An information processing device 1 acquires the total number of rewriting times for each of modules of persistent memories (PMEM), and acquires the number of times a specific file is rewritten based on the numbers of times respective pages of PMEMs 301 to 303 are rewritten, and when the number of times the specific file is rewritten is equal to or larger than a transfer threshold, transfers the specific file to a module with a first total number of rewriting times that is smaller than a second total number of rewriting times of a source module in which the specific file is stored.

A computing device, a method, and a computer readable medium for transferring data objects predictively to reduce consumption of resources. In some embodiments, a computing device includes: a memory; and a processor coupled to the memory. The processor is configured to store data objects in a storage system. The storage system is a multi-tier storage system. Storage of the data objects includes: determining a future demand status for at least one data object stored in the storage system based on a set of access activity rules; and moving the at least one data object between tiers of the storage system in response to the determined future demand status being different from a current demand status of the at least one data object to reduce consumption of resources in which to store that data object.

A memory device includes a first memory area including a first memory cell array having a plurality of first memory cells each for storing N-bit data according to an M-bit data access scheme, where N is a natural number, and a first peripheral circuit for controlling the first memory cells and disposed below the first memory cell array, a second memory area including a second memory cell array having a plurality of second memory cells each for storing M-bit data according to an M-bit data access scheme, where M is a natural number greater than N, and a second peripheral circuit for controlling the second memory cells and disposed below the second memory cell array, the first memory area and the second memory area are included in a single semiconductor chip and share an input and output interface, and a controller configured to generate calculation data by applying a weight stored in the first memory area to sensing data in response to receiving the sensing data obtained by an external sensor, and store the calculation data in one of the first memory area or the second memory area according to the weight.

A computer-implemented method, according to one embodiment, includes: processing records by, for each of the records: shearing the key associated with the record from the payload data, normalizing the sheared key, and storing the normalized sheared key in a first target area of memory. A determination is made whether a size of the payload data is outside a first predetermined range. In response to determining that the size of the payload data is outside the first predetermined range, the payload data is stored in a second target area of memory, and a data locator is appended to the normalized sheared key. Furthermore, in response to determining that a storage capacity of the memory is outside a second predetermined range, some of the payload data is transferred to external physical storage. Moreover, an external list is integrated with each of the data locators that correspond to the transferred payload data.

A storage device is disclosed. The storage device may include storage to store data, which may include a first storage of a first type and a second storage of a second type. The storage device may support a number of device streams, some of which associated with the first storage and some associated with the second storage. The storage device may also include a streaming capabilities analyzer that may inventory the streaming capabilities for the storage device. Finally, the storage device may include a transmitter to transmit the streaming capabilities of the storage device to a storage manager.

Managing hybrid cloud resources by grouping at least a portion of the elements of a data set according to attribute sensitivity into a cluster of elements, computing a resource allocation impact of the cluster of elements, computing an information gain associated with the set of elements, and allocating cloud resources according to the resource allocation impact and information gain.

A computing system has a first processing device (e.g., CPU, FPGA, or GPU) and memory regions (e.g., in a DRAM device) used by the processing device during normal operation. In one approach, the computing system is configured to: collect data associated with operation of an autonomous vehicle; monitor, by a first processing device, the collected data; and based on the monitoring, determine that an event on the autonomous vehicle has occurred. The computing system is further configured to, in response to determining that the event has occurred, initiate a transfer of data controlled by a second processing device, the transfer including copying data stored in volatile memory of the autonomous vehicle to non-volatile memory of the autonomous vehicle, wherein the second processing device controls copying of the data independently of the first processing device. The computing system is also further configured to, in response to determining that the event has occurred, reduce or terminate power to the first processing device.

A method for provided use in a storage device having a controller, the method comprising: identifying, by the controller, a plurality of logical regions in the storage device; obtaining, by the controller, a respective usage metric for each of the logical regions; updating, by the controller, a translation data structure of the storage device, the translation data structure being updated to map any of the logical regions of the storage device to a respective physical portion of the storage device, the respective physical portion being selected based on the respective usage metric of the logical region, wherein the translation data structure is part of a flash translation layer of the storage device, and the translation data structure is configured to store mapping information between a logical address space of the storage device and a physical address space of the storage device.

A storage device that includes a nonvolatile memory device is described. The storage device includes areas and a controller. The controller receives a write command and data from an external host device. The controller then preferentially writes the data in an area associated with a turbo write based on a turbo write policy, or in an area not associated with a turbo write based on a normal write policy. The controller also receives a move command from the external host device and moves data stored in the area to a different area based on the move command.

A content delivery network may provide content items to requesting devices using a popularity-based distribution hierarchy. A central analysis system may determine popularity data for a content item stored in a first caching device. The central analysis system may determine that a change in the popularity data is beyond a threshold value. The central analysis system may then transmit an instruction to move the content item from the first caching device to a second caching device in a different tier of caching devices than the first caching device. The central analysis system may update a content index to indicate that the content item has been moved to the second caching device. A user device may be redirected to request the content item directly from the second caching device.