Abstract: A processing device for executing a machine learning neural network operation includes memory and a processor. The processor is configured to receive input data at a layer of the machine learning neural network operation, receive a plurality of sorted filters to be applied to the input data, apply the plurality of sorted filters to the input data to produce a plurality of different feature maps, compress the plurality of different feature maps according to a similarity of the feature maps relative to each other and store the plurality of different feature maps in the memory.

Abstract: A processing device for executing a machine learning neural network operation includes memory and a processor. The processor is configured to receive input data at a layer of the machine learning neural network operation, receive a plurality of sorted filters to be applied to the input data, apply the plurality of sorted filters to the input data to produce a plurality of different feature maps, compress the plurality of different feature maps according to a sparsity of the feature maps and store the plurality of different feature maps in the memory.

Abstract: A processing device for executing a machine learning neural network operation includes memory and a processor. The processor is configured to receive input data at a layer of the machine learning neural network operation, receive a plurality of sorted filters to be applied to the input data, apply the plurality of sorted filters to the input data to produce a plurality of different feature maps, compress the plurality of different feature maps according to a sparsity of the feature maps and store the plurality of different feature maps in the memory.

Abstract: A processing device for executing a machine learning neural network operation includes memory and a processor. The processor is configured to receive input data at a layer of the machine learning neural network operation, receive a plurality of sorted filters to be applied to the input data, apply the plurality of sorted filters to the input data to produce a plurality of different feature maps, compress the plurality of different feature maps according to a similarity of the feature maps relative to each other and store the plurality of different feature maps in the memory.

Abstract: A compressor is configured to determine delta color compression values for a plurality of pixels in a block and subdivide the plurality of pixels in the block into a plurality of groups and transmit a compressed bitstream representative of the delta values. The compressed bitstream includes bits representative of a block header that indicates a range of numbers of bits that are sufficient to represent the delta values, a plurality of group headers that each indicate a group minimum number of bits that is sufficient to represent the delta values in a corresponding one of the plurality of groups, and the delta values encoded using the group minimum number of bits for the group that includes the delta values. A decompressor configured to decompress the compressed bitstream based on the block header, the plurality of group headers, and the encoded delta values.

Abstract: A compressor is configured to determine delta color compression values for a plurality of pixels in a block and subdivide the plurality of pixels in the block into a plurality of groups and transmit a compressed bitstream representative of the delta values. The compressed bitstream includes bits representative of a block header that indicates a range of numbers of bits that are sufficient to represent the delta values, a plurality of group headers that each indicate a group minimum number of bits that is sufficient to represent the delta values in a corresponding one of the plurality of groups, and the delta values encoded using the group minimum number of bits for the group that includes the delta values. A decompressor configured to decompress the compressed bitstream based on the block header, the plurality of group headers, and the encoded delta values.