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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Machine Learning, Optimization, and Big Data - 1st International Workshop, MOD 2015 Taormina, Revised Selected Papers
Editors	Mario Pavone, Giovanni Maria Farinella, Vincenzo Cutello, Panos Pardalos
Publisher	Springer Verlag
Pages	209-221
Number of pages	13
ISBN (Print)	9783319279251
DOIs	https://doi.org/10.1007/978-3-319-27926-8_18
Publication status	Published - 1 Jan 2015
Externally published	Yes
Event	1st International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015 - Taormina, Sicily, Italy Duration: 21 Jul 2015 → 23 Jul 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9432
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015
Country/Territory	Italy
City	Taormina, Sicily
Period	21/07/15 → 23/07/15

Keywords

ARM
CUDA
Non-destructive testing
OpenCL
SoC

Access to Document

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

Cite this

Schiaratura, O., Ansaloni, P., Lughi, G., Neri, M., Roffilli, M., Serpi, F., & Simonetto, A. (2015). SoC-based pattern recognition systems for Non Destructive Testing. In 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 (pp. 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. editor / Mario Pavone ; Giovanni Maria Farinella ; Vincenzo Cutello ; Panos Pardalos. Springer Verlag, 2015. pp. 209-221 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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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author = "Omar Schiaratura and Pietro Ansaloni and Giovanni Lughi and Mattia Neri and Matteo Roffilli and Fabrizio Serpi and Andrea Simonetto",

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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. in 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, pp. 209-221, 1st International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015, Taormina, Sicily, Italy, 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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. In Pavone M, Farinella GM, Cutello V, Pardalos P, editors, 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

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