公开(公告)号：IL297331A

公开(公告)日：2022-12-01

申请号：IL29733122

申请日：2022-10-13

Applicant: IBM ,  HSINYU TSAI ,  GEOFFREY BURR ,  PRITISH NARAYANAN

Inventor： HSINYU TSAI ,  GEOFFREY BURR ,  PRITISH NARAYANAN

Abstract: Implementing a convolutional neural network (CNN) includes configuring a crosspoint array to implement a convolution layer in the CNN. Convolution kernels of the layer are stored in crosspoint devices of the array. Computations for the CNN are performed by iterating a set of operations for a predetermined number of times. The operations include transmitting voltage pulses corresponding to a subpart of a vector of input data to the crosspoint array. The voltage pulses generate electric currents that are representative of performing multiplication operations at the crosspoint device based on weight values stored at the crosspoint devices. A set of integrators accumulates an electric charge based on the output electric currents from the respective crosspoint devices. The crosspoint array outputs the accumulated charge after iterating for the predetermined number of times. The accumulated charge represents a multiply-add result of the vector of input data and the one or more convolution kernels.

公开(公告)号：GB2582233A

公开(公告)日：2020-09-16

申请号：GB202009750

申请日：2018-11-30

Applicant: IBM

Inventor： JUNGWOOK CHOI ,  PRITISH NARAYANAN ,  CHIA-YU CHEN ,  KAILASH GOPALAKRISHNAN ,  SUYOG GUPTA

IPC: G06N3/08

Abstract: A system, having a memory that stores computer executable components, and a processor that executes the computer executable components, reduces data size in connection with training a neural network by exploiting spatial locality to weight matrices and effecting frequency transformation and compression. A receiving component receives neural network data in the form of a compressed frequency-domain weight matrix. A segmentation component segments the initial weight matrix into original sub-components, wherein respective original sub-components have spatial weights. A sampling component applies a generalized weight distribution to the respective original sub-components to generate respective normalized sub-components. A transform component applies a transform to the respective normalized sub-components. A cropping component crops high-frequency weights of the respective transformed normalized sub-components to yield a set of low-frequency normalized sub-components to generate a compressed representation of the original sub-components.

公开(公告)号：GB2597000B

公开(公告)日：2022-12-07

申请号：GB202115312

申请日：2020-04-07

Applicant: IBM

Inventor： ESTEBAN AMBROGIO GALI ,  GEOFFREY BURR ,  CHARLES MACKIN ,  SIDNEY TSAI ,  PRITISH NARAYANAN

IPC: G06N3/063 ,  G06N3/04 ,  G11C11/54 ,  G11C13/00

Abstract: A computer implemented method includes updating weight values associated with a plurality of analog synapses in a cross-bar array that implements an artificial neural network by sending a pulse sequence to the analog synapses. Each analog synapse includes a conductance unit, wherein a weight value of the analog synapse is based on a conductance value of the conductance unit. The pulse sequence changes the conductance value. The method further includes comparing the weight values of the analog synapses with target weight values associated with the analog synapses and selecting a set of analog synapses based on the comparison. The method further includes updating the weight values of the selected analog synapses by sending a set of electric pulses of varying durations.

公开(公告)号：GB2594673A

公开(公告)日：2021-11-03

申请号：GB202113036

申请日：2020-03-03

Applicant: IBM

Inventor： AAKASH PUSHP ,  PRITISH NARAYANAN

IPC: H01L43/08 ,  G06N3/063 ,  H01L27/22

Abstract: A magnetic double tunnel junction (MDTJ) (which, preferably, has a large aspect ratio, wherein length L of the MDTJ >> width w of the MDTJ) has magnetic domain wall(s) or DW(s) in the free layer of the MDTJ, wherein controlled movement of the DW(s) across the free layer is effected in response to the polarity, magnitude, and duration of a voltage pulse across the MDTJ. The motion and relative position of DW(s) causes the conductance of the MDTJ (that is measured across the MDTJ) to change in a symmetric and linear fashion. By reversing the polarity of the bias voltage, the creation and/or direction of the DW(s) motion can be reversed, thereby allowing for a bi-directional response to the input pulse.

公开(公告)号：GB2594673B

公开(公告)日：2022-07-13

申请号：GB202113036

申请日：2020-03-03

Applicant: IBM

Inventor： AAKASH PUSHP ,  PRITISH NARAYANAN

IPC: H01L43/08 ,  G06N3/063 ,  H01L27/22

Abstract: A magnetic double tunnel junction (MDTJ) (which, preferably, has a large aspect ratio, wherein length L of the MDTJ>>width w of the MDTJ) has magnetic domain wall(s) or DW(s) in the free layer of the MDTJ, wherein controlled movement of the DW(s) across the free layer is effected in response to the polarity, magnitude, and duration of a voltage pulse across the MDTJ. The motion and relative position of DW(s) causes the conductance of the MDTJ (that is measured across the MDTJ) to change in a symmetric and linear fashion. By reversing the polarity of the bias voltage, the creation and/or direction of the DW(s) motion can be reversed, thereby allowing for a bi-directional response to the input pulse.

公开(公告)号：GB2597000A

公开(公告)日：2022-01-12

申请号：GB202115312

申请日：2020-04-07

Applicant: IBM

Inventor： ESTEBAN AMBROGIO GALI ,  GEOFFREY BURR ,  CHARLES MACKIN ,  SIDNEY TSAI ,  PRITISH NARAYANAN

IPC: G06N3/06

Abstract: A computer implemented method includes updating weight values associated with a plurality of analog synapses in a cross-bar array that implements an artificial neural network by sending a pulse sequence to the analog synapses. Each analog synapse includes a conductance unit, wherein a weight value of the analog synapse is based on a conductance value of the conductance unit. The pulse sequence changes the conductance value. The method further includes comparing the weight values of the analog synapses with target weight values associated with the analog synapses and selecting a set of analog synapses based on the comparison. The method further includes updating the weight values of the selected analog synapses by sending a set of electric pulses of varying durations.

公开(公告)号：GB2569710A

公开(公告)日：2019-06-26

申请号：GB201903530

申请日：2017-09-21

Applicant: IBM

Inventor： GEOFFREY BURR ,  PRITISH NARAYANAN

IPC: G06N3/04 ,  G06N3/08

Abstract: Single-shot learning and disambiguation of multiple predictions in hierarchical temporal memory is provided. In various embodiments an input sequence is read. The sequence comprises first, second, and third time-ordered components. Each of the time-ordered components is encoded in a sparse distributed representation. The sparse distributed representation of the first time-ordered component is inputted into a first portion of a hierarchical temporal memory. The sparse distributed representation of the second time- ordered component is inputted into a second portion of the hierarchical temporal memory. The second portion is connected to the first portion by a first plurality of synapses. A plurality of predictions as to the third time-ordered component is generated within a third portion of the hierarchical temporal memory. The third portion is connected to the second portion by a second plurality of synapses. Based on the plurality of predictions, additional synaptic connections are added between the first portion and the second portion.