tinyML EMEA – Wednesday Keynote – Marian Verhelst: Should Tiny ML Processors be Multi-core?

Should Tiny ML Processors be Multi-core?
Marian VERHELST, Associate Professor, KU Leuven

The real-time deployment of tinyML algorithms towards the dreams of smart spaces augmented humans, or personalized healthcare requires responsiveness at affordable energy or power budgets. To this end, many ML-optimized custom processors have been presented over the past decade. In their quest for higher and higher throughput and efficiency, ML accelerators have evolved from small single-core designs, over scaled-up datapath arrays, to multi-core implementations. While this trend towards multi-core processors is still mostly happening in the cloud, one can wonder whether it will penetrate the extreme edge as well. This lead to interesting questions, such as: Do tinyML devices need homogeneous or heterogeneous multi-core designs? How to schedule tinyML workloads across multi-core edge SoCs? This talk will dig deeper into the underlying motivations of this multi-core evolution, the accompanying challenges, and exciting future opportunities.

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