2020
M. J. Klaiber, I. Feldner, Y. Braatz, A. Acosta, S. Vogel, Armin Runge "End-to-End Performance Assessment of AI Systems with TVM and Virtual Models", Synopsys Virtual Prototyping Day 2021.
2021
M. J. Klaiber, A. Acosta, Y. Braatz, S. Vogel, I. Feldner "End-to-End Performance Assessment of AI Systems with TVM and Virtual Models", TVM Conference 2020.
2019
M. J. Klaiber, S. Vogel, A. Acosta, R. Korn, L. Ecco, K. Back, A. Guntoro, I. Feldner
"An End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models",
Proceedings of the INTelligent Embedded Systems Architectures and Applications Workshop 2019.
M. J. Klaiber, D. G. Bailey, S. Simon "Comparative Study and Proof of Single-Pass Connected ComponentsAlgorithms" in Journal of Mathematical Imaging and Vision, June 2019.
2018
Vijayalakshmi Srinivasan, Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Jungwook Choi, Silvia Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan in
"Aross the Stack Opportunities for Deep Learning Acceleration" in
Proceedings of the International Symposium on Low Power Electronics and Design, pp. 35
B. Fleischer, S. Shukla, M. Ziegler, J. Silberman, J. Oh, V. Srinivasan, J. Choi, S. Mueller, A. Agrawal, T. Babinsky, N. Cao, C.‐Y. Chen, P. Chuang, T.Fox, G. Gristede, M. Guillorn, H. Haynie, M. Klaiber, D. Lee, S.Lo, G. Maier, M. Scheuermann, S. Venkataramani, C. Vezyrtzis, N. Wang, F. Yee, C. Zhou, P.‐F. Lu, B. Curran, L. Chang, K. Gopalakrishnan "A Scalable Multi‐TeraOPS Deep Learning Processor Core for AI Training and Inference" in 2018 Symposia on VLSI Technology and Circuit,
Blog entry discussion the Multi‐TeraOPS Deep Learning Processor Core
IEEE Spectrum Article discussing the Multi‐TeraOPS Deep Learning Processor Core
2017
M. J. Klaiber "A Parallel and Resource-Efficient Single Lookup Connected Components Analysis Architecture for Reconfigurable Hardware" Dissertation, University of Stuttgart, 2017.
2016
Michael J. Klaiber, Donald G. Bailey, Sven Simon, "A single-cycle parallel multi-slice connected components analysis hardware architecture" in Springer Journal of Real-Time Image Processing, pp 1–11.
2015
Michael J. Klaiber, Donald G. Bailey, Yousef O. Baroud and Sven Simon, "A Resource-Efficient Hardware Architecture for Connected Components Analysis" in IEEE Transactions on Circuits and Systems for Video Technology.2014
Ghada Dessouky, Michael J. Klaiber, Donald G. Bailey and Sven Simon, "Adaptive Dynamic On-Chip Memory Management for FPGA-based Reconfigurable Architectures" in 24th International Conference on Field Programmable Logic and Applications (FPL), Munich, Germany, Sept. 2014.2013
Michael J. Klaiber, Donald G. Bailey, Silvia Ahmed, Yousef Baroud,
Sven Simon, "A High-Throughput FPGA Architecture for Parallel Connected
Components Analysis Based on Label Reuse" in 2013 International
Conference on Field-Programmable Technology (FPT), Kyoto, Japan, Dec. 2013.
Donald G. Bailey, Michael J. Klaiber, "Efficient Hardware Calculation of Running Statistics" in Image and Vision Computing New Zealand 2013, Wellington, New Zealand, Nov. 2013.
Donald G. Bailey, Michael J. Klaiber, "Efficient Hardware Calculation of Running Statistics" in Image and Vision Computing New Zealand 2013, Wellington, New Zealand, Nov. 2013.
2012
Michael J. Klaiber, Lars Rockstroh, Zhe Wang, Yousef Baroud and Sven Simon
"A memory-efficient parallel single pass architecture for connected component labeling of streamed images" in 2012 International Conference on Field-Programmable Technology (FPT), pages 159-165, Seoul, Korea, Dec. 2012.
"A memory-efficient parallel single pass architecture for connected component labeling of streamed images" in 2012 International Conference on Field-Programmable Technology (FPT), pages 159-165, Seoul, Korea, Dec. 2012.
