Generating and executing context-specific neural network models based on target runtime parameters

A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for generating and executing a deep neural network (DNN) based on target runtime parameters, the method comprising:

• receiving a trained original model and a set of target runtime parameters for the DNN, wherein the target runtime parameters are associated with one or more of the following for the DNN:
• desired operating conditions, desired resource utilization, and desired accuracy of results;
• generating a context-specific model based on the original model and the set of target runtime parameters;
• generating an operational plan for executing both the original model and the context-specific model to meet requirements of the target runtime parameters;
• and
• controlling execution of the original model and the context-specific model based on the operational plan.

A system that generates and executes a deep neural network (DNN) based on target runtime parameters, comprising:

• at least one processor and at least one associated memory;
• and
• a processing mechanism that executes on the at least one processor, wherein during operation, the processing mechanism:
• receives a trained original model and a set of target runtime parameters for the DNN, wherein the target runtime parameters are associated with one or more of the following for the DNN:
• desired operating conditions, desired resource utilization, and desired accuracy of results;
• generates a context-specific model based on the original model and the set of target runtime parameters;
• generates an operational plan for executing both the original model and the context-specific model to meet requirements of the target runtime parameters;
• and
• controls execution of the original model and the context-specific model based on the operational plan.