| 000 | 03377nlm2a2200349 4500 | ||
|---|---|---|---|
| 001 | 663233 | ||
| 005 | 20231030041847.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\34402 | ||
| 035 | _aRU\TPU\network\33889 | ||
| 090 | _a663233 | ||
| 100 | _a20210202a2020 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 105 | _ay z 100zy | ||
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aComputations of cross-correlation functions on a single board Raspberry Pi computer _fV. A. Faerman, M. P. Shvetsov, A. V. Tsavnin |
|
| 203 |
_aText _celectronic |
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| 300 | _aTitle screen | ||
| 320 | _a[References: 19 tit.] | ||
| 330 | _aThe 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 _tJournal of Physics: Conference Series |
|
| 463 |
_tVol. 1615 : High-performance computing systems and technologies in scientific research, automation of control and production (HPCST) _oproceedings of X International Conference, 24-25 April 2020, Barnaul, Russia _v[012004, 13 p.] _d2020 |
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| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 700 | 1 |
_aFaerman _bV. A. _cspecialist in the field of informatics and computer technology _cEngineer of Tomsk Polytechnic University _f1990- _gVladimir Andreevich _2stltpush _3(RuTPU)RU\TPU\pers\32970 |
|
| 701 | 1 |
_aShvetsov _bM. P. _gMikhail Pavlovich |
|
| 701 | 1 |
_aTsavnin _bA. V. _cSpecialist in the field of automatic control _cAssistant of the Department of Tomsk Polytechnic University _f1993- _gAlexey Vladimirovich _2stltpush _3(RuTPU)RU\TPU\pers\45865 |
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| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа информационных технологий и робототехники _bОтделение автоматизации и робототехники _h7952 _2stltpush _3(RuTPU)RU\TPU\col\23553 |
| 801 | 2 |
_aRU _b63413507 _c20210202 _gRCR |
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| 856 | 4 | _uhttps://doi.org/10.1088/1742-6596/1615/1/012004 | |
| 942 | _cCF | ||