A method of processing data related to a machine learning model, executed by a computer including a memory including a memory area and a processor, includes: compressing the data in a course of calculation of a first calculation process, to generate compressed data; storing the generated compressed data in the memory area; and executing a second calculation process by using the compressed data stored in the memory area.

A system and method for efficiently storing data in a storage system. A data storage subsystem includes multiple data storage locations on multiple storage devices in addition to at least one mapping table. A data storage controller determines whether data to store in the storage subsystem has one or more patterns of data intermingled with non-pattern data within an allocated block. Rather than store the one or more pattern on the storage devices, the controller stores information in a header on the storage devices. The information includes at least an offset for the first instance of a pattern, a pattern length, and an identification of the pattern. The data may be reconstructed for a corresponding read request from the information stored in the header.

Disclosed are various examples of providing efficient bit compression for direct mapping of physical memory addresses. In some examples, a hypervisor operating system component generates a mask of used address space bits indicated by memory map entries for a computing device. A longest range of unused address space bits is identified using the mask. The memory map entries are transformed to omit the longest range of unused address space bits.

Systems and methods for space allocation for block device compression are provided. In particular, a computing device may receive an allocation request to write the compressed data, select a range list adequate for serving the allocation request from a plurality of range list, dequeue a range entry from the selected range list to allocate free space for the compressed data, and allocate the free space corresponding to the range entry to the compressed data to serve the allocation request.

Aspects of the present disclosure relate to data deduplication (dedup) techniques for storage arrays. In embodiments, a sequence of input/output (IO) operations in an IO stream received from one or more host devices by a storage array are identified. Additionally, a determination is made as to whether previously received IO operations match the identified IO based on an IO rolling offsets empirical distribution model. Further, one or more data deduplication (dedup) techniques are performed on the matching IO sequence based on a comparison of a source compression technique and a target compression technique related to the identified IO sequence.

Techniques are provided for incrementally restoring a virtual machine hosted by a computing environment. In response to receiving an indication that the virtual machine is to be incrementally restored, a snapshot of the virtual machine may be created while the virtual machine is shut down into an off state. The snapshot is transmitted to a storage environment as a common snapshot. The snapshot and the common snapshot are common snapshots comprising a same representation of the virtual machine. The common snapshot and a prior snapshot of the virtual machine are evaluated to identify a data difference of the virtual machine between the common snapshot and the prior snapshot. An incremental restore is performed of the virtual machine by transmitting the data difference from the storage environment to the computing environment to restore the virtual machine to a state represented by the prior snapshot.

Techniques for shrinking a storage space involve determining a used storage space in a storage pool allocated to a plurality of file systems, and determining a usage level of a storage space in the storage pool based on the used storage space in and a storage capacity of the storage pool. The techniques further involve shrinking a storage space from one or more of the plurality of file systems based on the usage level of the storage pool. Such techniques may automatically shrink storage space in one or more file systems from the global level of the storage pool, which determines an auto shrink strategy according to overall performance of the storage pool, thereby improving efficiency of auto shrink and balancing system performance and saving space.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for precisely tracking memory usage in a multi-process computing environment. One of the methods includes implementing an instance of a memory usage tracker (MUT) in each process running in a node of a computer system. A MUT can maintain an account of memory usage for each of multiple logical owners running on a process on which the MUT is running. The MUT can determine an actual memory quota for each owner, and enforce the actual memory quota of the owner. Enforcing the actual memory quota of the owner can include receiving each memory allocation request, checking each allocation request and a current state of the account against the actual quota, approving or rejecting each allocation request, communicating the approval or rejection to an underlying memory manager, and updating the owner account for each approved allocation request.

Storage efficiency driven migration includes: determining a level of similarity between first data stored on a first storage system and second data stored on a second storage system; determining, in dependence upon the level of similarity, that an expected amount of storage space reduction from migrating similar data exceeds a threshold level; and responsive to determining that the expected amount of storage space reduction exceeds the threshold level, initiating a migration of one or more portions of the first data from the first storage system to the second storage system.

Methods, computer program products, computer systems, and the like for efficient metadata management are disclosed, which can include receiving a subunit of storage, storing a first metadata portion of the subunit of storage in a first unit of storage, and storing a second metadata portion of the subunit of storage in a second unit of storage.