CATS enables collaborative transformer inference on up to 16 ultra-low-power wireless devices, supporting models up to 14 times larger than a single device can run via SomeGather pruning and message-dropout robustness.
DISNET: Distributed micro-split deep learn- ing in heterogeneous dynamic IoT.IEEE Internet of Things Journal,
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Going Beyond the Edge: Distributed Inference of Transformer Models on Ultra-Low-Power Wireless Devices
CATS enables collaborative transformer inference on up to 16 ultra-low-power wireless devices, supporting models up to 14 times larger than a single device can run via SomeGather pruning and message-dropout robustness.