TY - GEN

T1 - The ZuSE-KI-Mobil AI Accelerator SoC

T2 - 2023 Design, Automation and Test in Europe Conference and Exhibition, DATE 2023

AU - Kempf, Fabian

AU - Hoefer, Julian

AU - Harbaum, Tanja

AU - Becker, Juergen

AU - Fasfous, Nael

AU - Frickenstein, Alexander

AU - Voegel, Hans Joerg

AU - Friedrich, Simon

AU - Wittig, Robert

AU - Matúš, Emil

AU - Fettweis, Gerhard

AU - Lueders, Matthias

AU - Blume, Holger

AU - Benndorf, Jens

AU - Grantz, Darius

AU - Zeller, Martin

AU - Engelke, Dietmar

AU - Eickel, Karl Heinz

N1 - Funding Information: ACKNOWLEDGMENT This work was funded by the German Federal Ministry of Education and Research (BMBF) under grant number 16ME0096 (ZuSE-KI-mobil). The responsibility for the content of this publication lies with the authors. Furthermore, we thank GlobalFoundries, Synopsys, Cadence, Arteris, and ARM for supporting this research.

PY - 2023

Y1 - 2023

N2 - ZuSE-KI-Mobil (ZuKIMo) is a nationally funded research project, currently in its intermediate stage. The goal of the ZuKIMo project is to develop a new System-on-Chip (SoC) platform and corresponding ecosystem to enable efficient Artificial Intelligence (AI) applications with specific requirements. With ZuKIMo, we specifically target applications from the mobility domain, i.e. autonomous vehicles and drones. The initial ecosystem is built by a consortium consisting of seven partners from German academia and industry. We develop the SoC platform and its ecosystem around a novel AI accelerator design. The customizable accelerator is conceived from scratch to fulfill the functional and non-functional requirements derived from the ambitious use cases. A tape-out in 22 nm FDX-technology is planned in 2023. Apart from the System-on-Chip hardware design itself, the ZuKIMo ecosystem has the objective of providing software tooling for easy deployment of new use cases and hardware-CNN co-design. Furthermore, AI accelerators in safety-critical applications like our mobility use cases, necessitate the fulfillment of safety requirements. Therefore, we investigate new design methodologies for fault analysis of Deep Neural Networks (DNNs) and introduce our new redundancy mechanism for AI accelerators.

AB - ZuSE-KI-Mobil (ZuKIMo) is a nationally funded research project, currently in its intermediate stage. The goal of the ZuKIMo project is to develop a new System-on-Chip (SoC) platform and corresponding ecosystem to enable efficient Artificial Intelligence (AI) applications with specific requirements. With ZuKIMo, we specifically target applications from the mobility domain, i.e. autonomous vehicles and drones. The initial ecosystem is built by a consortium consisting of seven partners from German academia and industry. We develop the SoC platform and its ecosystem around a novel AI accelerator design. The customizable accelerator is conceived from scratch to fulfill the functional and non-functional requirements derived from the ambitious use cases. A tape-out in 22 nm FDX-technology is planned in 2023. Apart from the System-on-Chip hardware design itself, the ZuKIMo ecosystem has the objective of providing software tooling for easy deployment of new use cases and hardware-CNN co-design. Furthermore, AI accelerators in safety-critical applications like our mobility use cases, necessitate the fulfillment of safety requirements. Therefore, we investigate new design methodologies for fault analysis of Deep Neural Networks (DNNs) and introduce our new redundancy mechanism for AI accelerators.

KW - AI Accelerator

KW - Development Methodology

KW - Fault Simulation

KW - Functional Safety

KW - System-on-Chip

UR - http://www.scopus.com/inward/record.url?scp=85162703402&partnerID=8YFLogxK

U2 - 10.23919/DATE56975.2023.10137257

DO - 10.23919/DATE56975.2023.10137257

M3 - Conference contribution

AN - SCOPUS:85162703402

T3 - Proceedings -Design, Automation and Test in Europe, DATE

BT - 2023 Design, Automation and Test in Europe Conference and Exhibition, DATE 2023 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 17 April 2023 through 19 April 2023

ER -