The pilot has received support through the GÉANT Innovation Programme. The proposal was submitted by CNIT (National Inter-University Consortium for Telecommunications), a non-profit consortium established in 1995, bringing together 38 public Italian universities to perform research. PI: Prof. Andrea Detti, University of Rome Tor Vergata.
The GÉANT Cloud Flow (GCF) platform allows to run large-scale workflows consisting of tasks. Tasks are typically embedded in Docker Container images, and GCF deploys these Containers to the most convenient GÉANT site offering a Container platform. The project goal is to extend GCF’s services with open-source software so that a user can not only run containerized-tasks, but platformed-tasks, i.e., tasks running within overlay platforms to leverage better the underlying cloud resources and make the workflow faster. For example, this extension would allow the execution of complex machine learning tasks within the Horovod distributed training platform, deployed by GCF as part of the workflow.
Automation and digitalisation for industry
The GÉANT Cloud Flow (GCF) platform was deployed as a pilot in the lightweight run-time digital twins installation segment of the Arrowhead Tools project, based on machine learning technology trained with simulation and measurement data. The application is improving design of electrical machines and the GCF platform was used for improving the capabilities of the Finite Element (FEM) software for development of more robust modelling capabilities and provisioning of the code as a service in a GCF enabled container cloud. Arrowhead’s target is a machine-learning (ML) digital twin that can learn both from FEM computation results and from the IoT data. The industrial partner in the project is ABB.
The EU-funded Arrowhead Tools project aims for digitalisation and automation solutions for the European industry. It is Europe’s largest project for solutions in automation and digitization for industry.
Digital services are becoming more common with sensors and continuous input also in the field of sports, with increasingly interest to use digital devices during training and exercises. But winter sports and climate conditions present their own challenges with regards to utilising these technologies. GÉANT Cloud Flow is utilized for sports analytics in a research project headed by The Faculty of Sport and Health Sciences at JyU, Finland under the auspices of The European Platform for Sports Innovation (EPSI). The pilot workflow is in the area of machine learning and training of neural networks for analyzing video footage of body movement during cross country skiing.
Process optimization in the steel industry
Choosing the right stainless steel is the key to maximize performance and optimize solutions in any industry. GÉANT Cloud Flow (GCF) is utilized in a pilot with the Outokumpu corporation focusing on predicting dimensional change in steel production. This experiment utilizes ready built GCF Finite Element (FEM) container images for the computing. Outokumpu, is the largest producer of stainless steel in Europe and the second largest producer in the Americas.