Project Snapshot
Identifying the optimal hardware configuration for running NN inference on edge devices is critical for maximizing performance. Tailoring HW designs to specific applications significantly increases resource utilization. We demonstrate how Virtual Prototypes can uncover previously unknown HW optimizations using edge AI workloads from the MLPerf Tiny benchmark suite.
In Their Own Words
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Meet the Authors
Jan Zielasko
PhD student in Computer Science at DFKI CPS / University of Bremen in Germany
Jan Zielasko is a PhD student at the University of Bremen and a researcher at the Cyber-Physical Systems department of the German Research Center for Artificial Intelligence (DFKI). His research focuses on Virtual Prototype-driven tracing, analysis, verification and hardware optimization.
Prof. Dr. Rolf Drechsler
Professor at University of Bremen, Director DFKI Bremen in Germany
Since October 2001, Rolf Drechsler is a Full Professor and Head of the Group of Computer Architecture, Institute of Computer Science, at the University of Bremen, Germany. In 2011, he additionally became the Director of the Cyber-Physical Systems Group at the German Research Center for Artificial Intelligence (DFKI) in Bremen. His current research interests include the development and design of data structures and algorithms with a focus on circuit and system design. He is an ACM Fellow and an IEEE Fellow.
