Western Digital Technologies, Inc.

Aimamorn Suvichakorn

Chun Sei Tsai

Stella Achtenberg

Ofir Pele

Jonathan Lloyd

Amit Chattopadhyay

Krzysztof Gladysz

Wiriya Choeiprathum

Kameron Jung

Anand Gupta

Methods are provided for tactically deploying machine learning operations within existing storage devices without the need for additional capital investment. Machine learning operations are specifically designed to locate and evaluate multiple types of data to complete an operation, including synthesizing missing data. These operations may be processed within a SoC of a storage device as embedded software. Storage devices designed to utilize machine learning methods within existing configurations can include a non-volatile memory for storing data, executable instructions, and a processor to conduct a variety of steps. The steps can include executing a plurality of applications stored in the non-volatile memory, and receiving a request for data, including measurements, from at least one of the applications. The steps can further determine if the requested data is suitable for substitution by an inference and subsequently select at least one machine learning model for generating a suitable inference.

Embedded multi-attribute machine learning for storage devices

Detecting surface irregularities on a disk of a data storage device (DSD) includes reading data from a first side of the disk using a first head of the DSD. A first set of variable gain amplifier (VGA) values is generated which is related to the reading of data from the first side using the first head. Data is read from a second side of the disk using a second head of the DSD and a second set of VGA values is generated which is related to the reading of data from the second side using the second head. A profile for the disk is determined using the first set of VGA values and the second set of VGA values. The profile is compared to at least one threshold to detect surface irregularities on the disk.

Detection of disk surface irregularities in data storage devices

Growing community of inventors

Pakkret, Thailand

Aimamorn Suvichakorn