HPC and Big Data Technologies for Global Systems
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This project is developing novel methods, algorithms, and software for HPC and HPDA to model and simulate complex processes that arise in connection with major global challenges.

The present European society struggles with a wide range of global challenges in areas such as sociology, economy, ecology and technology. Various examples of global challenges, such as health care, the transition of green technologies or the evolution of the global climate up to hazards and stress tests for the financial sector demonstrate the complexity of the involved systems and underpin their interdisciplinary as well as their globality.

Solving these problems frequently requires the computation and analysis of huge amounts of data. Nearly all global challenges have immense complexity due to their global scale, and require interdisciplinary approach, where specialists from various areas must work together on aspects related with modeling, data acquisition, simulation, analysis and visualization. HiDALGO project aims to tackle these aspects by capturing global challenges in a computational and data analytics environment, enabling systematic cooperation between scientists from different background, and allowing these challenges to be interpreted and understood under a wide yet controllable range of conditions.

Although the process for bringing together European GSS and HPC/HPDA communities has already started within the Centre of Excellence for Global Systems Science (CoeGSS), the importance of computer aided policy making by addressing global, multi-dimensional problems is more important than ever. HiDALGO continues CoeGSS developments and bridges that shortcoming by enabling highly accurate simulations, data analytics and data visualization but also by providing knowledge on how to integrate the various workflows and the corresponding data.

HiDALGO focuses on excellent simulations of global challenges and in particular, the integration of different problem statements in order to establish a sustainable Centre of Excellence, especially for future problem statements. On this way, HiDALGO conducts research in multiple scientific areas including: 

  • algorithmic and technological challenges for data-centric computation; 
  • coupled simulation, strong and weak coupling mechanisms;
  • AI assisted workflows to improve application lifecycle handling; 
  • methods for the integration of real-world sensor data into the simulation execution.

The overall goal of HiDALGO is to advance the uptake of HPC, but also HPDA and AI technology in order to improve data-centric computation in general. This goal is by evolving available technologies in the following directions: 

  • integrate HPC and HPDA technologies seamlessly; 
  • increase application scalability by implementing, optimizing, and/or porting the involved kernels. In particular, we work on kernels for: 
    • agent-based modeling and simulation, 
    • large scale network synthesis and analytics, 
    • uncertainty quantification, 
    • numerical linear algebra for algebraic graph theory and CFD model reduction, etc.; 
  • develop the intelligent HiDALGO platform; 
  • improve data management and analytics capabilities for HPC and HPDA environments.

This research is supported by three use cases

  • computer-aided policy making for migration, 
  • control of air pollution in the cities, and 
  • study of information spread in social media (in particular, fake news propagation).

Many European politicians and citizens recognize the management of immigrants as one of the a major challenges for European society, particularly when it concerns refugees. Air pollution is also one of the most urgent problems politicians and citizens need to address. Both presented challenges are strongly driven by the impact of human behavior. In the contemporary world the easiest way to learn about human behavior is to investigate the "information aorta" of modern society, i.e. social media.


01. December 2018 -
31. March 2022


EU Horizon 2020