Fast and Efficient Entropy Compression of ALICE Data using ANS Coding

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

Fast Entropy Coding for ALICE Run 3

In LHC Run 3, the upgraded ALICE detector will record Pb-Pb collisions at a rate of 50 kHz usingcontinuous readout. The resulting stream of raw data at 3.5 TB/s has to be processed with a setof lossy and lossless compression and data reduction techniques to a storage data rate of 90 GB/swhile preserving relevant data for physics analysis. This contribution presents a custom losslessdata compression scheme based on entropy coding as the final component in the data reductionchain which has to compress the data rate from 300 GB/s to 90 GB/s. A flexible, multi-processarchitecture for the data compression scheme is proposed that seamlessly interfaces with the datareduction algorithms of earlier stages and allows to use parallel processing in order to keep therequired firm real-time guarantees of the system. The data processed inside the compressionprocess have a structure that allows the use of an rANS entropy coder with more resource efficientstatic distribution tables. Extensions to the rANS entropy coder are introduced to efficientlywork with these static distribution tables and large but sparse source alphabets consisting of upto 25 Bit per symbol. Preliminary performance results show compliance with the firm real-timerequirements while offering close-to-optimal data compression

Prototype of Automated PLC Model Checking Using Continuous Integration Tools

To deal with the complexity of operating and supervising large scale industrial installations at CERN, often Programmable Logic Controllers (PLCs) are used. A failure in these control systems can cause a disaster in terms of economic loses, environmental damages or human losses. Therefore the requirements to software quality are very high. To provide PLC developers with a way to verify proper functionality against requirements, a Java tool named PLCverif has been developed which encapsulates and thus simplifies the use of third party model checkers. One of our goals in this project is to integrate PLCverif in development process of PLC programs. When the developer changes the program, all the requirements should be verified again, as a change on the code can produce collateral effects and violate one or more requirements. For that reason, PLCverif has been extended to work with Jenkins CI in order to trigger automatically the verication cases when the developer changes the PLC program. This prototype has been used in real-life PLC programs at CERN and its potential have been recognized

Multiplicity dependence of light (anti-)nuclei production in p–Pb collisions at sNN=5.02 TeV

The measurement of the deuteron and anti-deuteron production in the rapidity range −1 < y < 0 as a function of transverse momentum and event multiplicity in p–Pb collisions at √sNN = 5.02 TeV is presented. (Anti-)deuterons are identified via their specific energy loss dE/dx and via their time-of- flight. Their production in p–Pb collisions is compared to pp and Pb–Pb collisions and is discussed within the context of thermal and coalescence models. The ratio of integrated yields of deuterons to protons (d/p) shows a significant increase as a function of the charged-particle multiplicity of the event starting from values similar to those observed in pp collisions at low multiplicities and approaching those observed in Pb–Pb collisions at high multiplicities. The mean transverse particle momenta are extracted from the deuteron spectra and the values are similar to those obtained for p and particles. Thus, deuteron spectra do not follow mass ordering. This behaviour is in contrast to the trend observed for non-composite particles in p–Pb collisions. In addition, the production of the rare 3He and 3He nuclei has been studied. The spectrum corresponding to all non-single diffractive p-Pb collisions is obtained in the rapidity window −1 < y < 0 and the pT-integrated yield dN/dy is extracted. It is found that the yields of protons, deuterons, and 3He, normalised by the spin degeneracy factor, follow an exponential decrease with mass number

The FEROL40, a microTCA card interfacing custom point-to-point links and standard TCP/IP

In order to accommodate new back-end electronics of upgraded CMS sub-detectors, a new FEROL40 card in the microTCA standard has been developed. The main function of the FEROL40 is to acquire event data over multiple point-to-point serial optical links, provide buffering, perform protocol conversion, and transmit multiple TCP/IP streams (4x10Gbps) to the Ethernet network of the aggregation layer of the CMS DAQ (data acquisition) event builder. This contribution discusses the design of the FEROL40 and experience from operation

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

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

CMS DAQ current and future hardware upgrades up to post Long Shutdown 3 (LS3) times

Following the first LHC collisions seen and recorded by CMS in 2009, the DAQ hardware went through a major upgrade during LS1 (2013- 2014) and new detectors have been connected during 2015-2016 and 2016-2017 winter shutdowns. Now, LS2 (2019-2020) and LS3 (2024-mid 2026) are actively being prepared. This paper shows how CMS DAQ hardware has evolved from the beginning and will continue to evolve in order to meet the future challenges posed by High Luminosity LHC (HL-LHC) and the CMS detector evolution. In particular, post LS3 DAQ architectures are focused upon

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 system which 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