Performance assessment of the gPLUTO code for the numerical modeling of radio galaxy evolution

High-resolution tri-axial simulations are indispensable for realistically co-modeling the dynamical signatures and the radiative fingerprints of astrophysical jets, which are becoming increasingly important in modern computational studies of jet physics. However, such simulations impose extreme computational requirements that often exceed the capabilities of conventional CPU-based codes. GPU-accelerated simulations offer a transformative solution to mitigate these limitations. In this work, we present a detailed performance benchmarking of the recently developed GPU-enabled PLUTO code (gPLUTO), demonstrating runtime speed-ups ranging from an order of magnitude to (approximately) over 30 relative to CPU-only configurations. A direct comparison between computations of extragalactic jet propagation performed at different grid resolutions confirm the physical fidelity and production readiness of the gPLUTO code, while underscoring the importance of resolving the jet radius adequately to capture the jet dynamics accurately. Leveraging GPU-PLUTO’s capabilities, we finally present an application by performing high-resolution simulations of giant radio galaxy jets (GRGs ≳ 1 Mpc), representing the first such well-resolved 3D study to our knowledge (resolving scales down to 500 pc). These simulations probe a range of environmental effects on GRG jets, clarifying their formation from central galaxies within host cosmic structures, rapid peripheral expansion, and the development of asymmetric cocoon morphologies.

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Publication Details

Journal
Astronomy and Computing
Published
2026-03-09
DOI
https://doi.org/10.1016/j.ascom.2026.101091
Primary Topic
Astrophysics and Cosmic Phenomena
Type
article
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article

Performance assessment of the gPLUTO code for the numerical modeling of radio galaxy evolution

Gourab Giri, Marco Rossazza, A. Mignone, S. Truzzi et al.
Astronomy and Computing
Astrophysics and Cosmic Phenomena
article

Performance assessment of the gPLUTO code for the numerical modeling of radio galaxy evolution

Gourab Giri, Marco Rossazza, A. Mignone, S. Truzzi, Alessio Suriano
article en

Abstract

High-resolution tri-axial simulations are indispensable for realistically co-modeling the dynamical signatures and the radiative fingerprints of astrophysical jets, which are becoming increasingly important in modern computational studies of jet physics. However, such simulations impose extreme computational requirements that often exceed the capabilities of conventional CPU-based codes. GPU-accelerated simulations offer a transformative solution to mitigate these limitations. In this work, we present a detailed performance benchmarking of the recently developed GPU-enabled PLUTO code (gPLUTO), demonstrating runtime speed-ups ranging from an order of magnitude to (approximately) over 30 relative to CPU-only configurations. A direct comparison between computations of extragalactic jet propagation performed at different grid resolutions confirm the physical fidelity and production readiness of the gPLUTO code, while underscoring the importance of resolving the jet radius adequately to capture the jet dynamics accurately. Leveraging GPU-PLUTO’s capabilities, we finally present an application by performing high-resolution simulations of giant radio galaxy jets (GRGs ≳ 1 Mpc), representing the first such well-resolved 3D study to our knowledge (resolving scales down to 500 pc). These simulations probe a range of environmental effects on GRG jets, clarifying their formation from central galaxies within host cosmic structures, rapid peripheral expansion, and the development of asymmetric cocoon morphologies.

Astronomy and ComputingVol. 56
Osservatorio Astrofisico di Torino (IT), Istituto di Radioastronomia di Bologna (IT), Cineca (IT), University of Turin (IT)
Openalex Percentile: Top 29%
Astrophysics and Cosmic Phenomena
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Performance assessment of the gPLUTO code for the numerical modeling of radio galaxy evolution — Gourab Giri, Marco Rossazza, et al. · Astronomy and Computing (2026) | TGRS Research Map | TGRS