Boosting I/O and visualization for exascale era using Hercule: test case on RAMSES

TL;DR

This paper presents Hercule, a new parallel I/O library integrated with Ramses to improve I/O performance and flexibility for exascale astrophysical simulations, enabling better visualization and data management.

Contribution

Hercule library enhances Ramses by splitting output formats, boosting I/O scalability, and providing flexible data management for exascale applications.

Findings

Improved I/O performance and scalability for Ramses.

Enhanced flexibility in simulation data management.

Significant performance gains in analysis and visualization tools.

Abstract

It has been clearly identified that I/O is one of the bottleneck to extend application for the exascale era. New concepts such as 'in transit' and 'in situ' visualization and analysis have been identified as key technologies to circumvent this particular issue. A new parallel I/O and data management library called Hercule, developed at CEA-DAM, has been integrated to Ramses, an AMR simulation code for self-gravitating fluids. Splitting the original Ramses output format in Hercule database formats dedicated to either checkpoints/restarts (HProt format) or post-processing (HDep format) not only improved I/O performance and scalability of the Ramses code but also introduced much more flexibility in the simulation outputs to help astrophysicists prepare their DMP (Data Management Plan). Furthermore, the very lightweight and purpose-specific post-processing format (HDep) will significantly improve the overall performance of analysis and visualization tools such as PyMSES 5. An introduction to the Hercule parallel I/O library as well as I/O benchmark results will be discussed.