DMC is an annual international competition that brings together experts from industry and academia and tests their software and solutions for transferring huge amounts of research data.
The challenge focuses on optimising point-to-point data transfers between sites, which is essential for advancing research collaboration and sharing.
Seven international teams from Singapore, Japan, Poland, Australia, Malaysia, USA and Germany participated in DMC 2021 over three months to develop and deploy the best software tools on Data Transfer Nodes (DTNs) connected by 100 Gbps international research and education networks (NRENs).
The National Computational Infrastructure (NCI) hosted the Australian DTN for this year’s challenge, utilising the AARNet network to connect to the other global sites through international research and education networks and organisations Internet2, SingAREN, GÉANT, NORDUnet, KREONET, CENIC, Funet, Jisc, Sinet, SURF, KAUST, Pacific Wave, StarLight SDX, NICT, KISTI, Pacific Research Platform and TransPAC.
The winning teams of DMC 2021 were Team MUSASHINO of Japan, Arcitecta of Australia, Fast Is Good of Malaysia and China, Globus of USA and Ciena-iCair-UETN of Canada and USA.
These teams developed creative solutions to deliver reliable data transfer services over a range of network conditions, optimisations for large reliable dataset replication, application of well-established data transfer ecosystems, efficient movement of large data sets through firewalls and impaired networks, and employment of machine learning within a highly optimised data transfer framework.
The DMC judging committee was presented with an interesting range of participants who each had a unique approach to the challenge. The winning solutions covered the spectrum of network technology and the quality of the entries were highly regarded by the judging panel, with each presenting its own merits in various use cases.”
Associate Director of Cloud Services at NCI Australia, and Chief Judge of the DMC 2021 Judging Committee
Moving large amounts of data is an essential foundation of national and global science, and AARNet is proud to support initiatives like DMC that help improve the reliability and efficiency of networks for future research.
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