Presentation
Scalable In-Situ Visualization for Extreme-Scale SPH Simulations
DescriptionLarge-scale scientific simulations present significant challenges in data processing efficiency.
This paper addresses the critical issue of I/O and data processing performance bottlenecks within the domain of extreme-scale Smoothed-particle Hydrodynamics (SPH) and gravity simulations.
We present a novel I/O software architecture implemented in the scalable SPH-EXA framework, incorporating a variety of in-situ and post-hoc data analysis pipelines, facilitating rapid analysis and visualization of extreme-scale physical datasets.
The performance of our I/O architecture is evaluated through comprehensive benchmarking across a wide range of data scales, conducted on the Piz Daint supercomputer.
This paper addresses the critical issue of I/O and data processing performance bottlenecks within the domain of extreme-scale Smoothed-particle Hydrodynamics (SPH) and gravity simulations.
We present a novel I/O software architecture implemented in the scalable SPH-EXA framework, incorporating a variety of in-situ and post-hoc data analysis pipelines, facilitating rapid analysis and visualization of extreme-scale physical datasets.
The performance of our I/O architecture is evaluated through comprehensive benchmarking across a wide range of data scales, conducted on the Piz Daint supercomputer.