Nanosurveyor: a framework for real-time data processing

BACKGROUND: The ever improving brightness of accelerator based sources is enabling novel observations and discoveries with faster frame rates, larger fields of view, higher resolution, and higher dimensionality. RESULTS: Here we present an integrated software/algorithmic framework designed to capita...

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Detalles Bibliográficos
Autores principales: Daurer, Benedikt J., Krishnan, Hari, Perciano, Talita, Maia, Filipe R. N. C., Shapiro, David A., Sethian, James A., Marchesini, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313566/
https://www.ncbi.nlm.nih.gov/pubmed/28261545
http://dx.doi.org/10.1186/s40679-017-0039-0
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author Daurer, Benedikt J.
Krishnan, Hari
Perciano, Talita
Maia, Filipe R. N. C.
Shapiro, David A.
Sethian, James A.
Marchesini, Stefano
author_facet Daurer, Benedikt J.
Krishnan, Hari
Perciano, Talita
Maia, Filipe R. N. C.
Shapiro, David A.
Sethian, James A.
Marchesini, Stefano
author_sort Daurer, Benedikt J.
collection PubMed
description BACKGROUND: The ever improving brightness of accelerator based sources is enabling novel observations and discoveries with faster frame rates, larger fields of view, higher resolution, and higher dimensionality. RESULTS: Here we present an integrated software/algorithmic framework designed to capitalize on high-throughput experiments through efficient kernels, load-balanced workflows, which are scalable in design. We describe the streamlined processing pipeline of ptychography data analysis. CONCLUSIONS: The pipeline provides throughput, compression, and resolution as well as rapid feedback to the microscope operators.
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spelling pubmed-53135662017-03-01 Nanosurveyor: a framework for real-time data processing Daurer, Benedikt J. Krishnan, Hari Perciano, Talita Maia, Filipe R. N. C. Shapiro, David A. Sethian, James A. Marchesini, Stefano Adv Struct Chem Imaging Research BACKGROUND: The ever improving brightness of accelerator based sources is enabling novel observations and discoveries with faster frame rates, larger fields of view, higher resolution, and higher dimensionality. RESULTS: Here we present an integrated software/algorithmic framework designed to capitalize on high-throughput experiments through efficient kernels, load-balanced workflows, which are scalable in design. We describe the streamlined processing pipeline of ptychography data analysis. CONCLUSIONS: The pipeline provides throughput, compression, and resolution as well as rapid feedback to the microscope operators. Springer International Publishing 2017-01-31 2017 /pmc/articles/PMC5313566/ /pubmed/28261545 http://dx.doi.org/10.1186/s40679-017-0039-0 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Daurer, Benedikt J.
Krishnan, Hari
Perciano, Talita
Maia, Filipe R. N. C.
Shapiro, David A.
Sethian, James A.
Marchesini, Stefano
Nanosurveyor: a framework for real-time data processing
title Nanosurveyor: a framework for real-time data processing
title_full Nanosurveyor: a framework for real-time data processing
title_fullStr Nanosurveyor: a framework for real-time data processing
title_full_unstemmed Nanosurveyor: a framework for real-time data processing
title_short Nanosurveyor: a framework for real-time data processing
title_sort nanosurveyor: a framework for real-time data processing
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313566/
https://www.ncbi.nlm.nih.gov/pubmed/28261545
http://dx.doi.org/10.1186/s40679-017-0039-0
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