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The BondMachine toolkit: Enabling Machine Learning on FPGA

The BondMachine (BM) is an innovative prototype software ecosystem aimed at creating facilities where both hardware and software are co-designed, guaranteeing a full exploitation of fabric capabilities (both in terms of concurrency and heterogeneity) with the smallest possible power dissipation. In...

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Detalles Bibliográficos
Autores principales: Mariotti, Mirko, Storchi, Loriano, Spiga, Daniele, Salomoni, Davide, Boccali, Tommaso, Bonacorsi, Daniele
Lenguaje:eng
Publicado: SISSA 2019
Materias:
Acceso en línea:https://dx.doi.org/10.22323/1.351.0020
http://cds.cern.ch/record/2708682
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author Mariotti, Mirko
Storchi, Loriano
Spiga, Daniele
Salomoni, Davide
Boccali, Tommaso
Bonacorsi, Daniele
author_facet Mariotti, Mirko
Storchi, Loriano
Spiga, Daniele
Salomoni, Davide
Boccali, Tommaso
Bonacorsi, Daniele
author_sort Mariotti, Mirko
collection CERN
description The BondMachine (BM) is an innovative prototype software ecosystem aimed at creating facilities where both hardware and software are co-designed, guaranteeing a full exploitation of fabric capabilities (both in terms of concurrency and heterogeneity) with the smallest possible power dissipation. In the present paper we will provide a technical overview of the key aspects of the BondMachine toolkit, highlighting the advancements brought about by the porting of Go code in hardware. We will then show a cloud-based BM as a Service deployment. Finally, we will focus on TensorFlow, and in this context we will show how we plan to benchmark the system with a ML tracking reconstruction from pp collision at the LHC.
id oai-inspirehep.net-1766692
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
publisher SISSA
record_format invenio
spelling oai-inspirehep.net-17666922022-08-10T12:24:47Zdoi:10.22323/1.351.0020http://cds.cern.ch/record/2708682engMariotti, MirkoStorchi, LorianoSpiga, DanieleSalomoni, DavideBoccali, TommasoBonacorsi, DanieleThe BondMachine toolkit: Enabling Machine Learning on FPGAComputing and ComputersThe BondMachine (BM) is an innovative prototype software ecosystem aimed at creating facilities where both hardware and software are co-designed, guaranteeing a full exploitation of fabric capabilities (both in terms of concurrency and heterogeneity) with the smallest possible power dissipation. In the present paper we will provide a technical overview of the key aspects of the BondMachine toolkit, highlighting the advancements brought about by the porting of Go code in hardware. We will then show a cloud-based BM as a Service deployment. Finally, we will focus on TensorFlow, and in this context we will show how we plan to benchmark the system with a ML tracking reconstruction from pp collision at the LHC.SISSAoai:inspirehep.net:17666922019
spellingShingle Computing and Computers
Mariotti, Mirko
Storchi, Loriano
Spiga, Daniele
Salomoni, Davide
Boccali, Tommaso
Bonacorsi, Daniele
The BondMachine toolkit: Enabling Machine Learning on FPGA
title The BondMachine toolkit: Enabling Machine Learning on FPGA
title_full The BondMachine toolkit: Enabling Machine Learning on FPGA
title_fullStr The BondMachine toolkit: Enabling Machine Learning on FPGA
title_full_unstemmed The BondMachine toolkit: Enabling Machine Learning on FPGA
title_short The BondMachine toolkit: Enabling Machine Learning on FPGA
title_sort bondmachine toolkit: enabling machine learning on fpga
topic Computing and Computers
url https://dx.doi.org/10.22323/1.351.0020
http://cds.cern.ch/record/2708682
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