Application-specific soft-core vector processor for advanced driver assistance systems

verfasst von

Stephan Nolting, Florian Giesemann, Julian Hartig, Achim Schmider, Guillermo Paya-Vaya

Abstract

Implementing convolutional neural networks for scene labelling is a current hot topic in the field of advanced driver assistance systems. The massive computational demands under hard real-time and energy constraints can only be tackled using specialized architectures. Also, cost-effectiveness is an important factor when targeting lower quantities. In this PhD thesis, a vector processor architecture optimized for FPGA devices is proposed. Amongst other hardware mechanisms, a novel complex operand addressing mode and an intelligent DMA are used to increase perfromance. Also, a C-compiler support for creating applications is introduced.

Organisationseinheit(en)

Institut für Mikroelektronische Systeme

Typ

Aufsatz in Konferenzband

Publikationsdatum

2017

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Computernetzwerke und -kommunikation, Angewandte Informatik, Hardware und Architektur, Software

Elektronische Version(en)

https://doi.org/10.23919/FPL.2017.8056836 (Zugang: Geschlossen)