Performance of Lossless Data Compression Algorithms in the CMS Experiment

The High-Level Trigger (HLT) of the Compact Muon Solenoid (CMS) processes event data in real time, applying selection criteria to reduce the data rate from hundreds of kHz to around 5 kHz for raw data offline storage. Efficient lossless compression algorithms, such as LZMA and ZSTD, are essential in minimizing these storage requirements while maintaining easy access for subsequent analysis. Multiple compression techniques are currently employed in the experiment's trigger system. In this study, we benchmark the performance of existing lossless compression algorithms used in HLT for RAW data storage, evaluating their efficiency in terms of compression ratio, processing time, and CPU/memory usage. In addition, we investigate the potential improvements given by the introduction, in the CMSSW software framework, of RNTuples: the next-generation data storage format developed within the ROOT ecosystem. We explore how the new format can enhance data handling efficiency and reduce storage footprints compared to traditional storage solutions. With the upcoming Phase-2 upgrade of the CMS experiment, efficient compression strategies will be essential to ensure sustainable data processing and storage capabilities. This work provides insights into the different compression algorithms and how the new RNTuples data format can contribute to addressing the future data challenges of the CMS experiment.