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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2508.07523 |
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| _version_ | 1866916890525302784 |
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| author | Bremer, Bram Bigelow, Matthew Anstee, Stuart Cohen, Gregory van Schaik, Andre Xu, Ying |
| author_facet | Bremer, Bram Bigelow, Matthew Anstee, Stuart Cohen, Gregory van Schaik, Andre Xu, Ying |
| contents | This paper presents a real-time, energy-efficient embedded system implementing an array of Cascade of Asymmetric Resonators with Fast-Acting Compression (CARFAC) cochlea models for underwater sound analysis. Built on the AMD Kria KV260 System-on-Module (SoM), the system integrates a Rust-based software framework on the processor for real-time interfacing and synchronization with multiple hydrophone inputs, and a hardware-accelerated implementation of the CARFAC models on a Field-Programmable Gate Array (FPGA) for real-time sound pre-processing. Compared to prior work, the CARFAC accelerator achieves improved scalability and processing speed while reducing resource usage through optimized time-multiplexing, pipelined design, and elimination of costly division circuits. Experimental results demonstrate 13.5% hardware utilization for a single 64-channel CARFAC instance and a whole board power consumption of 3.11 W when processing a 256 kHz input signal in real time. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_07523 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Real-time CARFAC Cochlea Model Acceleration on FPGA for Underwater Acoustic Sensing Systems Bremer, Bram Bigelow, Matthew Anstee, Stuart Cohen, Gregory van Schaik, Andre Xu, Ying Audio and Speech Processing Sound 92C50 (Primary) 68Q25, 94A12 (Secondary) This paper presents a real-time, energy-efficient embedded system implementing an array of Cascade of Asymmetric Resonators with Fast-Acting Compression (CARFAC) cochlea models for underwater sound analysis. Built on the AMD Kria KV260 System-on-Module (SoM), the system integrates a Rust-based software framework on the processor for real-time interfacing and synchronization with multiple hydrophone inputs, and a hardware-accelerated implementation of the CARFAC models on a Field-Programmable Gate Array (FPGA) for real-time sound pre-processing. Compared to prior work, the CARFAC accelerator achieves improved scalability and processing speed while reducing resource usage through optimized time-multiplexing, pipelined design, and elimination of costly division circuits. Experimental results demonstrate 13.5% hardware utilization for a single 64-channel CARFAC instance and a whole board power consumption of 3.11 W when processing a 256 kHz input signal in real time. |
| title | Real-time CARFAC Cochlea Model Acceleration on FPGA for Underwater Acoustic Sensing Systems |
| topic | Audio and Speech Processing Sound 92C50 (Primary) 68Q25, 94A12 (Secondary) |
| url | https://arxiv.org/abs/2508.07523 |