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1. 发明授权

US10990651B2 Systems and methods for efficient matrix multiplication 有权
公开(公告)号：US10990651B2
公开(公告)日：2021-04-27
申请号：US16543426
申请日：2019-08-16
申请人： Rain Neuromorphics Inc.
发明人： Jack David Kendall
IPC分类号： G06F16/17 , G06N3/063 , G06F17/16 , G11C13/00
摘要： Disclosed are systems and methods for performing efficient vector-matrix multiplication using a sparsely-connected conductance matrix and analog mixed signal (AMS) techniques. Metal electrodes are sparsely connected using coaxial nanowires. Each electrode can be used as an input/output node or neuron in a neural network layer. Neural network synapses are created by random connections provided by coaxial nanowires. A subset of the metal electrodes can be used to receive a vector of input voltages and the complementary subset of the metal electrodes can be used to read output currents. The output currents are the result of vector-matrix multiplication of the vector of input voltages with the sparsely-connected matrix of conductances.

2. 发明申请

US20230127533A1 LEARNING IN TIME VARYING, DISSIPATIVE ELECTRICAL NETWORKS 有权
公开(公告)号：US20230127533A1
公开(公告)日：2023-04-27
申请号：US18077184
申请日：2022-12-07
申请人： Rain Neuromorphics Inc.
发明人： Jack David Kendall
IPC分类号： G06N3/08 , G06N3/063
摘要： A method for performing learning in a dissipative learning network is described. The method includes determining a trajectory for the dissipative learning network and determining a perturbed trajectory for the dissipative learning network based on a plurality of target outputs. Gradients for a portion of the dissipative learning network are determined based on the trajectory and the perturbed trajectory. The portion of the dissipative learning network is adjusted based on the gradients.

3. 发明申请

US20220284291A1 LEARNING IN TIME VARYING, DISSIPATIVE ELECTRICAL NETWORKS 有权
公开(公告)号：US20220284291A1
公开(公告)日：2022-09-08
申请号：US17685335
申请日：2022-03-02
申请人： Rain Neuromorphics Inc.
发明人： Jack David Kendall
IPC分类号： G06N3/08 , G06N3/063
摘要： A method for performing learning in a dissipative learning network is described. The method includes determining a trajectory for the dissipative learning network and determining a perturbed trajectory for the dissipative learning network based on a plurality of target outputs. Gradients for a portion of the dissipative learning network are determined based on the trajectory and the perturbed trajectory. The portion of the dissipative learning network is adjusted based on the gradients.

4. 发明申请

US20210216610A1 SYSTEMS AND METHODS FOR EFFICIENT MATRIX MULTIPLICATION 有权
公开(公告)号：US20210216610A1
公开(公告)日：2021-07-15
申请号：US17217776
申请日：2021-03-30
申请人： Rain Neuromorphics Inc.
发明人： Jack David Kendall
IPC分类号： G06F17/16 , G11C13/00 , G06N3/063
摘要： Disclosed are systems and methods for performing efficient vector-matrix multiplication using a sparsely-connected conductance matrix and analog mixed signal (AMS) techniques. Metal electrodes are sparsely connected using coaxial nanowires. Each electrode can be used as an input/output node or neuron in a neural network layer. Neural network synapses are created by random connections provided by coaxial nanowires. A subset of the metal electrodes can be used to receive a vector of input voltages and the complementary subset of the metal electrodes can be used to read output currents. The output currents are the result of vector-matrix multiplication of the vector of input voltages with the sparsely-connected matrix of conductances.

5. 发明申请

US20230023533A1 MEMRISTIVE DEVICE 有权
公开(公告)号：US20230023533A1
公开(公告)日：2023-01-26
申请号：US17889276
申请日：2022-08-16
申请人： Rain Neuromorphics Inc.
发明人： Jack David Kendall , Suhas Kumar , Nikita Gaur
IPC分类号： H01L27/24 , H01L45/00
摘要： A memristive device and mechanisms for providing and using the memristive device are described. The memristive device includes a nanowire, a plurality of memristive plugs and a plurality of electrodes. The nanowire has a conductive core and an insulator coating at least a portion of the conductive core. The insulator has a plurality of apertures therein. The memristive plugs are for the apertures. At least a portion of each of the memristive plugs resides in each of the apertures. The memristive plugs are between the conductive core and the electrodes.

6. 发明授权

US11450712B2 Memristive device 有权
公开(公告)号：US11450712B2
公开(公告)日：2022-09-20
申请号：US16794187
申请日：2020-02-18
申请人： Rain Neuromorphics Inc.
发明人： Jack David Kendall , Suhas Kumar , Nikita Gaur
IPC分类号： H01L45/00 , H01L27/24 , G06N3/063
摘要： A memristive device and mechanisms for providing and using the memristive device are described. The memristive device includes a nanowire, a plurality of memristive plugs and a plurality of electrodes. The nanowire has a conductive core and an insulator coating at least a portion of the conductive core. The insulator has a plurality of apertures therein. The memristive plugs are for the apertures. At least a portion of each of the memristive plugs resides in each of the apertures. The memristive plugs are between the conductive core and the electrodes.

7. 发明申请

US20210406656A1 LITHOGRAPHIC MEMRISTIVE ARRAY 有权
公开(公告)号：US20210406656A1
公开(公告)日：2021-12-30
申请号：US17354829
申请日：2021-06-22
申请人： Rain Neuromorphics Inc.
发明人： Suhas Kumar , Jack David Kendall , Alexander Almela Conklin
IPC分类号： G06N3/063 , H01L27/24 , H01L45/00 , G11C11/54 , G11C13/00 , G06N3/04
摘要： A memristive device is described. The memristive device includes a first layer having a first plurality of conductive lines, a second layer having a second plurality of conductive lines, and memristive interlayer connectors. The first and second layers differ. The first and second pluralities of conductive lines are each lithographically defined. The first and second pluralities of conductive lines are insulated from each other. The memristive interlayer connectors are memristively coupled with a first portion of the first plurality of conductive lines and memristively coupled with a second portion of the second plurality of conductive lines. The memristive interlayer connectors are thus sparsely coupled with the first and second pluralities of conductive lines. Each memristive interlayer connector includes a conductive portion and a memristive portion. The memristive portion is between the conductive portion and corresponding line(s) of the first plurality of conductive lines and/or the second plurality of conductive lines.

8. 发明申请

US20210257411A1 MEMRISTIVE DEVICE 有权
公开(公告)号：US20210257411A1
公开(公告)日：2021-08-19
申请号：US16794187
申请日：2020-02-18
申请人： Rain Neuromorphics Inc.
发明人： Jack David Kendall , Suhas Kumar , Nikita Gaur
IPC分类号： H01L27/24 , H01L45/00
摘要： A memristive device and mechanisms for providing and using the memristive device are described. The memristive device includes a nanowire, a plurality of memristive plugs and a plurality of electrodes. The nanowire has a conductive core and an insulator coating at least a portion of the conductive core. The insulator has a plurality of apertures therein. The memristive plugs are for the apertures. At least a portion of each of the memristive plugs resides in each of the apertures. The memristive plugs are between the conductive core and the electrodes.

9. 发明授权

US10430493B1 Systems and methods for efficient matrix multiplication 有权
公开(公告)号：US10430493B1
公开(公告)日：2019-10-01
申请号：US16376169
申请日：2019-04-05
申请人： Rain Neuromorphics INC.
发明人： Jack Kendall
IPC分类号： G06F17/16 , G11C13/00 , G06N3/063
摘要： Disclosed are systems and methods for performing efficient vector-matrix multiplication using a sparsely-connected conductance matrix and analog mixed signal (AMS) techniques. Metal electrodes are sparsely connected using coaxial nanowires. Each electrode can be used as an input/output node or neuron in a neural network layer. Neural network synapses are created by random connections provided by coaxial nanowires. A subset of the metal electrodes can be used to receive a vector of input voltages and the complementary subset of the metal electrodes can be used to read output currents. The output currents are the result of vector-matrix multiplication of the vector of input voltages with the sparsely-connected matrix of conductances.

10. 发明申请

US20230138695A1 LOCAL TRAINING OF NEURAL NETWORKS 有权
公开(公告)号：US20230138695A1
公开(公告)日：2023-05-04
申请号：US17977991
申请日：2022-10-31
申请人： Rain Neuromorphics Inc.
发明人： Suhas Kumar , Alexander Almela Conklin , Jack David Kendall
IPC分类号： G06N3/04 , G06N3/063
摘要： A method for performing learning is described. A free inference is performed on a learning network for input signals. The input signals correspond to target output signals. The learning network includes inputs that receive the input signals, neurons, weights interconnecting the neurons, and outputs. The learning network is described by an energy for the free inference. The energy includes an interaction term corresponding to interactions consisting of neuron pair interactions. The free inference results in output signals. A first portion of the plurality of weights corresponding to data flow for the free inference. A biased inference is performed on the learning network by providing the input signals to the inputs and bias signals to the outputs. The bias signals are based on the target output signals and the output signals. The bias signals are fedback to the learning network through a second portion of the weights corresponding to a transpose of the first portion of the weights. At locations in the learning network, learning network equilibrium states are determined for the biased inference. The weights are updated based on the learning network equilibrium states.

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