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Name: CFD Training Series: Introduction to Turbulence Modeling and Numerical Implementation Date: November 02, 2023 Time: 1.00 pm - 5.00 pm Format: online More Information Description Short abstract: In this course, the introduction to the structural properties of various turbulence modeling concepts (RANS, LES, and Hybrid RANS/LES) including associated equations will be given. […]
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We offer an open HPC consultation hour on a regular basis. This takes place every 3rd Thursday of the month. Here, we give you the opportunity to ask any HPC related question, e.g. about: Cluster usage Parallel Programming Performance analysis and optimization of self-written codes Workflow optimization (e.g. job management and data processing) Efficient usage […] |
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Name: Parallelization in OpenFOAM for HPC Deployment Date: November 06, 2023 & November 16, 2023 Time: 10am - 4pm Format: Online Flipped Classroom focusing on hands-on training More Information Description Short abstract: OpenFOAM is an open source, mature and established C++ library for computational continuum mechanics (CCM) including Computational Fluid Dynamics (CFD). For […] |
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3 events,
Name: Introduction to Machine Learning and Deep Learning Date: November 09, 2023 & November 10, 2023 Time: 9 a.m to 1 p.m. Format: Online More Information Description Short abstract: Not only in economics Machine- and Deep-Learning (ML/DL) are inherently used to solve highly complex problems in a data-driven way, but also the scientific […]
Name: Machine Learning in Combustion Date: November 09 & 10, 2023 Time: 2 pm – 6 pm Format: Online More Information Description Short abstract: Big data and Machine Learning (ML) are driving comprehensive economic and social transformations and are rapidly becoming a core technology for scientific computing, with numerous opportunities to advance different research […]
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Name: CFD Training Series: Introduction to Finite Element Methods for Flow Problems Date: November 09, 2023 Time: 1.00 pm - 5.00 pm Format: Online More Information Description Short abstract: In this course, we cover various techniques to solve fluid flow problems using the finite element method. The course consists of a combination of […] |
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Abstract The HPC JupyterHub service at the RWTH allows all eligible users of the RWTH Compute Cluster to utilize the existing compute hardware interactively with the use of Jupyter Notebooks. This HPC JupyterHub provides customization of Profiles with a variety of programming kernels, software packages, and hardware definitions. This workshop will showcase the HPC JupyterHub […] |
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Name: CFD Training Series: Introduction to Discontinuous Galerkin Methods for Flow Problems Date: November 16, 2023 Time: 1.00 pm - 5.00 pm Format: Online More Information Description Short abstract: In this course, we cover the main building blocks to solve fluid flow problems using the Discontinuous Galerkin (DG) method. The course consists of […]
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We offer an open HPC consultation hour on a regular basis. This takes place every 3rd Thursday of the month. Here, we give you the opportunity to ask any HPC related question, e.g. about: Cluster usage Parallel Programming Performance analysis and optimization of self-written codes Workflow optimization (e.g. job management and data processing) Efficient usage […] |
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Name: Data-Driven Healthcare: Leveraging Visualization and Data Management for Digital Patient Studies Date: November 21, 2023 & November 22, 2023 Time: 1.00 pm - 5.00 pm Format: Online More Information Description Short abstract: In today’s rapidly advancing medical landscape, data has become an invaluable asset, empowering healthcare professionals and researchers to make informed […] |
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Name: CFD Training Series: Introduction to Kernel-based approximation methods with applications to fluid dynamics Date: November 23, 2023 Time: 1.00 pm - 5.00 pm Format: hybrid More Information Description Short abstract: When data is provided in an unstructured format or is high-dimensional, classical interpolation or approximation schemes as Finite-Element Methods (FEM) struggle to […] |
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Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […] |
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Events
