Chipmunk: A Systolically Scalable 0.9 mm${}^2$, 3.08 Gop/s/mW @ 1.2 mW Accelerator for Near-Sensor Recurrent Neural Network Inference

Conference object, Preprint, Other literature type English OPEN
Conti, Francesco; Cavigelli, Lukas; Paulin, Gianna; Susmelj, Igor; Benini, Luca;
  • Publisher: IEEE
  • Identifiers: doi: 10.1109/CICC.2018.8357068, doi: 10.3929/ethz-b-000272086
  • Subject: Computer Science - Distributed, Parallel, and Cluster Computing | Computer Science - Sound | Hardware and Architecture | Electrical and Electronic Engineering | Electronic, Optical and Magnetic Materials | Computer Science - Neural and Evolutionary Computing | Computer Science - Learning

Recurrent neural networks (RNNs) are state-of-the-art in voice awareness/understanding and speech recognition. On-device computation of RNNs on low-power mobile and wearable devices would be key to applications such as zero-latency voice-based human-machine interfaces. ... View more
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