Description: This course gives beginner programmers an introduction to parallel programming.
Parallel programming describes the breaking down of a larger problem into smaller steps. Instructions are delivered to multiple processors, which will execute necessary calculations in parallel – hence the name.
On this course, you will explore the fundamentals of parallel programming using C, C++, Python, Fortran, CUDA/OpenCL or similar programming languages.
Language: Slovene or English (depending on registered people).
Maximum number of participants: 30
Location: Faculty of Mechanical Engineering, Aškerčeva cesta 6, 1000 Ljubljana, Slovenia (see timetable for room numbers).
|Description:||He is an assistant professor at ULFME and is well qualiﬁed for several HPC related topics. He is a qualiﬁed trainer from the HLRS train-the-trainers program and was the key developer of PRACE MOOC Managing Big Data with R and Hadoop. He has been the leader of PRACE Summer of HPC trainings in 2014, 2015, 2016, 2017, 2018 and 2019. He is also Slovenian holder of several national and international projects.|
|Description:||He is an associate professor at ULFME with a long track of teaching duties at university (a former Dean at Faculty of Information studies in Novo Mesto, Slovenia). With mathematical background he is a specialist in Big Data methods and their implementation in Hadoop and RHadoop. Beside this he is a well experienced with creating and implementing parallel algorithms for mathematical optimization problems. He is one of the leading educators in PRACE MOOC Managing Big Data with R and Hadoop. He is also Slovenian holder of several national and international projects.|
|Description:||He is a PhD student at the Faculty of Mechanical Engineering at the University of Ljubljana and a member of Plasma Engineering Group at LECAD laboratory. He is currently working on his PhD thesis titled “A Framework for Computation of Heat Loads on ITER First Wall Panel” under the supervision of dr. Leon Kos and dr. Richard Pitts from ITER Organisation. Aim of this PhD thesis is to develop synthetic diagnostic temperature distribution on first wall panels with the help of Elmer finite element package based on distribution of heat flux from SMARDDA code. He has an extensive knowledge of Smiter code, Elmer FEM package, CAD modelling and meshing. In recent years he contributed to SmiterGUI code and worked on benchmarking SMARDDA code against PFCFLUX. He has experience in Matlab, Python and Fortran90.. He will contribute to the code refactoring schemes of all project supported codes.|
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