CPC G06N 3/08 (2013.01) [G06F 17/16 (2013.01)] | 20 Claims |
1. A method of storing a sparse weight matrix for a trained artificial neural network in a circuit comprising a plurality of clusters, the method comprising:
partitioning the sparse weight matrix, based on an arrangement of zero-value weights and non-zero value weights in the sparse weight matrix, into at least one first sub-block and at least one second sub-block, the at least one first sub-block comprising a plurality of weight values, the plurality of weight values of the at least one first sub-block containing only zero-value weights and the at least one second sub-block comprising non-zero value weights; and
assigning the non-zero value weights in the at least one second sub-block to at least one cluster of the plurality of clusters of the circuit,
wherein the circuit is configured to perform matrix-vector-multiplication (MVM) between the non-zero value weights of the at least one second sub-block and an input vector.
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