Dr. Martin Lanser, Mathematical Institute

[Lecture] Introduction to High-Performance Computing

The field of high-performance computing (HPC) deals with the efficient and rapid execution of large-scale simulations on modern supercomputers. The lecture “Introduction to High-Performance Computing” covers the theoretical and practical fundamentals of HPC and parallel scientific computing. It begins by examining current parallel computer architectures, whose structure gives rise to the need for two different types of parallelism (shared memory and distributed memory). Following basic computational perations such as matrix-vector and matrix-matrix multiplications, complex parallel numerical methods for solving systems of linear equations are developed. Speedup, efficiency, and parallel scalability are introduced as metrics for the quality of the algorithms. For practical implementation, introductions are provided to the concept of message passing using MPI as well as to shared-memory parallel programming with OpenMP. Additionally, various software packages are presented that can be used for efficient parallel scientific computing.

Prof. Dr. Stefan Wesner with Dr. Lutz Schubert and Robert Keßler, Institute of Computer Science

[Lecture] Compute Continuum

Modern computing has moved away from the desktop computer to the cloud, where resources and data are shared alike. Yet the Cloud computing paradigm suffers from the scope and complexity of modern compute scenarios, where data may reside anywhere, be produced and consumed anytime in any amount, and where users are mobile and distributed all over the world. To reduce the load on servers and the network, Fog and Edge computing were introduced - forms of distributed computing with flexible and variable allocation and load. This course will introduce the concept of the compute continuum, which aims at executing distributed applications flexibly over any infrastructure. The goal is to adapt immediately to different usage contexts. The compute continuum aims at scenarios arising from connected smart homes, smart cities, global logistic networks etc.

Within this lecture, we will investigate the relevant technologies to realise such an environment, and when it can be used, as well as its obstacles. The lecture is essentially segmented into three parts: The first part focuses on the hardware layer, including equally the type of processors, embedded system architectures and their connectivity. In the second part we will talk about the main principles of distributed computing, including how data is distributed and processed, and which use case criteria are fulfilled how. The third part is focusing on adaptive execution in the compute continuum, that includes embedded Operating Systems, virtualisation and containerisation.