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Performance comparison of instrument automation pipelines using different programming languages.

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Název: Performance comparison of instrument automation pipelines using different programming languages.
Autoři: Kumar, Ankur, Goswami, Mayank
Zdroj: Scientific Reports; 10/30/2023, Vol. 13 Issue 1, p1-14, 14p
Témata: PROGRAMMING languages, ELECTRONIC data processing, REAL-time control, PYTHON programming language, COMPUTER performance, AUTOMATION, ULTRASONIC imaging
Abstrakt: The article presents a performance analysis of fully automated, in-house developed 2D ultrasound computerized tomography systems using different programming languages. The system is fully automated in four programming languages: LabVIEW, MATLAB, C and Python. It includes codes for sensors, instruments interfacing, real-time control, synchronized data acquisition, simultaneous raw data processing and analysis. Launch performance, eight performance indices and runtime performance are used for the analysis. It is found that C utilizes the least processing power and executes fewer I/O processes to perform the same task. In runtime analysis (data acquisition and real-time control), LabVIEW (365.69 s) performed best in comparison to MATLAB (623.83 s), Python (1505.54 s), and C (1252.03 s) to complete the experiment without data processing. However, in the experiment with data processing, MATLAB (640.33 s) performed best in comparison to LabVIEW (731.91 s), Python (1520.01 s) and C (1930.15 s). Python performed better in establishing faster interfacing and RAM usage. The study provides a methodology to select optimal programming languages for instrument automation-related aspects to optimize the available resources. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
Popis
Abstrakt:The article presents a performance analysis of fully automated, in-house developed 2D ultrasound computerized tomography systems using different programming languages. The system is fully automated in four programming languages: LabVIEW, MATLAB, C and Python. It includes codes for sensors, instruments interfacing, real-time control, synchronized data acquisition, simultaneous raw data processing and analysis. Launch performance, eight performance indices and runtime performance are used for the analysis. It is found that C utilizes the least processing power and executes fewer I/O processes to perform the same task. In runtime analysis (data acquisition and real-time control), LabVIEW (365.69 s) performed best in comparison to MATLAB (623.83 s), Python (1505.54 s), and C (1252.03 s) to complete the experiment without data processing. However, in the experiment with data processing, MATLAB (640.33 s) performed best in comparison to LabVIEW (731.91 s), Python (1520.01 s) and C (1930.15 s). Python performed better in establishing faster interfacing and RAM usage. The study provides a methodology to select optimal programming languages for instrument automation-related aspects to optimize the available resources. [ABSTRACT FROM AUTHOR]
ISSN:20452322
DOI:10.1038/s41598-023-45849-y