Evaluating FFT performance of the C and Rust Languages on Raspberry Pi platforms

Author:

Rooney Michael P.1,Matthews Suzanne J.1

Affiliation:

1. U.S. Military Academy,Department of Electrical Engineering & Computer Science,West Point,NY,USA

Publisher

IEEE

Reference33 articles.

1. De-velopment of a smart metering microservice based on fast fourier transform (fft) for edge/internet of things environments;buzachis;2019 IEEE 3rd International Conference on Fog and Edge Computing (ICFEC),0

2. Changing the world with a raspberry pi;brock;Journal of Computing Sciences in Colleges,2013

3. Real-Time Correlation Processing of Vibroacoustic Signals on Single Board Raspberry Pi Computers with HiFiBerry Cards

4. Comparing power and energy usage for scientific calculation with and without gpu acceleration on a raspberry pi model b+ and 3b;he;copyright - Copyright The Steering Committee of The World Congress in Computer Science Computer Engineering and Applied Computing (WorldComp) 2018 Last updated,2018

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1. An Empirical Study on the Energy Usage and Performance of Pandas and Polars Data Analysis Python Libraries;Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering;2024-06-18

2. Containers Unleashed: A Raspberry Pi Showdown Between Docker, Podman, and LXC/LXD;SoutheastCon 2024;2024-03-15

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