Parallelization and Resource Estimation of Algorithms for Heterogeneous FAS Architectures

Third party funded individual grant


Project Details

Project leader:
PD Dr.-Ing. Frank Hannig
Prof. Dr.-Ing. Jürgen Teich

Project members:
Jörg Fickenscher

Contributing FAU Organisations:
Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)

Funding source: Industrie (Audi AG)
Acronym: INI.FAU
Start date: 01/05/2015
End date: 31/10/2018


Abstract (technical / expert description):


With the institute INI.FAU, the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) strikes a new path in research and teaching. Together with the AUDI AG, a regional competence center is developed in the site of Ingolstadt that provides unique working conditions for scientific staff to transfer theoretic knowledge into practical applications. One major goal is to advance future Advanced Driver Assistance Systems (ADAS) via novel methods in parallelization and resource estimation.


Publications

Fickenscher, J., Hannig, F., & Teich, J. (2019). DSL-based Acceleration of Automotive Environment Perception and Mapping Algorithms for embedded CPUs, GPUs, and FPGAs. In Martin Schoeberl, Christian Hochberger, Sascha Uhrig, Jürgen Brehm, Thilo Pionteck (Eds.), Architecture of Computing Systems -- ARCS 2019 (pp. 71 - 86). Copenhagen, DK: Cham: Springer International Publishing.
Fickenscher, J., Hannig, F., Teich, J., & Bouzouraa, M.E. (2018). Base Algorithms of Environment Maps and Efficient Occupancy Grid Mapping on Embedded GPUs. In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS) (pp. 298-306). Funchal, Madeira, Portugal, PT: SCITEPRESS.
Fickenscher, J., Schlumberger, J., Hannig, F., Bouzouraa, M.E., & Teich, J. (2018). Cell-based Update Algorithm for Occupancy Grid Maps and new Hybrid Map for ADAS on Embedded GPUs. In IEEE (Eds.), Proceedings of the Design, Automation and Test in Europe (DATE) (pp. 443-448). Dresden, Germany, DE: IEEE.
Fickenscher, J., Hannig, F., Bouzouraa, M.E., & Teich, J. (2018). Embedded GPUs in Future Automated Cars. In Proceedings of the Design, Automation and Test in Europe (DATE). Dresden, DE.
Fickenscher, J., Schmidt, S., Hannig, F., Bouzouraa, M.E., & Teich, J. (Eds.) (2018). Path Planning for Highly Automated Driving on Embedded GPUs. Basel, Schweiz: Multidisciplinary Digital Publishing Institute.
Fickenscher, J., Reinhart, S., Bouzouraa, M.E., Hannig, F., & Teich, J. (2017). Convoy Tracking for ADAS on Embedded GPUs. In IEEE (Eds.), Proceedings of the Intelligent Vehicles Symposium (IV 2017) (pp. 959-965). Redondo Beach, CA, USA: IEEE.
Fickenscher, J., Bouzouraa, M.E., Hannig, F., & Teich, J. (2017, December). Environment Mapping Using Massively Parallel Architectures. Poster presentation at Vehicle Intelligence, München, DE.
Fickenscher, J., Reiche, O., Schlumberger, J., Hannig, F., & Teich, J. (2016). Modeling, Programming and Performance Analysis of Automotive Environment Map Representations on Embedded GPUs. In Proceedings of the 18th IEEE International High-Level Design Validation and Test Workshop (HLDVT) (pp. 70-77). Santa Cruz, CA, US.

Last updated on 2018-16-08 at 11:24