IP Library Granted Patent US 8,909,576
Granted Patent B2
US 8,909,576 · App. 13/235,341 · Granted Dec 9, 2014

Neuromorphic event-driven neural computing architecture in a scalable neural network

Inventors: Filipp Akopyan (New Windsor, NY); John V. Arthur (Mountain View, CA); Rajit Manohar (Ithaca, NY); Paul A. Merolla (Palo Alto, CA); Dharmendra S. Modha (San Jose, CA); Alyosha Molnar (Ithaca, NY); William P. Risk, III (Mountain View, CA)
Assignee: International Business Machines Corporation
G06N3/049G06N3/063
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Quick Facts
Patent No.
US 8,909,576
App. No.
13/235,341
Granted
Dec 9, 2014
Kind
B2
Abstract

An event-driven neural network includes a plurality of interconnected core circuits is provided. Each core circuit includes an electronic synapse array has multiple digital synapses interconnecting a plurality of digital electronic neurons. A synapse interconnects an axon of a pre-synaptic neuron with a dendrite of a post-synaptic neuron. A neuron integrates input spikes and generates a spike event in response to the integrated input spikes exceeding a threshold. Each core circuit also has a scheduler that receives a spike event and delivers the spike event to a selected axon in the synapse array based on a schedule for deterministic event delivery.

Claims (19)

1. A neural network, comprising:

a plurality of interconnected core circuits, each core circuit comprising:

an electronic synapse array comprising multiple digital synapses interconnecting a plurality of digital electronic neurons, wherein each synapse interconnects an axon of a pre-synaptic neuron with a dendrite of a post-synaptic neuron, wherein each neuron integrates input spikes and generates a spike event in response to the integrated input spikes exceeding a potentiation threshold, and wherein each spike event includes a corresponding timestamp indicating generation of the spike event; and

a scheduler that receives one or more spike events targeting one or more axons in the synapse array, and selectively imposes a delay on the spike events received before delivering the spike events to the axons, wherein, for each spike event received, the scheduler delivers the spike event to a selected axon in the synapse array based on a schedule for deterministic event delivery and a corresponding timestamp of the spike event.

2. The neural network of claim 1 , wherein the scheduler delivers the spike event to a selected axon in the synapse array after a delay period.

3. The neural network of claim 2 , wherein the delay period is based on a timestamp indicating generation of the spike event and a predetermined delay for event delivery.

4. The neural network of claim 1 , wherein the scheduler selectively imposes a delay on delivery of the received spike events for deterministic event delivery.

5. The neural network of claim 1 , wherein the events are delivered with the same propagation period from event generation.

6. The neural network of claim 1 , further comprising an intra-circuit event router for one or more core circuits, wherein the intra-circuit event router routes events from a spiking neuron to a destination axon in the synapse array.

7. The neural network of claim 6 , further comprising an event routing system interconnecting the core circuits.

8. The neural network of claim 7 , wherein the event routing system comprises a plurality of inter-circuit event routers that route events between core circuits.

9. A non-transitory computer-useable storage medium for event delivery in a neural network including multiple core modules, wherein each core module includes an electronic synapse array comprising multiple digital synapses interconnecting a plurality of digital electronic neurons such that each synapse interconnects an axon of a pre-synaptic neuron with a dendrite of a post-synaptic neuron, said medium having a computer-readable program, wherein the program upon being processed on a computer causes the computer to implement the steps of:

integrating input spikes in an integrate and fire digital neuron, and in response to the integrated inputs exceeding a threshold, generating and sending a spike event to digital synapses interconnecting the neuron to other neurons via the synapse array, wherein each spike event includes a corresponding timestamp indicating generation of the spike event;

receiving one or more spike events targeting one or more axons in the synapse array, and selectively imposing a delay on the spike events received before delivering the spike events to the axons, wherein, for each spike event received, the spike event is delivered to a selected axon in the synapse array based on a schedule for deterministic event delivery and a corresponding timestamp of the spike event.

10. The non-transitory computer-useable storage medium of claim 9 , wherein the program upon being processed on a computer causes the computer to further implement the steps of:

delivering the spike event to a selected axon in the synapse array after a delay period.

11. The non-transitory computer-useable storage medium of claim 10 , wherein the delay period is based on a timestamp indicating generation of the spike event and a predetermined delay for event delivery.

12. The non-transitory computer-useable storage medium of claim 9 , wherein the program upon being processed on a computer causes the computer to further implement the steps of:

selectively imposing a delay on delivery of the received spike events for deterministic event delivery.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 16, 2011
From: AKOPYAN, FILIPP; ARTHUR, JOHN V.; MEROLLA, PAUL A.; MODHA, DHARMENDRA S.; RISK, WILLIAM P., III
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 026922/0869 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 16, 2011
From: MANOHAR, RAJIT; MOLNAR, ALYOSHA
To: CORNELL UNIVERSITY
Reel/Frame 026922/0897 →
Continuity (1)
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