The storage device includes a first memory, a process device that stores data in the first memory and reads the data from the first memory, and an accelerator that includes a second memory different from the first memory. The accelerator stores compressed data stored in one or more storage drives storing data, in the second memory, decompresses the compressed data stored in the second memory to generate plaintext data, extracts data designated in the process device from the plaintext data, and transmits the extracted designated data to the first memory.

A memory system including a history buffer, a hash calculator, a read pointer table, a history buffer writing circuit, a read pointer writing circuit, a read pointer reading circuit, a history buffer reading circuit, a matching circuit replacing the input data string with a reference information referring the matching candidate data string in the case where at least a part of the input data string and a part of the matching candidate data string match. Reading of the read pointer by the read pointer reading circuit and reading of the stored input data string by the history buffer reading circuit are executed after writing of the read pointer by the read pointer writing circuit and writing of the input data string by the history buffer writing circuit are finished.

Examples may include racks for a data center and sleds for the racks, the sleds arranged to house physical resources for the data center. The sleds and racks can be arranged to be autonomously manipulated, such as, by a robot. The sleds and racks can include features to facilitate automated installation, removal, maintenance, and manipulation by a robot.

Techniques described herein relate to systems and methods of data storage, and more particularly to providing layering of file system functionality on an object interface. In certain embodiments, file system functionality may be layered on cloud object interfaces to provide cloud-based storage while allowing for functionality expected from a legacy applications. For instance, POSIX interfaces and semantics may be layered on cloud-based storage, while providing access to data in a manner consistent with file-based access with data organization in name hierarchies. Various embodiments also may provide for memory mapping of data so that memory map changes are reflected in persistent storage while ensuring consistency between memory map changes and writes. For example, by transforming a ZFS file system disk-based storage into ZFS cloud-based storage, the ZFS file system gains the elastic nature of cloud storage.

Embodiments are generally directed apparatuses, methods, techniques and so forth to select two or more processing units of the plurality of processing units to process a workload, and configure a circuit switch to link the two or more processing units to process the workload, the two or more processing units each linked to each other via paths of communication and the circuit switch.

A method of data reduction in a block-based data storage system includes selecting a starting position in a block based on a deterministic function of block data content. Then for an unaligned block beginning at the selected starting position, a block digest (e.g., block hash) is generated and compared with stored block digests of stored data blocks. If there is a match, and the stored block matches the unaligned block, then a reference to the stored block is stored in place of the unaligned block, and otherwise the unaligned block and a corresponding digest are stored. The storing of references to already stored blocks, without the constraint of observing aligned-block boundaries, realizes increased savings of physical storage space.

Embodiments are generally directed apparatuses, methods, techniques and so forth to receive a sled manifest comprising identifiers for physical resources of a sled, receive results of an authentication and validation operations performed to authenticate and validate the physical resources of the sled, determine whether the results of the authentication and validation operations indicate the physical resources are authenticate or not authenticate. Further and in response to the determination that the results indicate the physical resources are authenticated, permit the physical resources to process a workload, and in response to the determination that the results indicate the physical resources are not authenticated, prevent the physical resources from processing the workload.

Technologies for dynamically managing resources in disaggregated accelerators include an accelerator. The accelerator includes acceleration circuitry with multiple logic portions, each capable of executing a different workload. Additionally, the accelerator includes communication circuitry to receive a workload to be executed by a logic portion of the accelerator and a dynamic resource allocation logic unit to identify a resource utilization threshold associated with one or more shared resources of the accelerator to be used by a logic portion in the execution of the workload, limit, as a function of the resource utilization threshold, the utilization of the one or more shared resources by the logic portion as the logic portion executes the workload, and subsequently adjust the resource utilization threshold as the workload is executed. Other embodiments are also described and claimed.

The storage device includes a first memory, a process device that stores data in the first memory and reads the data from the first memory, and an accelerator that includes a second memory different from the first memory. The accelerator stores compressed data stored in one or more storage drives storing data, in the second memory, decompresses the compressed data stored in the second memory to generate plaintext data, extracts data designated in the process device from the plaintext data, and transmits the extracted designated data to the first memory.

Methods and systems for encoding of integers are discussed. For example, various methods and systems may utilize Huffman coding, Tunstall coding, Arithmetic Coding, LZ77 coding, LZ78 coding, LW coding, or Shannon Fano Elias coding to encode the integers.