SoC-based pattern recognition systems for Non Destructive Testing

Omar Schiaratura; Pietro Ansaloni; Giovanni Lughi; Mattia Neri; Matteo Roffilli; Fabrizio Serpi; Andrea Simonetto

doi:10.1007/978-3-319-27926-8_18

SoC-based pattern recognition systems for Non Destructive Testing

Omar Schiaratura
, Pietro Ansaloni
, Giovanni Lughi
, Mattia Neri
, Matteo Roffilli
, Fabrizio Serpi
, Andrea Simonetto

CRS4 S.c.a.r.l.
Bioretics Srl

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

Résumé

Non Destructive Testing (NDT) is one of the most important aspect in modern manufacturing companies. Automation of this task improves productivity and reliability of distribution chains. We present an optimized implementation of common pattern recognition algorithms that performs NDT on factory products. To the aim of enhancing the industrial integration, our implementation is highly optimized to work on SoC-based (System on Chip: an integrated circuit that integrates all components of a computer into a single chip.) hardware and we worked with the initial idea of an overall design for these devices. While perfectly working on general purpose SoCs, the best performances are achieved on GPU accelerated ones. We reached the notable performance of a PC-based workstation by exploiting technologies like CUDA and BLAS for embedded SoCs. The test case is a collection of toy scenarios commonly found in manufacturing companies.

langue originale	Anglais
titre	Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers
rédacteurs en chef	Mario Pavone, Giovanni Maria Farinella, Vincenzo Cutello, Panos Pardalos
Editeur	Springer Verlag
Pages	209-221
Nombre de pages	13
ISBN (imprimé)	9783319279251
Les DOIs	https://doi.org/10.1007/978-3-319-27926-8_18
état	Publié - 1 janv. 2015
Modification externe	Oui
Evénement	1st International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015 - Taormina, Sicily, Italie Durée: 21 juil. 2015 → 23 juil. 2015

Série de publications

Nom	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9432
ISSN (imprimé)	0302-9743
ISSN (Electronique)	1611-3349

Une conférence

Une conférence	1st International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015
Pays/Territoire	Italie
La ville	Taormina, Sicily
période	21/07/15 → 23/07/15

Accès au document

10.1007/978-3-319-27926-8_18

Autres fichiers et liens

Lien vers la publication dans Scopus

Contient cette citation

Schiaratura, O., Ansaloni, P., Lughi, G., Neri, M., Roffilli, M., Serpi, F., & Simonetto, A. (2015). SoC-based pattern recognition systems for Non Destructive Testing. Dans M. Pavone, G. M. Farinella, V. Cutello, & P. Pardalos (eds.), Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers (p. 209-221). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 9432). Springer Verlag. https://doi.org/10.1007/978-3-319-27926-8_18

Schiaratura, Omar ; Ansaloni, Pietro ; Lughi, Giovanni et al. / SoC-based pattern recognition systems for Non Destructive Testing. Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers. Editeur / Mario Pavone ; Giovanni Maria Farinella ; Vincenzo Cutello ; Panos Pardalos. Springer Verlag, 2015. p. 209-221 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{e6b0b57f214e4a99bdbab48ef5a453b8,

title = "SoC-based pattern recognition systems for Non Destructive Testing",

abstract = "Non Destructive Testing (NDT) is one of the most important aspect in modern manufacturing companies. Automation of this task improves productivity and reliability of distribution chains. We present an optimized implementation of common pattern recognition algorithms that performs NDT on factory products. To the aim of enhancing the industrial integration, our implementation is highly optimized to work on SoC-based (System on Chip: an integrated circuit that integrates all components of a computer into a single chip.) hardware and we worked with the initial idea of an overall design for these devices. While perfectly working on general purpose SoCs, the best performances are achieved on GPU accelerated ones. We reached the notable performance of a PC-based workstation by exploiting technologies like CUDA and BLAS for embedded SoCs. The test case is a collection of toy scenarios commonly found in manufacturing companies.",

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Schiaratura, O, Ansaloni, P, Lughi, G, Neri, M, Roffilli, M, Serpi, F & Simonetto, A 2015, SoC-based pattern recognition systems for Non Destructive Testing. Dans M Pavone, GM Farinella, V Cutello & P Pardalos (eds), Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), VOL. 9432, Springer Verlag, p. 209-221, 1st International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015, Taormina, Sicily, Italie, 21/07/15. https://doi.org/10.1007/978-3-319-27926-8_18

SoC-based pattern recognition systems for Non Destructive Testing. / Schiaratura, Omar; Ansaloni, Pietro; Lughi, Giovanni et al.
Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers. Ed. / Mario Pavone; Giovanni Maria Farinella; Vincenzo Cutello; Panos Pardalos. Springer Verlag, 2015. p. 209-221 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 9432).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

TY - GEN

T1 - SoC-based pattern recognition systems for Non Destructive Testing

AU - Schiaratura, Omar

AU - Ansaloni, Pietro

AU - Lughi, Giovanni

AU - Neri, Mattia

AU - Roffilli, Matteo

AU - Serpi, Fabrizio

AU - Simonetto, Andrea

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Non Destructive Testing (NDT) is one of the most important aspect in modern manufacturing companies. Automation of this task improves productivity and reliability of distribution chains. We present an optimized implementation of common pattern recognition algorithms that performs NDT on factory products. To the aim of enhancing the industrial integration, our implementation is highly optimized to work on SoC-based (System on Chip: an integrated circuit that integrates all components of a computer into a single chip.) hardware and we worked with the initial idea of an overall design for these devices. While perfectly working on general purpose SoCs, the best performances are achieved on GPU accelerated ones. We reached the notable performance of a PC-based workstation by exploiting technologies like CUDA and BLAS for embedded SoCs. The test case is a collection of toy scenarios commonly found in manufacturing companies.

AB - Non Destructive Testing (NDT) is one of the most important aspect in modern manufacturing companies. Automation of this task improves productivity and reliability of distribution chains. We present an optimized implementation of common pattern recognition algorithms that performs NDT on factory products. To the aim of enhancing the industrial integration, our implementation is highly optimized to work on SoC-based (System on Chip: an integrated circuit that integrates all components of a computer into a single chip.) hardware and we worked with the initial idea of an overall design for these devices. While perfectly working on general purpose SoCs, the best performances are achieved on GPU accelerated ones. We reached the notable performance of a PC-based workstation by exploiting technologies like CUDA and BLAS for embedded SoCs. The test case is a collection of toy scenarios commonly found in manufacturing companies.

KW - ARM

KW - CUDA

KW - Non-destructive testing

KW - OpenCL

KW - SoC

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DO - 10.1007/978-3-319-27926-8_18

M3 - Conference contribution

AN - SCOPUS:84955270360

SN - 9783319279251

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 209

EP - 221

BT - Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers

A2 - Pavone, Mario

A2 - Farinella, Giovanni Maria

A2 - Cutello, Vincenzo

A2 - Pardalos, Panos

PB - Springer Verlag

T2 - 1st International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015

Y2 - 21 July 2015 through 23 July 2015

ER -

Schiaratura O, Ansaloni P, Lughi G, Neri M, Roffilli M, Serpi F et al. SoC-based pattern recognition systems for Non Destructive Testing. Dans Pavone M, Farinella GM, Cutello V, Pardalos P, rédacteurs en chef, Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers. Springer Verlag. 2015. p. 209-221. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-27926-8_18

SoC-based pattern recognition systems for Non Destructive Testing

Résumé

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Une conférence

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