One of the main tasks on ML-INFN is to offer democratic access to R&D level resources to INFN researchers, independently from their location.

This is realized via:

  1. the direct acquisition of hardware, as funded by various INFN bodies
  2. the utilization of pre-existing resources in the various INFN structures

While the initial ML-INFN project was assuming the realization of a ML-INFN specific Cloud infrastructure, a later development guided to the utilization of the INFNCloud general infrastructure.

1General INFNCloud documentation 
Documentation on the generic INFNCloud infrastructure
2The INFNCloud portalWIP: Details here

Access portal to INFNCloud

3How to access and use ML-INFN resourcesAccess to ML-INFN resources on the INFNCloud
4(obsolete) Using INFNCloud to obtain access to ML-INFN resourcesDeltails hereEntry point How-to on how to get access to a machine for ML R&D
5A summary of available resources
List of resources kept as updated as possible

The ongoing developments towards a future Cloud-native provisioning model for hardware accelerators is describe in the document "A Scalable and Replicable Kubernetes Platform for ML_INFN".

Last Edit

T.Boccali, March 2nd 2020

  • No labels