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US Patent 11531873 Convolution acceleration with embedded vector decompression

OverviewStructured DataIssuesContributorsActivity
Is a
Patent
Patent
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Date Filed
June 23, 2020
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Date of Patent
December 20, 2022
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Patent Application Number
16909673
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Patent Citations
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US Patent 10394929 Adaptive execution engine for convolution computing systems
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US Patent 10417364 Tool to create a reconfigurable interconnect framework
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US Patent 10417560 Neural network unit that performs efficient 3-dimensional convolutions
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US Patent 10438115 Neural network unit with memory layout to perform efficient 3-dimensional convolutions
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US Patent 10452605 Method and apparatus for task scheduling on heterogeneous multi-core reconfigurable computing platform
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US Patent 10482155 Winograd algorithm on a matrix processing architecture
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US Patent 10546211 Convolutional neural network on programmable two dimensional image processor
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US Patent 10552222 Task scheduling method and apparatus on heterogeneous multi-core reconfigurable computing platform
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US Patent 10643129 Apparatus and methods for training in convolutional neural networks
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US Patent 10586148 Neural network unit with re-shapeable memory
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•••
Patent Citations Received
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US Patent 12118451 Deep convolutional network heterogeneous architecture
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US Patent 11836608 Convolution acceleration with embedded vector decompression
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US Patent 11880759 Vector quantization decoding hardware unit for real-time dynamic decompression for parameters of neural networks
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US Patent 12073308 Hardware accelerator engine
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US Patent 12079158 Reconfigurable neural engine with extensible instruction set architecture
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Patent Inventor Names
Carmine Cappetta
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Giuseppe Desoli
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Surinder Pal Singh
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Thomas Boesch
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
11531873
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Patent Primary Examiner
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Peguy Jean Pierre
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CPC Code
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G06N 3/063
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H03M 7/3082
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H03M 7/6005
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