- Description of the aim of the prospectives IN2P3
- Goals of the Town Hall Meeting
- Explanation of next steps
Tier-model, centralised architecture or data lake approach: which model or mix of models best answers to our scientific requirements?
First results of DOMA (Data Organisation Management and Access), data lake with xCache, possibility of diskless computing centres
The challenge of integrating HPC, accelerators (e.g. GPU) and commercial cloud solutions — is it worth the effort, what should be the focus, what are potential benefits?
Does it make sense to push for advancement in Machine Learning on the institute level, or are problems/solutions too specific for each project and lab? What does this mean for the effort on training and recruitement?
Distributed detectors and control systems are a reality in IN2P3 experiments (accelerators, telescope arrays, KM3NeT,...). What are the possible benefits in a coordinated IoT effort, e.g. in combination with Machine Learning, and shall this be a key element of the perspectives?
Virtualisation is not only interesting for small and medium size projects, but also in general a way to preserve and share workflows. Benefits and drawback of academic clouds, such as the ones provided through France Grilles.
Participants: Vincent Breton (LPC), Eric Chassande-Mottin (APC)
Solutions for WLCG and large projects are not necessarily applicable for a wide range of smaller projects within IN2P3. How can we better satisfy the different needs, how should this be coordinated and what should be the focus?
What can be the way forward in using accelerators (GPU, FPGA) and HPC in our field? Is dedicated re-coding necessary, or are abstraction layer libraries like alpaka, kokkos, SYCL the way forward?
Status and possible impact of Quantum Computing for our sciences
Participants: Catherine Biscarat (L2IT), Gilles Grasseau (LLR), Bogdan Vulpescu (LPC)
Emerging technologies, like Quantum Computing, provide a large potential but also a great risk. Shall IN2P3 engage actively in these domains as contributor / developer, or rather observe the field and enter as a user in a later stage?
The pressure on the scientific community, to provide open access to data derived in their experiments, is rising (e.g. loi numerique, plan national science ouverte). How do we respond to that, what changes are necessary?
WLCG and space projects impose strict quality assurance for developers. What are key points here? What could be the benefit for other, smaller projects to impose standards, rules, etc. Should IN2P3 provide centralised solutions and services in this context?
Short summary of the main topics raised during the Town Hall Meeting and outlook on the next steps to arrive at the final "Prospective Calcul & Données".
