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US 2022/0101083 A1Published application
Methods and apparatus for matrix processing in a convolutional neural network
AssigneeTexas Instruments Incorporated
InventorsMihir Narendra Mody, Shyam Jagannathan, Manu Mathew, Jason T. Jones
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Abstract
Described examples include an integrated circuit including a vector multiply unit including a plurality of multiply/accumulate nodes, in which the vector multiply unit is operable to provide an output from the multiply/accumulate nodes, a first data feeder operable to provide first data to the vector multiply unit in vector format, and a second data feeder operable to provide second data to the vector multiply unit in vector format.
Claims6
A method comprising:
- receiving, by a first data feeder, first data;
- providing, by a first data feeder, a portion of the first data to a plurality of multiply/accumulate nodes of a vector multiply unit;
- providing, by a second data feeder, second data to the plurality of multiply/accumulate nodes of the vector multiply unit;
- rearranging, using the first data feeder and the second data feeder, the first data and the second data;
- multiplying, by the multiply/accumulate nodes of the vector multiply unit, the first data and the second data as a partial product;
- accumulating, by the multiply/accumulator nodes of the vector multiply unit, the multiplied first data and second data;
- and
- receiving, from the multiply/accumulator nodes of the vector multiply unit by a feature processing unit, the accumulated multiplied first data and second data;
- in which the rearranging is performed so that individual feature values in the accumulated multiplied first data and second data are generated by corresponding individual ones of the multiply/accumulator nodes.
6 more elements
Dependencies are inferred from the claim text.