Invention Grant
- Patent Title: Efficient tile mapping for row-by-row convolutional neural network mapping for analog artificial intelligence network inference
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Application No.: US16884128Application Date: 2020-05-27
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Publication No.: US11562240B2Publication Date: 2023-01-24
- Inventor: Hsinyu Tsai , Geoffrey Burr , Pritish Narayanan
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Cantor Colburn LLP
- Agent Daniel Yeates
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

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.
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