Executing Machine Learning Models Using Transformed Datasets

A method comprising:

• receiving, by a processor that executes parallel matrix operations, a dataset transformed by a system that is external to the processor;
• and
• executing, by the processor, one or more machine learning algorithms using the transformed dataset as input.

An artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, the artificial intelligence infrastructure configured to carry out the steps of:

• receiving, by a processor that executes parallel matrix operations, a dataset transformed by a system that is external to the processor;
• and
• executing, by the processor, one or more machine learning algorithms using the transformed dataset as input.

An apparatus for data transformation offloading in an artificial intelligence infrastructure that includes one or more storage systems and one or more processors, the apparatus comprising a computer processor, a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, cause the apparatus to carry out the steps of:

• identifying, in dependence upon one or more machine learning models to be executed on the processors, one or more transformations to apply to a dataset;
• and
• generating, by the storage system in dependence upon the one or more transformations, a transformed dataset.