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Ktirio Urban Building: A Computational Framework for City Energy Simulations Enhanced by CI/CD Innovations on EuroHPC Systems

Christophe Prud'Homme, Vincent Chabannes, Luca Berti, Maryam Maslek, Philippe Pincon, Javier Cladellas, Abdoulaye Diallo

TL;DR

This paper presents Ktirio Urban Building (KUB), a city-scale energy and environmental simulation framework built on the Feel++ toolchain and deployed via CI/CD and HPCOps on EuroHPC systems. It details a data-to-simulation workflow, multi-fidelity geometry modeling, shading masks, view-factor computations, and heat-transfer modeling through Modelica integration, enabling end-to-end urban energy assessments. Benchmark results show near-linear scaling for the simulation core but reveal bottlenecks in end-to-end performance due to parallel file I/O in post-processing, guiding future I/O optimizations. Overall, the work advances scalable, automated urban simulations for energy efficiency planning and policy support by enabling reproducible benchmarking on European HPC infrastructure.

Abstract

The building sector in the European Union significantly impacts energy consumption and greenhouse gas emissions. The EU's Horizon 2050 initiative sets ambitious goals to reduce these impacts through enhanced building renovation rates. The CoE HiDALGO2 supports this initiative by developing high-performance computing solutions, specifically through the Urban Building pilot application, which utilizes advanced CI/CD methodologies to streamline simulation and deployment across various computational platforms, such as the EuroHPC JU supercomputers. The present work provides an overview of the Ktirio Urban Building framework (KUB), starting with an overview of the workflow and a description of some of the main ingredients of the software stack and discusses some current results performed on EuroHPC JU supercomputers using an innovative CI/CD pipeline.

Ktirio Urban Building: A Computational Framework for City Energy Simulations Enhanced by CI/CD Innovations on EuroHPC Systems

TL;DR

This paper presents Ktirio Urban Building (KUB), a city-scale energy and environmental simulation framework built on the Feel++ toolchain and deployed via CI/CD and HPCOps on EuroHPC systems. It details a data-to-simulation workflow, multi-fidelity geometry modeling, shading masks, view-factor computations, and heat-transfer modeling through Modelica integration, enabling end-to-end urban energy assessments. Benchmark results show near-linear scaling for the simulation core but reveal bottlenecks in end-to-end performance due to parallel file I/O in post-processing, guiding future I/O optimizations. Overall, the work advances scalable, automated urban simulations for energy efficiency planning and policy support by enabling reproducible benchmarking on European HPC infrastructure.

Abstract

The building sector in the European Union significantly impacts energy consumption and greenhouse gas emissions. The EU's Horizon 2050 initiative sets ambitious goals to reduce these impacts through enhanced building renovation rates. The CoE HiDALGO2 supports this initiative by developing high-performance computing solutions, specifically through the Urban Building pilot application, which utilizes advanced CI/CD methodologies to streamline simulation and deployment across various computational platforms, such as the EuroHPC JU supercomputers. The present work provides an overview of the Ktirio Urban Building framework (KUB), starting with an overview of the workflow and a description of some of the main ingredients of the software stack and discusses some current results performed on EuroHPC JU supercomputers using an innovative CI/CD pipeline.
Paper Structure (32 sections, 11 figures)

This paper contains 32 sections, 11 figures.

Table of Contents

  1. Introduction
  2. Ktirio Urban Building Workflow
  3. Data Handling and Simulation Process
  4. Final Analysis and Urban Scale Energy Evaluation
  5. Overview of Urban Building Modeling and Simulation
  6. Geometry Reconstruction of the KUB Urban Model
  7. Building Modeling
  8. Terrain Modeling
  9. Vegetation Modeling
  10. Integration of all urban geometric components
  11. Visual Representation
  12. Computational Tools for Meshes Generation
  13. Current Mesh Generation Strategy
  14. Advancing Towards Full Parallelism
  15. Partitioning Strategies Depending on Simulation Use Cases
  16. ...and 17 more sections

Figures (11)

  • Figure 1: Current Urban Building Workflow from localization to city energy simulation report.
  • Figure 2: Different representations of a building using our LOD definition
  • Figure 3: Various representations of cities and terrain. Representation of Strasbourg center with LOD-0 in the top left panel and LOD-1 in the top right. LOD-1 city (Grenoble, France) representation with terrain elevation.
  • Figure 4: Mesh partitioning illustrations
  • Figure 5: $20 \times 20 \mathrm{km}^2\ $ geometric reconstruction of New York City (LOD-1)
  • ...and 6 more figures