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Carry-through checksum is proposed, a fundamentally new scheme for soft-error detection in CNN inference on embedded GPUs that embeds dedicated carry-through filters into the convolutional layers, which compute a checksum from the CNN's own operations and propagate it through inference, enabling end-to-end error detection with a single output verification.
Real-time gait analysis is now 4x faster thanks to a new LSTM accelerator that co-optimizes hardware and software.