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Title: LLNL Partners with IBM on Brain-Like Computing Chip

Abstract

Lawrence Livermore National Laboratory (LLNL) will receive a first-of-a-kind brain-inspired supercomputing platform for deep learning developed by IBM Research. Based on a breakthrough neurosynaptic computer chip called IBM TrueNorth, the scalable platform will process the equivalent of 16 million neurons and 4 billion synapses and consume the energy equivalent of a hearing aid battery – a mere 2.5 watts of power. The brain-like, neural network design of the IBM Neuromorphic System is able to infer complex cognitive tasks such as pattern recognition and integrated sensory processing far more efficiently than conventional chips.

Authors:
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1245171
Resource Type:
Multimedia
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; IBM; TRUENORTH; IBM TRUENORTH NEUROMORPHIC CHIP; HUMAN BRAIN; TRUENORTH ARCHITECTURE; COMPUTING ARCHITECTURE; ADVANCED SIMULATION

Citation Formats

Van Essen, Brian. LLNL Partners with IBM on Brain-Like Computing Chip. United States: N. p., 2016. Web.
Van Essen, Brian. LLNL Partners with IBM on Brain-Like Computing Chip. United States.
Van Essen, Brian. Tue . "LLNL Partners with IBM on Brain-Like Computing Chip". United States. https://www.osti.gov/servlets/purl/1245171.
@article{osti_1245171,
title = {LLNL Partners with IBM on Brain-Like Computing Chip},
author = {Van Essen, Brian},
abstractNote = {Lawrence Livermore National Laboratory (LLNL) will receive a first-of-a-kind brain-inspired supercomputing platform for deep learning developed by IBM Research. Based on a breakthrough neurosynaptic computer chip called IBM TrueNorth, the scalable platform will process the equivalent of 16 million neurons and 4 billion synapses and consume the energy equivalent of a hearing aid battery – a mere 2.5 watts of power. The brain-like, neural network design of the IBM Neuromorphic System is able to infer complex cognitive tasks such as pattern recognition and integrated sensory processing far more efficiently than conventional chips.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {3}
}

Multimedia:

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