Systolic array having support for output sparsity

A method comprising:

• receiving an instruction having an operand indicating output sparsity metadata;
• performing multiply-accumulate operations with output sparsity on matrix elements selected via the output sparsity metadata, wherein the output sparsity metadata indicates an operation to perform and an operation to bypass;
• and
• generating updates for weights of a machine learning model according to output sparsity operations performed based on the output sparsity metadata.

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:

• determine an output sparsity pattern to apply during training of a machine learning model;
• generate output sparsity metadata to process weights of the machine learning model according to a determined sparsity pattern;
• perform multiply-accumulate operations with output sparsity on matrix elements selected via the output sparsity metadata, the output sparsity metadata to indicate an operation to perform and an operation to bypass;
• and
• generate weight updates for the machine learning model according to output sparsity operations performed based on the output sparsity metadata.

A data processing system comprising:

• one or more processors;
• and
• a memory coupled with the one or more processors, the memory configured to store instructions to cause the one or more processors to perform operations to:
• receive an instruction having an operand indicating output sparsity metadata;
• perform multiply-accumulate operations with output sparsity on matrix elements selected via the output sparsity metadata, wherein the output sparsity metadata indicates an operation to perform and an operation to bypass;
• and
• generate updates for weights of a machine learning model according to output sparsity operations performed based on the output sparsity metadata.