Adaptive scheduling for executing machine learning operations in a multiprocessor computing device

A processing system, comprising:

• a memory comprising computer-executable instructions;
• and
• one or more processors configured to execute the computer-executable instructions and cause the processing system to:
• measure, during execution of operations in a first portion of a machine learning model on a first processing unit of a computing device, a temperature for each of a plurality of locations on the computing device;
• determine that a temperature measured for the first processing unit exceeds a threshold temperature;
• select, based on one or more operating parameters for the computing device, a second processing unit of the computing device to use in executing operations in a second portion of the machine learning model;
• and
• schedule execution of operations in the second portion of the machine learning model on the second processing unit.

A processing system, comprising:

• means for measuring, during execution of operations in a first portion of a machine learning model on a first processing unit of a computing device, a temperature for each of a plurality of locations on the computing device;
• means for determining that a temperature measured for the first processing unit exceeds a threshold temperature;
• means for selecting, based on one or more operating parameters for the computing device, a second processing unit of the computing device to use in executing operations in a second portion of the machine learning model;
• and
• means for scheduling execution of operations in the second portion of the machine learning model on the second processing unit.

A non-transitory computer-readable medium comprising computer-executable instructions that, when executed by one or more processors of a processing system, cause the processing system to perform a method comprising:

• during execution of operations in a first portion of a machine learning model on a first processing unit of a computing device, measuring a temperature for each of a plurality of locations on the computing device;
• determining that a temperature measured for the first processing unit exceeds a threshold temperature;
• selecting, based on one or more operating parameters for the computing device, a second processing unit of the computing device to use in executing operations in a second portion of the machine learning model;
• and
• scheduling execution of operations in the second portion of the machine learning model on the second processing unit.