The mission of this project is a methodological approach towards complementing the gaps in current HE courses and taking up high performance computing (HPC) knowledge for future science, technology, engineering and mathematics (STEM) professionals. 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. Our insight on the topic has revealed a regional wide requirement. Although in the smart strategy specialisation (S3) within the EU strategy, the topic of HPC adoption has been recognised, there is currently a lack of national programs. In recent years there is increased activity aiming at filling this gap – countries involved in this Erasmus+ call are establishing new HPC competence centres (EuroHPC program). Through them, basic educational programs are foreseen – HPC literacy programs for researchers, but a further systematical approach (bottom-up) is needed to efficiently raise the level of knowledge of HPC. Furthermore, the EU has made the decision to establish large “pre-exascale” and “exascale” trans-European centres that will meet the needs of scientific disciplines and be able to compete with similar centres in USA, China and Japan. In order to compete in this area of expertise, it is necessary to have experience in developing applications that exploit the high capacities of HPC. In recent years, there is an increased need of the industry to incorporate super-computing in their Research & Development and thus increase their own competitiveness. Unfortunately, current established courses in HE do not offer comprehensive support for HPC adoption. Therefore, researching and knowledge gathering through involvement of all project participants will raise the level of competences in STEM. Furthermore, success of the developed training will offer a starting point for future implementation of such a program into HE courses. Project partners included in the project are: - University of Ljubljana, Faculty for Mechanical Engineering, Slovenia, - IT4I, Czech national HPC center as part of VŠB University in Ostrava, - VSC (Vienna Scientific Cluster) Research Center of TU Wien, Austria, - CINECA, consortium of all Italian universities taking care of HPC and IT infrastructure. The project addresses the issue of raising the HPC knowledge by educating the educators and thus preparing them for future implementation. During the project duration, research in the field of HPC in Engineering and Data science is divided into four stages, each covered by an output: - O1; covering the topic of HPC in Engineering – focus on FEM (Finite Element Method), - O2; covering the topic of HPC in Data Science – focus on Parallelisation with MPI, - O3; covering the topic of HPC in Engineering – focus on CFD (Computational Fluid Dynamics), - O4; covering the topic of HPC in Data Science – focus on IOT and Big Data, - O5; combined collection of knowledge on the topic of HPC in Engineering and Data Science. Within each objective, output will include the creation of a knowledge base in form of lectures (core knowledge) and exercises/tutorials (hands-on approach) that form content, available through an e-learning portal. The e-learning portal enables better informing about the program, increases availability, tailoring of presented topics for specific area and offers better inclusion for enrolled participants. The relevance of the collected topics will be tested by introducing training events that will benefit both the verification of knowledge transfer to students and the enhancement of the educators by gaining experience. At the end of this program, the covered long term impact will present: 1.) increase of knowledge and competences of educators (covered during every stage of project duration) 2.) creation of 4 different training packages, available through the e-learning portal, that include both theoretical background and hands-on practical exercises (covered by O1-O4 output) 3.) a well-organised accumulated knowledge covering individual topics of HPC in Engineering and Data science (covered by the last output O5) available through an e-learning portal and can be gradually introduced into current HE courses 4.) training courses will enable transfer of knowledge to students already during the project duration (4 trainings, at each 7 participants from each project member, altogether 112 participants)
The main goals that the SCtrain project wanted to achieve through its implementation are summed as: - implementation of e-learning portal; with testing and updating through training events - gathering various material for HPC trainings usage with a focus on Engineering and Data Science - development of a comprehensive knowledge base of learning content for HPC - educating the educators involved in the project - supporting highly motivated individuals that have an interest at tackling HPC adaptation for STEM - cross border exchange of skill sets in the field of HPC within the Central European region - development of methodological approach for various topics in the field of HPC - development and improvement of hands-on approach for the training program. - development of a educational platform and the training program for the field of HPC In the last few years the needs of most of our main goals have recognised on EU level and several projects have been funded under the EuroHPC framework to tackle these goals individually.
The main objective of the Erasmus+ project SCtrain was to raise the level of competence in the field of Engineering and Data Science using High-Performance Computing (HPC), also called super-computing. To achieve this, the project has addresses three main priorities: - Tackling skills gaps and mismatches; the need was addressed throughout the duration of the project by carefully chosen topics for our objectives O1-O5. - Supporting individuals in acquiring and developing basic skills and key competences; the project focused on raising the level of competences of involved individuals in the Science, Technology, Engineering, Mathematics (STEM) field with HPC adaptation. - Supporting educators, educational leaders, and support staff; the proposed aim of advancement in HPC's knowledge was achieved by providing more adaptive teaching and training styles, making the established courses more future-orientated. It must be noted that the need for the digitization of HE and the inclusion of the e-learning platform for the teaching aid was highlighted in the project proposal, proven to be of high importance during the Covid-19 pandemic and nowadays presents the usual way of distribution of teaching material to students in the HE.