Chair(s):
Andrés Escala
Universidad de Chile,
Chile
aescala@das.uchile.cl
Dominik R.G.
Schleicher
Universidad de Concepción,
Chile
dschleicher@astro-udec.cl
Location:
Esplanade (Main Courtyard), d’Etigny Auditorium
09:30: Ignacio Reyes Jainaga, ALeRCE – the first
Chilean broker for LSST
10:15: Pierluigi
Cerulo, Machine learning in
astrophysics
11:00: Coffee
break
11:30: Iley El Mellah: Astrophysical
simulations on GPUs
12:15: Leonardo Krapp,
Pablo Benitez-Llambay, FARGO3D on GPUs
13:00:
Finish

Advances in using High-Performance GPUs for Astroinformatics
Description
This workshop will focus on the usage of
high-performance GPUs in the context of astroinformatics, including
advanced computational modeling as well as data analysis (including
machine learning / artificial intelligence) employing high-performance
GPUs. We are interested in bringing together the relevant South American
and international community working on this topic, with the purpose of
elevating and employing the current state of the art both in the fields
of astrophysical simulations and astrophysical data analysis. For this
purpose, we will be considering a very broad range of possible
applications, where we provide specific examples below though our
workshop will not be limited to these examples.
Within the context of numerical simulations,
our range of interest encompasses techniques that include individual
powerful GPU servers up to methodologies developed for the purpose of
upcoming peta-scale computing. An example of that is the methodology
employed in the new magneto-hydrodynamics (MHD) code
AthenaPK, which presents an
adaption of the original ATHENA code using the performance portable
block-structured adaptive mesh refinement framework (Parthenon)
developed by Grete et al. 2022 (arXiv:2202.12309), a framework adopting
the Kokkos programming model to target exascale simulations employing
clusters with powerful GPUs. In the context of fluid dynamics,
additional codes will be discussed such as FARGO3D, a grid-based multi-physics MHD code allowing
the usage of GPUs, of which one of the main developers is now in Chile
(invited speaker Leonardo Krapp). These will be contrasted with
approaches based on Smoothed Particle Hydrodynamics (SPH) such as the
StarSmasher code that also
strongly utilizes GPUs.
Beyond the fluid dynamics, however, important
applications concern the modeling of dense stellar clusters and the
formation of very massive objects within these clusters. Here an
important example is the stellar dynamics code Nbody6++GPU (Wang et al. 2015) utilizing hybrid
parallelization methods (MPI, GPU, OpenMP, and AVX/SSE) to accelerate
large direct N-body simulations, and in particular to solve the
million-body problem. Particularly, this code has been employed for
producing the DRAGON simulations (Wang et al. 2016, MNRAS, 458, 1450),
the first simulations of globular clusters modeling the evolution of one
million stars. This code currently forms the basis for in-depth
investigations of star cluster evolution and the formation of massive
objects within these clusters due to collisions.