Dynamic Uncompression For Channel Separable Operation In Neural Network

Abstract: A compute block can dynamically uncompress compressed data for executing a channel-separable operation. The compressed data includes one or more nonzero-valued data elements. The compressed data may be stored in a datastore along with a sparsity bitmap of an input operand including the compressed data. An uncompressing module may determine whether the input operand includes any zero-valued data element, e.g., by determining whether the sparsity bitmap includes a zero-valued bit. After determining that the sparsity bitmap includes a zero-valued bit, the uncompressing module inserts a zero-valued data element into the compressed data based on a position of the bit in the sparsity bitmap and generates uncompressed data and update the sparsity bitmap so that all the bits become ones. The uncompressed dense data is transmitted to one or more processing elements (PE) in the compute block for computing an output operand based on the uncompressed dense data.

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