US 11,899,975 B2
Machine learning for a multi-memory system
Chinnakrishnan Ballapuram, San Jose, CA (US)
Assigned to Micron Technology, Inc., Boise, ID (US)
Filed by Micron Technology, Inc., Boise, ID (US)
Filed on Jan. 28, 2022, as Appl. No. 17/587,665.
Claims priority of provisional application 63/185,201, filed on May 6, 2021.
Prior Publication US 2022/0357888 A1, Nov. 10, 2022
Int. Cl. G06F 3/06 (2006.01); G06N 3/04 (2023.01); G06F 12/0862 (2016.01); G06F 18/214 (2023.01)
CPC G06F 3/0659 (2013.01) [G06F 3/0604 (2013.01); G06F 3/0634 (2013.01); G06F 3/0673 (2013.01); G06F 12/0862 (2013.01); G06F 18/214 (2023.01); G06N 3/04 (2013.01)] 19 Claims
OG exemplary drawing
 
1. An apparatus, comprising:
a non-volatile memory;
a volatile memory configured to operate as a cache for the non-volatile memory; and
an interface controller coupled with the non-volatile memory and the volatile memory, the interface controller configured to cause the apparatus to:
receive a first command from a host device;
communicate the first command to a machine learning engine and to circuitry configured to store and manage commands for the non-volatile memory and the volatile memory, wherein the machine learning engine is configured to:
group, according to one or more shared characteristics, commands received from the host device during a training mode; and
detect one or more patterns associated with the commands based at least in part on grouping the commands; and
communicate a second command generated by the machine learning engine to the circuitry, the second command based at least in part on information determined by the machine learning engine during the training mode, wherein the information determined by the machine learning engine is based at least in part on the one or more patterns.