SpiNNaker: A Spiking Neural Network Architecture...SpiNNaker racks (1M ARM cores) • HBP platform...
Transcript of SpiNNaker: A Spiking Neural Network Architecture...SpiNNaker racks (1M ARM cores) • HBP platform...
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Can massively-parallel computing resources accelerate our understanding of brain function?
Can our growing understanding of brain function point the way to more efficient parallel, fault-tolerant computation?
Chapter 1: Origin
Bio-inspiration
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Chip resources
Chapter 2: The SpiNNaker Chip
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SpiNNaker Multicast routing
Chapter 2: The SpiNNaker Chip
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SpiNNaker racks
(1M ARM cores)
• HBP platform– 1M cores
– 11 cabinets (including server)
• Launch 30 March 2016– then 500k cores
– 112 remote users
– 6,103 SpiNNaker jobs run
SpiNNaker chip
(18 ARM cores)
SpiNNaker board
(864 ARM cores)
SpiNNaker machines
Chapter 3: Building the SpiNNaker Machines
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Simulation
Computational Neuroscience
Theoretical Neuroscience
Neurorobotics
Application range
Chapter 5: Applications – Doing Stuff on the Machine
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Focus: structural plasticity for motion detection
Chapter 7: Learning in neural networksBogdan et. al (2019, EMiT Conference) Bogdan (2019, Thesis)
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Intuition
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Intuition
Homogenous delays
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Intuition
Heterogeneous delays
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Structural plasticity in the wild
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Summary• Building neuromorphic hardware to make computation
more efficient, and to advance our understanding of the brain
• SpiNNaker is a 1-million ARM core digital neuromorphic machine currently in use to explore theoretical and computational neuroscience simulations and neurorobotics applications
• Various models of synaptic and structural plasticity are and can be implemented on this platform; digital substrate offers flexibility in exchange for efficiency
• Structural plasticity is a cool learning mechanism that can be used to grow synapses with different synaptic delays to optimize neuron responses to movement