Sergiy Gogolenko, Technical Coordinator of HiDALGO, will give a presentation at ISC High Performance 2020 on June 23, one of the leading conferences for High-Performance Computing in the world. In his talk, entitled "HiDALGO: HPC and Big Data Technologies for Global Challenges", he will present the most recent advances and results in our project. In particular, he will focus on the simulation of air pollution in urban environments; see attached image about the results of this simulation with respect to the city of Stuttgart.
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Community detection is an essential tool for analyzing the organization of complex social, biological and information networks. Among the numerous community detection algorithms proposed so far, Infomap is a prominent and well-established framework. In this thesis, we propose a novel method for community detection inspired by Infomap.
Due to Covid19 related safety measures, our General Assembly is being held
online. From May 18 to May 20 the consortium is discussing the most recent
advancements of the project in a number of teleconferences.
The details can be found in the file below.
The recent Covid-19 outbreak has had a tremendous impact on the world, and
many countries are struggling to help incoming patients and at the same time,
rapidly implement new public health measures such as lock downs.
Many of these decisions are guided by the outcomes of so-called SEIR
(susceptible-exposed-infectious-recovered) models that operate on a national
level. Within HiDALGO, we are using our agent-based modelling expertise to
develop the Flu And Coronavirus Simulator (FACS), an agent-based model that
The HiDALGO project has several contributions at major HPC and computational science events this year. Besides several talks at ICCS 2020, it has a paper at the same conference with the title "Accurate Simulation of Global Challenges on Data Centers Infrastructures via Coupling of Models and Data Sources". In this paper, we explore ways to bridge the gap between traditional high performance computing (HPC) and data-centric computation in order to provide efficient technological solutions in the domain of Global Challenges (GC).
