| Issue |
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 7 | |
| Section | 1 - Online and Real-time Computing | |
| DOI | https://doi.org/10.1051/epjconf/202024501001 | |
| Published online | 16 November 2020 | |
https://doi.org/10.1051/epjconf/202024501001
Fast and Efficient Entropy Compression of ALICE Data using ANS Coding
CERN, Technische Universität München
* e-mail: michael.lettrich@cern.ch
Published online: 16 November 2020
In LHC Run 3, the upgraded ALICE detector will record 50 kHz Pb-Pb collisions using continuous readout. The resulting stream of raw data to be inspected increases to ~ 1 TB/s a hundredfold increase over Run 2 must be processed with a set of lossy and lossless compression and data reduction techniques to decrease the data rate to storage to 90 GB/s without affecting the physics.
This contribution focuses on lossless entropy coding for ALICE Run 3 data which is the final component in the compression stage. We analyze data from the ALICE TPC and point out the challenges imposed by the non-standard data with a patchy distribution and symbol sizes of up to 25 Bit. We then explain why rANS, a variant of Asymmetric Numeral System coders is suitable for compressing this data effectively. Finally we present first compression performance numbers and bandwidth measurements obtained from a prototype implementation and give an outlook for future developments.
© The Authors, published by EDP Sciences, 2020
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.