SIAM Conference on Parallel Processing for Scientific Computing
Minisymposium: Approaches Towards Exascale Computational Fluid Dynamics
The complex nature of turbulent fluid flows implies that the computational resources needed to accurately model problems of industrial and academic relevance is virtually unbounded. Computational Fluid Dynamics (CFD) is therefore a natural driver for exascale computing and has the potential for substantial societal impact, like reduced energy consumption, alternative sources of energy, improved health care, and improved climate models.
Extreme-scale CFD possesses several cross disciplinary challenges e.g. algorithmic issues in scalable solver design, handling of extreme sized data with compression and in-situ analysis, resilience and energy awareness in both hardware and algorithm design. The wide range of topics makes exascale CFD relevant to a great HPC audience, extending outside the traditional fluid dynamics community.
This proposed minisymposium will be organized by the EU funded Horizon 2020 project ExaFLOW together with RIKEN AICS, and will feature presentations showcasing their work on addressing key algorithmic challenges in CFD in order to facilitate simulations at exascale, e.g. accurate and scalable solvers, data reduction methods and strategies for accuracy and error control.
This session aims at bringing together the CFD community as a whole, from HPC experts to domain scientists, discussing current and future challenges towards exascale fluid dynamics simulations and facilitating international collaboration.
Organizer: Niclas Jansson
KTH Royal Institute of Technology, Sweden
Kobe University, Japan
9:25-9:45 Efficient Gather Scatter Operations in Nek5000 Using PGAS abstract
Niclas Jansson, KTH Royal Institute of Technology, Sweden
9:50-10:10 A Parallel Algorithm of Pre and Post Processing for Industrial CFD Applications abstract
Keiji Onishi, RIKEN Advanced Institute for Computational Science, Japan; Niclas Jansson, KTH Royal Institute of Technology, Sweden; Rahul Bale, RIKEN Advanced Institute for Computational Science, Japan; Makoto Tsubokura, Kobe University, Japan
10:15-10:35 Adaptive Meshes and Error Control in Nek5000 abstract
Philipp Schlatter, KTH Stockholm, Sweden
10:40-11:00 A Stencil Penalty Approach For Improving Accuracy of Constraint Immersed Boundary Method abstract
Rahul Bale, RIKEN Advanced Institute for Computational Science, Japan; Niclas Jansson, KTH Royal Institute of Technology, Sweden; Keiji Onishi, RIKEN Advanced Institute for Computational Science, Japan; Makoto Tsubokura, Kobe University, Japan; Neelesh Patankar, Northwestern University, USA
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