Currently we are working on the following funded projects.


NFDIxCS (2023 – 2028)

The diversity and complexity of domain-specific data structures introduced by the variety of subdisciplines in computer science pose a challenge for the scientific community to achieve reusability when storing research data. The NFDIxCS consortium aims to identify, define, and deploy services to store domain-specific data by applying the FAIR principles and storing research data alongside related metadata, its corresponding software, context, and execution instructions, assembling all services in a cooperative and interoperable infrastructure.

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ENSIMA (2022 – 2025)

The capabilities of modern computer simulations have the potential to change the industrial product design process by optimizing a vast number of design parameters while saving resources in production. For the optimization of the process, however, substantial amounts of computing time on HPC systems are often necessary. In this project, we apply AI methods to improve and accelerate the determination of design parameters. At the same time, we use approximate and heterogeneous computing to reduce the processing time of the steps of the simulation process.


ADMIRE (2021 – 2024)

The flat storage hierarchies found in classic HPC architectures no longer satisfy the performance requirements of the growing share of data-processing applications. At the same time, the shift towards data-centric computing is accompanied by a disruptive change of the underlying storage technology towards multi-tier storage hierarchies with fast non-volatile memory with the potential to remove this bottleneck. The objective of this project is the development of an intelligent I/O stack for such architectures that helps exploit their full performance potential. Our focus is the proper balance between computational and I/O requirements.

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DEEP-SEA (2021 – 2024)

This project will deliver the programming environment for future European exascale systems, adapting all levels of the software stack – including low-level drivers, computation and communication libraries, resource management, and programming abstractions with associated runtime systems and tools – to support highly heterogeneous compute and memory configurations and to allow code optimisation across existing and future architectures and systems. We contribute tools to map applications onto modular heterogeneous supercomputers.

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NHR4CES (2021 – 2030)

A national high-performance computing center for computational engineering. In this project, RWTH Aachen and TU Darmstadt join forces to combine their existing strengths in HPC applications, algorithms and methods, and the efficient use of HPC hardware. NHR4CES aims to create an HPC ecosystem combining best practices of HPC and research data management. The focus of NHR4CES will be on engineering and materials science, and engineering-oriented physics, chemistry, and medicine. Our contribution lies in the area of parallelism and performance.

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ExtraNoise (2021 – 2024)

The key to understanding and ultimately improving the performance of HPC applications is performance measurement. Unfortunately, many HPC systems expose their jobs to substantial amounts of noise, leading to significant run-to-run variation. This makes performance measurements generally irreproducible, heavily complicating performance analysis and modeling. In this project, we develop methods and tools to make performance measurement and analysis more noise resilient.

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