Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards the TrueNorth cognitive computing system inspired by the brain's function and efficiency. The non-von Neumann nature of the TrueNorth architecture necessitates a novel approach to efficient system design. To this end, we have developed a set of abstractions, algorithms, and applications that are natively efficient for TrueNorth. First, we developed repeatedly-used abstractions that span neural codes (such as binary, rate, population, and time-to-spike), long-range connectivity, and short-range connectivity. Second, we implemented ten algorithms that include convolution networks, spectral content estimators, liquid state machines, restricted Boltzmann machines, hidden Markov models, looming detection, temporal pattern matching, and various classifiers. Third, we demonstrate seven applications that include speaker recognition, music composer recognition, digit recognition, sequence prediction, collision avoidance, optical flow, and eye detection. Our results showcase the parallelism, versatility, rich connectivity, spatio-temporality, and multi-modality of the TrueNorth architecture as well as compositionality of the corelet programming paradigm and the flexibility of the underlying neuron model.

Cognitive computing systems : Algorithms and applications for networks of neurosynaptic cores / S.K. Esser, A. Andreopoulos, R. Appuswamy, P. Datta, D. Barch, A. Amir, J. Arthur, A. Cassidy, M. Flickner, P. Merolla, S. Chandra, N. Basilico, S. Carpin, T. Zimmerman, F. Zee, R. Alvarez Icaza, J.A. Kusnitz, T.M. Wong, W.P. Risk, E. Mcquinn, T.K. Nayak, R. Singh, D.S. Modha (PROCEEDINGS OF ... INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS). - In: The 2013 International Joint Conference on Neural Networks (IJCNN)Piscataway (NJ, USA) : Institute of Electrical and Electronic Engineers (IEEE), 2013 Aug 04. - ISBN 9781467361286. - pp. 1-10 (( convegno International Joint Conference on Neural Networks (IJCNN) : August, 4-9 tenutosi a Dallas (Tx, USA) nel 2013 [10.1109/IJCNN.2013.6706746].

Cognitive computing systems : Algorithms and applications for networks of neurosynaptic cores

N. Basilico;
2013

Abstract

Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards the TrueNorth cognitive computing system inspired by the brain's function and efficiency. The non-von Neumann nature of the TrueNorth architecture necessitates a novel approach to efficient system design. To this end, we have developed a set of abstractions, algorithms, and applications that are natively efficient for TrueNorth. First, we developed repeatedly-used abstractions that span neural codes (such as binary, rate, population, and time-to-spike), long-range connectivity, and short-range connectivity. Second, we implemented ten algorithms that include convolution networks, spectral content estimators, liquid state machines, restricted Boltzmann machines, hidden Markov models, looming detection, temporal pattern matching, and various classifiers. Third, we demonstrate seven applications that include speaker recognition, music composer recognition, digit recognition, sequence prediction, collision avoidance, optical flow, and eye detection. Our results showcase the parallelism, versatility, rich connectivity, spatio-temporality, and multi-modality of the TrueNorth architecture as well as compositionality of the corelet programming paradigm and the flexibility of the underlying neuron model.
Computer architecture; Connectors; Convolution; Feature extraction; Liquids; Nerve fibers
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/250336
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