Western Digital Technologies, Inc.

Keen Personal Media, Inc.

Keen Personal Technologies, Inc.

Other

Sandisk Technologies Inc.

International Business Machines Corporation

Spectrasensors, Inc.

Trinity Tool Company

William Bernard Boyle

Robert Morelli Fallone

Mei-Man L Syu

Chun Sei Tsai

James N Malina

Alan T Meyer

Virgil V Wilkins

William Pat Price

Carl E Barlow

Sang Huynh

Shay Benisty

Alexander Bazarsky

Ariel Navon

Toshiki Hirano

Guoxiao Guo

Daniel Joseph Linnen

Michael Stephen Rothberg

Shaomin Xiong

Timothy J Elliott

William C Cain

Srinivas Neppalli

Alan P Rice

Ronald G Parkinen

Curtis Edgar Stevens

Kei Yasuna

Kenny T Coker

Ayberk Ozturk

Na Wang

Marc A Bombet

Aznizam Abdullah Salehudin

Anthony L Pei

Kai Ling Lee

Billy Rickey

Erhard Theodor Schreck

Robert P Ryan

Robert L Horn

Jie Yu

Qinghua Zeng

Edwin Scott Olds

Jun Xu

Bernhard Hiller

Nikolai Fink

Shad Henry Thorstenson

Kenneth J Smith

Jih-Ping Peng

Keith Benjamin Helbley

David W Chew

Young H Lee

Mark L Watson

Kenneth J D'Souza

Peter Dorn

Daniel D Reno

Harald Mueller

Junpeng Niu

Robert H Krebs, Jr

Dan Wang

Joo Peng Teh

Peng Lee Liang

Ralph O Weber

Rodolfo Candelaria, Jr

Juergen Dessecker

Jerome D Shulec

Kenneth J Motyl

Glenn Cheng

Paulo Silva

Kuang Hwa Teo

Anthony P Sannino

Vipin A Vitikkate

Tim J Elliott

Edward P Hecker

Data storage devices configured to exploit generative-adversarial-networks (GANs). The GANs include super-resolution GANs (SRGANs). In some examples, a GAN-based reconstruction procedure is implemented within a data storage controller to replace or supplement an error correction coding (ECC) decoding procedure. In other examples, soft bit information is exploited using GANs during decoding. A dissimilarity matrix may be generated to represent differences between an initial image and a GAN-reconstructed image, with matrix values mapped into low-density parity check (LDPC) codewords to facilitate LDPC decoding of data. In still other examples, confidence information obtained from a GAN is incorporated into image pixels. In some examples, GAN reconstruction of data is limited to modifying valley bits. Multiple GANs may be used in parallel with their outcome aggregated.

Data storage device configured for use with a generative-adversarial-network (GAN)

Data storage devices configured to exploit generative-adversarial-networks (GANs). The GANs include super-resolution GANs (SRGANs). In some examples, a GAN-based decoding (reconstruction) procedure is implemented within a data storage controller to replace or supplement an error correction coding (ECC) decoding procedure to permit a reduction in the number of parity bits used while storing the data. In other examples, soft bit information is exploited using GANs during decoding. A dissimilarity matrix may be generated to represent differences between an initial image and a GAN-reconstructed image, with matrix values mapped into low-density parity check (LDPC) codewords to facilitate LDPC decoding of data. In still other examples, confidence information obtained from a GAN is incorporated into image pixels. In some examples, GAN reconstruction of data is limited to modifying valley bits. Multiple GANs may be used in parallel with their outcome aggregated.

Various illustrative aspects are directed to a data storage device including one or more disks, an actuator mechanism configured to position a selected head among one or more heads proximate to a corresponding disk surface among the one or more disks, the selected head comprising a write element and an assistive energy emitter, and one or more processing devices configured to, individually or in combination: apply an assistive energy current to the assistive energy emitter while refraining from applying a write current to the write element, and vary a level of the assistive energy current over time while refraining from applying the write current to the write element.

Energy-assisted magnetic recording data storage device with opportunistic boosted laser pre-biasing

Data storage devices configured to exploit generative-adversarial-networks (GANs). The GANs include super-resolution GANs (SRGANS). In some examples, a GAN-based decoding reconstruction procedure is implemented within a data storage controller to replace or supplement an error correction coding (ECC) decoding procedure. In other examples, soft bit information is exploited using GANs during decoding. A dissimilarity matrix may be generated to represent differences between an initial image and a GAN-reconstructed image, with matrix values mapped into low-density parity check (LDPC) codewords to facilitate LDPC decoding of data. In still other examples, confidence information obtained from a GAN is incorporated into image pixels. In some examples, GAN reconstruction of data is limited to modifying valley bits. Multiple GANs may be used in parallel with their outcome aggregated.

Various illustrative aspects are directed to a data storage device, comprising one or more disks; an actuator mechanism configured to position one or more heads proximate to a corresponding disk surface of the one or more disks; and one or more processing devices. The selected head comprises a write element and an assistive energy emitter. The one or more processing devices are configured to apply an assistive energy current to the assistive energy emitter while refraining from applying a write current to the write element.

Various illustrative aspects are directed to a data storage device, comprising one or more disks; an actuator mechanism configured to position one or more heads proximate to a corresponding disk surface of the one or more disks; and one or more processing devices. The one or more processing devices are configured to: select a sector on the corresponding disk surface to which to write data, wherein the sector is selected in accordance with a data erosion mitigation pattern; and output, while the head is positioned proximate to a preceding sector that precedes the selected sector, a laser pre-bias current to a laser-generating component of the head, wherein the laser pre-bias current is sufficient to induce significant data erosion on the preceding sector.

Data storage device with enhanced management of laser pre-bias and logic block addressing in heat-assisted magnetic recording

A data storage device is disclosed comprising at least one head configured to access a magnetic tape. A plurality of access commands are stored in a command queue, and a wear value is generated for each access command in the command queue, wherein the wear value represents a level of wear on the head or magnetic tape associated with executing the access command. An execution order for the access commands is generated based on the wear values, and at least one of the access commands is executed based on the execution order.

Data storage device compensating for head/tape wear

A data storage device is disclosed comprising a non-volatile storage medium (NVSM), and a head configured to access the NVSM. During a first interval, the head is used to write first data to a first segment of the NVSM, and during a second interval, the head is used to read the first data from the first segment of the NVSM and erase at least part of the first data from the first segment of the NVSM.

Data storage device with burn-after-read mode

A storage device comprises a storage medium, storage controller, a host interface, and a bridge slot. The storage controller is configured to control read and write operations to the storage medium and operates according to a firmware written by a storage device manufacturer. The bridge slot is configured to receive a removable bridge storing software written by a third-party different from the storage device manufacturer. The removable bridge is configured to intercept a first command sent from the host system to the storage controller, modify the first command according to the software stored on removable bridge, and transmit the first command to the storage controller.

Secure storage using a removable bridge

A laser spectrometer can be operated for analysis of one or more analytes present in a combustible gas mixture. The spectrometer can include one or more features that enable intrinsically safe operation. In other words, electrical, electronic, thermal, and/or optical energy sources can be limited within an hazardous are of the spectrometer where it is possible for an explosive gas mixture to exist. Methods, systems, articles and the like are described.

Intrinsically safe spectroscopic analyzer

A Data Storage Device (DSD) includes at least one disk for storing data in a plurality of storage areas including at least a first area type for using a first data access methodology and a second area type for using a second data access methodology. It is determined whether to perform a command in a storage area of the first or second area type. If the command is to be performed in the first area type, the command is prioritized over at least one other command for the second area type. In another aspect, a value is determined representing a number of data access operations within a predetermined time period for a data storage capacity of the DSD. Storage areas of the DSD are configured as one of at least the first area type and the second area type based at least in part on the determined value.

Dynamic performance density tuning for data storage device

A data storage device includes a disk and a plurality of actuators for reading and writing data on the disk in different physical realms. Each physical realm is associated with at least one logical zone domain including at least one logical zone. The at least one logical zone domain corresponds to an actuator of a plurality of actuators that accesses the physical realms associated with the at least one logical zone domain. In one aspect, reading and writing of data is enabled in one or more logical zones in response to a SATA zone activate command. In another aspect, a SATA read or write command is received indicating at least one logical address for data to read or written on the disk. Data is read or written in a physical realm using the actuator corresponding to a logical zone domain including the at least one logical address.

Data storage device configuration for accessing data in physical realms

A data storage device is disclosed comprising a first head actuated over a first disk surface, wherein the first head comprises a write coil and a write-assist component. First data is written to the first disk surface using the write coil and the write-assist component of the first head. An electrical bias is applied to the write-assist component of the first head to physically damage the write-assist component, thereby rendering the first disk surface read-only.

Data storage device converting disk surface to read-only

A data storage system may include one or more storage arrays. Each storage array may include a first set of solid-state drives and a first set of striped hard disk drives. Each solid-state drive of the first set of solid-state drives has a first data throughput and the set of stripe hard disk drives has a second data throughput. The second data throughput of the first set of striped hard disk drives is within a threshold throughput of the first data throughput. The data storage system also includes a processing device configured to receive an access request to write first data to the storage array and determine a read access frequency of the first data. The processing device may also be configured to determine a write access frequency of the first data and write the first data to the first set of solid-state drives or the first set of striped hard disk drives, based on the read access frequency and the write access frequency.

Hybrid data storage array

A data storage device is disclosed comprising a first disk surface comprising a plurality of data tracks, and a first head actuated over the first disk surface. First data is written to the first disk surface based on a first format. At least part of the first disk surface is reformatted based on a second format, wherein the second format defines a lower recording density for the first disk surface as compared to a recording density defined by the first format. After reformatting the at least part of the first disk surface, second data is written to the first disk surface based on the second format and the first data is read from the first disk surface based on the first format.

Data storage device formatting a disk surface with a write format and a read format

Growing community of inventors

Lake Forest, CA, United States of America

William Bernard Boyle