagawa, I. Fujiwara, Yusuke Tanimura, Takayuki Aoki, Toshio Endo, S. Ohshima, K. Fukazawa, S. Date, Toshihiro Uchibayashi
/ Abstract
The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edge devices through high-performance networks. We have built such a nation-wide cloud platform, called "mdx" to meet this need. The mdx platform's virtualization service, jointly operated by 9 national universities and 2 national research institutes in Japan, launched in 2021, and more features are in development. Currently mdx is used by researchers in a wide variety of domains, including materials informatics, geo-spatial information science, life science, astronomical science, economics, social science, and computer science. This paper provides an overview of the mdx platform, details the motivation for its development, reports its current status, and outlines its future plans.
Journal: 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)