C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA

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We report the latest development in ROOT/TMVA, a new system that takes trained ONNX deep learning models and emits C++ code that can be easily included and invoked for fast inference of the model, with minimal dependency. We present an overview of the current solutions for conducting inference in C+...

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Detalles Bibliográficos
Autores principales: An, Sitong, Moneta, Lorenzo
Lenguaje:eng
Publicado: 2021
Materias:
Computing and Computers
Acceso en línea:https://dx.doi.org/10.1051/epjconf/202125103040
http://cds.cern.ch/record/2780369
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author An, Sitong
Moneta, Lorenzo
author_facet An, Sitong
Moneta, Lorenzo
author_sort An, Sitong
collection CERN
description We report the latest development in ROOT/TMVA, a new system that takes trained ONNX deep learning models and emits C++ code that can be easily included and invoked for fast inference of the model, with minimal dependency. We present an overview of the current solutions for conducting inference in C++ production environment, discuss the technical details and examples of the generated code, and demonstrates its development status with a preliminary benchmark against popular tools.
id cern-2780369
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
record_format invenio
spelling cern-27803692021-09-07T19:17:05Zdoi:10.1051/epjconf/202125103040http://cds.cern.ch/record/2780369engAn, SitongMoneta, LorenzoC++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVAComputing and ComputersWe report the latest development in ROOT/TMVA, a new system that takes trained ONNX deep learning models and emits C++ code that can be easily included and invoked for fast inference of the model, with minimal dependency. We present an overview of the current solutions for conducting inference in C++ production environment, discuss the technical details and examples of the generated code, and demonstrates its development status with a preliminary benchmark against popular tools.oai:cds.cern.ch:27803692021
spellingShingle Computing and Computers
An, Sitong
Moneta, Lorenzo
C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
title C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
title_full C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
title_fullStr C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
title_full_unstemmed C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
title_short C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
title_sort c++ code generation for fast inference of deep learning models in root/tmva
topic Computing and Computers
url https://dx.doi.org/10.1051/epjconf/202125103040
http://cds.cern.ch/record/2780369
work_keys_str_mv AT ansitong ccodegenerationforfastinferenceofdeeplearningmodelsinroottmva
AT monetalorenzo ccodegenerationforfastinferenceofdeeplearningmodelsinroottmva

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