Data analysis at the CMS level-1 trigger: migrating complex selection algorithms from offline analysis and high-level trigger to the trigger electronics

The CMS experiment has been designed with a two-level trigger system: the Level-1 Trigger, implemented on custom-designed electronics, and the High Level Trigger, a streamlined version of the CMS offline reconstruction software running on a computer farm. During its second phase the LHC will reach a luminosity of 7.5 1034 cm−2 s−1 with a pileup of 200 collisions, producing integrated luminosity greater than 3000 fb−1 over the full experimental run. To fully exploit the higher luminosity, the CMS experiment will introduce a more advanced Level-1 Trigger and increase the full readout rate from 100 kHz to 750 kHz. CMS is designing an efficient data-processing hardware trigger that will include tracking information and high-granularity calorimeter information. The current Level-1 conceptual design is expected to take full advantage of advances in FPGA and link technologies over the coming years, providing a high-performance, low-latency system for large throughput and sophisticated data correlation across diverse sources. The higher luminosity, event complexity and input rate present an unprecedented challenge to the High Level Trigger that aims to achieve a similar efficiency and rejection factor as today despite the higher pileup and more pure preselection. In this presentation we will discuss the ongoing studies and prospects for the online reconstruction and selection algorithms for the high-luminosity era.

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CMS trigger performance

EPJ Web of Conferences ◽

10.1051/epjconf/201818202037 ◽

2018 ◽

Vol 182 ◽

pp. 02037

Author(s):

Silvio Donato

Keyword(s):

Computing Time ◽

Track Reconstruction ◽

Trigger System ◽

Drastic Reduction ◽

Event Selection ◽

Level Trigger ◽

Reconstruction Software ◽

Last Stage ◽

Level 1 ◽

High Level

During its second run of operation (Run 2), started in 2015, the LHC will deliver a peak instantaneous luminosity that may reach 2 · 1034 cm-2s-1 with an average pileup of about 55, far larger than the design value. Under these conditions, the online event selection is a very challenging task. In CMS, it is realized by a two-level trigger system: the Level-1 (L1) Trigger, implemented in custom-designed electronics, and the High Level Trigger (HLT), a streamlined version of the offine reconstruction software running on a computer farm. In order to face this challenge, the L1 trigger has been through a major upgrade compared to Run 1, whereby all electronic boards of the system have been replaced, allowing more sophisticated algorithms to be run online. Its last stage, the global trigger, is now able to perform complex selections and to compute high-level quantities, like invariant masses. Likewise, the algorithms that run in the HLT have been greatly improved; in particular, new approaches for the online track reconstruction lead to a drastic reduction of the computing time, and to much improved performances. This document will describe the performance of the upgraded trigger system in Run 2.

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Reconstruction of track candidates at the LHC crossing rate using FPGAs

EPJ Web of Conferences ◽

10.1051/epjconf/202024510001 ◽

2020 ◽

Vol 245 ◽

pp. 10001

Author(s):

Giulia Tuci ◽

Giovanni Punzi

Keyword(s):

Real Time ◽

Average Rate ◽

Computational Effort ◽

Lhcb Experiment ◽

Level Trigger ◽

Full Reconstruction ◽

Potential Benefits ◽

Level 1 ◽

High Level ◽

New System

In 2021 the LHCb experiment will be upgraded, and the DAQ system will be based on full reconstruction of events, at the full LHC crossing rate. This requires an entirely new system, capable of reading out, building and reconstructing events at an average rate of 30 MHz. In facing this challenge, the system could take advantage of a fast pre-processing of data on dedicated FPGAs. The results of an R&D on these technologies, developed in the context of the LHCb Upgrade I, are presented in this document. In particular, the details and potential benefits of an approach based on producing in real-time sorted collections of hits in the VELO detector (pre-tracks) are discussed. These pre-processed data can then be used as seeds by the High Level Trigger (HLT) farm to find tracks for the Level 1 trigger with much lower computational effort than possible by starting from the raw detector data, thus freeing an important fraction of the power of the CPU farm for higher level processing tasks.

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The CMS high level trigger

International Journal of Modern Physics Conference Series ◽

10.1142/s201019451460297x ◽

2014 ◽

Vol 31 ◽

pp. 1460297 ◽

Cited By ~ 1

Author(s):

Valentina Gori

Keyword(s):

Trigger System ◽

Output Rate ◽

Computing Power ◽

Level Trigger ◽

Cms Experiment ◽

Pile Up ◽

Reconstruction Software ◽

Physics Performance ◽

Level 1 ◽

High Level

The CMS experiment has been designed with a 2-level trigger system: the Level 1 Trigger, implemented on custom-designed electronics, and the High Level Trigger (HLT), a streamlined version of the CMS offline reconstruction software running on a computer farm. A software trigger system requires a tradeoff between the complexity of the algorithms running on the available computing power, the sustainable output rate, and the selection efficiency. Here we will present the performance of the main triggers used during the 2012 data taking, ranging from simpler single-object selections to more complex algorithms combining different objects, and applying analysis-level reconstruction and selection. We will discuss the optimisation of the triggers and the specific techniques to cope with the increasing LHC pile-up, reducing its impact on the physics performance.

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The Impact of Applying Wildcards to Disabled Modules for Ftk Pattern Banks on Efficiency and Data Flow

EPJ Web of Conferences ◽

10.1051/epjconf/201921401039 ◽

2019 ◽

Vol 214 ◽

pp. 01039

Author(s):

Khalil Bouaouda ◽

Stefan Schmitt ◽

Driss Benchekroun

Keyword(s):

Early Stage ◽

Hadron Collider ◽

Track Reconstruction ◽

Trigger System ◽

Level Trigger ◽

Efficiency Losses ◽

Level 1 ◽

High Level ◽

The Impact ◽

Fast Tracker

Online selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities for identifying interesting physics processes through track-based signatures. The FTK is reconstructing after each Level-1 trigger all tracks with pT > 1 GeV, such that the high-level trigger system gains access to track information at an early stage. FTK track reconstruction starts with a pattern recognition step. Patterns are found with hits in seven out of eight possible detector layers. Disabled detector modules, as often encountered during LHC operation, lead to efficiency losses. To recover efficiency, WildCards (WC) algorithms are implemented in the FTK system. The WC algorithm recovers inefficiency but also causes high combinatorial background and thus increased data volumes in the FTK system, possibly exceeding hardware limitations. To overcome this, a refined algorithm to select patterns is developed and investigated in this article.

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Trigger Rate Monitoring Tools at CMS

EPJ Web of Conferences ◽

10.1051/epjconf/201921401047 ◽

2019 ◽

Vol 214 ◽

pp. 01047

Author(s):

Andrew Wightman ◽

Geoffrey Smith ◽

Kelci Mohrman ◽

Charles Mueller

Keyword(s):

Event Rate ◽

Trigger System ◽

Level Trigger ◽

Cms Experiment ◽

Trigger Rate ◽

Monitoring Tools ◽

Pile Up ◽

Overall Performance ◽

Level 1 ◽

High Level

One of the major challenges for the Compact Muon Solenoid (CMS)experiment, is the task of reducing event rate from roughly 40 MHz down to a more manageable 1 kHz while keeping as many interesting physics events as possible. This is accomplished through the use of a Level-1 (L1) hardware based trigger as well as a software based High-Level Trigger (HLT). Monitoring and understanding the output rates of the L1 and HLT triggers is of key importance for determining the overall performance of the trigger system and is intimately tied to what type of data is being recorded for physics analyses. We present here a collection of tools used by CMS to monitor the L1 and HLT trigger rates. One of these tools is a script (run in the CMS control room) that gives valuable real-time feedback of trigger rates to the shift crew. Another useful tool is a plotting library, that is used for observing how trigger rates vary over a range of beam and detector conditions, in particular how the rates of individual triggers scale with event pile-up.

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Operational experience with the new CMS DAQ-Expert

EPJ Web of Conferences ◽

10.1051/epjconf/201921401015 ◽

2019 ◽

Vol 214 ◽

pp. 01015 ◽

Cited By ~ 1

Author(s):

Jean-Marc Andre ◽

Ulf Behrens ◽

James Branson ◽

Philipp Brummer ◽

Sergio Cittolin ◽

...

Keyword(s):

Expert Knowledge ◽

Operational Experience ◽

Trigger System ◽

Web Based ◽

High Data ◽

Software Applications ◽

Level Trigger ◽

Level 1 ◽

Logic Modules ◽

High Level

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.

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Recording and reconstructing 10 billion unbiased b hadron decays in CMS

EPJ Web of Conferences ◽

10.1051/epjconf/202024501025 ◽

2020 ◽

Vol 245 ◽

pp. 01025

Author(s):

Robert Bainbridge

Keyword(s):

Data Stream ◽

High Efficiency ◽

Data Set ◽

Level Trigger ◽

Cms Experiment ◽

Trigger Strategy ◽

Reconstruction Performance ◽

Level 1 ◽

High Level ◽

New Algorithms

The CMS experiment has recorded a high-purity sample of 10 billion unbiased b hadron decays. The CMS trigger and data acquisition systems were configured to deliver a custom data stream at an average throughput of 2 GB s−1, which was “parked” prior to reconstruction. The data stream was defined by level-1 and high level trigger algorithms that operated at peak trigger rates in excess of 50 and 5 kHz, respectively. New algorithms have been developed to reconstruct and identify electrons with high efficiency at transverse momenta as low as 0.5 GeV. The trigger strategy and electron reconstruction performance were validated with pilot processing campaigns. The accumulation and reconstruction of this data set, now complete, were delivered without significant impact on the core physics programme of CMS. This unprecedented sample provides a unique opportunity for physics analyses in the flavour sector and beyond.

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The ATLAS electron and photon trigger performance in Run 2

International Journal of Modern Physics A ◽

10.1142/s0217751x20440078 ◽

2020 ◽

Vol 35 (34n35) ◽

pp. 2044007

Author(s):

Daniela Maria Köck

Keyword(s):

Large Hadron Collider ◽

Hadron Collider ◽

Final States ◽

Atlas Experiment ◽

Level Trigger ◽

Level 1 ◽

High Level ◽

Electron And Photon

Electron and photon triggers are an important part of many physics analyses at the ATLAS experiment, where electron and photon final states are considered. Understanding the performance of electron and photon triggers at the High Level trigger as well as the Level-1 trigger was crucial to improve and adapt the trigger during changing run conditions of the Large Hadron Collider in Run 2 (2015–2018).

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Evolution of the ALICE Software Framework for Run 3

EPJ Web of Conferences ◽

10.1051/epjconf/201921405010 ◽

2019 ◽

Vol 214 ◽

pp. 05010 ◽

Cited By ~ 1

Author(s):

Giulio Eulisse ◽

Piotr Konopka ◽

Mikolaj Krzewicki ◽

Matthias Richter ◽

David Rohr ◽

...

Keyword(s):

Data Processing ◽

Data Model ◽

Message Passing ◽

Software Framework ◽

Distributed Software ◽

Central Collisions ◽

Modular Software ◽

Level Trigger ◽

Data Throughput ◽

High Level

ALICE is one of the four major LHC experiments at CERN. When the accelerator enters the Run 3 data-taking period, starting in 2021, ALICE expects almost 100 times more Pb-Pb central collisions than now, resulting in a large increase of data throughput. In order to cope with this new challenge, the collaboration had to extensively rethink the whole data processing chain, with a tighter integration between Online and Offline computing worlds. Such a system, code-named ALICE O2, is being developed in collaboration with the FAIR experiments at GSI. It is based on the ALFA framework which provides a generalized implementation of the ALICE High Level Trigger approach, designed around distributed software entities coordinating and communicating via message passing. We will highlight our efforts to integrate ALFA within the ALICE O2 environment. We analyze the challenges arising from the different running environments for production and development, and conclude on requirements for a flexible and modular software framework. In particular we will present the ALICE O2 Data Processing Layer which deals with ALICE specific requirements in terms of Data Model. The main goal is to reduce the complexity of development of algorithms and managing a distributed system, and by that leading to a significant simplification for the large majority of the ALICE users.

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