Tool for facilitating efficiency in machine learning

A method comprising:

• causing a neural network application to implement a library comprising machine learning primitives, wherein the machine learning primitives are usable to analyze a skew pattern observed in a distributed gradient synchronization implemented by the neural network application;
• determining, using the machine learning primitives of the library, a point to apply frequency scaling in a computing device hosting the neural network application without degrading performance of the neural network application at the computing device, the point determined based on analysis of the skew pattern generated by the distributed gradient synchronization;
• and
• determining, using the library as implemented by the neural network application, a core frequency of the frequency scaling applied at the point, wherein the library is to account for skew characteristics associated with the distributed gradient synchronization to decide the core frequency.

A non-transitory machine-readable medium comprising instructions that when executed by a computing device, cause the computing device to perform operations comprising:

• causing a neural network application to implement a library comprising machine learning primitives, wherein the machine learning primitives are usable to analyze a skew pattern observed in a distributed gradient synchronization implemented by the neural network application;
• determining, using the machine learning primitives of the library, a point to apply frequency scaling in the computing device without degrading performance of the neural network application, the point determined based on analysis of the skew pattern generated by the distributed gradient synchronization;
• and
• determining, using the library as implemented by the neural network application, a core frequency of the frequency scaling applied at the point, wherein the library is to account for skew characteristics associated with the distributed gradient synchronization to decide the core frequency.

A system comprising:

• a memory;
• and
• a graphics processor communicably coupled to the memory, the graphics processor to:
• cause a neural network application to implement a library comprising machine learning primitives, wherein the machine learning primitives are usable to analyze a skew pattern observed in a distributed gradient synchronization implemented by the neural network application;
• determine, using the machine learning primitives of the library, a point to apply frequency scaling in the graphics processor without degrading performance of the neural network application, the point determined based on analysis of the skew pattern generated by the distributed gradient synchronization;
• and
• determine, using the library as implemented by the neural network application, a core frequency of the frequency scaling applied at the point, wherein the library is to account for skew characteristics associated with the distributed gradient synchronization to decide the core frequency.