Neuromorphic computing
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Neuromorphic computing is an emerging interdisciplinary field that takes inspiration from biology to design hardware models of neural systems. Specifically, it uses very-large-scale integrated circuits containing analog electronic circuits to mimic the neurobiological architectures in the nervous system, as conceived by Carver Mead in the late 1980s. Two examples are Neurogrid, a mixed-analog-digital multichip system emulating a million neurons and billion connections using subthreshold analog logic, and IBM's TrueNorth, which contains 16 neuromorphic cores and is completely digital. Both aim to achieve the scale and low power operation of the biological brain through novel computing architectures.
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Neuromorphic computing
- 1. Neuromorphic Computing - An intro to building brains
- 2. What is Neuromorphic computing? "Neuromorphic engineering, also known as neuromorphic computing started as a concept developed by Carver Mead in the late 1980s, describing the use of very-large-scale integration (VLSI) systems containing electronic analogue circuits to mimic neurobiological architectures present in the nervous system."
- 3. simply put... "Neuromorphic engineering is a new emerging interdisciplinary field which takes inspiration from biology, physics, mathematics, computer science and engineering to design hardware/physical models of neural and sensory systems."
- 4. Moore's Law In 1965, Gordon Moore made a prediction that would set the pace for our modern digital revolution. From careful observation of an emerging trend, Moore extrapolated that computing would dramatically increase in power, and decrease in relative cost, at an exponential pace. The insight, known as Moore’s Law, became the golden rule for the electronics industry, and a springboard for innovation
- 6. Analogy Biology Machine learning Arbor Connectivity
- 7. Analogies Biology • Neuron • Arbor • Scale 1. ~100B Neurons 2. ~100T connections Machine learning • Neuron/Filter/Feature extractor • Connectivity • Scale ???
- 8. Analogies Biology • Neuron • Arbor • Power • ~20W Machine learning • Neuron/Filter/Feature extractor • Connectivity • Power ???
- 9. Neuromorphic Computing Neurogrid IBM TrueNorth
- 10. Neurogrid 1 16 chip system, which emulates a million neurons with a billion connection 2 Morphs analog property of neurons of brain by using sub threshold analog logic 3 Extremely low level transistor circuit that could emulate the non linearities that are captured by neurons of brain 4 Asynchronous digital logic for communication
- 11. TrueNorth 1 Comes from IBM's cognitive computing division 2 16x times the size of Neurogrid 3 Instead of subthreshold analog, they are completely digital
- 21. Reference 1 Ben Varkey Benjamin ; Peiran Gao ; Emmett McQuinn ; Swadesh Choudhary ; Anand R. Chandrasekaran ; Jean-Marie Bussat ; Rodrigo Alvarez-Icaza ; John V. Arthur ; Paul A. Merolla ; Kwabena Boahen - Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations - Stanford University 2 Wen Ma: Mohammed A. Zidan - Neuromorphic computing with memristive devices - Springer journal
- 22. Thank you