Extending the FairRoot framework to allow for simulation and reconstruction of free streaming data

Al-Turany, M.; Klein, D.; Manafov, Anar; Rybalchenko, A.; Uhlig, F.

doi:10.1088/1742-6596/513/2/022001

Cited by 14 publications

(8 citation statements)

References 2 publications

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“…To coordinate the processing of the data and to simplify the task of writing algorithms by physicists, ALICE developed a software framework, named Data Processing Layer [5] (DPL), which hides the complexities of having to deal with a distributed system and presents a traditional, task based, interface to the user. In such a framework the user provides a high level description of the computation, specifying inputs and outputs and how to process the former to obtain the latter, and the DPL takes care of creating the actual distributed topology implemented using the message passing toolkit FairMQ [3]. All the data processing needs of the experiment, from data taking to analysis will be provided by such a framework, ensuring familiarity to the user and reducing the maintenance effort.…”

Section: Data Processing Layermentioning

confidence: 99%

“…In order to tackle the challenge, the software and computing experts will have to work in close collaboration with the physics community in order to organise the analysis efforts. Moreover a close collaboration with the GSI Helmholtzzentrum für Schwerionenforschung and the Facility for Antiproton and Ion Research (FAIR) has been established on a common software stack [3].…”

Section: Introductionmentioning

confidence: 99%

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Preparation for ALICE data processing and analysis in LHC Run 3

Eulisse¹

2022

Proceedings of the European Physical Society Conference on High Energy Physics — PoS(EPS-HEP2021)

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After the ALICE Long Shutdown 2 detector upgrades, including a new silicon tracker and a GEM-based readout for the TPC, the experiment will operate during LHC Run 3 at a peak Pb-Pb collision rate of 50 kHz, about 50 times higher than in previous running periods. To maximise the significance of physics signals with low S/B ratios for which triggering is not possible, all events will be read out and written to permanent storage without any selective trigger. In order to minimise the costs and computing time of the online and offline systems, data volume reduction is performed synchronous with data taking on the newly installed Online/Offline facility O 2 . The facility consists of two types of compute nodes, the First Level Processors (FLP) and the Event Processing Nodes (EPN). Each FLP receives data from parts of individual detectors, performs a first level of data compression by zero suppression as well as calibration tasks, and sends its output to the EPNs over an InfiniBand network. Using the EPN's CPU cores and GPUs, data is reconstructed and further compressed. Moreover, data for detector calibration is created. Online data processing is followed by offline reconstruction passes using fully calibrated data producing the input for data analysis (AOD). In addition, large samples of simulated data as input for detector response and performance studies will be produced.Here we describe the data processing chain and give an overview of the design choices and implementations for the newly developed software frameworks, which can cope with the unprecedented data rates and volumes. The status of the preparation for data processing and analysis in view of the first physics runs in 2022 is presented.

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Section: Data Processing Layermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Preparation for ALICE data processing and analysis in LHC Run 3

Eulisse¹

2022

Proceedings of the European Physical Society Conference on High Energy Physics — PoS(EPS-HEP2021)

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“…It derives originally from ALICE High Level Trigger architecture [4], a message-passing multiprocess system, used in Run 1 and 2, and consists of three major components, the transport layer, the data model and the data processing layer. The transport layer of the system, a component that provides inter-process communication, is implemented using the FairMQ [5] message passing toolkit, defining the core blocks of the architecture in terms of FairMQDevices (devices) and their communication in a medium-agnostic way. A shared-memory-backed message passing transport for devices running on the same computing node is available.…”

Section: Alice Software Frameworkmentioning

confidence: 99%

ALICE Run 3 Analysis Framework

et al. 2021

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In LHC Run 3 the ALICE Collaboration will have to cope with an increase of lead-lead collision data of two orders of magnitude compared to the Run 1 and 2 data-taking periods. The Online-Offline (O2) software framework has been developed to allow for distributed and efficient processing of this unprecedented amount of data. Its design, which is based on a message-passing back end, required the development of a dedicated Analysis Framework that uses the columnar data format provided by Apache Arrow. The O2 Analysis Framework provides a user-friendly high-level interface and hides the complexity of the underlying distributed framework. It allows the users to access and manipulate the data in the new format both in the traditional “event loop” and a declarative approach using bulk processing operations based on Arrow’s Gandiva sub-project. Building on the well-tested system of analysis trains developed by ALICE in Run 1 and 2, the AliHyperloop infrastructure is being developed. It provides a fast and intuitive user interface for running demanding analysis workflows in the GRID environment and on the dedicated Analysis Facility. In this document, we report on the current state and ongoing developments of the Analysis Framework and of AliHyperloop, highlighting the design choices and the benefits of the new system.

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“…The main software framework of the BM@N experiment is BmnRoot [7] serving for raw data conversion, realistic simulation and processing of interaction events. The development of the framework was started in 2014 based on the ROOT and FairRoot [8] environments to avoid many software issues and not submerge into low-level details. To study physics feasibilities of the experiment, BmnRoot supports a wide list of Monte-Carlo event generators with the proper physics effects.…”

Section: Offline Software Systems Of the Bm@n Experimentsmentioning

confidence: 99%

Software Development for the BM@N Experiment at NICA: Challenges and Status

et al. 2020

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A new generation of experiments on relativistic nuclear physics is planned to be started in the nearest years at the Nuclotron-based Ion Collider facility (NICA) under construction at the Joint Institute for Nuclear Research in Dubna. The fixed target experiment BM@N (Baryonic Matter at Nuclotron) is considered as a first stage towards the implementation of the physics program available at NICA. For a successful accomplishment of the BM@N physics program, a well-developed and tested software package for simulation, digitization, reconstruction and analysis of collision events and other supporting tasks is of utmost importance. The data flow scheme of the experiment is shown. Offine and online software systems, such as the main BmnRoot framework, databases of the experiment, data monitoring and others providing information support for the experiment are presented. The implementation of the software systems is a necessary stage for the successful operation of the BM@N experiment.

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Extending the FairRoot framework to allow for simulation and reconstruction of free streaming data

Cited by 14 publications

References 2 publications

Preparation for ALICE data processing and analysis in LHC Run 3

Preparation for ALICE data processing and analysis in LHC Run 3

ALICE Run 3 Analysis Framework

Software Development for the BM@N Experiment at NICA: Challenges and Status

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