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FPGA Correlator for Applications in Embedded Smart Devices

Correlation has a variety of applications that require signal processing. However, it is computationally intensive, and software correlators require high-performance processors for real-time data analysis. This is a challenge for embedded devices because of the limitation of computing resources. Har...

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Detalles Bibliográficos
Autores principales: Moore, Christopher H., Lin, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024689/
https://www.ncbi.nlm.nih.gov/pubmed/35448296
http://dx.doi.org/10.3390/bios12040236
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author Moore, Christopher H.
Lin, Wei
author_facet Moore, Christopher H.
Lin, Wei
author_sort Moore, Christopher H.
collection PubMed
description Correlation has a variety of applications that require signal processing. However, it is computationally intensive, and software correlators require high-performance processors for real-time data analysis. This is a challenge for embedded devices because of the limitation of computing resources. Hardware correlators that use Field Programmable Gate Array (FPGA) technology can significantly boost computational power and bridge the gap between the need for high-performance computing and the limited processing power available in embedded devices. This paper presents a detailed FPGA-based correlator design at the register level along with the open-source Very High-Speed Integrated Circuit Hardware Description Language (VHDL) code. It includes base modules for linear and multi-tau correlators of varying sizes. Every module implements a simple and unified data interface for easy integration with standard and publicly available FPGA modules. Eighty-lag linear and multi-tau correlators were built for validation of the design. Three input data sets—constant signal, pulse signal, and sine signal—were used to test the accuracy of the correlators. The results from the FPGA correlators were compared against the outputs of equivalent software correlators and validated with the corresponding theoretical values. The FPGA correlators returned results identical to those from the software references for all tested data sets and were proven to be equivalent to their software counterparts. Their computation speed is at least 85,000 times faster than the software correlators running on a Xilinx MicroBlaze processor. The FPGA correlator can be easily implemented, especially on System on a Chip (SoC) integrated circuits that have processor cores and FPGA fabric. It is the ideal component for device-on-chip solutions in biosensing.
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spelling pubmed-90246892022-04-23 FPGA Correlator for Applications in Embedded Smart Devices Moore, Christopher H. Lin, Wei Biosensors (Basel) Article Correlation has a variety of applications that require signal processing. However, it is computationally intensive, and software correlators require high-performance processors for real-time data analysis. This is a challenge for embedded devices because of the limitation of computing resources. Hardware correlators that use Field Programmable Gate Array (FPGA) technology can significantly boost computational power and bridge the gap between the need for high-performance computing and the limited processing power available in embedded devices. This paper presents a detailed FPGA-based correlator design at the register level along with the open-source Very High-Speed Integrated Circuit Hardware Description Language (VHDL) code. It includes base modules for linear and multi-tau correlators of varying sizes. Every module implements a simple and unified data interface for easy integration with standard and publicly available FPGA modules. Eighty-lag linear and multi-tau correlators were built for validation of the design. Three input data sets—constant signal, pulse signal, and sine signal—were used to test the accuracy of the correlators. The results from the FPGA correlators were compared against the outputs of equivalent software correlators and validated with the corresponding theoretical values. The FPGA correlators returned results identical to those from the software references for all tested data sets and were proven to be equivalent to their software counterparts. Their computation speed is at least 85,000 times faster than the software correlators running on a Xilinx MicroBlaze processor. The FPGA correlator can be easily implemented, especially on System on a Chip (SoC) integrated circuits that have processor cores and FPGA fabric. It is the ideal component for device-on-chip solutions in biosensing. MDPI 2022-04-12 /pmc/articles/PMC9024689/ /pubmed/35448296 http://dx.doi.org/10.3390/bios12040236 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Moore, Christopher H.
Lin, Wei
FPGA Correlator for Applications in Embedded Smart Devices
title FPGA Correlator for Applications in Embedded Smart Devices
title_full FPGA Correlator for Applications in Embedded Smart Devices
title_fullStr FPGA Correlator for Applications in Embedded Smart Devices
title_full_unstemmed FPGA Correlator for Applications in Embedded Smart Devices
title_short FPGA Correlator for Applications in Embedded Smart Devices
title_sort fpga correlator for applications in embedded smart devices
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024689/
https://www.ncbi.nlm.nih.gov/pubmed/35448296
http://dx.doi.org/10.3390/bios12040236
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