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Complementing the gaps in current HE courses and taking up high performance computing (HPC) knowledge for future science, technology, engineering and mathematics (STEM) professionals.

We aim to establish international cooperation and exchange of knowledge between acknowledged professionals in the field of High-performance computing (HPC). Usage of HPC, presenting nowadays the prospective field of business professionals, is one of the main accelerators of modern science and has certainly the ability to expand future-driven EU potential. A great deal of the most popular software tools that researchers are using nowadays is not developed to exploit the tremendous possibilities of HPC. Therefore, researchers must often start by learning the appropriate programming tools before they start using HPC. We strive to remove these obstacles through the gathering of necessary knowledge and testing it in the form of trainings of participants that will address their individual difficulties when using HPC.

For students

Gain skills that present a knowledge gap in current HE system, enabling future competitiveness in the fields of Engineering and Data Science.

For educators

Gain skills needed for conducting courses with HPC. Raising level of competences in theoretical, programming, mathematical and teaching skills.

For business experts

Gain skills needed for professional growth and competitiveness in the fields of Engineering and Data Science with introduction of HPC.

For future HPC HE courses

Creation of a comprehensive set of learning and teaching material, which will embrace the field of HPC in Engineering and Data Science.

What is HPC?

HPC, often called super-computing, is a mandatory tool addressing problems that are too complex for desktop or laptop computers. For data analyzing, the size of the researched problem is limited by the RAM available in the computer and by the maximum object size. Therefore, data files with sizes up to a few GB can be analyzed. However, using HPC we can scale this limit up to several PB (1,000,000 GB) by using frameworks for distributed data storage and parallel processing. HPC enables researchers to use much bigger (therefore much more accurate) models (meaning many more equations and variables) to simulate the performance of new products, materials, medications etc. in a virtual environment.

HPC as a tool of tommorow

Usage of HPC, presenting nowadays a prospective field of business professionals, is one of the main accelerators of modern science and has certainly the ability to expand future-driven EU potential. A great deal of the most popular software tools that researchers are using nowadays is not developed to exploit the tremendous possibilities of HPC. Therefore, researchers must often start by learning the appropriate programming tools before they start using HPC. The current project will, therefore, remove these obstacles through the gathering of necessary knowledge and testing it in the form of trainings of participants that will address their individual difficulties when using HPC. Collaboration and exchange of different skill sets between project partners together with experts-researchers will be beneficial not only for educational programs but also for raising the level of competences among participants through distribution in the form of multiple training events.

Our training weeks

At the end of each intelectual output we will present the gathered knowledge in a training week.

Promotion

The formed training program will be presented on multiplier events to promote and share the outputs among the leading experts in the field of engineering, mathematics, computer and other HPC- relevant education fields.

Knowledge base

After each knowledge topic has been explored a knowledge base will be set. Fur further information and availability of the material you can contact the SCtrain partners.

Knowledge bundles

Bundles of combined knowledge material that serve as a gateway for a specific HPC related topic.

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This project has been funded with support from the European Commission. Copyright © 2020 Faculty of Mechanical Engineering, University of Ljubljana.