From C/C++ to Dynamically Scheduled Circuits

Explore the journey from C/C++ to Dynamically Scheduled Circuits with Lana Josipović, an expert in high-level synthesis and reconfigurable computing. Join her recorded workshop session on innovative hardware design techniques.

Social share preview for From C/C++ to Dynamically Scheduled Circuits

Upcoming Workshops

No workshops are currently scheduled. Check back soon for new events!

Are you an expert in a neuromorphic topic? We invite you to share your knowledge with our community. Hosting a workshop is a great way to engage with peers and share your work.

About the Speaker

Lana Josipović is an Assistant Professor in the Department of Information Technology and Electrical Engineering at ETH Zurich. Prior to joining ETH Zurich in January 2022, she received a Ph.D. degree in Computer Science from EPFL, Switzerland. Her research interests include reconfigurable computing and electronic design automation, with an emphasis on high-level synthesis techniques to generate hardware designs from high-level programming languages. She developed Dynamatic, an open-source high-level synthesis tool that produces dynamically scheduled circuits from C/C++ code. She is a recipient of the EDAA Outstanding Dissertation Award, Google Ph.D. Fellowship in Systems and Networking, Google Women Techmakers Scholarship, and Best Paper Award at FPGA'20.

Inspired? Share your work.

Share your expertise with the community by speaking at a workshop, student talk, or hacking hour. It’s a great way to get feedback and help others learn.

Related Workshops

Does the Brain do Gradient Descent?

Does the Brain do Gradient Descent?

Explore the brain's potential use of gradient descent in learning processes with Konrad Kording in this engaging recorded session.

Low-power Spiking Neural Network Processing Systems for Extreme-Edge Applications

Low-power Spiking Neural Network Processing Systems for Extreme-Edge Applications

Join Dr. Federico Corradi as he explores low-power spiking neural network processing systems, offering insights into energy-efficient computing for extreme-edge applications.

Hybrid Learning for Event-based Visual Motion Detection and Tracking of Pedestrians

Hybrid Learning for Event-based Visual Motion Detection and Tracking of Pedestrians

Revolutionize traffic safety with neuromorphic visual sensing. Explore award-winning solutions for pedestrian detection and tracking, emphasizing sustainability and city-level deployment. Join Dr. Cristian Axenie in this groundbreaking AI exploration