Related papers: In-Situ High Performance Visualization for Astrono…
Implicit neural representations (INRs) have emerged as a powerful tool for compressing large-scale volume data. This opens up new possibilities for in situ visualization. However, the efficient application of INRs to distributed data…
Heterogeneity has been an indispensable aspect of distributed computing throughout the history of these systems. In particular, with the increasing prevalence of accelerator technologies (e.g., GPUs and TPUs) and the emergence of…
The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously…
High-quality, usable, and effective software is essential for supporting astronomers in the discovery-focused tasks of data analysis and visualisation. As the volume, and perhaps more crucially, the velocity of astronomical data grows, the…
For large-scale scientific simulations, it is expensive to store raw simulation results to perform post-analysis. To minimize expensive I/O, "in-situ" analysis is often used, where analysis applications are tightly coupled with scientific…
Remote sensing image scene classification remains a challenging task, primarily due to the complex spatial structures and multi-scale characteristics of ground objects. Although CNN-based methods excel at extracting local inductive biases,…
Cosmological simulations are the key tool for investigating the different processes involved in the formation of the universe from small initial density perturbations to galaxies and clusters of galaxies observed today. The identification…
Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific…
An important topic in medical research is the process of improving the images obtained from medical devices. As a consequence, there is also a need to improve medical image resolution and analysis. Another issue in this field is the large…
The amount of data generated by numerical simulations in various scientific domains such as molecular dynamics, climate modeling, biology, or astrophysics, led to a fundamental redesign of application workflows. The throughput and the…
As astronomy enters the petascale data era, astronomers are faced with new challenges relating to storage, access and management of data. A shift from the traditional approach of combining data and analysis at the desktop to the use of…
Agent-based cellular models simulate tissue evolution by capturing the behavior of individual cells, their interactions with neighboring cells, and their responses to the surrounding microenvironment. An important challenge in the field is…
The size of astronomical observational data is increasing yearly. For example, while Atacama Large Millimeter/submillimeter Array is expected to generate 200 TB raw data every year, Large Synoptic Survey Telescope is estimated to produce 15…
The emergence of large-scale AI models, like GPT-4, has significantly impacted academia and industry, driving the demand for high-performance computing (HPC) to accelerate workloads. To address this, we present HPCClusterScape, a…
Blue Brain has pushed high-performance visualization (HPV) to complement its HPC strategy since its inception in 2007. In 2011, this strategy has been accelerated to develop innovative visualization solutions through increased funding and…
Upcoming astronomical surveys produce imagery that spans many orders of magnitude in spatial scale, requiring scientists to reason fluidly between global structure and local detail. Data from the Vera C. Rubin Observatory exemplifies this…
Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision…
As software systems increase in complexity, conventional monitoring methods struggle to provide a comprehensive overview or identify performance issues, often missing unexpected problems. Observability, however, offers a holistic approach,…
We introduce NebulOS, a Big Data platform that allows a cluster of Linux machines to be treated as a single computer. With NebulOS, the process of writing a massively parallel program for a datacenter is no more complicated than writing a…
Understanding of the structure evolution in the Universe has been greatly advanced with a rapid progress in high-resolution cosmological simulations. In this contribution, we report a new set of cosmological simulations with $512^3$ ($\sim…