Projects from Prof. Dr. Christian Plessl
National Research Data Infrastructure for and with Computer Science
The main goal of the consortium NFDIxCS is to identify, define and finally deploy services to store complex domain specific data objects from the specific variety of sub-domains from Computer Science (CS) and to realize the FAIR principles across the board. This includes to produce re-usable data objects specific to the various types of CS data ...
Duration: 01/2023 - 12/2028
Funded by: DFG
EKI-App: Energy-efficient artificial intelligence in the data center by approximating deep neural networks for field-programmable gate arrays
The goal of the project is to increase the energy efficiency of AI systems for DNN inference by approximation methods and mapping on high-performance FPGAs. By adapting, further developing and providing a software tool chain based on the open source tool FINN for the automated, optimized and hardware-adapted implementation of DNNs on FPGAs and ...
Duration: 01/2023 - 12/2025
Funded by: BMUV
FPGA4XPCS: Efficient Real-Time Computation of Autocorrelation Functions for X-Ray Photon Correlation Spectroscopy using FPGAs
Dynamical processes in condensed matter are of importance in various scientific disciplines. X-ray photon correlation spectroscopy (XPCS) is a coherent synchrotron X-ray scattering technique that allows measurements of dynamical phenomena in condensed matter over a wide range of length and time scales. The length scales currently accessible with ...
Duration: 10/2022 - 09/2025
Funded by: BMBF
SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems
Current systems that incorporate AI technology mainly target the introduction phase, where a core component is training and adaptation of AI models based on given example data. SAIL’s focus on the full life-cycle moves the current emphasis towards sustainable long-term development in real life. The joint project SAIL addresses both basic research ...
Duration: 08/2022 - 07/2026
Funded by: MKW NRW
Green IT: Accurate calculations with inaccurate but energy-efficient computers
Prof. Dr. Christian Plessl, Lehrstuhl für Hochleistungs-IT-Systeme, und Prof. Dr. Thomas D. Kühne, Lehrstuhl für Theoretische Chemie, erhielten 2018 für ihr Projekt „Green IT: Exakte Berechnungen mit ungenauen, aber energieeffizienten Rechnern“ den Forschungspreis der Uni Paderborn. Ziel des interdisziplinären Projekts war es, die Machbarkeit des ...
Duration: 01/2018 - 01/2020
HighPerMeshes: Domain-specific programming and target-platform-aware compiler infrastructure for algorithms on unstructured grids
HighPerMeshes is a collaborative research project funded by German Ministry of Education and Research (BMBF). The project comprises a consortium of four funded partners and one associated partner and is coordinated by the Paderborn Center for Parallel Computing at Paderborn University.
Duration: 04/2017 - 03/2020
Funded by: BMBF
Contact: Bernard Bauer
Hochleistungsrechner Noctua in Paderborn
Die computergestützte Modellierung, Simulation, Analyse und Optimierung ist in den Natur- und Ingenieurwissen-schaften für den Gewinn wissenschaftlicher Erkenntnisse unverzichtbar. Für die stetig wachsende Gruppe von interdisziplinär arbeitenden Forscherinnen und Forschern der Universität Paderborn ist die Verfügbarkeit einer leistungsfähigen ...
Duration: 01/2017 - 12/2017
Funded by: DFG
PerficienCC: Performance and Efficiency in HPC with Custom Computing
To improve the energy efficiency of HPC systems they are increasingly augmented with hardware accelerators. The use of accelerators does however fall behind their fundamental performance and efficiency potential. In the PerficienCC project we work at closing this gap in cooperation with computational scientists that are customers of the HPC ...
Duration: 01/2016 - 05/2020
Funded by: DFG
InnoArchIT: Innovative Hardware und Software Architekturen durch Industrial IT
Innovationsprojekt: Kleiner Chip – großer EffektUnsere Volkswirtschaft setzt auf Hightech-Produkte wie z.B. computerbasierte Maschinensteuerungen. Diese haben meistens nur kurze Produktlebenszyklen und geringe Losgrößen. Daher müssen die Maschinen und automatisierten Anlagen zur Herstellung dieser Produkte immer wieder schnell für neue ...
Duration: 10/2014 - 06/2017
Funded by: BMBF
Contact: Carlos Paiz Gatica
SAVE: Self-Adaptive Virtualisation-Aware High-Performance/Low-Energy Heterogeneous System Architectures
Duration: 09/2013 - 08/2016
Funded by: European Commission, FP7 STREP Project