Taking on RISC for Energy-Efficient Computing in HEP
In pursuit of energy-efficient solutions for computing in High Energy Physics (HEP) we have extended our investigations of non-x86 architectures beyond the ARM platforms that we have previously studied. In this work, we have taken a first look at the RISC-V architecture for HEP workloads, leveraging advancements in both hardware and software maturity. We introduce the Pioneer Milk-V, a 64-core RISC-V machine running Fedora Linux, as our new testbed, available at ScotGrid Glasgow (UK) and INFN Bologna and Pisa (Italy). Despite this early stage of RISC-V adoption in HEP, significant progress has been made in software compatibility. Standard frameworks such as ROOT, Geant4, CVMFS, and XRootD can be successfully built and run on the RISC-V platform, showcasing the evolving ecosystem. Additionally, efforts are underway to port CMSSW, promising further integration of HEP experiment software. In this first study, we assess performance and power efficiency, and we leverage various benchmarking tools to compare the RISC-V system with existing ARM and x86 architectures. Although it is not yet possible to run the HEPScore suite, we have conducted other tests such as running ROOT, DB12 and Geant4 benchmarks, while assessing and comparing performance per Watt across various platforms. These early results suggest that RISC-V architecture, despite being still immature for large scale adoption, holds potential for entering the increasingly heterogeneous computing landscape of HEP.
Authors
- T. Boccali (ORCID: https://orcid.org/0000-0002-9930-9299)
- Shahzad Muzaffar (ORCID: https://orcid.org/0000-0001-9237-1148)
- A. G. Borbély
- Samuel Cadellin Skipsey
- Gordon Stewart
- D. Britton (ORCID: https://orcid.org/0000-0001-9998-4342)
- E. Simili
Institutions
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (IT)
- European Organization for Nuclear Research (CH)
- University of Glasgow (GB)
Publication Details
- Journal
- EPJ Web of Conferences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1051/epjconf/202533701163
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- University of Glasgow