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GPU Accelerating Algorithms for Three-Layered Heat Conduction Simulations

Author

Listed:
  • Nicolás Murúa

    (Departamento de Ciencias de la Computación y Tecnologías de la Información, Facultad de Ciencias Empresariales, Universidad del Bío-Bío, Campus Fernando May, Chillán 3780000, Chile)

  • Aníbal Coronel

    (Departamento de Ciencias Básicas, Centro de Ciencias Exactas UBB (CCE-UBB), Facultad de Ciencias, Universidad del Bío-Bío, Campus Fernando May, Chillán 3780000, Chile)

  • Alex Tello

    (Departamento de Matemáticas, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1270300, Chile)

  • Stefan Berres

    (Núcleo de Investigación en Bioproductos y Materiales Avanzados (BioMA), Universidad Católica de Temuco, Temuco 4780002, Chile
    Integrata-Stiftung für Humane Nutzung der Informationstechnologie, Vor dem Kreuzberg 28, 72070 Tübingen, Germany)

  • Fernando Huancas

    (Departamento de Matemática, Facultad de Ciencias Naturales, Matemáticas y del Medio Ambiente, Universidad Tecnológica Metropolitana, Las Palmeras 3360, Ñuñoa, Santiago 7750000, Chile)

Abstract

In this paper, we consider the finite difference approximation for a one-dimensional mathematical model of heat conduction in a three-layered solid with interfacial conditions for temperature and heat flux between the layers. The finite difference scheme is unconditionally stable, convergent, and equivalent to the solution of two linear algebraic systems. We evaluate various methods for solving the involved linear systems by analyzing direct and iterative solvers, including GPU-accelerated approaches using CuPy and PyCUDA. We evaluate performance and scalability and contribute to advancing computational techniques for modeling complex physical processes accurately and efficiently.

Suggested Citation

  • Nicolás Murúa & Aníbal Coronel & Alex Tello & Stefan Berres & Fernando Huancas, 2024. "GPU Accelerating Algorithms for Three-Layered Heat Conduction Simulations," Mathematics, MDPI, vol. 12(22), pages 1-22, November.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:22:p:3503-:d:1517537
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    References listed on IDEAS

    as
    1. Anibal Coronel & Esperanza Lozada & Stefan Berres & Fernando Huancas & Nicolás Murúa, 2024. "Mathematical Modeling and Numerical Approximation of Heat Conduction in Three-Phase-Lag Solid," Energies, MDPI, vol. 17(11), pages 1-23, May.
    2. Hanna Koshlak & Borys Basok & Borys Davydenko, 2024. "Heat Transfer through Double-Chamber Glass Unit with Low-Emission Coating," Energies, MDPI, vol. 17(5), pages 1-17, February.
    3. Walery Jezierski & Adam Święcicki & Anna Justyna Werner-Juszczuk, 2024. "Deterministic Mathematical Model of Energy Demand of Single-Family Building with Different Parameters and Orientation of Windows in Climatic Conditions of Poland," Energies, MDPI, vol. 17(10), pages 1-19, May.
    4. Talha Batuhan Korkut & Ahmed Rachid, 2024. "Numerical Investigation of Interventions to Mitigate Heat Stress: A Case Study in Dubai," Energies, MDPI, vol. 17(10), pages 1-17, May.
    5. Marek Walacik & Aneta Chmielewska, 2024. "Energy Performance in Residential Buildings as a Property Market Efficiency Driver," Energies, MDPI, vol. 17(10), pages 1-18, May.
    6. Walery Jezierski & Miroslaw Zukowski, 2023. "Evaluation of the Impact of Window Parameters on Energy Demand and CO 2 Emission Reduction for a Single-Family House," Energies, MDPI, vol. 16(11), pages 1-20, May.
    7. António M. Raimundo & A. Virgílio M. Oliveira, 2024. "Assessing the Impact of Climate Changes, Building Characteristics, and HVAC Control on Energy Requirements under a Mediterranean Climate," Energies, MDPI, vol. 17(10), pages 1-30, May.
    8. Linfang Tan & Da Gao & Xiaowei Liu, 2024. "Can Environmental Information Disclosure Improve Energy Efficiency in Manufacturing? Evidence from Chinese Enterprises," Energies, MDPI, vol. 17(10), pages 1-15, May.
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