ZuSE-KI-Mobil AI Chip Design Platform: An Overview

Shaown Mojumder; Simon Friedrich; Emil Matus; Gerhard Fettweis; Matthias Lueders; Martin Friedrich; Oliver Renke; Holger Blume; Julian Hoefer; Patrick Schmidt; Juergen Becker; Darius Grantz; Markus Kock; Jens Benndorf; Nael Fasfous; Pierpaolo Mori; Hans Joerg Voegel; Samira Ahmadifarsani; Leonidas Kontopoulos; Ulf Schlichtmann; Kay Bierzynski

doi:10.1109/NorCAS64408.2024.10752454

ZuSE-KI-Mobil AI Chip Design Platform: An Overview

Shaown Mojumder
, Simon Friedrich
, Emil Matus
, Gerhard Fettweis
, Matthias Lueders
, Martin Friedrich
, Oliver Renke
, Holger Blume
, Julian Hoefer
, Patrick Schmidt
, Juergen Becker
, Darius Grantz
, Markus Kock
, Jens Benndorf
, Nael Fasfous
, Pierpaolo Mori
, Hans Joerg Voegel
, Samira Ahmadifarsani
, Leonidas Kontopoulos
, Ulf Schlichtmann

Kay Bierzynski

Chair of Electronic Design Automation

Technische Universität Dresden
Leibniz Universität Hannover
Humanoid Technologies Lab (H2T)
Dream Chip Technologies GmbH
BMW AG
Technical University of Munich
Infineon Technologies AG

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

The ZuSE-KI-Mobil (ZuKIMo) project, a nationally funded initiative, focuses on creating an advanced ecosystem optimized for AI-driven applications in automotive, drone, and industrial domains. At the heart of this effort is a state-of-the-art System-on-Chip (SoC), successfully taped out using 22 nm FDX technology, integrating a novel AI accelerator tailored to specific use case requirements, along with proof-of-concept demonstrators that validate the platform's real-world application potential. Key aspects include the customized compiler flow, the hardware generation process of the novel AI accelerator, and the acceleration of different applications using the ZuKIMo platform. Examples of these applications are 3D object detection and disengagement prediction in autonomous driving. The paper provides an overview of the ZuKIMo ecosystem, highlighting its contributions to AI performance, energy efficiency, and safety in heterogeneous AI hardware platforms.

Original language	English
Title of host publication	2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings
Editors	Jari Nurmi, Joachim Rodrigues, Luca Pezzarossa, Viktor Aberg, Baktash Behmanesh
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331517663
DOIs	https://doi.org/10.1109/NorCAS64408.2024.10752454
State	Published - 2024
Event	10th IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Lund, Sweden Duration: 29 Oct 2024 → 30 Oct 2024

Publication series

Name	2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings

Conference

Conference	10th IEEE Nordic Circuits and Systems Conference, NORCAS 2024
Country/Territory	Sweden
City	Lund
Period	29/10/24 → 30/10/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

AI Accelerator
Compiler
System-on-Chip

Access to Document

10.1109/NorCAS64408.2024.10752454

Cite this

Mojumder, S., Friedrich, S., Matus, E., Fettweis, G., Lueders, M., Friedrich, M., Renke, O., Blume, H., Hoefer, J., Schmidt, P., Becker, J., Grantz, D., Kock, M., Benndorf, J., Fasfous, N., Mori, P., Voegel, H. J., Ahmadifarsani, S., Kontopoulos, L., ... Bierzynski, K. (2024). ZuSE-KI-Mobil AI Chip Design Platform: An Overview. In J. Nurmi, J. Rodrigues, L. Pezzarossa, V. Aberg, & B. Behmanesh (Eds.), 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings (2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NorCAS64408.2024.10752454

Mojumder, Shaown ; Friedrich, Simon ; Matus, Emil et al. / ZuSE-KI-Mobil AI Chip Design Platform : An Overview. 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings. editor / Jari Nurmi ; Joachim Rodrigues ; Luca Pezzarossa ; Viktor Aberg ; Baktash Behmanesh. Institute of Electrical and Electronics Engineers Inc., 2024. (2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings).

@inproceedings{9eb2edef372c41b38af5dde2c0e6bec9,

title = "ZuSE-KI-Mobil AI Chip Design Platform: An Overview",

abstract = "The ZuSE-KI-Mobil (ZuKIMo) project, a nationally funded initiative, focuses on creating an advanced ecosystem optimized for AI-driven applications in automotive, drone, and industrial domains. At the heart of this effort is a state-of-the-art System-on-Chip (SoC), successfully taped out using 22 nm FDX technology, integrating a novel AI accelerator tailored to specific use case requirements, along with proof-of-concept demonstrators that validate the platform's real-world application potential. Key aspects include the customized compiler flow, the hardware generation process of the novel AI accelerator, and the acceleration of different applications using the ZuKIMo platform. Examples of these applications are 3D object detection and disengagement prediction in autonomous driving. The paper provides an overview of the ZuKIMo ecosystem, highlighting its contributions to AI performance, energy efficiency, and safety in heterogeneous AI hardware platforms.",

keywords = "AI Accelerator, Compiler, System-on-Chip",

author = "Shaown Mojumder and Simon Friedrich and Emil Matus and Gerhard Fettweis and Matthias Lueders and Martin Friedrich and Oliver Renke and Holger Blume and Julian Hoefer and Patrick Schmidt and Juergen Becker and Darius Grantz and Markus Kock and Jens Benndorf and Nael Fasfous and Pierpaolo Mori and Voegel, \{Hans Joerg\} and Samira Ahmadifarsani and Leonidas Kontopoulos and Ulf Schlichtmann and Kay Bierzynski",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 10th IEEE Nordic Circuits and Systems Conference, NORCAS 2024 ; Conference date: 29-10-2024 Through 30-10-2024",

year = "2024",

doi = "10.1109/NorCAS64408.2024.10752454",

language = "English",

series = "2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Jari Nurmi and Joachim Rodrigues and Luca Pezzarossa and Viktor Aberg and Baktash Behmanesh",

booktitle = "2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings",

}

Mojumder, S, Friedrich, S, Matus, E, Fettweis, G, Lueders, M, Friedrich, M, Renke, O, Blume, H, Hoefer, J, Schmidt, P, Becker, J, Grantz, D, Kock, M, Benndorf, J, Fasfous, N, Mori, P, Voegel, HJ, Ahmadifarsani, S, Kontopoulos, L, Schlichtmann, U & Bierzynski, K 2024, ZuSE-KI-Mobil AI Chip Design Platform: An Overview. in J Nurmi, J Rodrigues, L Pezzarossa, V Aberg & B Behmanesh (eds), 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings. 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 10th IEEE Nordic Circuits and Systems Conference, NORCAS 2024, Lund, Sweden, 29/10/24. https://doi.org/10.1109/NorCAS64408.2024.10752454

ZuSE-KI-Mobil AI Chip Design Platform: An Overview. / Mojumder, Shaown; Friedrich, Simon; Matus, Emil et al.
2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings. ed. / Jari Nurmi; Joachim Rodrigues; Luca Pezzarossa; Viktor Aberg; Baktash Behmanesh. Institute of Electrical and Electronics Engineers Inc., 2024. (2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - ZuSE-KI-Mobil AI Chip Design Platform

T2 - 10th IEEE Nordic Circuits and Systems Conference, NORCAS 2024

AU - Mojumder, Shaown

AU - Friedrich, Simon

AU - Matus, Emil

AU - Fettweis, Gerhard

AU - Lueders, Matthias

AU - Friedrich, Martin

AU - Renke, Oliver

AU - Blume, Holger

AU - Hoefer, Julian

AU - Schmidt, Patrick

AU - Becker, Juergen

AU - Grantz, Darius

AU - Kock, Markus

AU - Benndorf, Jens

AU - Fasfous, Nael

AU - Mori, Pierpaolo

AU - Voegel, Hans Joerg

AU - Ahmadifarsani, Samira

AU - Kontopoulos, Leonidas

AU - Schlichtmann, Ulf

AU - Bierzynski, Kay

PY - 2024

Y1 - 2024

N2 - The ZuSE-KI-Mobil (ZuKIMo) project, a nationally funded initiative, focuses on creating an advanced ecosystem optimized for AI-driven applications in automotive, drone, and industrial domains. At the heart of this effort is a state-of-the-art System-on-Chip (SoC), successfully taped out using 22 nm FDX technology, integrating a novel AI accelerator tailored to specific use case requirements, along with proof-of-concept demonstrators that validate the platform's real-world application potential. Key aspects include the customized compiler flow, the hardware generation process of the novel AI accelerator, and the acceleration of different applications using the ZuKIMo platform. Examples of these applications are 3D object detection and disengagement prediction in autonomous driving. The paper provides an overview of the ZuKIMo ecosystem, highlighting its contributions to AI performance, energy efficiency, and safety in heterogeneous AI hardware platforms.

AB - The ZuSE-KI-Mobil (ZuKIMo) project, a nationally funded initiative, focuses on creating an advanced ecosystem optimized for AI-driven applications in automotive, drone, and industrial domains. At the heart of this effort is a state-of-the-art System-on-Chip (SoC), successfully taped out using 22 nm FDX technology, integrating a novel AI accelerator tailored to specific use case requirements, along with proof-of-concept demonstrators that validate the platform's real-world application potential. Key aspects include the customized compiler flow, the hardware generation process of the novel AI accelerator, and the acceleration of different applications using the ZuKIMo platform. Examples of these applications are 3D object detection and disengagement prediction in autonomous driving. The paper provides an overview of the ZuKIMo ecosystem, highlighting its contributions to AI performance, energy efficiency, and safety in heterogeneous AI hardware platforms.

KW - AI Accelerator

KW - Compiler

KW - System-on-Chip

UR - https://www.scopus.com/pages/publications/85211924264

U2 - 10.1109/NorCAS64408.2024.10752454

DO - 10.1109/NorCAS64408.2024.10752454

M3 - Conference contribution

AN - SCOPUS:85211924264

T3 - 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings

BT - 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings

A2 - Nurmi, Jari

A2 - Rodrigues, Joachim

A2 - Pezzarossa, Luca

A2 - Aberg, Viktor

A2 - Behmanesh, Baktash

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 29 October 2024 through 30 October 2024

ER -

Mojumder S, Friedrich S, Matus E, Fettweis G, Lueders M, Friedrich M et al. ZuSE-KI-Mobil AI Chip Design Platform: An Overview. In Nurmi J, Rodrigues J, Pezzarossa L, Aberg V, Behmanesh B, editors, 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2024. (2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings). doi: 10.1109/NorCAS64408.2024.10752454

ZuSE-KI-Mobil AI Chip Design Platform: An Overview

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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