Scientific Computing Seminar

Date and Place: Thursdays and hybrid (live in 32-349/online via Zoom). For detailed dates see below!

Content

In the Scientific Computing Seminar we host talks of guests and members of the SciComp team as well as students of mathematics, computer science and engineering. Everybody interested in the topics is welcome.

List of Talks

  • Thu
    16
    May
    2024
    Thu
    25
    Jul
    2024

    Prof. Dr. Nicolas Gauger, Chair for Scientific Computing (SciComp), TU Kaiserslautern

    SciComp Seminar Series

    Please contact Prof. Gauger, if you want to register for an online talk in our SciComp Seminar Series or just to register for the seminar.

    A list of the already scheduled talks can be found –> here:

  • Thu
    16
    May
    2024

    11:45Hybrid (Room 32-349 and via Zoom)

    Xuân Tùng Nguyễn, INFN / University of Padua

    Title: Neural connectivity: a parallel in vitro and in silico analysis

    Abstract:

    In this talk, we will analyze neuronal recordings obtained by multi-electrode arrays (MEAs) on in vitro neuronal cultures from prof. Vassanelli’s laboratory, trying to estimate synaptic connectivity between the neurons. To this aim, we will adopt several time series analysis techniques, including transfer entropy and coincidence analysis. We will develop a silico dynamical model of the biological neuronal network, building on the standard Izhikevich model and adding some realistic constraints on the network topology. The model will be used to simulate neuronal time series and validate the connectivity inference methods. The end goal of the project is being able to reliably estimate how synaptic connectivity spontaneously varies in time.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Thu
    23
    May
    2024

    11:45Hybrid (Room 32-349 and via Zoom)

    Dr. Max Sagebaum, RPTU Kaiserslautern-Landau

    Title: Introduction to cppfront – a new syntax for C++ – and compile time regular expression generation

    Abstract:

    cppfront is a compiler for an experimental alternate syntax for C++ (aka Cpp2) initiated and driven by Herb Sutter. The project wants to explore ideas for a new syntax of C++ that makes it simpler, safer, and faster to write C++. cppfront does not want to create a C++ sucessor. It wants to evolve C++. In this talk, we will present the current status of the project and introduce the new syntax. Afterwards, the implementation of a compile-time regular expression generator is presented.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Thu
    13
    Jun
    2024

    11:45Hybrid (Room 32-349 and via Zoom)

    Ivan Barranco Gomez, School of Civil, Aerospace and Design Engineering; University of Bristol

    Title: Optimising Ion Thruster Performance: Advances in Particle-in-Cell and Monte Carlo Simulations

    Abstract:

    Motivated by the need to enhance physical modelling and optimization techniques in the design of ion thrusters, this seminar delves into the challenges and advancements in simulating ion thrusters using Particle-in-Cell (PIC) codes coupled with Monte Carlo methods. In this talk, we investigate the physical modelling of ion thrusters, with a particular focus on plasma physics. We address the inherent complexities in PIC codes, which are widely used for simulating plasma behaviour in ion thrusters. These codes combine kinetic and fluid descriptions of plasma particles, relying heavily on Monte Carlo methods for handling collisions and other stochastic processes. Finally, the seminar outlines future research directions, emphasizing the need for continued advancements in simulation techniques and optimization algorithms to further refine the modelling and performance of ion thrusters in aerospace applications.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Thu
    20
    Jun
    2024

    11:45Hybrid (Room 32-349 and via Zoom)

    Max Aehle, RPTU Kaiserslautern-Landau

    Title: Algorithmic Derivatives of Electromagnetic Shower Simulations

    Abstract:

    Applying algorithmic differentiation to particle simulations like Geant4 would allow us to evaluate derivatives of simulation outputs with respect to inputs, e.g. of the mean energy depositions in calorimeter layers with respect to geometry parameters. Such derivatives could become instrumental for a number of application like detector optimization or parameter fitting in HEP. However, besides the technical challenge of applying AD to over one million lines of code, there is a number of mathematical/statistical challenges: Does the high density of discontinuities, induced for example by ‘if’ and ‘while’ statements in the code, cause problems in the derivative computation? Are we allowed to treat random numbers like constants with respect to AD? How large is the error when the mean pathwise derivative is evaluated as a proxy for the actual derivative of expectancies computed by Monte-Carlo algorithms?

    To approach these questions, we have applied the operator-overloading AD tool CoDiPack to the compact G4HepEm/HepEmShow package for the simulation of electromagnetic showers in a simple sampling calorimeter. After disabling multiple scattering in the simulation, our pathwise gradient estimator approximates derivatives of energy depositions with only a small bias, which proved unproblematic in a simple optimization study. In this talk, we will report on our methodology and give an overview on our findings.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Wed
    26
    Jun
    2024

    9:00Room 32-349

    Daniel Maue, RPTU Kaiserslautern-Landau

    Title: Depth-Aware Traffic Sign Recognition – A Multi-Stage 3D Localization & Classification Pipeline for Traffic Signs

    Abstract:

    Recognizing objects within images is a key task in computer vision. There are many traditional algorithmic approaches for locating objects in images and with the rise of research of artificial intelligence also deep learning recognition models were proposed. State-of-the-art methods already achieve matching or better performance than humans. The goal of this thesis is to give the common recognition task a third dimension, by not only locating objects in the 2D image but also estimating the depth of this object within the captured scene. Especially traffic sign recognition would benefit from the additional depth information, since capturing the distance and thus the order of oncoming traffic signs could greatly improve safety in vehicles since the depth can have important semantic meanings to the current and future driver assistance system. Therefore this bachelor thesis focuses on proposing a multi-stage 3D localization pipeline for traffic signs, by thoroughly analyzing and comparing state-of-the-art methods in object recognition and depth estimation. With that, these two topics are first introduced by covering related work and the needed theoretical background. Additionally, the considered approaches for object recognition and depth estimation are explained and finally evaluated in experiments, to find the most suitable methods for a 3D localization pipeline.

  • Thu
    27
    Jun
    2024

    11:45Hybrid (Room 32-349 and via Zoom)

    Johannes Albert Stegmann, RPTU Kaiserslautern-Landau

    Title: Improving Evaluation Performance for Large Derivative Computations Through Cache Optimisation Techniques in CoDiPack

    Abstract:

    This presentation will discuss optimisation techniques to improve CPU caching between statements of large derivative calculations in the C++ CoDiPack library. These enhancements focus on improving cache friendliness through the reordering of statements and reallocating identifiers given to the variables in the statements. Modifying identifiers aims to improve spatial locality caching, while reordering statements takes advantage of temporal caching.

    Initial tests show that identifier selection significantly impacts evaluation performance. With a basic reallocation of identifiers, performance improvements of greater than 25% are possible. Investing a few minutes in upfront processing leads to substantial time savings in large derivative calculations. Additionally, how users write their programs using CoDiPack affects the performance of functionally identical tapes. The goal of these techniques is to reduce the dependency on the structure of the user’s program. The reordering of a tape is further used to remove redundant or unused statements.

    To support these techniques, we have added functionality to CoDiPack to enable tape storage. This includes providing text and graphical methods for easier debugging and a binary file output for efficient storage outside the current program’s scope. The stored tape can later be reloaded into CoDiPack to reproduce a valid tape.

    This presentation discusses the storage and cache enhancement methods, ideas for further improvement, and the preliminary results of the implemented solutions.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Fri
    05
    Jul
    2024

    11:00Hybrid (Room 32-349 and via Zoom)

    Prof. Sarah Neuwirth, Johannes Gutenberg University of Mainz

    Title: Transforming HPC with Holistic Performance Engineering and the Pursuit of Reproducibility

    Abstract:

    HPC applications are evolving not only to include traditional modeling and simulation workloads but also so-called scale-out workloads, including artificial intelligence, big data analytics, deep learning, and complex workflows. Given the ever-increasing complexity of supercomputers and the emergence of exascale computing, these trends are leading to a widening gap between expected and observed peak performance. Therefore, holistic performance engineering is critical to bridge this gap through reproducible benchmarking, modeling, optimization, and analysis of large-scale HPC workloads.

    This seminar will delve into innovative approaches to scale HPC performance engineering horizons and unlock the full potential of computational capabilities. Strategies for optimizing hardware and software utilization, identifying and mitigating performance bottlenecks, and implementing cutting-edge techniques to maximize scalability, efficiency, and productivity will be explored. Moreover, this talk will question to what extent reproducibility, replicability, comparability, and portability should influence the performance analysis cycle of workloads and supercomputing systems.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Thu
    18
    Jul
    2024

    11:45Hybrid (Room 32-349 and via Zoom)

    Lena Dittrich, RPTU Kaiserslautern-Landau

    Title: An overview over publications simulating Ride-pooling services using the simulation framework MATSim

    Abstract:

    Ride-pooling Services, also often referred to as Ride-Hailing or Ride-Sharing Services, are becoming more and more common. Humanity is facing problems like climate change and increased population density, and we are increasingly aware of the necessity to change and adjust our way of life accordingly. To combat this, we are attempting to rebuild and adapt our infrastructure to our new challenges. Public transportation systems are an important part of that transition and, therefore, a useful and much needed area of research. An efficient system will attract more passengers who will substitute their private vehicle by public transportation, thereby saving not only carbon emissions but also space and resources that can be used more efficiently elsewhere.
    This talk will give an overview over some research that has been done about Ridepooling services. We will look at publications in which different scenarios were simulated using the agent-based simulation framework MATSim to asses the necessary fleet size of a ride-pooling service provider.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Thu
    22
    Aug
    2024

    11:45Hybrid (Room 32-349 and via Zoom)

    Prof. Hans Hagen, Geometric Modeling Group, RPTU

    There will be two short presentations:

    Title: Differential Geometry as a ” tool box”

    Abstract:

    Geometric Modelling Algorithms need a strong mathematical basis.
    One is Differential Geometry. We present in this talk some basic concepts
    in an “intuitive way”. Geometry has a lot to do with intuition and imagination.
    Same “tools” work in geometric modelling, some do not.
    After this introductionary talk we will and should have a constructive and critical discussion.

    Title: Killing Vector Fields — a concept for simulation and scientific visualization?

    Abstract:

    Killing Vector Fields ( named after Wolfgang Killing) are infinitesimal generators of isometries.
    The flow generated by these fields are continuous isometries of the surface.
    There is no distortion moving long these directions.
    We present in this talk the basic ideas and the PDE system, which has to be solved.

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09

  • Wed
    09
    Oct
    2024

    11:00Hybrid (Room 32-349 and via Zoom)

    Prof. Hans Hagen, Geometric Modeling Group, RPTU

    Title: Non-Standard Metrics for Machine Learning

    Abstract:

    Euclidean Metrics and L2-Norms are the dominating standards
    — . BUT are they good enough in all applications ?—-
    I do not think so. Finslertyp metrics , which deal with point locations and directions show a lot of promise of being influential in important research areas.
    The Lagrange Multiplier technique is a very powerfull tool assuming the “right energy functionals”.
    What about energy functionals depending on non – standard metrics for GANs ( Generative Adversal Networks) ??
    This would open the door for using Lagrange Multipliers.
    To start a constructive and critical discussion is the goal of this talk .

    How to join online

    You can join online via Zoom, using the following link:
    https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09