Efficient execution of machine learning models using partitioning

A processing system, comprising:

• a memory having executable instructions stored thereon;
• and
• one or more processors coupled to the memory and configured to execute the executable instructions in order to cause the processing system to:
• receive a graph for a machine learning model, the graph for the machine learning model including a plurality of subgraphs representing different portions of the machine learning model;
• instantiate the machine learning model across a plurality of process domains associated with a same application based on the plurality of subgraphs in the graph for the machine learning model;
• generate an inference based on executing the machine learning model across the plurality of process domains;
• and
• take one or more actions based on the generated inference.

A processing system, comprising:

• means for receiving a graph for a machine learning model, the graph for the machine learning model including a plurality of subgraphs representing different portions of the machine learning model;
• means for instantiating the machine learning model across a plurality of process domains associated with a same application based on the plurality of subgraphs in the graph for the machine learning model;
• means for generating an inference based on executing the machine learning model across the plurality of process domains;
• and
• means for taking one or more actions based on the generated inference.

A non-transitory computer-readable medium having executable instructions stored thereon which, when executed by one or more processors, perform an operation comprising:

• receiving a graph for a machine learning model, the graph for the machine learning model including a plurality of subgraphs representing different portions of the machine learning model;
• instantiating the machine learning model across a plurality of process domains associated with a same application based on the plurality of subgraphs in the graph for the machine learning model;
• generating an inference based on executing the machine learning model across the plurality of process domains;
• and
• taking one or more actions based on the generated inference.