Harnessing the Distributed Computing Paradigm for Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy allows fast and versatile elemental analysis, standing as a promising technique for a wide range of applications both at the research and industry levels. Yet, its high operation speed comes with a high throughput of data, which introduces some challenges at the level of the data processing domain, mainly due to the large computational load and data volume. In this work, we analyze and discuss opportunities of distributed computing paradigms and resources to address some of these challenges, covering most of the procedures usually employed in typical applications. We infer the possible impact of such computing resources by presenting some metrics of simple processing prototypes running in state-of-the-art computing facilities. Our results allow us to conclude that, while underexplored so far, these computing resources may allow for the development of tools for timely research and analysis in demanding applications and introduce novel solutions toward a more agile working environment.

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Publication Details

Journal
Big Data and Cognitive Computing
Published
2024-11-11
DOI
https://doi.org/10.3390/bdcc8110154
Primary Topic
Laser-induced spectroscopy and plasma
Type
article
Field-Weighted Citation Impact
0.00

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article

Harnessing the Distributed Computing Paradigm for Laser-Induced Breakdown Spectroscopy

Nuno A. Silva
Big Data and Cognitive Computing
Laser-induced spectroscopy and plasma
article

Harnessing the Distributed Computing Paradigm for Laser-Induced Breakdown Spectroscopy

Nuno A. Silva
article en

Abstract

Laser-induced breakdown spectroscopy allows fast and versatile elemental analysis, standing as a promising technique for a wide range of applications both at the research and industry levels. Yet, its high operation speed comes with a high throughput of data, which introduces some challenges at the level of the data processing domain, mainly due to the large computational load and data volume. In this work, we analyze and discuss opportunities of distributed computing paradigms and resources to address some of these challenges, covering most of the procedures usually employed in typical applications. We infer the possible impact of such computing resources by presenting some metrics of simple processing prototypes running in state-of-the-art computing facilities. Our results allow us to conclude that, while underexplored so far, these computing resources may allow for the development of tools for timely research and analysis in demanding applications and introduce novel solutions toward a more agile working environment.

Big Data and Cognitive ComputingVol. 8(11)
INESC TEC (PT)
Fundação para a Ciência e a Tecnologia
Industry, innovation and infrastructure
Openalex Percentile: Top 78%
Laser-induced spectroscopy and plasma
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Harnessing the Distributed Computing Paradigm for Laser-Induced Breakdown Spectroscopy — Nuno A. Silva · Big Data and Cognitive Computing (2024) | TGRS Research Map | TGRS