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CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data

We will present the latest developments in CutLang, the runtime interpreter of a recently-developed analysis description language (ADL) for collider data analysis. ADL is a domain-specific, declarative language that describes the contents of an analysis in a standard and unambiguous way, independent...

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Detalles Bibliográficos
Autores principales: Unel, G., Sekmen, S., Toon, A. M., Gokturk, B., Orgen, B., Paul, A., Ravel, N., Setpal, J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218547/
https://www.ncbi.nlm.nih.gov/pubmed/34169274
http://dx.doi.org/10.3389/fdata.2021.659986
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author Unel, G.
Sekmen, S.
Toon, A. M.
Gokturk, B.
Orgen, B.
Paul, A.
Ravel, N.
Setpal, J.
author_facet Unel, G.
Sekmen, S.
Toon, A. M.
Gokturk, B.
Orgen, B.
Paul, A.
Ravel, N.
Setpal, J.
author_sort Unel, G.
collection PubMed
description We will present the latest developments in CutLang, the runtime interpreter of a recently-developed analysis description language (ADL) for collider data analysis. ADL is a domain-specific, declarative language that describes the contents of an analysis in a standard and unambiguous way, independent of any computing framework. In ADL, analyses are written in human-readable plain text files, separating object, variable and event selection definitions in blocks, with a syntax that includes mathematical and logical operations, comparison and optimisation operators, reducers, four-vector algebra and commonly used functions. Adopting ADLs would bring numerous benefits to the LHC experimental and phenomenological communities, ranging from analysis preservation beyond the lifetimes of experiments or analysis software to facilitating the abstraction, design, visualization, validation, combination, reproduction, interpretation and overall communication of the analysis contents. Since their initial release, ADL and CutLang have been used for implementing and running numerous LHC analyses. In this process, the original syntax from CutLang v1 has been modified for better ADL compatibility, and the interpreter has been adapted to work with that syntax, resulting in the current release v2. Furthermore, CutLang has been enhanced to handle object combinatorics, to include tables and weights, to save events at any analysis stage, to benefit from multi-core/multi-CPU hardware among other improvements. In this contribution, these and other enhancements are discussed in details. In addition, real life examples from LHC analyses are presented together with a user manual.
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spelling pubmed-82185472021-06-23 CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data Unel, G. Sekmen, S. Toon, A. M. Gokturk, B. Orgen, B. Paul, A. Ravel, N. Setpal, J. Front Big Data Big Data We will present the latest developments in CutLang, the runtime interpreter of a recently-developed analysis description language (ADL) for collider data analysis. ADL is a domain-specific, declarative language that describes the contents of an analysis in a standard and unambiguous way, independent of any computing framework. In ADL, analyses are written in human-readable plain text files, separating object, variable and event selection definitions in blocks, with a syntax that includes mathematical and logical operations, comparison and optimisation operators, reducers, four-vector algebra and commonly used functions. Adopting ADLs would bring numerous benefits to the LHC experimental and phenomenological communities, ranging from analysis preservation beyond the lifetimes of experiments or analysis software to facilitating the abstraction, design, visualization, validation, combination, reproduction, interpretation and overall communication of the analysis contents. Since their initial release, ADL and CutLang have been used for implementing and running numerous LHC analyses. In this process, the original syntax from CutLang v1 has been modified for better ADL compatibility, and the interpreter has been adapted to work with that syntax, resulting in the current release v2. Furthermore, CutLang has been enhanced to handle object combinatorics, to include tables and weights, to save events at any analysis stage, to benefit from multi-core/multi-CPU hardware among other improvements. In this contribution, these and other enhancements are discussed in details. In addition, real life examples from LHC analyses are presented together with a user manual. Frontiers Media S.A. 2021-06-07 /pmc/articles/PMC8218547/ /pubmed/34169274 http://dx.doi.org/10.3389/fdata.2021.659986 Text en Copyright © 2021 Unel, Sekmen, Toon, Gokturk, Orgen, Paul, Ravel and Setpal. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Unel, G.
Sekmen, S.
Toon, A. M.
Gokturk, B.
Orgen, B.
Paul, A.
Ravel, N.
Setpal, J.
CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data
title CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data
title_full CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data
title_fullStr CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data
title_full_unstemmed CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data
title_short CutLang v2: Advances in a Runtime-Interpreted Analysis Description Language for HEP Data
title_sort cutlang v2: advances in a runtime-interpreted analysis description language for hep data
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218547/
https://www.ncbi.nlm.nih.gov/pubmed/34169274
http://dx.doi.org/10.3389/fdata.2021.659986
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