US 11,907,830 B2 · Neural network architecture using control logic determining convolution operation sequence

Abstract

Hardware for implementing a Deep Neural Network (DNN) having a convolution layer. A plurality of convolution engines each perform a convolution operation by applying a filter to a data window. Each of the plurality of convolution engines includes multiplication logic that combines a weight of a filter with a respective data value of a data window; control logic that receives configuration information identifying a set of filters for operation on a set of data windows at the plurality of convolution engines; determines a sequence of convolution operations for evaluation at the multiplication logic; requests weights and data values for at least partially applying a filter to a data window; and causes the multiplication logic to combine the weights with their respective data values. Accumulation logic accumulates the results of a plurality of combinations performed by the multiplication logic to form an output for a convolution operation of the determined sequence.

Claims20

Dependent claims

Hardware for implementing a Deep Neural Network (DNN), the hardware comprising a plurality of convolution engines each operable to perform a convolution operation by applying a filter to a data window, each filter comprising a set of weights for combination with respective data values of the data window, and each of the plurality of convolution engines comprising:

multiplication logic operable to combine a filter weight with a respective data window value;
control logic configured to:
receive configuration information identifying a set of filters for combination with a set of data windows,
determine, using the configuration information, a sequence of convolution operations, and
in dependence on the determined sequence of convolution operations, cause the multiplication logic to at least partially combine the set of filters with respective data windows of the set of data windows;
and
accumulation logic configured to accumulate results of a plurality of combinations performed by the multiplication logic so as to form an output for a convolution operation of the determined sequence.

4 more elements

A method for implementing a Deep Neural Network (DNN) in hardware, the hardware comprising a plurality of convolution engines each operable to perform a convolution operation by applying a filter to a data window, and each filter comprising a set of weights for combination with respective data values of the data window, the method comprising, at each of the plurality of convolution engines:

receiving configuration information identifying a set of the filters for combination with a set of the data windows;
determining, using the configuration information, a sequence of convolution operations;
in dependence on the determined sequence of convolution operations, at least partially combining, by multiplication, the set of filters with respective data windows of the set of data windows;
and
accumulating results of a plurality of the multiplications so as to form an output for a convolution operation of the determined sequence.

2 more elements

Dependencies are inferred from the claim text.

Neural network architecture using control logic determining convolution operation sequence

Life of this patent

Neural network architecture using control logic determining convolution operation sequence

Life of this patent

Abstract

Claims20