Abstract: Embodiments described herein provide improved methods and systems for generating metadata for media objects at a computational engine (such as an artificial intelligence engine) within the storage edge controller, and for storing and using such metadata, in data processing systems.

Abstract: The present disclosure describes apparatuses and methods for artificial intelligence-enabled management of storage media. In some aspects, a media access manager of a storage media system receives, from a host system, host input/output commands (I/Os) for access to storage media of the storage media system. The media access manager provides information describing the host I/Os to an artificial intelligence engine and receives, from the artificial intelligence engine, a prediction of host system behavior with respect to subsequent access of the storage media. The media access manager then schedules, based on the prediction of host system behavior, the host I/Os for access to the storage media of the storage system. By so doing, the host I/Os may be scheduled to optimize host system access of the storage media, such as to avoid conflict with internal I/Os of the storage system or preempt various thresholds based on upcoming idle time.

Abstract: Systems and methods for selecting an optimal error recovery procedure for correcting a read error in a solid-state drive are provided. A machine learning model is trained to forecast which error recovery procedure of a plurality of error recovery procedures is most likely to achieve a predetermined goal given a state of a solid-state drive. The predetermined goal is based on at least one of a read latency and a failure rate of the solid-state drive. A current state of the solid-state drive is determined. An error recovery procedure is selected from among the plurality of error recovery procedures by inputting the current state of the solid-state drive into the trained machine learning model, thereby triggering the trained machine learning model to output the selected error recovery procedure. The selected error recovery procedure is executed to recover data from the solid-state drive.

Abstract: A solid state drive (SSD) device includes: non-volatile memory, and volatile memory associated with an SSD device controller. In response to determining that the SSD device is to transition to a power saving mode, information is transferred from the volatile memory to a host memory of a host computer via a communication interface, and the at least some of the volatile memory is transitioned to an OFF state. In response to determining that the SSD device is to transition from the power saving mode to a normal operating mode, the at least some of the volatile memory of the SSD device is transitioned to an ON state in which the at least some of the volatile memory is capable of retaining data, and the information from the host memory is transferred to the volatile memory of the SSD device via the communication interface.

Abstract: The present disclosure describes apparatuses and methods for artificial intelligence-enabled management of storage media. In some aspects, a media access manager of a storage media system receives, from a host system, host input/output commands (I/Os) for access to storage media of the storage media system. The media access manager provides information describing the host I/Os to an artificial intelligence engine and receives, from the artificial intelligence engine, a prediction of host system behavior with respect to subsequent access of the storage media. The media access manager then schedules, based on the prediction of host system behavior, the host I/Os for access to the storage media of the storage system. By so doing, the host I/Os may be scheduled to optimize host system access of the storage media, such as to avoid conflict with internal I/Os of the storage system or preempt various thresholds based on upcoming idle time.

Abstract: The present disclosure describes apparatuses and methods for artificial intelligence-enabled management of storage media. In some aspects, a media access manager of a storage media system receives, from a host system, host input/output commands (I/Os) for access to storage media of the storage media system. The media access manager provides information describing the host I/Os to an artificial intelligence engine and receives, from the artificial intelligence engine, a prediction of host system behavior with respect to subsequent access of the storage media. The media access manager then schedules, based on the prediction of host system behavior, the host I/Os for access to the storage media of the storage system. By so doing, the host I/Os may be scheduled to optimize host system access of the storage media, such as to avoid conflict with internal I/Os of the storage system or preempt various thresholds based on upcoming idle time.

Abstract: Systems and methods for selecting an optimal error recovery procedure for correcting a read error in a solid-state drive are provided. A machine learning model is trained to forecast which error recovery procedure of a plurality of error recovery procedures is most likely to achieve a predetermined goal given a state of a solid-state drive. The predetermined goal is based on at least one of a read latency and a failure rate of the solid-state drive. A current state of the solid-state drive is determined. An error recovery procedure is selected from among the plurality of error recovery procedures by inputting the current state of the solid-state drive into the trained machine learning model, thereby triggering the trained machine learning model to output the selected error recovery procedure. The selected error recovery procedure is executed to recover data from the solid-state drive.

Abstract: Embodiments described herein provide improved methods and systems for generating metadata for media objects at a computational engine (such as an artificial intelligence engine) within the storage edge controller, and for storing and using such metadata, in data processing systems.

Abstract: The present disclosure describes apparatuses and methods for artificial intelligence-enabled management of storage media. In some aspects, a media access manager of a storage media system receives, from a host system, host input/output commands (I/Os) for access to storage media of the storage media system. The media access manager provides information describing the host I/Os to an artificial intelligence engine and receives, from the artificial intelligence engine, a prediction of host system behavior with respect to subsequent access of the storage media. The media access manager then schedules, based on the prediction of host system behavior, the host I/Os for access to the storage media of the storage system. By so doing, the host I/Os may be scheduled to optimize host system access of the storage media, such as to avoid conflict with internal I/Os of the storage system or preempt various thresholds based on upcoming idle time.

Abstract: Embodiments described herein provide improved methods and systems for generating metadata for media objects at a computational engine (such as an artificial intelligence engine) within the storage edge controller, and for storing and using such metadata, in data processing systems.

Abstract: The present disclosure describes apparatuses and methods for artificial intelligence-enabled management of storage media. In some aspects, a media access manager of a storage media system receives, from a host system, host input/output commands (I/Os) for access to storage media of the storage media system. The media access manager provides information describing the host I/Os to an artificial intelligence engine and receives, from the artificial intelligence engine, a prediction of host system behavior with respect to subsequent access of the storage media. The media access manager then schedules, based on the prediction of host system behavior, the host I/Os for access to the storage media of the storage system. By so doing, the host I/Os may be scheduled to optimize host system access of the storage media, such as to avoid conflict with internal I/Os of the storage system or preempt various thresholds based on upcoming idle time.

Abstract: The present disclosure describes apparatuses and methods for artificial intelligence-enabled management of storage media. In some aspects, a media access manager of a storage media system receives, from a host system, host input/output commands (I/Os) for access to storage media of the storage media system. The media access manager provides information describing the host I/Os to an artificial intelligence engine and receives, from the artificial intelligence engine, a prediction of host system behavior with respect to subsequent access of the storage media. The media access manager then schedules, based on the prediction of host system behavior, the host I/Os for access to the storage media of the storage system. By so doing, the host I/Os may be scheduled to optimize host system access of the storage media, such as to avoid conflict with internal I/Os of the storage system or preempt various thresholds based on upcoming idle time.

Abstract: Embodiments described herein provide improved methods and systems for generating metadata for media objects at a computational engine (such as an artificial intelligence engine) within the storage edge controller, and for storing and using such metadata, in data processing systems.

Abstract: A data storage device includes a first data storage medium having a first capacity and a first speed, a second data storage medium having a second capacity and a second speed, and a device controller for interfacing between the data storage device and a host system. The second capacity is greater than the first capacity and the second speed is slower than the first speed. The device controller presents the data storage device to the host system as having a device capacity at least equal to the second capacity and a device speed at least equal to the first speed. The first data storage medium may be a solid-state drive while the second data storage medium is a hard disk drive. The device controller may be a solid-state drive controller, or a hard disk drive controller that may accept at least one solid-state drive command, such as a TRIM command.

Abstract: A disk array controller detects disk drive power-on-reset events that may cause a disk drive to lose uncommitted write data stored in its cache. When an unexpected disk drive power-on-reset event is detected, the disk array controller may initiate an appropriate corrective action. For example, the disk array controller may initiate a disk drive rebuild operation, or may re-send a set of write commands to the disk drive.

Abstract: A system and method are provided for efficiently initializing a redundant array of independent disks (RAID). The method monitors host write operations and uses that information to select the optimal method to perform a parity reconstruction operation. The bins to which data access write operations have not occurred can be initialized using a zeroing process. In one aspect, the method identifies drives in the RAID array capable of receiving a ‘WriteRepeatedly’ command and leverages that capability to eliminate the need for the RAID disk array controller to provide initialization data for all disk array initialization transfers. This reduces the RAID array controller processor and I/O bandwidth required to initialize the array and further reduces the time to initialize a RAID array. In a different aspect, a method is provided for efficiently selecting a host write process for optimal data redundancy and performance in a RAID array.

Abstract: A system and method are provided for efficiently initializing a redundant array of independent disks (RAID). The method monitors host write operations and uses that information to select the optimal method to perform a parity reconstruction operation. The bins to which data access write operations have not occurred can be initialized using a zeroing process. In one aspect, the method identifies drives in the RAID array capable of receiving a ‘WriteRepeatedly’ command and leverages that capability to eliminate the need for the RAID disk array controller to provide initialization data for all disk array initialization transfers. This reduces the RAID array controller processor and I/O bandwidth required to initialize the array and further reduces the time to initialize a RAID array. In a different aspect, a method is provided for efficiently selecting a host write process for optimal data redundancy and performance in a RAID array.

Abstract: A system and method are provided for efficiently initializing a redundant array of independent disks (RAID). The method monitors host write operations and uses that information to select the optimal method to perform a parity reconstruction operation. The bins to which data access write operations have not occurred can be initialized using a zeroing process. In one aspect, the method identifies drives in the RAID array capable of receiving a ‘WriteRepeatedly’ command and leverages that capability to eliminate the need for the RAID disk array controller to provide initialization data for all disk array initialization transfers. This reduces the RAID array controller processor and I/O bandwidth required to initialize the array and further reduces the time to initialize a RAID array. In a different aspect, a method is provided for efficiently selecting a host write process for optimal data redundancy and performance in a RAID array.

Abstract: A disk array controller detects disk drive power-on-reset events that may cause a disk drive to lose uncommitted write data stored in its cache. When an unexpected disk drive power-on-reset event is detected, the disk array controller may initiate an appropriate corrective action. For example, the disk array controller may initiate a disk drive rebuild operation, or may re-send a set of write commands to the disk drive.

Abstract: A disk array controller reliably detects disk drive power-on-reset events that may cause a disk drive that has uncommitted write data stored in its cache to lose such data. The methods for detecting the power-on-reset events include operating the disk drives in an ATA security mode in which a power-on-reset of a disk drive will cause the drive to enter a locked state in which data transfer commands are aborted; and tracking power cycle count attributes of the disk drives over time. When a disk drive power-on-reset event is detected, the disk array may be efficiently restored to an operational state by re-executing or “replaying” a set of write commands that are cached within the disk array controller. The invention is also applicable to single-disk-drive storage systems.