CECAM - E-CAM

The E-CAM centre of excellence is built around the scientific community of CECAM. It is a partnership of 16 CECAM Nodes, 4 PRACE Centers and one Centre for Industrial Computing (Hartree Centre)

GOALS

Software Development to solve important modelling and simulation problems in industry and academia
Tuning those codes to run on HPC, through application co-design and the provision of HPC oriented libraries and services.
Training scientists from industry and academia .
Supporting industrial end-users in their use of simulation and modelling, via workshops and direct discussions with experts in the CECAM community.

Highlights

Highlights from the E-CAM project.

Repositories

Access the software produced in E-CAM and the training material generated at our events.

Success Stories

A selection of case studies and success stories related to E-CAM’s pilot projects focused on industrially oriented problems.

Events

E-CAM events can run at CECAM HQ and at different CECAM Node locations. We run three categories of events : Scoping workshops in collaboration with industry, State-of-the-art workshops and Extended Software Development Workshops.

Latest News

LearnHPC

In newly successful PRACE-ICEI proposal, E-CAM, FocusCoE, HPC Carpentry and EESSI join forces to bring HPC resources to the classroom in a simple, secure and scalable way.

EKHAM the Comics

Identifying exciting and original tools to engage the general public with advanced research is an intriguing and non-trivial challenge for the scientific community. E-CAM decided to try something unusual: collaborated with experts and artists to create a Comics that talks about HPC and simulation and modelling!

December newsletter

Our December newsletter is out. Read about the collaborative project LearnHPC, E-CAM’s Load Balancing Library ALL and our efforts in disseminating the role of HPC and simulation and modelling to the general public via a Comics book!

Get the latest news from E-CAM

Signup for our quartely newsletter

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 676531

Back