Course Duration Dates
Syllabus: Introduction to Digital Humanities; Overview of Data Sets; Introduction to GRACE; Data Analytics & Visualisation With GRACE; Handling Data: Advanced Features; Hands-on session.
10,5 h 29-30.07.2021
Syllabus: Training session comprising the setup of the computing environment using environment modules, software compilation, SLURM work manager on the user perspective, job submissions. Hands-on session.
4 h 15.09.2021 06.12.2021
Syllabus: Introduction (Terminology; Parallelization, load balancing; Evaluating program performance; Architectures (Distributed memory, Shared memory, Hybrid systems); Parallel programming (Message passing, MPI; Multithreading, OpenMP; Accelerators, OpenACC); Debugging and Parallel program performance analysis.
18 h 06-08.10.2021
Syllabus: Storage filesystems; I/O strategies (one process, task-local files, shared files) and workflow; Parallel I/O software stack; MPI I/O; Portable data formats (HDF5, parallel NetCDF4).
12 h 27-28.10.2021
Syllabus: Fundamental issues; Agents; Search Strategies for single agent problems. Advanced Search Strategies. Knowledge and Reasoning. Natural computing.
18 h 17-19.11.2021
Syllabus: Introduction to code profiling and refactoring; Profiling tools; Refactoring tools and software; Refactoring analysis; Acceleration techniques; Practical examples using Scalasca, Score-P, Vampir.
18 h 14-16.12.2021
Syllabus: Cluster management utilities, setup of compute and storage nodes, SLURM installation and configuration, accounting and resources limits configuration, environmental software installation, administration tools, e.g., pdsh, clush. Parallel filesystems, e.g., Lustre, BeeGFs.
24 h 08-11.02.2022
Syllabus: Overview of distributed and shared memory models. The Fortran 2008 coarray model; Data distribution through coarrays; Synchronization (sync images, critical sections, sync memory, lock variables, atomic updates); Linear mapping across images; Multiple co-dimensions; Allocatable coarrays; I/O conventions in coarray Fortran.
24 h 08-11.03.2022
Syllabus: Parallel models; Message passing interface – MPI; Multithreading, OpenMP; Debugging and Parallel program performance analysis. Hands-on activities
18 h 11-13.04.2022
“High performance computing with Julia”
Syllabus: Julia overview; Variables, types and operations; Functions, modules; Profiling and optimisation; Distributed-memory parallel programming; Bindings to other programming languages and HPC libraries; Interfaces to GPUs.
18 h May 2022
“High performance computing with Python” (ERASMUS+)
Syllabus: Interactive parallel programming with Ipython; Profiling and optimisation; High-performance NumPy and SciPy, numba; Distributed-memory parallel programming with Python and MPI; Bindings to other programming languages and HPC libraries; Interfaces to GPUs.
18 h June 2022
“High performance data analytics”
Syllabus: Introduction to scientific data management and analytics; Big Data in HPC: High-performance data management; Analytics workflows; Open-source High Performance Data Analytics tools; Data Processing using CDO; Introduction to data visualization using ParaView; Visualization workflows.
30 h July 2022
“Introduction to high performance visualization” (ERASMUS+)
Syllabus: Visualization of extreme-scale data; Flow visualization; Large-scale image and volume processing Task; Visualization software.
24 h September 2022
“Advanced programming with Fortran 2018”
Syllabus: Overview of Fortran 2003/2008. Fortran 2018 features; Object-based and object-oriented programming; Advanced I/O; Container types; Parameterised derived types; Interoperation with C; Introduction to Coarray programming.
24 h November 2022