TY - GEN A1 - Medina Méndez, Juan Ali A1 - Klein, Marten A1 - Schöps, Mark Simon A1 - Schmidt, Heiko T1 - Predicting volatile wind energy: Stochastic forward modeling and machine learning T2 - 86. Jahrestagung der DPG (86th Annual Conference of the DPG), DPG-Frühjahrstagung 2023, (DPG Spring Meeting 2023 of the Matter and Cosmos Section (SMuK), 20-24 March 2023, Technische Universität Dresden Y1 - 2023 UR - https://smuk23.dpg-tagungen.de/programm/assets/verhandlungen-smuk23.pdf UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_poster_dpg23.pdf SN - 2751-0522 SP - S. 343 PB - Deutsche Physikalische Gesellschaft CY - Bad Honnef ER - TY - GEN A1 - Klein, Marten A1 - Schöps, Mark Simon A1 - Medina Méndez, Juan Alí A1 - Schmidt, Heiko T1 - Numerical simulation and analysis of transient Ekman boundary layers using a stochastic turbulence model T2 - EGU General Assembly 2023 KW - stochastic modeling KW - one-dimensional turbulence KW - turbulent Ekman flow KW - transient boundary layer Y1 - 2023 UR - https://meetingorganizer.copernicus.org/EGU23/EGU23-9116.html U6 - https://doi.org/10.5194/egusphere-egu23-9116 PB - EGU - European Geophysical Union CY - Vienna, Austria ER - TY - CHAP A1 - Medina Méndez, Juan Ali A1 - Glawe, Christoph A1 - Starick, Tommy A1 - Schöps, Mark Simon A1 - Schmidt, Heiko T1 - IMEX-ODTLES: A multi-scale and stochastic approach for highly turbulent flows T2 - 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics February 18-22, 2019 Vienna, Austria, Abstract book Y1 - 2019 UR - https://jahrestagung.gamm-ev.de/images/2019/Photos/GAMM2019_BookofAbstracts.pdf SN - 978-3-903024-84-7 PB - TU-Verlag CY - Wien ER - TY - GEN A1 - Medina Méndez, Juan Ali A1 - Glawe, Christoph A1 - Starick, Tommy A1 - Schöps, Mark Simon A1 - Schmidt, Heiko T1 - IMEX-ODTLES: A multi-scale and stochastic approach for highly turbulent flows T2 - Proceedings in Applied Mathematics and Mechanics N2 - The stochastic One-Dimensional Turbulence (ODT) model is used in combination with a Large Eddy Simulation (LES) approach in order to illustrate the potential of the fully coupled model (ODTLES) for highly turbulent flows. In this work, we use a new C++ implementation of the ODTLES code in order to analyze the computational performance in a classical incompressible turbulent channel flow problem. The parallelization potential of the model, as well as its physical and numerical consistency are evaluated and compared to Direct Numerical Simulations (DNSs). The numerical results show that the model is capable of reproducing a representative part of the DNS data at a cheaper computational cost. This advantage can be enhanced in the future by the implementation of a straightforward parallelization approach. Y1 - 2019 U6 - https://doi.org/10.1002/pamm.201900433 SN - 1617-7061 VL - 19 IS - 1 ER - TY - GEN A1 - Rotta, Randolf A1 - Kuban, Robert A1 - Schöps, Mark Simon A1 - Nolte, Jörg T1 - Dealing with Layers of Obfuscation in pseudo-Uniform Memory Architectures T2 - Euro-Par 2016: Parallel Processing Workshops, Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016 N2 - Pseudo-Uniform Memory Architectures hide the memory's throughput bottlenecks and the network's latency differences in order to provide near-peak average throughput for computations on large datasets. This obviates the need for application-level partitioning and load balancing between NUMA domains but the performance of cross-core communication still depends on the actual placement of the involved variables and cores, which can result in significant variation within applications and between application runs. This paper analyses the pseudo-uniform memory latency on the Intel Xeon Phi Knights Corner processor, derives strategies for the optimised placement of important variables, and discusses the role of localised coordination in pUMA systems. For example, a basic cache line ping-pong benchmark showed a 3x speedup between adjacent cores. Therefore, pUMA systems combined with support for controlled placement of small datasets are an interesting option when processor-wide load balancing is difficult while localised coordination is feasible. Y1 - 2016 SN - 978-3-319-58942-8 SN - 978-3-319-58943-5 U6 - https://doi.org/10.1007/978-3-319-58943-5_55 SP - 685 EP - 696 PB - Springer International Publishing CY - Cham ER -