Introduction to Scientific Computing and HPC

Presented by Julian Kunkel, University of Reading

This talk introduces the evening and gives a short introduction to Scientific Computing and HPC.

In public data centers and in computational science, open-source software plays a key role to create a productive environment for researchers.

Computational science is the modeling and simulation of the laws of nature within computer systems that offer a well-defined environment for experimental investigation. Models for climate, protein folding, or nanomaterials, for example, can be simulated and manipulated at will without being restricted by the laws of nature, and scientists no longer have to conduct time-consuming and error-prone experiments in the real world. This method leads to new observations and understandings of phenomena that would otherwise be too fast or too slow to comprehend in vitro. The processing of observational data like sensor networks, satellites, and other data-driven workflows is yet another challenge as it usually dominated by the input/output of data.

Complex climate and weather simulations can have 100.000 to million lines of codes and must be maintained and developed further for a decade at least. Therefore, scientific software is mostly open-source, particularly for large scale simulations and bleeding-edge research in a scientific domain.