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 part of the CMS Data Acquisition (DAQ) system responsible for data readout and event building is a complex network of interdependent distributed applications. To ensure successful data taking, ...these programs have to be constantly monitored in order to facilitate the timeliness of necessary corrections in case of any deviation from specified behaviour. A large number of diverse monitoring data samples are periodically collected from multiple sources across the network. Monitoring data are kept in memory for online operations and optionally stored on disk for post-mortem analysis. We present a generic, reusable solution based on an open source NoSQL database, Elasticsearch, which is fully compatible and non-intrusive with respect to the existing system. The motivation is to benefit from an offthe-shelf software to facilitate the development, maintenance and support efforts. Elasticsearch provides failover and data redundancy capabilities as well as a programming language independent JSON-over-HTTP interface. The possibility of horizontal scaling matches the requirements of a DAQ
monitoring system. The data load from all sources is balanced by redistribution over an Elasticsearch cluster that can be hosted on a computer cloud. In order to achieve the necessary robustness and to validate the scalability of the approach the above monitoring solution currently runs in parallel with an existing in-house developed DAQ monitoring system.
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.
The Compact Muon Solenoid (CMS) is one of the experiments at the CERN Large Hadron Collider (LHC). The CMS Online Monitoring system (OMS) is an upgrade and successor to the CMS Web-Based Monitoring ...(WBM)system, which is an essential tool for shift crew members, detector subsystem experts, operations coordinators, and those performing physics analyses. The CMS OMS is divided into aggregation and presentation layers. Communication between layers uses RESTful JSON:API compliant requests. The aggregation layer is responsible for collecting data from heterogeneous sources, storage of transformed and pre-calculated (aggregated) values and exposure of data via the RESTful API. The presentation layer displays detector information via a modern, user-friendly and customizable web interface. The CMS OMS user interface is composed of a set of cutting-edge software frameworks and tools to display non-event data to any authenticated CMS user worldwide. The web interface tree-like component structure comprises (top-down): workspaces, folders, pages, controllers and portlets. A clear hierarchy gives the required flexibility and control for content organization. Each bottom element instantiates a portlet and is a reusable component that displays a single aspect of data, like a table, a plot, an article, etc. Pages consist of multiple different portlets and can be customized at runtime by using a drag-and-drop technique. This is how a single page can easily include information from multiple online sources. Different pages give access to a summary of the current status of the experiment, as well as convenient access to historical data. This paper describes the CMS OMS architecture, core concepts and technologies of the presentation layer.
The data acquisition system (DAQ) of the CMS experiment at the CERN Large Hadron Collider (LHC) assembles events of 2MB at a rate of 100 kHz. The event builder collects event fragments from about 750 ...sources and assembles them into complete events which are then handed to the High-Level Trigger (HLT) processes running on
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(1000) computers. The aging eventbuilding hardware will be replaced during the long shutdown 2 of the LHC taking place in 2019/20. The future data networks will be based on 100 Gb/s interconnects using Ethernet and Infiniband technologies. More powerful computers may allow to combine the currently separate functionality of the readout and builder units into a single I/O processor handling simultaneously 100 Gb/s of input and output traffic. It might be beneficial to preprocess data originating from specific detector parts or regions before handling it to generic HLT processors. Therefore, we will investigate how specialized coprocessors, e.g. GPUs, could be integrated into the event builder. We will present the envisioned changes to the event-builder compared to today’s system. Initial measurements of the performance of the data networks under the event-building traffic pattern will be shown. Implications of a folded network architecture for the event building and corresponding changes to the software implementation will be discussed.
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.
The production of strange hadrons ($ {\textrm{K}}_{\textrm{S}}^0 $, Λ, Ξ$^{±}$, and Ω$^{±}$), baryon-to-meson ratios (Λ/$ {\textrm{K}}_{\textrm{S}}^0 $, Ξ/$ {\textrm{K}}_{\textrm{S}}^0 $, and Ω/$ ...{\textrm{K}}_{\textrm{S}}^0 $), and baryon-to-baryon ratios (Ξ/Λ, Ω/Λ, and Ω/Ξ) associated with jets and the underlying event were measured as a function of transverse momentum (p$_{T}$) in pp collisions at $ \sqrt{s} $ = 13 TeV and p Pb collisions at $ \sqrt{s_{\textrm{NN}}} $ = 5.02 TeV with the ALICE detector at the LHC. The inclusive production of the same particle species and the corresponding ratios are also reported. The production of multi-strange hadrons, Ξ$^{±}$ and Ω$^{±}$, and their associated particle ratios in jets and in the underlying event are measured for the first time. In both pp and p–Pb collisions, the baryon-to-meson and baryon-to-baryon yield ratios measured in jets differ from the inclusive particle production for low and intermediate hadron p$_{T}$ (0.6–6 GeV/c). Ratios measured in the underlying event are in turn similar to those measured for inclusive particle production. In pp collisions, the particle production in jets is compared with Pythia 8 predictions with three colour-reconnection implementation modes. None of them fully reproduces the data in the measured hadron p$_{T}$ region. The maximum deviation is observed for Ξ$^{±}$ and Ω$^{±}$ which reaches a factor of about six. The event multiplicity dependence is further investigated in p−Pb collisions. In contrast to what is observed in the underlying event, there is no significant event-multiplicity dependence for particle production in jets. The presented measurements provide novel constraints on hadronisation and its Monte Carlo description. In particular, they demonstrate that the fragmentation of jets alone is insufficient to describe the strange and multi-strange particle production in hadronic collisions at LHC energies.graphic not available: see fulltext
Two-particle correlations with $\textrm{K}^{0}_\mathrm{{S}}$, $\Lambda $/$\overline{\Lambda }$, and charged hadrons as trigger particles in the transverse momentum range ...$8{<}p_{{\textrm{T}},{\textrm{trig}}}{<}16$ GeV/$c$, and associated charged particles within $1{<}p_{{\textrm{T}},{\textrm{assoc}}}{<}8$ GeV/$c$, are studied at midrapidity in pp and central Pb–Pb collisions at a centre-of-mass energy per nucleon–nucleon collision $\sqrt{s_{\textrm{NN}}}~=~5.02$ TeV with the ALICE detector at the LHC. After subtracting the contributions of the flow background, the per-trigger yields are extracted on both the near and away sides, and the ratio in Pb–Pb collisions with respect to pp collisions ($I_{\textrm{AA}}$) is computed. The per-trigger yield in Pb–Pb collisions on the away side is strongly suppressed to the level of $I_{\textrm{AA}}\approx 0.6$ for $p_{{\textrm{T}},{\textrm{assoc}}}>3$ GeV/$c$ as expected from strong in-medium energy loss, while an enhancement develops at low $p_{{\textrm{T}},{\textrm{assoc}}}$ on both the near and away sides, reaching $I_{\textrm{AA}}\approx 1.8$ and 2.7 respectively. These findings are in good agreement with previous ALICE measurements from two-particle correlations triggered by neutral pions ($\pi ^{0}$–h) and charged hadrons (h–h) in Pb–Pb collisions at $\sqrt{s_{\textrm{NN}}}~=~2.76$ TeV. Moreover, the correlations with $\textrm{K}^{0}_\mathrm{{S}}$ mesons and $\Lambda $/$\overline{\Lambda }$ baryons as trigger particles are compared to those of inclusive charged hadrons. The results are compared with the predictions of Monte Carlo models.
Two-particle angular correlations are measured in high-multiplicity proton-proton collisions at $ \sqrt{s} $ = 13 TeV by the ALICE Collaboration. The yields of particle pairs at short-(∆η ∼ 0) and ...long-range (1.6 < |∆η| < 1.8) in pseudorapidity are extracted on the near-side (∆φ ∼ 0). They are reported as a function of transverse momentum (p$_{T}$) in the range 1 < p$_{T}$< 4 GeV/c. Furthermore, the event-scale dependence is studied for the first time by requiring the presence of high-p$_{T}$ leading particles or jets for varying p$_{T}$ thresholds. The results demonstrate that the long-range “ridge” yield, possibly related to the collective behavior of the system, is present in events with high-p$_{T}$ processes as well. The magnitudes of the short- and long-range yields are found to grow with the event scale. The results are compared to EPOS LHC and PYTHIA 8 calculations, with and without string-shoving interactions. It is found that while both models describe the qualitative trends in the data, calculations from EPOS LHC show a better quantitative agreement for the p$_{T}$ dependency, while overestimating the event-scale dependency.graphic not available: see fulltext
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