ENCCS/HiDALGO Workshop, 2021.
Material of the online course on April 27, 2021:
https://enccs.se/events/2021/04/enccshidalgo-workshop-on-high-performance-data-analytics/
This training event will start with
an introductory talk to provide a view of high-performance data
analytics (HPDA) from the HiDALGO perspective. The main concepts will be
presented, listing the tools that have been used, together with
information about benchmarks the consortium has done (as a source of
information about their scalability). This introduction also presents
how these tools are being applied in HiDALGO, in order to solve
different problems.
The following part of the
training will focus on HPC and HPDA technologies, applied to use-cases
such as Urban Air Pollution (UAP). The UAP application is a software
framework for modeling the vehicular traffic emitted air pollution and
its dispersion at very high resolution by using geometry inputs (Open
Street Map), coupled weather data (ECMWF) and traffic simulation (SUMO),
computational fluid dynamics (CFD) tools running on HPC infrastructures
(OpenFOAM), and evaluation with HPDA methods.
This HPC/HPDA/UAP-part of the training will introduce the UAP concept, workflows, implementations, application of the CFD-module in HPC environment, deployment to HPC, running, and HPDA for evaluation and model order reduction. Participants will learn the techniques of these parts from a general perspective, namely, HPC workflow modeling (TOSCA in YAML rendering), basics of OpenFOAM for computation of air pollutant dispersion using HPC, and the applied HPDA methods for fast evaluation and model reduction (POD with SVD).
The last part will provide an introduction to the data available at ECMWF and Copernicus, and the APIs for retrieving the data, followed by practical sessions on data exploration and manipulation. After this web-seminar, participants will be able to independently discover weather, climate, and environmental data produced and hosted by ECMWF, and also to retrieve and process these data using Python libraries.
The hands-on part will be carried out using the PSNC (https://www.psnc.pl/) training cluster.