Enabling Cross-Domain Communication: How to Bridge the Gap between AI and HW Engineers

no code implementations • 8 Apr 2021 • Michael J. Klaiber, Axel J. Acosta, Ingo Feldner, Falk Rehm

This position paper discusses possibilities how to establish such a methodology for systems that include (reconfigurable) dedicated accelerators and outlines the central role that languages and tools play in the process.

An End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models

no code implementations • 25 Oct 2019 • Michael J. Klaiber, Sebastian Vogel, Axel Acosta, Robert Korn, Leonardo Ecco, Kristine Back, Andre Guntoro, Ingo Feldner

End-to-end performance estimation and measurement of deep neural network (DNN) systems become more important with increasing complexity of DNN systems consisting of hardware and software components.