| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01028 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/epjconf/202533701028 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701028
Enabling Alternative Architectures in the ALICE Grid
1 CERN, Esplanade des Particules 1, Meyrin, Switzerland
2 University of Moratuwa, Bandaranayake Mawatha, Moratuwa, Sri Lanka
* e-mail: mstoretv@cern.ch
Published online: 7 October 2025
The ALICE Collaboration is exploring the use of Arm resources for the execution of Grid payloads. This was prompted by both their recent availability in the WLCG, as well as their increased competitiveness with traditional x86-based hosts in terms of both cost and performance. With the number of manufacturers providing Arm offerings aimed towards servers and HPC growing, the presence of these resources in the Grid is anticipated to rise further. Consequently, it becomes a priority to ensure the underlying middleware is capable of running across architectures, ensuring available resources in the Grid are fully utilised.
This contribution outlines a reworked middleware stack, now used in production within ALICE, capable of running jobs across both Amd64 and Aarch64 ISAs, and the initial findings when used to execute Grid jobs compiled for the latter. Furthermore, it will examine how the middleware stack is able to dynamcally match packages and binaries depending on the host. This makes both the selection process and executing architecture transparent for the end-user. At the same time, an overview is provided of how the middleware remains agnostic to the underlying architecture, allowing it to scale across various other types of CPUs – enabling support for additional architectures beyond Arm if needed, such as RISC-V.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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