https://doi.org/10.1051/epjconf/202429511015
Optimising the Configuration of the CMS GPU Reconstruction
1 University of Bahrain
2 CERN
* e-mail: asubah@uob.edu.bh
Published online: 6 May 2024
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.
© The Authors, published by EDP Sciences, 2024
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.
