MET-ENV computing tool: Speedflyer
Speedflyer is ZAV’s computer cluster for numerical modelling and simulations featuring two nodes, Castor and Pollux.
To run our numerical modeling tools and software, the MET-ENV group acquired and is maintaining a small yet powerful computer cluster. The cluster, which we refer to as “Speedflyer”, consists of two nodes sporting two Intel Xeon Platinum 8164 processors with 26 cores each, 768 GB of RAM and 140 TB of storage. In total, the system comprises 104 usable cores, 1536 GB of RAM, 220 TB of storage in RAID6 configuration and high speed InifiniBand interfaces for system-internal communication. With that, the cluster is a valuable tool for reducing computational runtimes and allows running our medium to large scale simulations around the clock. Due to the affinity of the MET-ENV Team to the Swiss mountains, the two nodes of the cluster were named “Castor” and “Pollux” – named after the “twin” mountains located in the Monte Rosa massif in the Valais alps.
The Speedflyer is configured with the server version of Linux Ubuntu 18.04.3 LTS. The employment of the Environment Modules package allows easy reconfiguration of the cluster system to various use cases of individual users of it. Among its users are of course the MET-ENV group, performing simulations with the numerical weather models PALM and WRF, and other simulation codes. Furthermore, in terms of air traffic research, the cluster is used for Collision Risk Modeling in the scope of projects at the Centre for Aviation. In the future, the Aerodynamics group of the Centre for Aviation will also be user of Castor and Pollux running open source computational fluid dynamic codes like OpenFOAM or SU2 of which the former is already operational on the cluster.
PALM Modelling System:
PALM-4U is a modern meteorological weather modelling system that is well suited for studies of the processes in the planetary boundary layer and in urban scenarios. PALM is a large eddy simulation tool and is optimized to run on massive parallel computing architectures, allowing high resolution simulations. Contrary to other numerical weather prediction models, PALM is based on a cartesian grid, permitting the representation of topography and buildings more accurately than the use of terrain-following pressure coordinates would allow. With its built-in radiation and land surface models and its capability for large scale forcing and grid nesting, terrain can be accurately parametrized; this permits simulations with very realistic boundary conditions and high resolutions in the areas of interest. With our 104-core cluster speedflyer, we can handle computationally heavy simulations in an appropriate timeframe.
At the Centre of Aviation, we apply PALM in practical scenarios and generate data for informed decision making and to gain insights into the intricacies of flows in complex terrain. This is especially relevant in Switzerland with its unique location and weather phenomenon induced by the Alps. PALM is a well-suited tool for aviation-related studies in Switzerland providing new insights in accident investigations, educational purposes for pilots, and numerous research opportunities.