SPLITTING OF INPUT DATA FOR PROCESSING IN NEURAL NETWORK PROCESSOR

Abstract: embodiments of the present disclosure relate to splitting input data into smaller units for loading into a data buffer and neural engines in a neural processor circuit for performing neural network operations. the input data of a large size is split into slices and each slice is again split into tiles. the tile is uploaded from an external source to a data buffer inside the neural processor circuit but outside the neural engines. each tile is again split into work units sized for storing in an input buffer circuit inside each neural engine. the input data stored in the data buffer and the input buffer circuit is reused by the neural engines to reduce re-fetching of input data. operations of splitting the input data are performed at various components of the neural processor circuit under the management of rasterizers provided in these components.

Inventor(s): Christopher L. MILLS

CPC Classification: G06N3/08 (Learning methods)

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