WEIGHT SPARSITY IN DATA PROCESSING ENGINES

Examples herein describe techniques for reducing the amount of memory used during weight sparsity. When decompressing the weights, the uncompressed weight data typically has many zero values. By knowing the location of these zero values (e.g., their indices in a weight matrix), the processor core can prune some of the activations (e.g., logically reduce the size of the activation matrix) which improves the efficiency of the processor core. In embodiments herein, the processor core includes logic for identifying the indices of the non-zero value after decompressing the compressed weights. These indices can then be used to prune the activations to improve the efficiency of the processor core.