ZuSE KI-AVF
Application-Specific AI Processor for Intelligent Sensor Signal Processing in Autonomous Driving
Abstract
Modern and future AI-based automotive applications, such as autonomous driving, require the efficient real-time processing of huge amounts of data from different sensors, like camera, radar, and LiDAR. In the ZuSE-KI-AVF project, multiple university, and industry partners collaborate to develop a novel massive parallel processor architecture, based on a cus-tomized RISC-V host processor, and an efficient high-performance vertical vector coprocessor. In addition, a software development framework is also provided to efficiently program AI-based sensor processing applications. The proposed processor system was verified and evaluated on a state-of-the-art UltraScale+ FPGA board, reaching a processing performance of up to 126.9 FPS, while executing the YOLO-LITE CNN on 224x224 input images. Further optimizations of the FPGA design and the realization of the processor system on a 22nm FDSOI CMOS technology are planned.
Details
- Organisation(s)
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Institute of Microelectronic Systems
- External Organisation(s)
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RWTH Aachen University
Robert Bosch GmbH
Dream Chip Technologies GmbH
Cadence Design Systems
Technische Universität Braunschweig
University of Kaiserslautern
- Type
- Conference contribution
- Publication date
- 2023
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- General Engineering
- Electronic version(s)
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https://doi.org/10.23919/date56975.2023.10136978 (Access:
Closed
)
