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<h1 class="publications-title">Publications</h1>
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Research papers and publications related to the Shamrock framework for astrophysical hydrodynamics
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<h3>Numerical planet formation on exascale architectures</h3>
<p class="publication-authors">T. David--Cléris</p>
<p class="publication-type">PhD Thesis</p>
<p class="publication-abstract">
Numerical simulations are essential to our understanding of star and planet formation. They imply processes being multi-physics, complex, multi-scale, out of equilibrium, and non linear. Recently, the computing power of supercomputer in- creased up to the exascale, namely a quintillion operations per seconds. In principle, this computing power makes it possible to resolve crucial questions about planet formation, thanks to simulations of unprecedented accuracy. To achieve this, it is necessary to develop code based on algorithms capable of taking advantage of this new computing power. The aim of this thesis is to develop Shamrock, the first astrophysical code with exascale multi-methods (particles or adaptive grids). The core of this work is the adaptation and optimization of a binary algorithm for finding randomly distributed neighbors, which is fully parallelizable on architectures using graphics cards. In its current version, Shamrock achieves a parallel efficiency of over 90% for a Sedov test performed with the Smoothed Particle Hydrodynamics (SPH) method on 1024 nodes, enabling the first simulations with 65 billion particles to be carried out in 7 seconds per time step.
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<span class="publication-date">September 2024</span>
<span class="publication-institution">École normale supérieure de Lyon</span>
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<h3>The SHAMROCK code: I - smoothed particle hydrodynamics on GPUs</h3>
<p class="publication-authors">T. David--Cléris, G. Laibe, Y. Lapeyre</p>
<p class="publication-type">Journal Article</p>
<p class="publication-abstract">
We present SHAMROCK, a performance portable framework developed in C++ 17 with the SYCL programming standard, tailored for numerical astrophysics on Exascale architectures. The core of SHAMROCK is an accelerated parallel tree with negligible construction time, whose efficiency is based on binary algebra. The smoothed particle hydrodynamics algorithm of the PHANTOM code is implemented in SHAMROCK. On-the-fly tree construction circumvents the necessity for extensive data communications. In tests displaying a uniform density with global time-stepping with tens of billions of particles, SHAMROCK completes a single time-step in a few seconds using over the thousand of GPUs of a supercomputer. This corresponds to processing billions of particles per second, with tens of millions of particles per GPU. The parallel efficiency across the entire cluster is larger than ~90 per cent .
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<span class="publication-date">May 2025</span>
<span class="publication-journal">Monthly Notices of the Royal Astronomical Society</span>
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<h3>A highly accurate drag solver for multi-fluid dust and gas hydrodynamics on GPUs</h3>
<p class="publication-authors">L. Sewanou, G. Laibe, B. Commerçon</p>
<p class="publication-type">Journal Article</p>
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Exascale supercomputing unleashes the potential for simulations of astrophysical systems with unprecedented resolution. Taking full advantage of this computing power requires the development of new algorithms and numerical methods that are GPU friendly and scalable. In the context of multi-fluid dust-gas dynamics, we propose a highly accurate algorithm that is specifically designed for GPUs. We developed a multi-fluid gas-dust algorithm capable of computing friction terms on GPU architectures to machine precision, with the constraint for the drag-time step to remain a fraction of the global hydrodynamic time step for computational efficiency in practice. We present a scaling-and-squaring algorithm tailored to modern architectures for computing the exponential of the drag matrix, enabling high accuracy in friction calculations across relevant astrophysical regimes. The algorithm was validated through the Dustybox, Dustywave, and Dustyshock tests. The algorithm was implemented and tested in two multi-GPU codes with different architectures and GPU programming models: Dyablo, an adaptive mesh refinement code based on the Kokkos library, and Shamrock, a multi-method code based on Sycl. On current architectures, the friction computation remains acceptable for both codes (below the typical hydro time step) up to 16 species, enabling a further implementation of growth and fragmentation. This algorithm might be applied to other physical processes, such as radiative transfer or chemistry.
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<span class="publication-date">November 2025</span>
<span class="publication-journal">Astronomy and Astrophysics</span>
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<h3>Shamrock: Exascale hydrodynamics for astrophysics using SYCL.</h3>
<p class="publication-authors">T. David--Cléris</p>
<p class="publication-type">Conference Paper</p>
<p class="publication-abstract">
We present Shamrock, a native SYCL framework for astrophysics, designed to implement various numerical methods for modelling hydrodynamic flows, in particular Smoothed Particle Hydrodynamics (SPH). At the core of Shamrock lies a fast radix tree building algorithm that allows the tree to be rebuilt at each timestep with minimal cost, eliminating the need for tree communications or updates. Additionally, a domain decomposition method is used on top of the radix tree, allowing for a nearly linear multi-GPU weak scalability, resulting in 92% weak scaling efficiency on 1024 Mi250x AMD graphical accelerators for large SPH simulations.
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<span class="publication-date">2025</span>
<span class="publication-journal">ACM International Conference on Supercomputing</span>
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