arXiv subjects

Milan Jaros

Publications and source records attributed to Milan Jaros.

6 recordsLinked to original sources

arXiv2026

Streami: An MPI Data-Parallel Library to Compute Field Lines on GPUs

We present Streami, an extensible GPU-accelerated library for the computation of field lines in fluid flows on high-performance computers. Streami acts as a thin layer used for both post-hoc or in-situ analysis and can interface with existing MPI applications. We discuss Streami's application programming interface, key design decisions that led to Streami's high performance and extensibility, as well as extensions to support different fluid flow field representations. We also present a sample application for rapid prototyping and interactive seed point placement. Streami is released under a permissive open-source software license.

cs.CE↗

arXiv2026

RAFI -- A Ray/Work Forwarding Infrastructure for Data Parallel Multi-Node/Multi-GPU Computing

We present RaFI, a CUDA and MPI based software framework that simplifies the task of building GPU-enabled data-parallel software where rays or similar work items need to migrate between different GPUs. RaFI provides a simple interface for CUDA kernels to forward such work items to other GPUs, while under the hood managing all the CUDA and MPI related work required to make this happen. We describe RaFI's motivation and implementation, and show its potential in several example applications.

cs.DC↗

arXiv2025

EuroHPC SPACE CoE: Redesigning Scalable Parallel Astrophysical Codes for Exascale

High Performance Computing (HPC) based simulations are crucial in Astrophysics and Cosmology (A&C), helping scientists investigate and understand complex astrophysical phenomena. Taking advantage of exascale computing capabilities is essential for these efforts. However, the unprecedented architectural complexity of exascale systems impacts legacy codes. The SPACE Centre of Excellence (CoE) aims to re-engineer key astrophysical codes to tackle new computational challenges by adopting innovative programming paradigms and software (SW) solutions. SPACE brings together scientists, code developers, HPC experts, hardware (HW) manufacturers, and SW developers. This collaboration enhances exascale A&C applications, promoting the use of exascale and post-exascale computing capabilities. Additionally, SPACE addresses high-performance data analysis for the massive data outputs from exascale simulations and modern observations, using machine learning (ML) and visualisation tools. The project facilitates application deployment across platforms by focusing on code repositories and data sharing, integrating European astrophysical communities around exascale computing with standardised SW and data protocols.

astro-ph.IM↗

arXiv2025

Dynamical friction and massive black hole orbits: analytical predictions and numerical solutions

We investigate the orbital decay of a massive BH embedded in a dark matter halo and a stellar bulge, using both analytical and numerical simulations with the aim of developing and validating a reliable dynamical friction (DF) correction across simulation resolutions. We develop a Python-based library to solve the equations of motion of the BH and provide an analytical framework for the numerical results. Then, we carry out simulations at different resolutions and for different softening choices using the Tree-PM code OpenGADGET3, where we implement an improved DF correction based on a kernel-weighted local density estimation. Our results demonstrate that the DF correction significantly accelerates BH sinking and ensures convergence with increasing resolution, closely matching analytical predictions. We find that in low-resolution regimes - particularly when the BH mass is smaller than that of the background particles - our DF model still effectively controls BH dynamics. Contrary to expectations, the inclusion of a stellar bulge can delay sinking due to numerical heating, an effect partially mitigated by the DF correction. We conclude that our refined DF implementation provides a robust framework for modeling BH dynamics both in controlled simulation setups of galaxies and in large-scale cosmological simulations. This will be crucial for future simulation campaigns, to enable more accurate predictions of AGN accretion and feedback, and to estimate gravitational-wave event rates.

astro-ph.GA↗

arXiv2025

GPU Volume Rendering with Hierarchical Compression Using VDB

We propose a compression-based approach to GPU rendering of large volumetric data using OpenVDB and NanoVDB. We use OpenVDB to create a lossy, fixed-rate compressed representation of the volume on the host, and use NanoVDB to perform fast, low-overhead, and on-the-fly decompression during rendering. We show that this approach is fast, works well even in a (incoherent) Monte Carlo path tracing context, can significantly reduce the memory requirements of volume rendering, and can be used as an almost drop-in replacement into existing 3D texture-based renderers.

cs.GR↗

arXiv2024

Standardized Data-Parallel Rendering Using ANARI

We propose and discuss a paradigm that allows for expressing \emph{data-parallel} rendering with the classically non-parallel ANARI API. We propose this as a new standard for data-parallel sci-vis rendering, describe two different implementations of this paradigm, and use multiple sample integrations into existing apps to show how easy it is to adopt this paradigm, and what can be gained from doing so.

cs.GR↗