MaX implementation strategy

MaX concurrently works  to develop a new application and data ecosystem, and to serve its industrial and academic community through end-user oriented actions. Key actions include

  • advancing materials simulations codes:
    • widening the scope of materials simulations in terms of computed functionalities and materials complexity;
    •  advanced software engineering to disentangle the quantum engines from low-level domain specific libraries;
    • designing and promoting sustainable programming models to disseminate advanced functionalities to arbitrary quantum engines;
  • building the materials modelling and data ecosystem: delivering the informatics ecosystem for the automation of high-throughput calculations, the automatic storage of data, a working environment where workflows and turn-key solutions are enabled, and sharing of data and workflows is made possible, while provenance, storage and preservation, reproducibility, and reuse are guaranteed (in collaboration with the MARVEL project);
  • enabling the exascale transition: novel algorithms and programming models, domain-specific libraries, in-memory data management, software/hardware co-design, technology transfer actions with other FET-HPC initiative in H2020.

They are complemented by further end-user oriented key actions:

  • integrating needs and solutions:
    •  aligning the technological offer of the CoE with leading end-users, by identifying and responding to their scientific, technological and industrial needs;
    • expanding code capabilities to design materials and functions of relevance for industrial and societal challenges;
  • supporting end users and integrating communities:
    • industrial outreach, user support/forum for each reference code;
    • a set of flexible services;
    • custom development and consulting;
  • training & education:
    • addressing the skills gap by offering training via an integrated portal and a program of schools and workshops;
    • supporting education in University programs via pilot courses;
    • developing a MOOC (Massive Open On-line Course) model;
    • and a flexible training offer for industrial researchers in our labs or at industrial premises.