Achieving Maximum Audio Processing Throughput on the Latest Chipsets

Beckmann P, Whitecar J, Peil J, Hegde K. Achieving Maximum Audio Processing Throughput on the Latest Chipsets. In: AES Conference: AES 2022 International Automotive Audio Conference. Audio Engineering Society; 2022. Paper 21. Available from: https://aes.org/publications/elibrary-page/?id=21822

@inproceedings{Beckmann2022_21822,
  author = {Beckmann, Paul and Whitecar, John and Peil, Jeff and Hegde, Karthik},
  title = {{Achieving Maximum Audio Processing Throughput on the Latest Chipsets}},
  booktitle = {AES Conference: AES 2022 International Automotive Audio Conference},
  note = {Paper 21},
  year = {2022},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=21822}
}

TY  - CPAPER
TI  - Achieving Maximum Audio Processing Throughput on the Latest Chipsets
AU  - Beckmann, Paul
AU  - Whitecar, John
AU  - Peil, Jeff
AU  - Hegde, Karthik
T2  - AES Conference: AES 2022 International Automotive Audio Conference
M1  - Paper 21
PY  - 2022
DA  - 2022/06/06
UR  - https://aes.org/publications/elibrary-page/?id=21822
PB  - Audio Engineering Society
LA  - en
AB  - Automotive audio systems continue to grow in complexity with an ever-increasing set of use cases. System architectures must now consider not only playback processing, but also telephony, voice control, safety sounds, individual sound zones, and even road noise cancellation. These use cases require huge compute resources that must be distributed across multiple cores. This paper explores the audio processing throughput of the latest standalone automotive DSPs and multicore SOCs with integrated DSPs. The effects of caching, memory architecture, and multicore are presented and demonstrate how to configure an automotive audio system for maximum audio processing throughput.
ER  -