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DTSTART;TZID=Europe/Berlin:20250424T160000
DTEND;TZID=Europe/Berlin:20250424T180000
DTSTAMP:20250422T081608Z
CREATED:20250422T081547Z
LAST-MODIFIED:20250422T081608Z
UID:1687-1745510400-1745517600@www.hsu-hh.de
SUMMARY:Seminar Series & HPC Café: Computation & Data
DESCRIPTION:Scientific Talk (4:00 PM to 5:00 PM): Julio Gutiérrez (HSU) \n\n\n\nStudy of nozzle influence on aerosol deposition (AD) by using 3D CFD simulationsIn aerosol deposition\, fine ceramic powders in sizes of less than typically 5 μm are deposited as a coating at room temperature. Aerosol deposition must be performed under a vacuum to apply such fine powders and avoid bow shock effects. According to experimental results\, coating formation by aerosol deposition only occurs if particle velocities exceed a material-specific threshold velocity. Thus\, knowledge of attained particle velocities over acceleration in the nozzle and under the expansion into a vacuum is essential for deriving conditions for successful deposition. In the present study\, 3D-CFD simulations were used to investigate the key geometrical variables in powder acceleration. Three different nozzle geometries were investigated: a convergent nozzle\, a convergent-divergent nozzle\, and a convergent nozzle followed by a constant cross-section toward the exit. In addition\, these three nozzle geometries were optimized to maximize the particle impact velocity. The results show that the convergent-divergent nozzle supplies the highest particle velocities within this comparison. The particle velocities attained by the other nozzles are substantially lower but could be improved by geometry. \n\n\n\nHPC Café (5:00 PM to 6:00 PM): Piet Jarmatz (HSU)\n\n\n\nImmediately after the talk\, the HPC Café will take place. \n\n\n\nWhat is the HPC Café? The goal of this new format is peer-to-peer learning within the community. At each session\, an expert from the discipline will be present and available to answer questions. All target groups are warmly invited – both those with prior knowledge in the field of HPC or related disciplines and those who are just starting out.This collaborative exchange aims to discuss direct questions and application issues in the field of HPC and related disciplines\, and to jointly search for solutions. Feel free to bring your questions and concerns as well as a laptop and a cup of coffee with you. \n\n\n\nThis time\, the expert Piet Jarmatz (Head of HPC Lab) from the Chair of High Performance Computing will be available to answer your questions and discuss with you in a peer-to-peer format.
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-hpc-cafe-computation-data/
LOCATION:H1\, room 109\, Holstenhofweg 85\, Hamburg\, 22043
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20241030T160000
DTEND;TZID=Europe/Berlin:20241030T180000
DTSTAMP:20241016T125118Z
CREATED:20241016T125024Z
LAST-MODIFIED:20241016T125118Z
UID:1542-1730304000-1730311200@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Katharina Goldberg (HSU) – Legal Introduction to the AI ActThe AI Act (Regulation (EU) 2024/1689) was adopted by the European Parliament and the Council on 13 June 2024. This regulation was preceded by many years of preparation\, discussions and lobbying by various interest groups. The result is a 144-page regulation that does not convince all legal experts and is currently the subject of much debate in specialist circles.This presentation will provide an overview of the basic regulatory structure of the AI Act\, its (future) areas of application\, the legal consequences of categorising AI systems into the various risk groups and the new players for AI governance created by the AI Act.The term “AI system” will be discussed first. The regulation has created a new definition here\, which will be used in all EU member states in the future to define technical systems. In addition\, the AI Regulation refers to the European standardization organizations CEN\, CENELEC and ETSI\, which will be responsible for formulating technical standards for the use of AI in the future. From a legal perspective\, this is problematic because it means that important (definitional) decisions are taken away from the democratic legislator and entrusted to expert bodies.For the regulation of the different types of AI\, the regulation distinguishes between AI applications with an unacceptable risk\, which are generally prohibited\, and those of different risk categories\, which are generally permitted. The prohibited category includes AI applications that manipulate human behaviour\, use real-time remote biometric identification in public places and are used for social scoring. AI applications are on the other hand permitted in different graded risk categories: High-risk applications\, General-purpose AI\, Limited Risk AI and Minimal Risk AI. The use of AI in these risk groups is subject to graduated requirements (risk-based approach). The presentation will present these distinctions and outline their legal consequences.A new governance structure for AI in the EU will also be created. Future actors are the AI Office\, the European Artificial Intelligence Board\, the Advisory Forum and the Scientific Panel of Independent Experts. The member states must also appoint competent national authorities. The presentation will also address the tasks of these actors. \n\n\n\n\n\n\n\nFelix Gehlhoff – Working on the Edge: Harnessing AI at the Frontier of Professional InnovationsThis presentation delves into the expanding role of AI across various professional and creative domains. The discussion will cover the broad capabilities and potential risks of integrating AI into modern practices. Key points will include the “jagged frontier” of AI’s capabilities\, advocating for a proactive exploration of AI applications to fully leverage its potential while being mindful of its limitations. The analogy of treating AI like a person will be highlighted\, emphasizing AI’s proficiency in language-based tasks and its implications for educational contexts. This perspective invites us to reconsider how AI can facilitate active and engaging learning opportunities.
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data/
LOCATION:H1\, room 110\, Holstenhofweg 85\, Hamburg\, HH\, 22043\, Germany
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240424T160000
DTEND;TZID=Europe/Berlin:20240424T180000
DTSTAMP:20240421T135704Z
CREATED:20240421T135703Z
LAST-MODIFIED:20240421T135704Z
UID:1469-1713974400-1713981600@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data on Wed\, 24.04.2024\, 16:00-18:00
DESCRIPTION:Location:on-site: complex room 1006digital: MS Teams (link shared via e-mail) \n\n\n\nFabian Dethof: Simulating “semi-guided” elastic wave propagation in concrete – understanding Impact Echo dataThe usage of low-frequency signals and easy data acquisition make Impact Echo a widely applied NDT method in the field of civil engineering ever since its introduction in the 80’s. However\, the physical principle of the method was not fully understood until 2005. Numerical simulations are used to better understand acquired datasets and improve data evaluation by introducing new evaluation procedures and using existing machine learning methods. \n\n\n\nLizzie Neumann: Confounder-adjusted Covariances of System Outputs and Applications to Structural Health MonitoringAutomated damage detection is integral to structural health monitoring (SHM) systems. However\, changes in the data result not only from damage but also from environmental or operational influences. Consequently\, it is necessary to determine the confounding factors and remove their effects from the measurements or extracted features. Methods used so far\, however\, neglect potential changes in higher-order statistical moments\, although the output covariances are essential for generating reliable diagnostics for damage detection. We propose an approach that explicitly quantifies changes in the covariance using conditional covariance matrices\, and we apply the method toreal-world bridge data. Our results show that temperature changes affect the covariances of sensor measurements and natural frequencies. By combining our new approach with standard methodsfor damage detection\, we can generate more reliable diagnostic values and fewer false alarms. 
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data-on-wed-24-04-2024-1600-1800/
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240327T160000
DTEND;TZID=Europe/Berlin:20240327T180000
DTSTAMP:20240311T140350Z
CREATED:20240311T140349Z
LAST-MODIFIED:20240311T140350Z
UID:1395-1711555200-1711562400@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data on Wed\, 27.03.2024\, 16:00-18:00
DESCRIPTION:Locationon-site: Mensa Room 0001digital: MS Teams (link shared via e-mail) \n\n\n\nSebastian Brandstäter (UniBw M): Sensitivity Analysis for Biomechanical Models \n\n\n\nRuben Horn (HSU): Energy Efficiency of Molecular(-Continuum) Simulations
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data-on-wed-27-03-2024-1600-1800/
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240228T160000
DTEND;TZID=Europe/Berlin:20240228T180000
DTSTAMP:20240214T151548Z
CREATED:20240205T094810Z
LAST-MODIFIED:20240214T151548Z
UID:1382-1709136000-1709143200@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data on Wed\, 28.02.2024\, 16:00-18:00
DESCRIPTION:Location: Mensa-Room 0001; digital participation (link shared via e-mail) \n\n\n\nAli Khalifa: Neural Network-Based Multiscale Modeling of Deagglomeration due to Wall Impact and CollisionsPredicting the evolution of micron-sized particle system  in fluid flows is crucial for natural processes and industrial applications like pharmaceuticals. Fully-resolved simulations are costly due to scale variations. Hence\, data-driven approaches offer an attractive alternative. This study enhances an Euler-Lagrange method with neural-network models for deagglomeration from collisions and wall impacts\, integrated into LES-based simulations. Tested in various turbulent flows\, such as funnel-duct dispersers and bend pipes\, this approach provides cost-effective predictions. \n\n\n\nDenis Kramer: Designing Functional Materials: Dream\, Predict\, Synthesise\, Characterise\, Repeat
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data-on-wed-28-02-2024-1600-1800/
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240131T040000
DTEND;TZID=Europe/Berlin:20240131T060000
DTSTAMP:20240117T121613Z
CREATED:20240117T121518Z
LAST-MODIFIED:20240117T121613Z
UID:1345-1706673600-1706680800@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data on Wed\, 31.01.2024\, 16:00-18:00
DESCRIPTION:Location: Mensa-Room 0001; digital participation (link shared via e-mail) \n\n\n\nVolker Gravemeier: A Multiphysics Computational Method for Coupled Simulations of Tribological Systems \n\n\n\nA novel multiphysics computational method for thermal elastohydrodynamic lubrication and results obtained from applying it to tribological systems will be presented. It enables detailed insights beyond the ones having been achievable to date. For such systems\, it is typically both mandatory and challenging to consider all nonlinear effects of the physical fields as well as their mutual interactions. Only this way\, it is ensured that one obtains reliable predictive simulation results eventually. \n\n\n\nJan L. Augustin: SmartShip: AI-Driven Maritime Rescue – Enhanced Readiness and Detection in Search Operations \n\n\n\nThe SmartShip project merges AI capabilities in two critical areas for maritime rescue. First\, it employs an advanced multimodal camera system\, utilizing deep learning for precise detection of boats and individuals in distress. Second\, it integrates anomaly detection models analyzing sensor time-series data to ensure the constant readiness of rescue cruisers. This dual approach supports rapid deployment and efficient rescue operations\, epitomizing the synergy of AI and maritime safety.
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data-on-wed-31-01-2024-1600-1800/
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231213T160000
DTEND;TZID=Europe/Berlin:20231213T180000
DTSTAMP:20231212T141804Z
CREATED:20231009T174607Z
LAST-MODIFIED:20231212T141804Z
UID:1213-1702483200-1702490400@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data on Wed\, 13.12.2023\, 16:00-18:00
DESCRIPTION:Valentina Pessina (UniBw M): Modeling Rarefied and Continuous High Angle-of-Attack Hypersonic. Reentry into Martian Atmosphere with Open-Source Software \n\n\n\nMaximilian Maigler (UniBw M): Coupled PIC-DSMC and Molecular Dynamics Modeling of Radio-Frequency. Gridded Ion Thruster Erosion \n\n\n\n \n\n\n\nJoining the event online will be possible via MS Teams: https://teams.microsoft.com/l/meetup-join/19:Vp54PUGbuDskc_Y5YooVbR5uKIY-BPuzvyxZtSeGg5Q1@thread.tacv2/1668524366704?context=%7B%22Tid%22:%225832f73f-b0fa-45a0-80d9-7e32bd7fa822%22\,%22Oid%22:%226003e630-5d1e-4ccb-a8ab-e5d81b1bf8b1%22%7D
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data-on-wed-13-12-2023-1600-1800/
LOCATION:Container Building C2/S2 (near  Grandplatz)\, room 113-115\, Holstenhofweg 85\, Hamburg\, 22043
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231129T160000
DTEND;TZID=Europe/Berlin:20231129T180000
DTSTAMP:20231024T122808Z
CREATED:20231009T180306Z
LAST-MODIFIED:20231024T122808Z
UID:1218-1701273600-1701280800@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data on Wed\, 29.11.2023\, 16:00-18:00
DESCRIPTION:Therese Rosemann & Yannis Schumann (HSU): Digital  Competences and Digital Learning Behavior in Higher Education – Generation of individualized Feedback in a Longitudinal Study (DigiTaKS* and hpc.bw) \n\n\n\nSergej Grednev (HSU): Prediction of Structure-Property Relationships in Cellular Materials
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data-on-wed-29-11-2023-1600-1800/
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231025T160000
DTEND;TZID=Europe/Berlin:20231025T180000
DTSTAMP:20231025T143054Z
CREATED:20231009T180448Z
LAST-MODIFIED:20231025T143054Z
UID:1220-1698249600-1698256800@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data on Wed\, 25.10.2023\, 16:00-18:00
DESCRIPTION:Link to eventLink for online participation
URL:https://www.hsu-hh.de/hpccp/event/seminar-series-computation-data-on-wed-25-10-2023-1600-1800/
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230525T160000
DTEND;TZID=Europe/Berlin:20230525T180000
DTSTAMP:20230515T143415Z
CREATED:20230515T143415Z
LAST-MODIFIED:20230515T143415Z
UID:1024-1685030400-1685037600@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Gerhard Wellein: Application Knowledge Required: Performance Modeling for Fund and Profit \n\n\n\nGerhard Wellein is a Professor for High Performance Computing at the Department for Computer Science of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and holds a PhD in theoretical physics from the University of Bayreuth. He is a member of the board of directors of the German NHR-Alliance which coordinates the national HPC Tier-2 infrastructures at German universities. As a member of the scientific steering committees of the Leibniz Supercomputing Centre (LRZ) and the Gauss-Centre for Supercomputing (GCS) he is organizing and surveying the compute time application process for national HPC resources. Gerhard Wellein has more than twenty years of experience in teaching HPC techniques to students and scientists from computational science and engineering\, is an external trainer in the Partnership for Advanced Computing in Europe (PRACE) and received the “2011 Informatics Europe Curriculum Best Practices Award” (together with Jan Treibig and Georg Hager) for outstanding teaching contributions. His research interests focus on performance modelling and performance engineering\, architecture-specific code optimization\, novel parallelization approaches and hardware-efficient building blocks for sparse linear algebra and stencil solvers. \n\n\n\nAxel Klawonn: What can machine learning be used for in domain decomposition methods? \n\n\n\nProf. Dr. Axel Klawonn heads the research group on numerical mathematics and scientific computing at the Universität zu Köln. The group works on the development of efficient numerical methods for the simulation of problems from computational science and engineering. This comprises the development of efficient algorithms\, their theoretical analysis\, and the implementation on large parallel computers with up to several hundreds of thousands of cores. A special focus in the applications is currently on problems from biomechanics/medicine\, structural mechanics\, and material science. The research is in the field of numerical methods for partial differential equations and high performance parallel scientific computing\, including machine learning.
URL:https://www.hsu-hh.de/hpccp/event/cd2305/
LOCATION:Container Building C2/S2 (near  Grandplatz)\, room 113-115\, Holstenhofweg 85\, Hamburg\, 22043
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230427T150000
DTEND;TZID=Europe/Berlin:20230427T163000
DTSTAMP:20230427T103730Z
CREATED:20230417T072244Z
LAST-MODIFIED:20230427T103730Z
UID:1010-1682607600-1682613000@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Philipp Marienhagen: Calculation of equation-of-state data in many-particle systems consisting of hard-anisotropic particles \n\n\n\nYannis Schumann: Distinguishing Molecular Tumor Subgroups Using Deep Learning
URL:https://www.hsu-hh.de/hpccp/event/cp2304/
LOCATION:Container Building C2/S2 (near  Grandplatz)\, room 113-115\, Holstenhofweg 85\, Hamburg\, 22043
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230330T143000
DTEND;TZID=Europe/Berlin:20230330T160000
DTSTAMP:20230330T123433Z
CREATED:20230119T093907Z
LAST-MODIFIED:20230330T123433Z
UID:522-1680186600-1680192000@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Frederike Vogel (HSU/Statistics and Data Science): Supervised learning for analyzing movement patterns in a virtual reality experiment \n\n\n\nMarcel Eckert (HSU/Computer Engineering): How FPGAs can speed up algorithms by 2 examples
URL:https://www.hsu-hh.de/hpccp/event/cd2303/
LOCATION:H1\, room 308\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230223T143000
DTEND;TZID=Europe/Berlin:20230223T160000
DTSTAMP:20230215T192315Z
CREATED:20230119T093632Z
LAST-MODIFIED:20230215T192315Z
UID:517-1677162600-1677168000@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Nils Margenberg (HSU/Numerical Mathematics): Hybrid Finite Element/Deep Neural Networks Methods for Accelerating Fluid-Dynamics SimulationsLouis Viot (HSU/High Performance Computing): New developments within the Macro/Micro Coupling software MaMiCo for highly parallelized multiscale flow simulation
URL:https://www.hsu-hh.de/hpccp/event/cd2302/
LOCATION:H1\, room 308\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230126T143000
DTEND;TZID=Europe/Berlin:20230126T160000
DTSTAMP:20230215T192432Z
CREATED:20230119T094108Z
LAST-MODIFIED:20230215T192432Z
UID:525-1674743400-1674748800@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Chaitanya Kandekar (HSU/Structural Analysis): A Thermo-hydro-mechanical modelling for concrete under fire loads \n\n\n\nMaria Krantz (HSU/Computer Science in Mechanical Engineering): Generating Data for the Training of Machine Learning Algorithms for CPPS \n\n\n\n\n\n\n\nThe link for online participation is shared via the seminar newsletter.
URL:https://www.hsu-hh.de/hpccp/event/cd2301/
LOCATION:H1\, room 308\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221215T143000
DTEND;TZID=Europe/Berlin:20221215T160000
DTSTAMP:20230203T092346Z
CREATED:20221115T094853Z
LAST-MODIFIED:20230203T092346Z
UID:149-1671114600-1671120000@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Bernd Flemisch (Universität Stuttgart): The open-source simulator DuMux – experiences and practices from 15 years of development \n\n\n\nDuMux is a free and open-source simulator for flow and transport processes in and around porous media written in C++. Its main intention is to provide a sustainable and consistent framework for the implementation and application of porous media model concepts and constitutive relations.To this day\, 25 versions of DuMux have been released with contributions by over 70 people\, mainly located at but not restricted to the Department of Hydromechanics and Modelling of Hydrosystems at the University of Stuttgart. In this talk\, we want to give an overview of the organizational aspects of DuMux: the development and maintenance process\, software quality assurance\, documentation\, tutorials and the integration of new developers. \n\n\n\n\n\n\n\nPowei Huang (Eidgenössische Technische Hochschule Zürich): Reactive transport modeling in aqueous environments using the Nernst-Planck formulation \n\n\n\nIn this seminar\, we discuss the validity of applying the Nernst-Planck (NP) equation to model the transport of ionic species. We compare the simulation results of the NP model to the commonly used single-diffusivity model and benchmark the NP model with reaction-driven flow experiments. Our results show that the NP model is relevant for modeling reactive transport processes with an intricate interplay between diffusion\, reaction\, electromigration\, and density-driven convection.
URL:https://www.hsu-hh.de/hpccp/event/cd2212/
LOCATION:H1\, room 205\, Holstenhofweg 85\, Hamburg\, 22043
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221124T143000
DTEND;TZID=Europe/Berlin:20221124T160000
DTSTAMP:20230203T092353Z
CREATED:20230119T090442Z
LAST-MODIFIED:20230203T092353Z
UID:493-1669300200-1669305600@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Christian Brandlhuber (21 strategies GmbH): Battlefield superiority by enhanced tactics. AI for tactical decision sequences and emergence \n\n\n\nArtificial intelligence is already playing an increasingly important role in the timely evaluation of sensor data and is thus making a significant contribution to improving situational awareness. Future systems\, however\, will go far beyond the ability of pure evaluation and will be able to independently develop tactical behaviour in order to always be one step ahead of the opponent through the intelligent use of their own resources. The lecture presents the possibilities of tactical AI systems that develop emergent behaviour (also called context-aware/consequence-sensitive 3rd wave AI by DARPA) in the areas of Markov decision processes and multi-agent learning based on current results from the dtec.bw project Ghostplay. \n\n\n\n\n\n\n\nAlexander Popp (UniBW M): Scalable computational kernels and linear solvers for FEM-based computational contact mechanics \n\n\n\nTargeting simulations on parallel hardware architectures\, this seminar talk presents scalable computational kernels and linear solvers for mortar finite element methods in computational contact mechanics. Mortar methods enable a variationally consistent imposition of coupling conditions at high accuracy but come with considerable numerical effort and cost. We identify bottlenecks in parallel data layout and domain decomposition that hinder an efficient evaluation and solution and propose a set of computational strategies to restore optimal parallel communication and scalability.
URL:https://www.hsu-hh.de/hpccp/event/cd2211/
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221109T110000
DTEND;TZID=Europe/Berlin:20221109T120000
DTSTAMP:20230203T092356Z
CREATED:20230119T085009Z
LAST-MODIFIED:20230203T092356Z
UID:483-1667991600-1667995200@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Matthias Mayr (UniBw M): Sustainable development of multi-level block preconditioners in Trilinos/MueLu \n\n\n\nIn this talk\, we will summarize our developments of scalable multi-level block-preconditioning methods in the framework of Trilinos/MueLu for the efficient solution of multi-physics phenomena. The simulation of such phenomena plays an important role in various disciplines. To efficiently solve the arising linear systems of equations\, the preconditioners can be tailored to coupled problems\, ranging from volume\, mixed-dimensional to interface coupled scenarios.
URL:https://www.hsu-hh.de/hpccp/event/cd2211s/
LOCATION:Aula\, room 2\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221027T143000
DTEND;TZID=Europe/Berlin:20221027T160000
DTSTAMP:20230203T092400Z
CREATED:20230119T083739Z
LAST-MODIFIED:20230203T092400Z
UID:450-1666881000-1666886400@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Andreas Fink (HSU): HPC for Solving Combinatorial Optimization Problems in Logistics: Challenges and Examples \n\n\n\nWhile HPC is established in engineering and science\, this is not yet the case for solving NP-hard combinatorial optimization problems in business administration (e.g. in logistics). Existing optimization methods for such problems often have a sequential flow logic and thus must be adapted. We will discuss if and how mixed-integer mathematical optimization methods and solvers are already able to exploit parallel computing power and we will consider the parallelization of (meta-)heuristic methods. \n\n\n\n\n\n\n\nBenedikt Hein (HSU): Distributed Deep Reinforcement Learning: How a hundred years of experience can be gathered in one day \n\n\n\nOver the past decade\, Deep Reinforcement Learning has received considerable attention in Artificial Intelligence research. Successful training in Deep Reinforcement Learning generally requires millions of interactions with a simulated environment. The massive parallelization of simulated training environments recently enabled the training of an outstanding game AI for the computer game DOTA. This talk presents the techniques\, principles and goals of this kind of parallelization.
URL:https://www.hsu-hh.de/hpccp/event/cd2210/
LOCATION:H1\, room 205\, Holstenhofweg 85\, Hamburg\, 22043
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220630T150000
DTEND;TZID=Europe/Berlin:20220630T160000
DTSTAMP:20230203T092409Z
CREATED:20230119T082851Z
LAST-MODIFIED:20230203T092409Z
UID:475-1656601200-1656604800@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Speakers: Thomas Döbbert and Martin Holters \n\n\n\nTitle: Digital sensor-2-cloud campus platform \n\n\n\nAbstract: Wireless networks support highly flexible manufacturing processes towards the digitization of industrial production (automation). 5G is currently being marketed as universal solution for future wireless communication. However\, also other wireless technologies are beneficial and are offering energy efficient and cost-effective solutions\, even with battery-powered smart sensor devices. In this project\, features of 5G are also combined with IO-Link Wireless (IOLW) with respect to robustness and latency to realize highly demanding safety applications in industrial environments.
URL:https://www.hsu-hh.de/hpccp/event/cd2206/
LOCATION:H1\, Hörsaal 3\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220602T150000
DTEND;TZID=Europe/Berlin:20220602T160000
DTSTAMP:20230203T092412Z
CREATED:20230119T080741Z
LAST-MODIFIED:20230203T092412Z
UID:470-1654182000-1654185600@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:Speaker: Derek Groen from Brunel University London. Derek is a lecturer in simulation and modeling\, and his research is interdisciplinary\, focusing primarily on multiscale modelling and high-performance computing for various applications. \n\n\n\nTitle: Multiscale Migration Modelling using Supercomputers: enabling agent-based modelling forecasts in a world of messy\, inaccessible\, biased and incomplete data \n\n\n\nAbstract: In this talk I will present the multiscale migration modelling approach that we have developed in my group during the EU-funded HiDALGO CoE project (hidalgo-project.eu). The approach aims to forecast where persons displaced abroad by conflict may arrive. This information is useful to NGOs and other humanitarian organizations as it can enable them to prepare refugee camps in advance\, and at the right level of capacity. We apply an agent-based modelling algorithm to construct the simulations\, and have coupled them to a range of other models and data sources (e.g. weather data\, food security data and conflict generators) to try and produce accurate forecasts. Our approach has been validated against data from ~8 different conflicts\, and it is being tested in a collaboration with the Save The Children NGO. Additionally\, it is currently one of the main simulation approaches used in the ITFLOWS project (itflows.eu). \n\n\n\nAs part of this talk\, I will also present some highlights on (a) executing our approach in parallel on large scale supercomputers\, (b) how we can use sensitivity analysis to guide our development directions\, (c) how we try to cope with the imperfect data that is rife in these contexts and (d) how we are currently working on many-objective optimisation algorithms to make automatic camp site selection possible.
URL:https://www.hsu-hh.de/hpccp/event/cd2205/
LOCATION:H1\, Hörsaal 3\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220428T150000
DTEND;TZID=Europe/Berlin:20220428T160000
DTSTAMP:20230203T092418Z
CREATED:20230119T075829Z
LAST-MODIFIED:20230203T092418Z
UID:465-1651158000-1651161600@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:“Infrastructure Information Modelling: Workflow for an overall model infrastructure embedded in spatial base data” \n\n\n\nJens Bartnitzek (A+S Consult GmbH) \n\n\n\nInfrastructure Information Modelling is an approach which requires rethinking in the sense of cultural shift towards a systematic and partnership-based approach to major projects. Essentials from mathematics\, computer science and civil engineering are necessary for describing the workflow reasonable. The seminar shows in a real world example the process of creating a 3D overall model of an infrastructure facility starting with federal spatial base data. We take a deeper look on the relevant data interfaces and technical workflows. After the inventory model is constructed\, we connect different data from specialized models into the overall model for interdisciplinary use cases. The overall model is for a collaborative “3D planning” with complete information linkage. We show how those use cases can be realized over multiple objects\, connecting multiple data formats based on results from multiple software products.
URL:https://www.hsu-hh.de/hpccp/event/cd2204/
LOCATION:H1\, Hörsaal 3\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220331T150000
DTEND;TZID=Europe/Berlin:20220331T160000
DTSTAMP:20230203T092421Z
CREATED:20230119T074938Z
LAST-MODIFIED:20230203T092421Z
UID:451-1648738800-1648742400@www.hsu-hh.de
SUMMARY:Seminar Series: Computation & Data
DESCRIPTION:15:00-15:30 Yannis Schumann (HSU): Data-driven Inference of Stencils for Discrete Differential Operators \n\n\n\nPartial differential equations (PDEs) are extensively used across scientific disciplines for modeling and describing various processes under consideration. Finite element\, finite difference or similar methods allow to numerically solve them by discretizing the variables under consideration\, e.g. space and time. In this discretized domain\, differential operators can be approximated by matrices with nonzero coefficients for positions in the neighborhood of the considered point –the so called stencil. \n\n\n\nWe consider the inference of stencil weights for differential operators from linear\, one-dimensional and two-dimensional PDEs using comprehensive regression techniques. Starting with the 1D case\, we show that linear regression using an ordinary-least-squares (OLS) approach is able to recover mathematically meaningful stencils given a full-rank matrix of predictor variables. We discuss\, how regularization techniques can allow the inference of the correct stencils even for rank-deficient matrices. We discuss the impact of noise on the data in both predictor and predicted variables for various noise levels and compare different errors-in-variables approaches to mitigate the inherent consequences of noisy predictors. The presented techniques will be extended to the two dimensional case and applied to problems from physics and hydrogeology. \n\n\n\n\n\n\n\n15:30-16:00 Henrik Steude (HSU): It’s more than a “model.train()” — Modern tools and architectures for ML systems \n\n\n\nThe code to train machine learning (ML) models only covers a small part of the entire complexity required by a production-ready ML system. In particular\, model and data versioning\, reproducibility and scalability represent grand challenges. To address these challenges\, various new tools and technologies have been developed under the umbrella term “ML-Ops” over the last years. \n\n\n\nIn our contribution\, we present a selection of technologies\, that have evolved to be popular in the rapidly developing field of ML-Ops. As a concrete example\, we further present a system architecture for a ML platform\, which is used in the dtec.bw project (K)ISS for ML-based analysis of telemetry data of the international space station.
URL:https://www.hsu-hh.de/hpccp/event/cd2203/
LOCATION:H1\, Hörsaal 3\, Holstenhofweg 85\, Hamburg\, 22043\, Deutschland
CATEGORIES:Seminar Computation & Data
ORGANIZER;CN="hpc.bw":MAILTO:info-hpc-bw@hsu-hh.de
END:VEVENT
END:VCALENDAR