Computations of cross-correlation functions on a single board Raspberry Pi computer

Podrobná bibliografie
Parent link:Journal of Physics: Conference Series
Vol. 1615 : High-performance computing systems and technologies in scientific research, automation of control and production (HPCST).— 2020.— [012004, 13 p.]
Hlavní autor: Faerman V. A. Vladimir Andreevich
Korporativní autor: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение автоматизации и робототехники
Další autoři: Shvetsov M. P. Mikhail Pavlovich, Tsavnin A. V. Alexey Vladimirovich
Shrnutí:Title screen
The paper discusses the implementation of correlation algorithm for time delay estimation on a Raspberry Pi single-board computer. The implemented correlation algorithm is based on Fourier transform. In the course of the study, we applied two alternative solutions for the software implementation of discrete Fourier transform. The first solution stands on FFTW library and uses general-purpose quad-core ARM Cortex A53 processing unit. The alternative method uses VideoCore IV graphic processing unit and is implemented via firmware GPU_FFT library. We have performed a computational experiment on a Raspberry Pi 3B to determine which solution is more preferable for the implementation of correlator. After a comparative study we figured out that estimated processing time is highly dependent on computations parameters and input signals. For small FFT window sizes CPU is proved to be a preferable option. However, for large FFT windows GPU allows significantly accelerating the computations. At some point, you can achieve even better performance by using batching and GPU for direct FFT and CPU for inverse FFT. According with the results, we have concluded that both alternatives have their own potential advantages and particular drawback. We also establish, that Raspberry Pi 3 B computer with HiFiberry extension can be used as a real-time correlator for audio signals.
Jazyk:angličtina
Vydáno: 2020
Témata:
On-line přístup:https://doi.org/10.1088/1742-6596/1615/1/012004
Médium: Elektronický zdroj Kapitola
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663233

MARC

LEADER 00000naa0a2200000 4500
001 663233
005 20250813100907.0
035 |a (RuTPU)RU\TPU\network\34402 
035 |a RU\TPU\network\33889 
090 |a 663233 
100 |a 20210202d2020 k||y0engy50 ba 
101 0 |a eng 
135 |a drcn ---uucaa 
181 0 |a i  
182 0 |a b 
200 1 |a Computations of cross-correlation functions on a single board Raspberry Pi computer  |f V. A. Faerman, M. P. Shvetsov, A. V. Tsavnin 
203 |a Text  |c electronic 
300 |a Title screen 
320 |a [References: 19 tit.] 
330 |a The paper discusses the implementation of correlation algorithm for time delay estimation on a Raspberry Pi single-board computer. The implemented correlation algorithm is based on Fourier transform. In the course of the study, we applied two alternative solutions for the software implementation of discrete Fourier transform. The first solution stands on FFTW library and uses general-purpose quad-core ARM Cortex A53 processing unit. The alternative method uses VideoCore IV graphic processing unit and is implemented via firmware GPU_FFT library. We have performed a computational experiment on a Raspberry Pi 3B to determine which solution is more preferable for the implementation of correlator. After a comparative study we figured out that estimated processing time is highly dependent on computations parameters and input signals. For small FFT window sizes CPU is proved to be a preferable option. However, for large FFT windows GPU allows significantly accelerating the computations. At some point, you can achieve even better performance by using batching and GPU for direct FFT and CPU for inverse FFT. According with the results, we have concluded that both alternatives have their own potential advantages and particular drawback. We also establish, that Raspberry Pi 3 B computer with HiFiberry extension can be used as a real-time correlator for audio signals. 
461 0 |0 (RuTPU)RU\TPU\network\3526  |t Journal of Physics: Conference Series 
463 |t Vol. 1615 : High-performance computing systems and technologies in scientific research, automation of control and production (HPCST)  |o proceedings of X International Conference, 24-25 April 2020, Barnaul, Russia  |v [012004, 13 p.]  |d 2020 
610 1 |a электронный ресурс 
610 1 |a труды учёных ТПУ 
700 1 |a Faerman  |b V. A.  |c specialist in the field of informatics and computer technology  |c Engineer of Tomsk Polytechnic University  |f 1990-  |g Vladimir Andreevich  |3 (RuTPU)RU\TPU\pers\32970 
701 1 |a Shvetsov  |b M. P.  |g Mikhail Pavlovich 
701 1 |a Tsavnin  |b A. V.  |c Specialist in the field of automatic control  |c Associate Professor of Tomsk Polytechnic University, Candidate of Technical Sciences  |f 1993-  |g Alexey Vladimirovich  |3 (RuTPU)RU\TPU\pers\45865  |9 22010 
712 0 2 |a Национальный исследовательский Томский политехнический университет  |b Инженерная школа информационных технологий и робототехники  |b Отделение автоматизации и робототехники  |3 (RuTPU)RU\TPU\col\23553 
801 2 |a RU  |b 63413507  |c 20210202  |g RCR 
850 |a 63413507 
856 4 |u https://doi.org/10.1088/1742-6596/1615/1/012004 
942 |c CF