R&D: Design of Distributed Key-Value Store for Petascale Hot Storage in Data Acquisition Systems

EDP Sciences has published, in EPJ Web of Conferences (Volume 214, 2019, 23^rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018), an article written by Danilo Cicalese, European Laboratory for Particle Physics, CERN, Geneva 23, CH-1211, Switzerland, Grzegorz Jereczek, Intel Technology Poland, ul. Slowackiego 173, 80-298 Gdansk, Poland, Fabrice Le Goff, Giovanna Lehmann Miotto, European Laboratory for Particle Physics, CERN, Geneva 23, CH-1211, Switzerland, Jeremy Love, Argonne National Laboratory 9700 S. Cass Avenue, IL 60439, Argonne, USA, Maciej Maciejewski, Intel Technology Poland, ul. Slowackiego 173, 80-298 Gdansk, Poland, Remigius K Mommsen, Fermi National Accelerator Laboratory Batavia, IL 60510, USA, Jakub Radtke, Jakub Schmiegel, Intel Technology Poland, ul. Slowackiego 173, 80-298 Gdansk, Poland, and Malgorzata Szychowska, European Laboratory for Particle Physics, CERN, Geneva 23, CH-1211, Switzerland.

Abstract: “Data acquisition systems for high energy physics experiments readout terabytes of data per second from a large number of electronic components. They are thus inherently distributed systems and require fast online data selection, otherwise requirements for permanent storage would be enormous. Still, incoming data need to be buffered while waiting for this selection to happen. Each minute of an experiment can produce hundreds of terabytes that cannot be lost before a selection decision is made. In this context, we present the design of DAQDB (Data Acquisition Database) — a distributed key-value store for high-bandwidth, generic data storage in event-driven systems. DAQDB offers not only high-capacity and low-latency buffer for fast data selection, but also opens a new approach in high-bandwidth data acquisition by decoupling the lifetime of the data analysis processes from the changing event rate due to the duty cycle of the data source. This is achievable by the option to extend its capacity even up to hundreds of petabytes to store hours of an experiment’s data. Our initial performance evaluation shows that DAQDB is a promising alternative to generic database solutions for the high luminosity upgrades of the LHC at CERN.“

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