Artículo
Asynchronous Spiking Neurons, the Natural Key to Exploit Temporal Sparsity
Autor/es | Yousefzadeh, Amirreza
Khoei, Mina A. Hosseini, Sahar Holanda, Priscila Leroux, Sam Moreira, Orlando Tapson, Jonathan Dhoedt, Bart Simoens, Pieter Serrano Gotarredona, María Teresa Linares Barranco, Bernabé |
Departamento | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores |
Fecha de publicación | 2019 |
Fecha de depósito | 2020-10-15 |
Publicado en |
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Resumen | Inference of Deep Neural Networks for stream
signal (Video/Audio) processing in edge devices is still challenging.
Unlike the most state of the art inference engines which are
efficient for static signals, our brain is ... Inference of Deep Neural Networks for stream signal (Video/Audio) processing in edge devices is still challenging. Unlike the most state of the art inference engines which are efficient for static signals, our brain is optimized for real-time dynamic signal processing. We believe one important feature of the brain (asynchronous state-full processing) is the key to its excellence in this domain. In this work, we show how asynchronous processing with state-full neurons allows exploitation of the existing sparsity in natural signals. This paper explains three different types of sparsity and proposes an inference algorithm which exploits all types of sparsities in the execution of already trained networks. Our experiments in three different applications (Handwritten digit recognition, Autonomous Steering and Hand-Gesture recognition) show that this model of inference reduces the number of required operations for sparse input data by a factor of one to two orders of magnitudes. Additionally, due to fully asynchronous processing this type of inference can be run on fully distributed and scalable neuromorphic hardware platforms. |
Agencias financiadoras | European Union (UE) European Union (UE) Ministerio de Economía y Competitividad (MINECO). España |
Identificador del proyecto | Horizon 2020 No 687299 NeuRAM
Horizon 2020 No 824164 HERMES TEC2015-63884-C2-1-P |
Cita | Yousefzadeh, A., Khoei, M.A., Hosseini, S., Holanda, P., Leroux, S., Moreira, O.,...,Linares Barranco, B. (2019). Asynchronous Spiking Neurons, the Natural Key to Exploit Temporal Sparsity. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 9 (4), 668-678. |
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