Toward Attention-Based TinyML: A Heterogeneous Accelerated Architecture and Automated Deployment Flow

Abstract

Editor’s notes: This article presents a flexible and co-optimized hardware–software architecture template tailored to the demands of attention-based AI workloads in TinyML systems. The article offers a compelling and practical advancement in energy-efficient attention model deployment for TinyML platforms. —Theocharis Theocharides, University of Cyprus, Cyprus —Marian Verhelst, KU Leuven, Belgium —Vijay Janapa Reddy, Harvard University, USA —Evgeni Gousev, Qualcomm, USA