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.
Gain skills that present a knowledge gap in current HE system, enabling future competitiveness in the fields of Engineering and Data Science.
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 as a tool of tommorow
Our training weeks
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.
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.
Presented topics: Tensorflow and Keras; Parallelism; Horovod; Data Pipeline; Tensorflow Dataset Recommendations; Demonstration of Multi-node/-GPU Examples using Tensorflow; Singularities. Data …
Overview of several topics: Heterogeneous Parallel Computing; GPU Architecture; CUDA Programming; Multi-GPU programming; Multi-Dimensional Grids; Thread Execution; CUDA Memories; Global …
OpenMP Introduction: comparison with MPI approach; Explaining data sharing attributes, worksharing constructs, SIMD management and OpenMP Tasks. Introduction to OpenMP …
Introduction to more intermediate/advanced MPI topics MPI such as groups and communicators, virtual topologies and derived datatypes. Introduction to the …
Introduction to OpenFOAM Finite Volume Toolbox with presentation of geometry management, meshing, different solvers, data sampling, plotting during calculations and …
About the massively parallel open-source simulation tool ESPRESO, which uses the finite element tearing and interconnecting domain decomposition method to …
Understanding the difference between CPU and GPU, emphasizing the advantages of utilizing GPUs. Explaining heterogeneous programming and the basics for …