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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:20230413T100000
DTEND;TZID=Europe/Berlin:20230413T110000
DTSTAMP:20230313T114723Z
CREATED:20230217T091030Z
LAST-MODIFIED:20230313T114723Z
UID:944-1681380000-1681383600@www.hsu-hh.de
SUMMARY:User Meeting
DESCRIPTION:The user meeting is open to every HSUper user to share experiences. Feel free to join us.Please send an e-mail to info-cbrz@hsu-hh.de in case of any questions regarding the meeting.
URL:https://www.hsu-hh.de/hpccp/event/user-meeting-3/
LOCATION:H1\, room 109\, Holstenhofweg 85\, Hamburg\, 22043
CATEGORIES:User Meetings
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:20221201T150000
DTEND;TZID=Europe/Berlin:20221201T153000
DTSTAMP:20230119T094928Z
CREATED:20221103T163218Z
LAST-MODIFIED:20230119T094928Z
UID:387-1669906800-1669908600@www.hsu-hh.de
SUMMARY:User Meeting
DESCRIPTION:The user meeting is open to every HSUper user to share experiences. \nPlease send an e-mail to info-cbrz@hsu-hh.de if you wish to participate. Depending on the user size an adequate room will be reserved.
URL:https://www.hsu-hh.de/hpccp/event/user-meeting/
CATEGORIES:User Meetings
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:20220927T100000
DTEND;TZID=Europe/Berlin:20220927T110000
DTSTAMP:20230217T091823Z
CREATED:20220908T085303Z
LAST-MODIFIED:20230217T091823Z
UID:536-1664272800-1664276400@www.hsu-hh.de
SUMMARY:User Meeting
DESCRIPTION:The user meeting is open to every HSUper user to share experiences. \n\n\n\nPlease send an e-mail to info-cbrz@hsu-hh.de if you wish to participate. Depending on the user size an adequate room will be reserved.
URL:https://www.hsu-hh.de/hpccp/event/user-meeting-2/
CATEGORIES:User Meetings
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
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