Hard disk drive employing neural network for performing expected access time calculations

Abstract

A method and apparatus for calculating an expected access time associated with one of a plurality of disk drive commands employs one or more neural networks. A plurality of disk drive commands received from an external source are stored in a memory, typically in a queue. Using a neural network, an expected access time associated with each of the queued commands is determined. Determining the expected access time associated with each of the queued commands involves determining a time for performing a seek and settle operation for each of the queued commands and a latency time associated with each of the queued commands. The command indicated by the neural network as having a minimum expected access time relative to access times associated with other ones of the queued commands is identified for execution. A first neural network may be used to determine an expected access time associated with each read command stored in a read command queue and a second neural network may be used to determine an expected access time associated with each write command stored in a write command queue. A pair of read and write neural networks may be associated with each of a number of read/write transducers employed in a disk drive system. The neural network may be trained at the time of manufacture and on a periodic basis during the service life of the disk drive.

Dependencies are inferred from the claim text.