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Analysis Tools for the VyPR Performance Analysis Framework for Python
VyPR (http://pyvypr.github.io/home/) is a framework being developed with the aim of automating as much as possible the performance analysis of Python programs. To achieve this, it uses an analysis-by-specification approach; developers specify the performance requirements of their programs (without a...
Autores principales: | , , , , |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1051/epjconf/202024505013 http://cds.cern.ch/record/2757348 |
_version_ | 1780969977691504640 |
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author | Dawes, Joshua Heneage Han, Marta Reger, Giles Franzoni, Giovanni Pfeiffer, Andreas |
author_facet | Dawes, Joshua Heneage Han, Marta Reger, Giles Franzoni, Giovanni Pfeiffer, Andreas |
author_sort | Dawes, Joshua Heneage |
collection | CERN |
description | VyPR (http://pyvypr.github.io/home/) is a framework being developed with the aim of automating as much as possible the performance analysis of Python programs. To achieve this, it uses an analysis-by-specification approach; developers specify the performance requirements of their programs (without any modifications of the source code) and such requirements are checked at runtime. VyPR then provides tools which allow developers to perform detailed analyses of the performance of their code. Such analyses can include determining the common paths taken to reach badly performing parts of code, deciding whether a single path through code led to variations in time taken by future observations, and more.This paper describes the developments that have taken place in the past year on VyPR’s analysis tools to yield a Python shell-based analysis library, and a web-based application. It concludes by demonstrating the use of the analysis tools on the CMS Experiment’s Conditions Upload service. |
id | oai-inspirehep.net-1831597 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
record_format | invenio |
spelling | oai-inspirehep.net-18315972021-03-22T22:08:57Zdoi:10.1051/epjconf/202024505013http://cds.cern.ch/record/2757348engDawes, Joshua HeneageHan, MartaReger, GilesFranzoni, GiovanniPfeiffer, AndreasAnalysis Tools for the VyPR Performance Analysis Framework for PythonComputing and ComputersVyPR (http://pyvypr.github.io/home/) is a framework being developed with the aim of automating as much as possible the performance analysis of Python programs. To achieve this, it uses an analysis-by-specification approach; developers specify the performance requirements of their programs (without any modifications of the source code) and such requirements are checked at runtime. VyPR then provides tools which allow developers to perform detailed analyses of the performance of their code. Such analyses can include determining the common paths taken to reach badly performing parts of code, deciding whether a single path through code led to variations in time taken by future observations, and more.This paper describes the developments that have taken place in the past year on VyPR’s analysis tools to yield a Python shell-based analysis library, and a web-based application. It concludes by demonstrating the use of the analysis tools on the CMS Experiment’s Conditions Upload service.oai:inspirehep.net:18315972020 |
spellingShingle | Computing and Computers Dawes, Joshua Heneage Han, Marta Reger, Giles Franzoni, Giovanni Pfeiffer, Andreas Analysis Tools for the VyPR Performance Analysis Framework for Python |
title | Analysis Tools for the VyPR Performance Analysis Framework for Python |
title_full | Analysis Tools for the VyPR Performance Analysis Framework for Python |
title_fullStr | Analysis Tools for the VyPR Performance Analysis Framework for Python |
title_full_unstemmed | Analysis Tools for the VyPR Performance Analysis Framework for Python |
title_short | Analysis Tools for the VyPR Performance Analysis Framework for Python |
title_sort | analysis tools for the vypr performance analysis framework for python |
topic | Computing and Computers |
url | https://dx.doi.org/10.1051/epjconf/202024505013 http://cds.cern.ch/record/2757348 |
work_keys_str_mv | AT dawesjoshuaheneage analysistoolsforthevyprperformanceanalysisframeworkforpython AT hanmarta analysistoolsforthevyprperformanceanalysisframeworkforpython AT regergiles analysistoolsforthevyprperformanceanalysisframeworkforpython AT franzonigiovanni analysistoolsforthevyprperformanceanalysisframeworkforpython AT pfeifferandreas analysistoolsforthevyprperformanceanalysisframeworkforpython |