| Article | |
| Title | Optimising the Configuration of the CMS GPU Reconstruction |
| Author(s) | Ebrahim, Abdulla (Bahrain U.) ; Bocci, Andrea (CERN) ; Elmedany, Wael (Bahrain U.) ; Al-Ammal, Hesham (Bahrain U.) |
| Publication | 2024 |
| Number of pages | 7 |
| In: | EPJ Web Conf. 295 (2024) 11015 |
| In: | 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023, pp.11015 |
| DOI | 10.1051/epjconf/202429511015 |
| Subject category | Computing and Computers |
| Accelerator/Facility, Experiment | CERN LHC ; CMS |
| Abstract | Particle track reconstruction for high energy physics experiments like CMS is computationally demanding but can benefit from GPU acceleration if properly tuned. This work develops an autotuning framework to automatically optimise the throughput of GPU-accelerated CUDA kernels in CMSSW. The proposed system navigates the complex parameter space by generating configurations, benchmarking performance, and leveraging multi-fidelity optimisation from simplified applications. The autotuned launch parameters improved CMSSW tracking throughput over the default settings by finding optimised, GPU-specific configurations. The successful application of autotuning to CMSSW demonstrates both performance portability across diverse accelerators and the potential of the methodology to optimise other HEP codebases. |
| Copyright/License | publication: © 2024 The authors (License: CC-BY-4.0) |
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Element opprettet 2024-12-11, sist endret 2024-12-11