US 12,229,016 B2
Storage device for storing model checkpoints of recommendation deep-learning models
Ariel Navon, Revava (IL); Alexander Bazarsky, Holon (IL); Shay Benisty, Beer Sheva (IL); and Judah Gamliel Hahn, Ofra (IL)
Assigned to Sandisk Technologies, Inc., Milpitas, CA (US)
Filed by Western Digital Technologies, Inc., San Jose, CA (US)
Filed on Oct. 20, 2022, as Appl. No. 17/970,190.
Application 17/970,190 is a continuation in part of application No. 17/592,953, filed on Feb. 4, 2022.
Prior Publication US 2023/0251935 A1, Aug. 10, 2023
Int. Cl. G06F 11/14 (2006.01); G06N 3/04 (2023.01)
CPC G06F 11/1456 (2013.01) [G06F 11/1451 (2013.01); G06N 3/04 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A data storage device, comprising:
a memory device; and
a controller coupled to the memory device, wherein the controller is configured to be coupled to a host device, and wherein the controller is further configured to:
receive a first command;
generate logical block address (LBA) to physical block address (PBA) (L2P) mappings for the first command, wherein the L2P mapping is generated based on a result of deep learning (DL) training model using a neural network (NN) structure;
store data of the first command in the memory device;
receive a second command;
determine a difference between the data of the first command and data of the second command;
generate LBA to PBA L2P mappings for the difference, wherein the L2P mapping is generated based on a result of DL training module using the NN structure; and
compress the data of the first command using a compression engine to store the difference in the memory device.