As part of an intensive and fruitful cooperation, the Centre of Excellence HiDALGO and HLRS will be participating remotely at SC'21, one of the biggest annual gatherings in the HPC community.
Visit the SC''21 Website, and register here:
https://sc21.supercomputing.org/attend/register/
The program will run from November 16 until November 18, 2021 at a joint virtual booth. HLRS will give talks on Tuesday, 16th Nov andThursday, 18th, and HiDALGO researchers on Wed, Nov 17.
The program and the virtual booth are also available through the SC'21 HUBB (for registered users only):
https://sc21.hubb.me/fe/schedule-builder/sponsors/49300
Feel free to participate in the talks if you are registered to SC'21 online exhibits.
The following partial schedule details 8 presentations from HiDALGO that will be given at SC21 on Wednesday.
Schedule Wed. 17th Nov. 2021 afternoon
|
Time Slot CST (USA) CET (Europe) |
Topic
|
Speaker
|
|---|---|---|
|
9.00-9.15am 4.00–4.15pm |
Francisco Javier Nieto de Santos (Atos, Spain) |
|
|
9.15-9.45am 4.15–4.45pm |
Diana Suleimenova (Brunel University London, UK) |
|
|
9.45-10.15am 4.45–5.15pm
|
Case study Introducing FACS: a hyperlocal and parallel agent-based COVID-19 simulation code |
Derek Groen (Brunel University London, UK) |
|
10.15-10.45am 5.15-5.45pm
|
Zoltán Horváth (Széchenyi István Egyetem, Hungary) |
|
|
10.45-11.15am 5.45-6.15pm
|
Spectral Methods to Compute Eigenvalue Histograms in the Context of Social Network Analysis |
Robert Elsässer (Paris Lodron Universität Salzburg, Austria) |
|
11.30-12.00am 6.30-7.00pm
|
Dennis Grieger, Marko Djuric and Fabian Dembski (HLRS, Germany) |
|
|
12.00-12.30pm 7.00-7.30pm
|
Big Data and Supercomputers : Utilizing High Performance Data Analytics in an HPC setup. |
Nikolaos Chalvantzis (CSLab, National Technical University of Athens, Greece) |
|
12.30-1.00pm 7.30-8.00pm
|
CPU and GPU optimization technics implemented in HiDALGO's use case applications |
Marcin Lawenda (Poznan Supercomputing and Networking Center, Poland) |
Introducing how HPC can address global challenges
November 17, 2021: 09:00 - 09:15 (CST)
As part of the EU-funded project HiDALGO, we develop novel methods, algorithms and software for HPC and HPDA to accurately model and simulate the complex processes, which arise in connection with major global challenges.
Speaker: Francisco Javier Nieto de Santos (Atos)
Case study: Coupling of multiscale forced displacement and weather simulations — the South Sudan conflict
November 17, 2021: 09:15 - 09:45 (CST)
We propose a multiscale forced displacement simulation approach that can assist organisations with the allocation of humanitarian resources. To provide more accurate simulations, we consider perceived levels of safety and road accessibility influenced by the level of precipitation and river discharge. Most studies in this area have only considered the effects of climate on forced displacement, but there are no studies on the impact of weather on people’s decision to flee or travel. Aiming to fill this gap, we investigate precipitation and river discharge levels affecting the movement speed of forcibly displaced people and their decision to remain in their current location or traverse through other routes. Specifically, we analyse the South Sudan conflict between 2016-2017 and evaluate the coupled multiscale and single-scale simulation results by comparing the total validation error, execution time and coupling overhead.
Speaker: Diana Suleimenova (Brunel University)
Case study: Introducing FACS — a hyperlocal and parallel agent-based COVID-19 simulation code
November 17, 2021: 09:45 - 10:15 (CST)
The Flu And Coronavirus Simulator, or FACS, is an agent-based simulation code that mimics the spread of COVID-19 in a local area, such as a municipality or a borough in a large city that serves as a catchment area for one or a few hospitals. Using FACS, we are able to (a) derive virtual human households from geospatial (OpenStreetMap) and demographic (ONS) data sources and (b) calculate how the people in these households infect each other as they visit a wide array of nearby locations. The code is unique in that it has an explicit sub-national/local scope, extracts its location graphs directly from geospatial data sources, and that FACS users have shown to be able to construct and execute new simulations in a matter of days.
Speaker: Derek Groen (Brunel University)
Case study: Simulation urban air pollution
November 17, 2021: 10:15 - 10:45 (CST)
The aim of the urban air pollution application is to create cleaner air in cities by using high performance computing (HPC) and mathematical technologies. To this end, this research will provide policy makers and society with an easy-to-use computational tool as a service that accurately and quickly forecasts air pollution in cities with very high resolution. Furthermore, a traffic control system will be developed as well to minimize air pollution while considering traffic flow constraints.
Speaker: Zoltán Horváth (Széchenyi István Egyetem)
Spectral methods to compute eigenvalue histograms in the context of social network analysis
November 17, 2021: 10:45 - 11:15 (CST)
Social networks are omnipresent in our daily life. They are used for communication and information dissemination, which highly influences our behavior. One of the main fields in social network analysis is the study of the topological and algorithmic properties of the underlying graphs, and the design of proper random graph models to describe these networks. Once a random graph model has been generated, it is crucial to compare its properties to the corresponding real-world networks. For this, the comparison of eigenvalue histograms is essential.
Speaker: Robert Elsässer (Paris Lodron Universität Salzburg)
Visualization of air pollution using digital urban twins
November 17, 2021: 11:30 - 12:00 (CST)
Digital urban twins can facilitate the understanding of complex, interdisciplinary processes in cities and regions. Within the HiDALGO project, a digital twin for the city of Stuttgart, Germany was employed for supporting the analysis of urban air pollution simulations. From the urban air pollution use case, estimates for the distribution of pollutants such as nitric oxides were obtained. In combination with further data sets these estimates can be studied in the frame of a digital twin. Visualization in Virtual Reality allows low-threshold access in an immersive, interactive manner. The presentation will be streamed live from the CAVE.
Speaker: Dennis Grieger, Marko Djuric und Fabian Dembski
Big data and supercomputers: Utilizing high performance data analytics in an HPC setup
November 17, 2021: 12:00 - 12:30 (CST)
In this presentation we will discuss the role of high performance data analytics (HPDA) in an HPC setup. Our goal is to showcase how HPDA has been utilized and leveraged to obtain insights into the simulation outcomes of the HPC processing tasks of HIDALGO, present some of the challenges we faced during the design, implementation and deployment of the HPDA methods and discuss lessons learned in the process.
Speaker: Nicolaos Chalvantzis (CSLab, National Technical University of Athens)
CPU and GPU optimization technics implemented in HiDALGO's use case applications
November 17, 2021: 12:30 - 13:00 (CST)
The Global Challenges applications are highly demanding in terms of the amount of processed data. This implicates that the application design must demonstrate sufficient resiliency to operate efficiently on incoming data on a given timeframe, taking into account manifold data sources and their particular characteristics. The first phase of yield testing is assesment of its performace while in the next step the focus is concentrated on excellence in application design and optimisation by examining algorithms, programming models, techniques and implementation methods to enable near-linear scalability for both compute-intensive and dataintensive applications. The achievements will be presented on the basis of the results of the analysis of pilot applications coming from "Urban Air Pollution" and "Social Networks" use cases and conducted on both CPU and GPU units.
Speaker: Marcin Lawenda (Poznan Supercomputing and Networking Center)
