Machine learning to improve caching efficiency in a storage system

A non-transitory, computer-readable storage medium, in which is stored computer program code for performing a method of managing blocks of data in a data cache having a first storage device and a second storage device, wherein each block of data has a fixed size that defines the unit of transfer between the first storage device and the second storage device, the method comprising:

• organizing the blocks of data in the first storage device into a plurality of extents, each extent comprising a plurality of the blocks of data having contiguous addresses in the first storage device, wherein at least two extents in the first storage device have different sizes;
• for each extent in the first storage device, generating feature data as a function of metadata associated with input/output operations on the blocks of data in the respective extent;
• using a data model trained by machine learning to infer a hotness value for each extent in the first storage device as a function of the generated feature data;
• and
• promoting blocks of data from the first storage device into the second storage device, and evicting blocks of data stored in the second storage device, according to the inferred hotness values for each extent in the first storage device.

A computerized system for managing blocks of data in a data cache having a first storage device and a second storage device, wherein each block of data has a fixed size that defines the unit of transfer between the first storage device and the second storage device, the computerized system comprising:

• a metadata generator, coupled to the first and second storage devices, for generating metadata associated with input/output operations on the blocks of data in the data cache;
• a feature generator, coupled to the metadata generator, for generating feature data, as a function of the generated metadata, for each of a plurality of extents in the first storage device, each extent comprising a plurality of the blocks of data in the first storage device having contiguous addresses, wherein at least two extents in the first storage device have different sizes;
• an inference engine, coupled to the feature generator and comprising a data model, trained by machine learning, for inferring a hotness value for each extent in the first storage device as a function of feature data generated by the feature generator;
• and
• a cache control interface, coupled to the inference engine and the first and second storage devices, for promoting blocks of data from the first storage device into the second storage device, and evicting blocks of data stored in the second storage device, according to the inferred hotness values for each extent in the first storage device.