DEEP NEURAL NETWORK (DNN) ACCELERATORS WITH HETEROGENEOUS TILING

An DNN accelerator includes one or more heterogenous tile sets. A heterogenous tile set includes tiles of different sizes, e.g., PE arrays including different numbers of columns or rows. The DNN accelerator may identify a tile set from the tile sets for running a DNN model based on dimensions of out...

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Main Authors MATHAIKUTTY, Deepak Abraham, RAHA, Arnab, GUPTA, Praveen Kumar, CHEEMA, Umer Iftikhar, SUNG, Raymond Jit-Hung
Format Patent
LanguageEnglish
French
German
Published 28.02.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:An DNN accelerator includes one or more heterogenous tile sets. A heterogenous tile set includes tiles of different sizes, e.g., PE arrays including different numbers of columns or rows. The DNN accelerator may identify a tile set from the tile sets for running a DNN model based on dimensions of output tensors convolutional layers in the DNN. Within the selected tile set, a tile may be selected for a convolutional layer in the DNN, e.g., based on dimensions of the output tensor of the convolutional layer and the size of the tile. After the tile is selected, the workload for running a convolutional operation of the layer may be partitioned and assigned to individual PEs in the tile by partitioning the output tensor into output tensor segments. The workload of computing an individual output tensor segment can be assigned to an individual PE in the tile.
Bibliography:Application Number: EP20230186330