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da Silva Gomes, Diego

Publications and source records attributed to da Silva Gomes, Diego.

Operational experience with the new CMS DAQ-Expert

The data acquisition (DAQ) system of the Compact Muon Solenoid (CMS) at CERN reads out the detector at the level-1 trigger accept rate of 100 kHz, assembles events with a bandwidth of 200 GB/s, provides these events to the high level-trigger running on a farm of about 30k cores and records the accepted events. Comprising custom-built and cutting edge commercial hardware and several 1000 instances of software applications, the DAQ system is complex in itself and failures cannot be completely excluded. Moreover, problems in the readout of the detectors,in the first level trigger system or in the high level trigger may provoke anomalous behaviour of the DAQ systemwhich sometimes cannot easily be differentiated from a problem in the DAQ system itself. In order to achieve high data taking efficiency with operators from the entire collaboration and without relying too heavily on the on-call experts, an expert system, the DAQ-Expert, has been developed that can pinpoint the source of most failures and give advice to the shift crew on how to recover in the quickest way. The DAQ-Expert constantly analyzes monitoring data from the DAQ system and the high level trigger by making use of logic modules written in Java that encapsulate the expert knowledge about potential operational problems. The results of the reasoning are presented to the operator in a web-based dashboard, may trigger sound alerts in the control room and are archived for post-mortem analysis - presented in a web-based timeline browser. We present the design of the DAQ-Expert and report on the operational experience since 2017, when it was first put into production.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Experience with dynamic resource provisioning of the CMS online cluster using a cloud overlay

The primary goal of the online cluster of the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is to build event data from the detector and to select interesting collisions in the High Level Trigger (HLT) farm for offline storage. With more than 1500 nodes and a capacity of about 850 kHEPSpecInt06, the HLT machines represent similar computing capacity of all the CMS Tier1 Grid sites together. Moreover, it is currently connected to the CERN IT datacenter via a dedicated 160 Gbps network connection and hence can access the remote EOS based storage with a high bandwidth. In the last few years, a cloud overlay based on OpenStack has been commissioned to use these resources for the WLCG when they are not needed for data taking. This online cloud facility was designed for parasitic use of the HLT, which must never interfere with its primary function as part of the DAQ system. It also allows to abstract from the different types of machines and their underlying segmented networks. During the LHC technical stop periods, the HLT cloud is set to its static mode of operation where it acts like other grid facilities. The online cloud was also extended to make dynamic use of resources during periods between LHC fills. These periods are a-priori unscheduled and of undetermined length, typically of several hours, once or more a day. For that, it dynamically follows LHC beam states and hibernates Virtual Machines (VM) accordingly. Finally, this work presents the design and implementation of a mechanism to dynamically ramp up VMs when the DAQ load on the HLT reduces towards the end of the fill.

97 MATHEMATICS AND COMPUTING↗