As a German national supercomputing center, HLRS offers world-class high-performance computing systems and expertise that can support the most computationally demanding simulation projects. Our HPC resources enable scientists to conduct research at the frontiers of science, private companies to develop globally competitive products, and public administration to make data-informed decisions.
With a peak performance of 26 petaflops, Hawk is among Europe's fastest HPC systems and is optimized to provide large-scale computing power for complex simulations. It also includes a GPU partition to support hybrid HPC / AI applications.
This standard PC cluster is continually adapted to meet increasing demands and provide requirement-optimized solutions, including CPU, GPU, and vector computing components.
HLRS's high-performance storage system is designed to safely manage and archive petabytes of data generated by large-scale simulation projects.
Programming high-performance computing systems requires special expertise. HLRS's comprehensive HPC training and user support programs help our system users to use them more effectively.
Taught by experienced HPC professionals, our courses can help you develop the skills to program highly parallel computing clusters like Hawk confidently and effectively.
Our staff works closely with new and experienced system users to optimize their codes and enable new applications of HPC.
Are you a scientist or engineer who is interested in using our computing systems? Click here to learn more about getting access.
HLRS facilitates access to commonly used ISV and open source application software packages for science and engineering. Our systems are also installed with tools, compilers, and libraries to support users who bring their own codes.
Staff scientists at HLRS participate in funded research projects that are addressing key technical problems facing the future of high-performance computing. These activities include efforts to scale codes to larger supercomputing architectures, improve data management procedures for large-scale datasets, and enable better integration of HPC with other computing infrastructures. These activities contribute to the continuing evolution of high-performance computing and enable us to build expertise that we pass on to our system users.
This project aims to identify and reduce bottlenecks in performance scaling for computational fluid dynamics applications on massively powerful HPC systems, with emphases on preprocessing, postprocessing, and I/O.
ChEESE is developing European flagship codes for upcoming pre-exascale and exascale supercomputing systems, focusing on Earth science fields such as computational seismology, magnetohydrodynamics, physical volcanology, tsunamis, and earthquake monitoring.
This project aims to enable the creation of disaggregated computing infrastructures for processing and storing data close to their end users, while integrating edge computing, cloud computing, and high-performance computing infrastructures.
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