An information processing device includes a first memory, a second memory, and a processor. The first memory stores clusters into which first data segments are grouped according to distances among the first data segments and each including one or more first data segments. The second memory is operable at a higher speed than the first memory and stores second data segments corresponding one-to-one to the clusters. The processor receives an input query and identify a third data segment being one of the second data segments closest to the query, from the second data segments. The processor collectively reads, from the first memory, one or more first data segments included in a cluster corresponding to the third data segment among the clusters, and identify a fourth data segment being one of the first data segments closest to the query from the one or more first data segments for output.

According to one embodiment, a write instructing unit instructs a data access unit to write, in a storage area of a data storage unit indicated by a first physical address, write object data, instructs a management information access unit to update address conversion information, and instructs a first access unit to update the first physical address. A compaction unit extracts a physical address of compaction object data, instructs the data access unit to read the compaction object data stored in a storage area of the data storage unit indicated by the physical address, instructs the data access unit to write the compaction object data in a storage area of the data storage unit indicated by a second physical address, instructs the management information access unit to update the address conversion information, and instructs a second access unit to update the second physical address.

A storage system includes a plurality of storage media and a method of managing volumes of the storage system is applied thereto. The method includes receiving a volume management request and correlation information between the volumes, and allocating storage spaces of the storage media to the volumes based on the correlation information between the volumes. The correlation information indicates information of the volumes in which the allocated storage media are physically isolated from each other.

A system and methods for in-storage on-demand data decompression. Compressed data are stored in a storage device connected to a host computer. When decompressed data are needed, the host computer sends a decompression command to the storage device indicating which data are to be decompressed, and instructing it how to decompress the data. The storage device decompresses the data and stores the decompressed data, making it available to the host.

Example artificial intelligence systems and methods provide parallel storage of data to primary storage and notification to a model server supported by the primary storage. A primary storage system receives operations on a training data set from a model trainer and sends a model instance of a computational model to a model server. When a new data element is received by a data ingester, the model server is initiated to evaluate the new data element using the model instance while the primary storage system stores the new data element in parallel.

A network of collection, charging and distribution machines collect, charge and distribute portable electrical energy storage devices (e.g., batteries, supercapacitors or ultracapacitors). Locations of collection, charging and distribution machines having available charged portable electrical energy storage devices are communicated to or acquired by a mobile device of a user, or displayed on a collection, charging and distribution machine. The locations are indicated on a graphical user interface on a map on a user's mobile device relative to the user's current location. The user may use their mobile device select particular locations on the map to reserve an available portable electrical energy storage device. The system nay also warn the user that the user is near an edge of the pre-determined area having portable electrical energy storage device collection, charging and distribution machines. Reservations may also be made automatically based on information regarding a potential route of a user.

A method includes determining, by a computing device of a plurality of computing devices of a storage network, a data processing plan for processing an access request based on a data type of the access request and one or more storage access requirements of the access request. The method further includes identifying two or more processing units of a plurality of processing units of the storage network based on the data processing plan. The method further includes determining processing capabilities of each of the two or more processing units. The method further includes selecting a processing unit of the two or more processing units to process the access request based on a favorable comparison of the processing capabilities of the processing unit and the data processing plan. The method further includes sending the access request to the processing unit.

A system and method for two-level indexing for key-value persistent storage. The method may include: sorting two or more key-value pairs to form a sorted key-value pair set; determining an address of a first key-value pair of the key-value pairs, the first key-value pair including a first key and a first value; determining an address of a second key-value pair of the key-value pairs, the second key-value pair including a second key and a second value; and training a first linear regression model to generate a first line corresponding to the key-value pairs, the training including training the first linear regression model with key-value pairs including the first key-value pair and the second key-value pair.

Provided are a computer program product, system, and method for dynamically increasing capacity of a storage device. For address mappings, each addressing mapping indicates a storage device block address for a host block address and a compressed block size indicating a number of blocks storing compressed data for data written to the host block address starting at the storage device block address. Write data for a write request to a host block address is compressed to produce compressed data. A block size of the compressed data is less than request block size of the write data for the write request. Indication is made in the address mapping for the host block address of a storage device address at which to start storing the compressed data in the storage device and the compressed block size. The compressed data is sent to the storage device to write at the storage device block address.

A compilation system using an energy model based on a set of generic and practical hardware and software parameters is presented. The model can represent the major trends in energy consumption spanning potential hardware configurations using only parameters available at compilation time. Experimental verification indicates that the model is nimble yet sufficiently precise, allowing efficient selection of one or more parameters of a target computing system so as to minimize power/energy consumption of a program while achieving other performance related goals. A voltage and/or frequency optimization and selection is presented which can determine an efficient dynamic hardware configuration schedule at compilation time. In various embodiments, the configuration schedule is chosen based on its predicted effect on energy consumption. A concurrency throttling technique based on the energy model can exploit the power-gating features exposed by the target computing system to increase the energy efficiency of programs.