Biblio

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.

Clean slate design of computing system is an emerging topic for continuing growth of warehouse-scale computers. A famous custom design is rackscale (RS) computing by considering a single rack as a computer that consists of a number of processors, storages and accelerators customized to a target application. In RS, each user is expected to occupy a single or more than one rack. However, new users frequently appear and the users often change their application scales and parameters that would require different numbers of processors, storages and accelerators in a rack. The reconfiguration of interconnection networks on their components is potentially needed to support the above demand in RS. In this context, we propose the inter-rackscale (IRS) architecture that disaggregates various hardware resources into different racks according to their own areas. The heart of IRS is to use free-space optics (FSO) for tightly-coupled connections between processors, storages and GPUs distributed in different racks, by swapping endpoints of FSO links to change network topologies. Through a large IRS system simulation, we show that by utilizing FSO links for interconnection between racks, the FSO-equipped IRS architecture can provide comparable communication latency between heterogeneous resources to that of the counterpart RS architecture. A utilization of 3 FSO terminals per rack can improve at least 87.34% of inter-CPU/SSD(GPU) communication over Fat-tree and improve at least 92.18% of that over 2-D Torus. We verify the advantages of IRS over RS in job scheduling performance.