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SAFARI Live Seminar - Software-Hardware Co-design of Edge AI Systems
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https://www.youtube.com/watch?v=kOw0UgtWP9E&list=WL&index=20 Title: Software-Hardware Co-design of Edge AI Systems Speaker: Yiran Chen, Duke University, John Cocke Distinguished Professor, Fellow of the AAAS/ACM/IEEE Website: https://cei.pratt.duke.edu/people/yir... SAFARI Live Seminar Talk & co-sponsored by IEEE Swiss CAS Chapter https://safari.ethz.ch/safari-live-se... Slides (pdf): Slides (pptx): Abstract: Artificial Intelligence (AI) has become pervasive in cloud and edge systems alike. However, despite the time-sensitive nature of many edge AI tasks, such edge systems are resource constrained, making the deployment of many large AI models on the edge unfeasible. Cross-layer optimizations bridge the gap between model size and edge resources by (1) reducing the computation and memory cost of the model and (2) improving the performance and efficiency of the device. In this talk, we present an overview of our effort in boosting the deployment of AI in edge systems. We first introduce efficient AI models via hardware-friendly model compression and topology-aware Neural Architecture Search to optimize quality-efficiency trade-off on AI models. Then, we involve cross-optimized design of edge AI hardware using efficient dataflows, sparse-skipping mechanisms, and quantization. Lastly, we demonstrate the capabilities of such AI models on a wide range of applications and scenarios, such as Electronic Design Automation (EDA) and reliable Machine Learning. Through the previous exploration, we present our vision on the future challenges and opportunities of full-stack Edge AI.
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