Sram architecture for convolutional neural network application
AssigneeTaiwan Semiconductor Manufacturing Company, Ltd.
InventorsJaw-Juinn Horng, Szu-Chun Tsao
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AssigneeTaiwan Semiconductor Manufacturing Company, Ltd.
InventorsJaw-Juinn Horng, Szu-Chun Tsao
Estimating the term…
One aspect of this description relates to a convolutional neural network (CNN). The CNN includes a memory cell array including a plurality of memory cells. Each memory cell includes at least one first capacitive element of a plurality of first capacitive elements. Each memory cell is configured to multiply a weight bit and an input bit to generate a product. The at least one first capacitive element is enabled when the product satisfies a predetermined threshold. The CNN includes a reference cell array including a plurality of second capacitive elements. The CNN includes a memory controller configured to compare a first signal associated with the plurality of first capacitive elements with a second signal associated with at least one second capacitive element of the plurality of second capacitive elements, and, based on the comparison, determine whether the at least one first capacitive element is enabled.
A convolutional neural network (CNN) comprises:
A method, by a memory controller, comprising:
A memory cell comprising:
Dependencies are inferred from the claim text.