Quantized neural network training and inference
AssigneeNVIDIA Corporation
InventorsThierry TAMBE, Steve DAI, Brucek KHAILANY, Rangharajan VENKATESAN
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Abstract
One embodiment of a computer-implemented method for processing a neural network comprises receiving a first quantized matrix that corresponds to a portion of a multi-dimensional input tensor and has been quantized based on a first scale factor; and performing one or more computational operations using the first quantized matrix and the first scale factor to generate one or more data values that correspond to a first portion of a multi-dimensional output tensor.
Claims20
A computer-implemented method for processing a neural network, the method comprising:
- receiving a first quantized matrix that corresponds to a portion of a multi-dimensional input tensor and has been quantized based on a first scale factor;
- and
- performing one or more computational operations using the first quantized matrix and the first scale factor to generate one or more data values that correspond to a first portion of a multi-dimensional output tensor.
One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of:
- receiving a first quantized matrix that corresponds to a portion of a multi-dimensional input tensor and has been quantized based on a first scale factor;
- and
- performing one or more computational operations using the first quantized matrix and the first scale factor to generate one or more data values that correspond to a first portion of a multi-dimensional output tensor.
A system comprising:
- one or more memories storing instructions;
- and
- one or more processors that are coupled to the one or more memories and,
- when executing the instructions, perform the steps of:
- receiving a first quantized matrix that corresponds to a portion of a multi-dimensional input tensor and has been quantized based on a first scale factor;
- and
- performing one or more computational operations using the first quantized matrix and the first scale factor to generate one or more data values that correspond to a first portion of a multi-dimensional output tensor.
Dependencies are inferred from the claim text.