arXiv subjects

Victor Azizi

Publications and source records attributed to Victor Azizi.

4 recordsLinked to original sources

arXiv2026

Astrophysics on GPUs: introducing AGILE 1.0

We present AGILE, a GPU-enabled adaptive mesh refinement (AMR) framework for the solution of (near-) conservation laws which occur in astro- and solar-physical applications. AGILE is written in modern fortran 2003, inherits a part of its modules and mesh handling from MPI-AMRVAC, and achieves excellent GPU performance via OpenACC offloading. We here discuss the design decisions which enable AGILE to perform cost-efficient and scalable deeply nested AMR simulations with moderate block sizes of e.g. $16^3$ cells. AGILE currently implements several physics modules, ie. hydrodynamics, frozen-field hydrodynamics, magnetohydrodynamics and special-relativistic hydrodynamics and can easily be extended further through its modular design. Besides strong scaling tests to up to 2048 GPUs and standard benchmarks which show consistent performance across a large range of devices and problem sizes, we demonstrate AGILE's capabilities by means of state-of-the art science applications with all currently available physics modules.

astro-ph.IM↗

arXiv2026

foap4: Adaptive mesh refinement with OpenACC, MPI, and p4est

GPUs and other accelerators are increasingly used for scientific computing. In the future, we want to add GPU support to parallel adaptive mesh refinement (AMR) codes written in Fortran. To understand which changes are necessary to obtain good performance we have developed foap4, an AMR framework implemented in Fortran that uses OpenACC, MPI, and the p4est library. We discuss the design and implementation of the framework. Several benchmark problems are considered, in which Euler's equations of gas dynamics are solved using explicit time integration. These benchmarks are performed in both 2D and 3D, using static and adaptive meshes, for varying problem sizes on different hardware. Our results show that AMR simulations can be carried out efficiently on GPUs with OpenACC and MPI, even when using relatively small grid blocks of $8^3$ or $16^3$ cells.

physics.comp-ph↗

arXiv2024

Duqtools: Dynamic uncertainty quantification for Tokamak reactor simulations modelling

Large scale validation and uncertainty quantification are essential in the experimental design, control, and operations of fusion reactors. Reduced models and increasing computational power means that it is possible to run many simulations, yet setting up simulation runs remaining a time-consuming and error-prone process that involves many manual steps. duqtools is an open-source workflow tool written in Python for that addresses this bottleneck by automating the set up of new simulations. This enables uncertainty quantification and large scale validation of fusion energy modelling simulations. In this work, we demonstrate how duqtools can be used to set up and launch 2000 different simulations of plasma experiments to validate aspects of the JINTRAC modelling suite. With this large-scale validation we identified issues in preserving data consistency in model initialization of the current ($I(p)$) distribution. Furthermore, we used duqtools for sensitivity analysis on the QLKNN-jetexp-15D surrogate model to verify its correctness in multiple regimes.

physics.plasm-ph↗

arXiv2020

ESiWACE2 Services: RSE collaborations in Weather and Climate

We present the collaborative model of ESiWACE2 Services, where Research Software Engineers (RSEs) from the Netherlands eScience Center (NLeSC) and Atos offer their expertise to climate and earth system modeling groups across Europe. Within 6-month collaborative projects, the RSEs intend to provide guidance and advice regarding the performance, portability to new architectures, and scalability of selected applications. We present the four awarded projects as examples of this funding structure.

cs.SE↗