The ATLAS online High Level Trigger framework: Experience reusing offline software components in the ATLAS trigger

The Belle II experiment is designed to collect 50 times more data than its predecessor. For a smooth collection of high-quality data, a robust and automated data transport and processing pipeline has been established. We describe the basic software components employed by the high level trigger. It performs a reconstruction of all events using the same algorithms as offline, classifies the events according to physics criteria, and provides monitoring information. The improved system described in this paper has been deployed successfully since 2019.

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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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Commissioning of the ATLAS High Level Trigger with single beam and cosmic rays

Journal of Physics Conference Series ◽

10.1088/1742-6596/219/2/022006 ◽

2010 ◽

Vol 219 (2) ◽

pp. 022006 ◽

Cited By ~ 1

Author(s):

A Di Mattia ◽

the Atlas Collaboration

Keyword(s):

Cosmic Rays ◽

Single Beam ◽

Level Trigger ◽

High Level

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The CMS High-Level Trigger

10.1063/1.3293780 ◽

2009 ◽

Cited By ~ 2

Author(s):

R. Covarelli ◽

Marvin L. Marshak

Keyword(s):

Level Trigger ◽

High Level

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High Level Trigger for the channel in fully hadronic decay at LHC with the CMS detector

Nuclear Physics B - Proceedings Supplements ◽

10.1016/j.nuclphysbps.2005.01.072 ◽

2005 ◽

Vol 142 ◽

pp. 426-429 ◽

Cited By ~ 2

Author(s):

D. Benedetti ◽

L. Fanò ◽

M. Biasini

Keyword(s):

Hadronic Decay ◽

Level Trigger ◽

Cms Detector ◽

High Level

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ATLAS Sim@P1 upgrades during long shutdown two

EPJ Web of Conferences ◽

10.1051/epjconf/202024507044 ◽

2020 ◽

Vol 245 ◽

pp. 07044

Author(s):

Frank Berghaus ◽

Franco Brasolin ◽

Alessandro Di Girolamo ◽

Marcus Ebert ◽

Colin Roy Leavett-Brown ◽

...

Keyword(s):

Large Hadron Collider ◽

Data Acquisition ◽

Process Simulation ◽

Hadron Collider ◽

Simulation Data ◽

Level Trigger ◽

Offline Processing ◽

High Level

The Simulation at Point1 (Sim@P1) project was built in 2013 to take advantage of the ATLAS Trigger and Data Acquisition High Level Trigger (HLT) farm. The HLT farm provides around 100,000 cores, which are critical to ATLAS during data taking. When ATLAS is not recording data, such as the long shutdowns of the LHC, this large compute resource is used to generate and process simulation data for the experiment. At the beginning of the second long shutdown of the large hadron collider, the HLT farm including the Sim@P1 infrastructure was upgraded. Previous papers emphasised the need for simple, reliable, and efficient tools and assessed various options to quickly switch between data acquisition operation and offline processing. In this contribution, we describe the new mechanisms put in place for the opportunistic exploitation of the HLT farm for offline processing and give the results from the first months of operation.

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The CMS Trigger Upgrade for the HL-LHC

EPJ Web of Conferences ◽

10.1051/epjconf/202024501031 ◽

2020 ◽

Vol 245 ◽

pp. 01031

Author(s):

Thiago Rafael Fernandez Perez Tomei

Keyword(s):

High Performance ◽

Second Phase ◽

Level Trigger ◽

Cms Experiment ◽

Rejection Factor ◽

Reconstruction Software ◽

Efficient Data ◽

Level 1 ◽

High Level ◽

Selection Algorithms

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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