Techniques for layer fusion group selection in deep learning compilers

An apparatus for scheduling a workflow, comprising:

• a memory;
• and
• at least one processor coupled to the memory and configured to:
• obtain, data sizes of operations in a model graph corresponding to the workflow, wherein the model graph includes multiple operations and an execution order of the operations;
• determine, one or more operation fusion groups based on data sizes of adjacent operations and a storage capacity of one or more target memories, wherein intermediate data generated during processing by each operation fusion group is not transferred outside a corresponding target memory;
• and
• update, the model graph based on the determined one or more operation fusion groups.

A computer-readable medium storing computer executable code for scheduling a workflow, comprising code to:

• obtain, data sizes of operations in a model graph corresponding to the workflow, wherein the model graph includes multiple operations and an execution order of the operations;
• determine, one or more operation fusion groups based on data sizes of adjacent operations and a storage capacity of one or more target memories, wherein intermediate data generated during processing by each operation fusion group is not transferred outside a corresponding target memory;
• and
• update, the model graph based on the determined one or more operation fusion groups.