A computer-implemented method according to one embodiment includes causing a plurality of I/O queues to be created between an initiator and a storage target device. The created I/O queues are reserved for I/O requests for which adjustments of current priorities of extents of data associated with the I/O requests are to be performed. The method further includes determining identifying information of an I/O request sent from the initiator to the storage target device and determining whether the I/O request was sent from the initiator to the storage target device using one of the created I/O queues. In response to a determination that the I/O request was sent using a first of the created I/O queues having one of the adjustments associated therewith, a tiering manager of the storage target device is instructed to perform the adjustment on the current priority of the extent of data associated with the I/O request.

A method for computational storage may include storing, at a storage device, two or more portions of data, wherein a first one of the two or more portions of data comprises a first fragment of a record and a second one of the two or more portions of data comprises a second fragment of the record, and performing, by the storage device, an operation on the first and second fragments of the record. The method may further include performing, by the storage node, a second operation on first and second fragments of a second record. The operation may include a data selection operation, and the method may further include sending a result of the data selection operation to a server. The method may further include sending a result of a first data selection operation to a server.

Method and system for training a machine learning model based on a training dataset formed by data objects distributed across a virtual object storage service. The method comprises fetching from the virtual object storage service, the training dataset; copying the fetched training dataset on a first local storage device and maintaining a list of modifications executed on the training dataset that occurred on the virtual object storage service. The method comprises, upon receiving a request to initiate training of the machine learning model, generating a synchronized training dataset mirroring the training dataset stored in the virtual object storage service; storing the synchronized training dataset in a second local storage device; and fetching training data from the synchronized training dataset stored in the second local storage device as the training of the machine learning model is executed.

A method for computational storage may include receiving, at a storage device, a modified version of a portion of data, generating, at the storage device, a restored portion of data from the modified version of the portion of data, and performing, at the storage device, an operation on the restored portion of data. The method may further include receiving, at the storage device, a request to perform the operation on the portion of data. The generating may include decompressing the modified version of the portion of data. The generating may include decrypting the modified version of the portion of data. The method may further include sending, from the storage device, a result of the operation on the restored portion of data. The operation may include a filtering operation. The operation may include a scanning operation. The method may further include dividing data to generate the portion of data.

A traditional storage platform performs many basic functions, such as storage partitions allocation (i.e., namespace masking) and many advanced functions, such as deduplication or dynamic storage allocation. These functions need to be managed and this results in a multiple management system paradigm, in which a fabric management application manages the fabric connectivity policies (i.e., Zoning), while a storage management application manages the storage namespace mappings and advanced functions. Embodiments herein provide for centralized management for both connectivity and storage namespace mapping, among other advanced features. Namespace zoning information may comprise Namespace ZoneGroups, Namespace Zones, Namespace Zone Members, Namespace ZoneAlias, and Namespace ZoneAlias Members, which expand the NVMe-oF zoning framework from just connectivity control to full Namespaces allocation.

An information processing apparatus performs first migration processing of migrating data from a relatively-old-generation magnetic tape included in one storage pool of a plurality of storage pools to relatively-new-generation magnetic tapes included in each of the plurality of storage pools in a case where the number of tape drives which are available for data migration is equal to or larger than a threshold value, the tape drives being relatively-new-generation tape drives among a plurality of generations of tape drives, and performs second migration processing of migrating data from migration-source magnetic tapes as relatively-old-generation magnetic tapes included in the storage pool to migration-destination magnetic tapes of which the number is smaller than a multiplicity in a case where the number of the tape drives is smaller than the threshold value.

Distributed storage nodes having specialized hardware can be pooled for servicing data requests. For example, a distributed storage system can include a group of storage nodes. The distributed storage system can determine a subset of storage nodes that include the specialized hardware based on status information received from the group of storage nodes. The specialized hardware can be preconfigured with specialized functionality. The distributed storage system can then generate a node pool that includes the subset of storage nodes with the specialized hardware. The node pool can be configured to perform the specialized functionality in relation to a data request.

Methods, systems, and devices for retiring pages of a memory device are described. An ordered set of device information pages may be used to store device information. The device information pages may be in non-volatile memory. Each page may include a counter value of the number of accesses to indicate if the page includes valid data. A flag associated with the page may be set when the counter value reaches a threshold, to retire the page. Upon power-up, the device may determine which page to use, based on the flags. The flag may be stored in the page, or may be separate (e.g., fuse elements). If fuse elements are used, the page may store a programming-in-process flag to indicate when programming of the fuse element may not have been completed before power loss, in which case the programming may be restarted after power is restored.

Embodiments of the invention provide systems and methods for managing processing, memory, storage, network, and cloud computing to significantly improve the efficiency and performance of processing nodes. More specifically, embodiments of the present invention are directed to an instruction set of an object memory fabric. This object memory fabric instruction set can include trigger instructions defined in metadata for a particular memory object. Each trigger instruction can comprise a single instruction and action based on reference to a specific object to initiate or perform defined actions such as pre-fetching other objects or executing a trigger program.

A computer storage device having a host interface, a controller, non-volatile storage media, and firmware. The firmware instructs the controller to: limit a crypto key to be used in data access requests made in a first namespace allocated on the non-volatile storage media of the computer storage device; store data in the first namespace in an encrypted form that is to be decrypted using the crypto key; free a portion of the non-volatile storage media from the first namespace, the portion storing the data; and make the portion of the non-volatile storage media available in a second namespace without erasing the data stored in the portion of the non-volatile storage media.