Dynamic quantization for energy efficient deep learning
AssigneeQUALCOMM Incorporated
InventorsRandy ARDYWIBOWO, Venkata Ravi Kiran DAYANA, Hau HWANG
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Abstract
A method performed by a deep neural network (DNN) includes receiving, at a layer of the DNN during an inference stage, a layer input comprising content associated with a DNN input received at the DNN. The method also includes quantizing one or more parameters of a plurality of parameters associated with the layer based on the content of the layer input. The method further includes performing a task corresponding to the DNN input, the task performed with the one or more one quantized parameters.
Claims30
A method performed by a deep neural network (DNN), comprising:
- receiving, at a layer of the DNN during an inference stage, a layer input comprising content associated with a DNN input received at the DNN;
- quantizing one or more parameters of a plurality of parameters associated with the layer based on the content of the layer input;
- and
- performing a task corresponding to the DNN input, the task performed with the one or more one quantized parameters.
An apparatus for implementing a deep neural network (DNN), comprising:
- a processor;
- a memory coupled with the processor;
- and
- instructions stored in the memory and operable, when executed by the processor, to cause the apparatus to:
- receive, at a layer of the DNN during an inference stage, a layer input comprising content associated with a DNN input received at the DNN;
- quantize one or more parameters of a plurality of parameters associated with the layer based on the content of the layer input;
- and
- perform a task corresponding to the DNN input, the task performed with the one or more one quantized parameters.
A non-transitory computer-readable medium having program code recorded thereon for a deep neural network (DNN), the program code executed by a processor and comprising:
- program code to receive, at a layer of the DNN during an inference stage, a layer input comprising content associated with a DNN input received at the DNN;
- program code to quantize one or more parameters of a plurality of parameters associated with the layer based on the content of the layer input;
- and
- program code to perform a task corresponding to the DNN input, the task performed with the one or more one quantized parameters.
An apparatus implementing a deep neural network (DNN), comprising:
- means for receiving, at a layer of the DNN during an inference stage, a layer input comprising content associated with a DNN input received at the DNN;
- means for quantizing one or more parameters of a plurality of parameters associated with the layer based on the content of the layer input;
- and
- means for performing a task corresponding to the DNN input, the task performed with the one or more one quantized parameters.
Dependencies are inferred from the claim text.