The Max Planck Computing and Data Facility (MPCDF) is a central facility which hosts clusters for high-performance computing (HPC) and supports the computational and data science needs of the Max Planck Society, Germany’s most successful research organization. MPCDF provides many services, including Data Services for large scale data analysis, transfer and collaboration, backup and archive.

MPCDF has been using Globus as a production (DataHub) service for data transfer since 2017. Globus was implemented because it allows for fast, reliable, and secure large scale data transfer. Plus, it provides researchers with a nice user experience through its “fire and forget” capabilities, where transferring large amounts of data through a point and click interface is trouble-free, even for datasets that are many GBs or even TBs in size.

Several projects that the MPCDF are involved in use Globus for large scale data transfers to and from the HPC systems at MPCDF. Projects such as the Fotothek of the Bibliotheca Hertziana in Rome and the Virgo Consortium, represented by the Max Planck Institute for Astrophysics are just two examples.

Now as international and multi-organization collaborations are becoming more commonplace, and datasets are growing exponentially, MPCDF decided to expand its use of Globus by subscribing to the Globus premium service. MPCDF recently deployed Globus collections and enabled Globus sharing, which gives researchers a simple, easy-to-use method of data sharing with external collaborators around the world. 

 

For more information on the Max Planck Computing & Data Facility please visit: https://www.mpcdf.mpg.de/

 

With the ever-increasing amount of research data - be it from observations, experiments or simulations - a solid, robust and easy-to-use solution for data transfer, sharing and publishing becomes ever more important for researchers."

The Globus subscription service provides researchers within the Max Planck Society a feature rich tool which also supports data handling in line with the FAIR (Findable, Accessible, Interoperable and Re-usable) Principles which are gaining increased recognition in modern research projects.”

Dr. Raphael Ritz, Head of Data Divsion at MPCDF