41 results about "Volume (computing)" patented technology

The technology disclosed herein enables a higher-level process to perform storage volume management with knowledge of a physical storage backend underlying a storage volume. In a particular example, a method includes mounting a storage volume to a computing node of the computing nodes. The storage volume is stored in a storage pool of a plurality of underlying storage pools. The method further includes determining an identifier for the storage pool, receiving a request to duplicate the storage volume, and determining a second identifier for a second storage pool of the plurality of underlying storage pools to which the storage volume will be duplicated. When the second identifier matches the identifier, creating a clone of the storage volume rather than copying the storage volume to the second storage pool.

The invention discloses a method for realizing QoS automatic control of a single cloud hard disk and a medium, mainly relates to the technical field of the single cloud hard disk, and is used for solving the problems that an independent QoS strategy cannot be set for a single cloud hard disk and QoS strategy change cannot be implemented on an online cloud hard disk through an effective interface in the prior art. Comprising the following steps: when a scope is a rear end, directly finding a corresponding block device according to a cloud hard disk id in a QoS attribute of a single volume, and setting the QoS attribute of the single volume; a nova rest api interface is newly added to the management and control node; when the action range is a front end, generating a rest request corresponding to the converted QoS attribute of the single volume, and when a preset second legality verification rule is met, initiating the rest request to a computing management service in the computing node; and when the rest request does not contain the preset attribute, performing flow control setting in a host machine user mode, otherwise, performing flow control setting in a virtual machine kernel mode.

A block-based storage system hosts logical volumes that are implemented via multiple replicas of volume data stored on multiple resource hosts in different failure domains. Also, the block-based storage service allows multiple client computing devices to attach to a same given logical volume at the same time. In order to prevent unnecessary failovers, a primary node storing a primary replica is configured with a health check application programmatic interface (API) and a secondary node storing a secondary replica determines whether or not to initiate a failover based on the health of the primary replica.

This application provides a data processing method, system, apparatus, device, storage medium, and program product, relating to the field of big data. Applied to any parent company computing node in a confidential environment cluster, the parent company computing node is configured with a confidential environment. The method includes: initiating a data usage request to a subsidiary node and receiving a subsidiary key sent by the subsidiary node; combining the parent company key and the subsidiary key to obtain a disk storage key; decrypting the disk storage data of the subsidiary node stored in the confidential environment using the disk storage key; performing distributed processing on the decrypted disk storage data in the confidential environment to obtain a processing result, and sending the processing result to the subsidiary node. This application's method reduces the risk of data leakage and meets data protection requirements; by distributing the processing tasks through the parent company computing node, it simultaneously solves the problems of large data volumes and high processing time requirements.

A computing device, non-transitory computer-readable storage medium, and method for automatically recreating a lost storage volume are provided. A volume command including volume metadata associated with a storage volume of an SCM storage device is received. The volume metadata is stored in another storage device that is more non-volatile than the SCM storage device. The storage volume is configured in accordance with the volume command, including forwarding the volume command to an SCM device driver. After forwarding the volume command, a notification of a persistent loss at the SCM storage device is received. After receiving the notification of the persistent loss, the volume metadata is retrieved from the other storage device. The storage volume is automatically reconfigured in accordance with the volume command, including submitting the retrieved volume metadata to the SCM device driver.

A computing device comprising a storage device and processing circuitry may perform the techniques of this disclosure. The storage device may have a plurality of blocks forming a volume. The processing circuitry may obtain volume changed block tracking (CBT) information identifying one or more of the blocks storing updated data that has changed relative to a previous backup of the one or more blocks, and determine file mapping information identifying one or more blocks of the plurality of blocks that store file data associated with a file. The processing circuitry may also determine, based on the volume CBT information and the file mapping information, file system CBT information identifying whether at least one of the one or more blocks store file data associated with the file have changed, and initiate, based on the file system CBT information, a subsequent backup of at least a portion of the file data.

A system or method for preventing or mitigating malicious processes in a computing environment having one or more processors and memory operatively coupled to the one or more processors can include computer instructions which when executed causes the one or more processors to perform certain operations. The operations can include the steps of obtaining all file system input and output paths using a kernel driver, performing a normalized entropy quantification calculation on data found on the file system input and output paths, determining an inverse density from the normalized entropy calculation, and flagging any data or data segment found having a difference in inverse densities of read and write volume equal to or higher than a predetermined threshold.

The invention provides a disk traffic control method and device, equipment, a medium and a program product, and the method comprises the steps: creating a volume type of a storage performance development suite type through a block storage service, and associating the volume type of the storage performance development suite to a service quality specification strategy; binding the volume type to a target back-end storage system; creating a volume by specifying a volume type through a block storage service, generating logic information of the volume on a corresponding open stacking platform, and generating a block storage volume entity on a corresponding target back-end storage system; mounting the volume to a virtual machine of the computing service, and adding the service quality value of the volume to the computing service according to a service quality specification strategy; and calling an interface of the storage performance development suite to create a block device corresponding to the volume in the target back-end storage system, and configuring the block device according to the service quality value. The method provided by the invention is used for achieving the technical effect of improving the disk flow control efficiency and universality.

The invention provides a resource scheduling method, a computing device and a system, and the method comprises the steps: responding to a scheduling request of a container group, and determining a second virtual machine; wherein the host where the second virtual machine is located and the host where the first virtual machine where the container group is located are associated with the same storage resource group; migrating the container group from the first virtual machine to a second virtual machine; unmounting the first storage volume mounted on the first virtual machine from the first virtual machine; determining a second storage volume based on the second virtual machine and the first storage volume; wherein the storage resource where the second storage volume is located is located in the storage resource group, and the host where the second virtual machine is located is associated with the storage resource where the second storage volume is located; mounting the second storage volume to a second virtual machine, so that the container group can access the second storage volume in a local disk mode; therefore, when a complex topological relation exists between various storage resources on the cloud platform and the cloud platform host, resource scheduling can be quickly realized based on the storage resource group.

The application provides a bare metal server instance management method, system, storage medium and program product, relates to the technical field of cloud computing, and the method comprises the following steps: obtaining the out-of-band management address of a target bare metal server, obtaining the hardware manufacturer identifier according to the out-of-band management address, and determining a target virtual local area network; injecting a hardware driver set matched with the hardware manufacturer identifier into an operating system image associated with a machine installation template to generate a target deployment image; allocating a temporary boot IP address in the target virtual local area network and configuring a pre-boot network parameter through a substrate out-of-band interface; controlling the target bare metal server to obtain the target deployment image according to the pre-boot network parameter to install the operating system; adjusting the computing resource quota to a target resource quota through a management and control agent program during the operation of the operating system; and when a storage expansion request is received, creating a target storage volume according to a target physical disk identifier through the management and control agent program and mounting the target storage volume to a target mounting point.

The invention relates to computing. What is claimed is a method for managing data in a block data storage system consisting of a random-access memory (RAM) and a solid-state drive (SSD), which involves: dividing the SSD into consecutive volumes, each of which consists of a metadata region and a user data region; dividing the RAM into dedicated memory for uploading segments from the SSD, volume arrays and service information; transferring valid tuples of metadata from each metadata-containing segment for each volume from the SSD to the RAM; creating a metadata storage segment in the RAM; updating a metadata tuple in the metadata storage segment; writing the metadata storage segment and a backup copy thereof to the SSD. The technical result consists in reducing the number of metadata writing operations for block data storage systems.

A data protection system includes a splitter configured to reduce latencies when splitting writes in a computing environment. The splitter captures a write and adds metadata to augment the write with virtual related information. The augmented data is provided to a smartNIC while the write is then processed in the IO stack. The smartNIC may have a volume only visible to the splitter. The smartNIC also includes processing power that allows data protection operations to be performed at the smartNIC rather than with the processing resources of the host.

There is provided an I / O latency reduction system, comprising at: (i) least one computing platform comprising at least one storage volume having at least two storage media; (ii) a storage stack striping component designated to perform data striping of at least one large I / O data segment into several minimally sized I / O data segments, wherein the data striping is configured to logically segment and re / compose sequential data segments such that consecutive segments are stored on different storage media; and (iii) computing resources associated with each of the at least two storage media, wherein the data striping and storage of the minimally sized I / O data segments in different storage media is configured to be conducted parallelly, wherein the minimally sized I / O data segments are a obtained by a low granularity striping process, wherein the system is configured to increase amplification of the minimally sized IO data segments while replicating them, and wherein said data striping and re / composing is designated to be performed by the said computing resources associated with each of the at least two storage media.

This invention relates to a method and apparatus for determining inter-particle interactions based on a matrix, comprising: acquiring multiple computing units currently participating in the computation, and dividing the physical space corresponding to the computing units to obtain a tower disk model corresponding to the computing units; selecting virtual subspace pairs that meet preset conditions from multiple virtual subspaces of each tower disk model, and constructing a target tower disk model based on the virtual subspace pairs; migrating the particles to be computed to the target tower disk model to determine the target particle pairs participating in the computation of Hamiltonians; and calculating the interactions between the target particle pairs based on the target tower disk model and the target particle pairs. Thus, by filtering out a large number of redundant particle pair computations, the computational load is reduced, computational efficiency is improved, and data transmission volume is reduced, load is lowered, and transmission rate is increased, thereby greatly improving supercomputing efficiency.

The embodiment of the invention relates to the field of large models and the field of near storage computing, and discloses a heterogeneous storage computing architecture scheduling method and equipment oriented to a hybrid expert model, and a medium. In the invention, the heterogeneous storage and calculation architecture comprises N storage channels and L accelerators. Each accelerator is connected with at least one of the N storage channels, and each storage channel is connected with at least one in-storage computing unit. The method comprises the following steps: acquiring channel delay of each storage channel and accelerator accumulated delay of L accelerators; obtaining a to-be-processed data volume distributed by the expert model in the in-memory calculation unit; in response to a target storage channel of which the channel delay is greater than the accumulated delay of the accelerator, moving the position of the expert model with the maximum to-be-processed data volume in the target storage channel to the accelerator from the in-memory calculation unit, and updating the channel delay and the accumulated delay of the accelerator; and in response to the channel delay of all the storage channels being less than or equal to the accelerator cumulative delay, terminating the scheduling. The problems of local overload and performance reduction during near storage calculation are solved.

The application discloses a disk data encryption and decryption method and device, equipment and a storage medium, and relates to the technical field of information security, and comprises the following steps: a virtualization computing node controller program sends a first key to a volume encryption application component by using a virtual encrypted volume constructed based on a created virtual machine image; the volume encryption application component triggers an encryption and decryption thread handle pool creation process by using an encrypted second key obtained based on the first key; when receiving encryption task information through a password management component, a first target password calculation resource linked list is determined based on an encryption and decryption thread handle pool corresponding to the encryption task information, and data encryption is performed by using a resource linked list scheduling rule and the first target password calculation resource linked list, so that disk data writing is completed; when receiving decryption task information through the password management component, decryption is performed by using a resource linked list scheduling rule and a second target password calculation resource linked list, so that data reading is completed. The encryption and decryption efficiency is effectively improved.

Techniques discussed herein relate to an object-relational database management system (ODMS) (e.g., a PostgreSQL ODMS) that utilizes a shared block storage volume (SBSV) for storage. The SBSV may utilize a file system that enables a single-writer-multiple reader model in which a primary computing node may read or write to the SBSV and one or more replica computing nodes are restricted from writing to the SBSV. To enable the primary computing node to write data at its own pace, regardless of the status of synchronization at each of the one or more replica computing nodes, the SBSV may include a staging area that maintains data that has not yet been updated at one or more of the replica computing nodes. When the primary computing node no longer maintains the data in local memory, the one or more replica computing nodes may obtain the data from the staging area of the SBSV.

Systems, methods, and software are disclosed herein for identifying duplicate blocks of a storage system and deduplicating the storage system. In one example, a method of operating a computing device includes scanning first metadata of blocks of a container file of a virtual volume to generate a first log file including records of virtual volume block numbers (VVBNs) and fingerprints of the blocks; scanning second metadata of blocks of an active file system of the virtual volume to generate a second log file including records of VVBNs and file block numbers (FBNs) of the blocks; generating tuples based on merging the records of the first log file and the second records of the second log file according to the VVBNs; identifying duplications among the blocks based on the tuples; and deduplicating the blocks based on the duplications in the active file system identified based on the tuples.

The embodiment of the invention provides a large model compiling optimization method and system based on in-memory computing equipment. According to the method, a high-dimensional tensor of a large model is split into sub-tensors adaptive to a storage array, waste of storage resources caused by mismatching of data sizes is avoided, weight data with the reuse rate larger than a preset threshold value is preloaded to an equipment storage area, and repeated carrying of the weight data can be avoided; on the basis of a preset operator instruction matching table, a mapping relation between a large model operator and an in-memory calculation instruction is constructed, and it is ensured that equipment instruction resources can be efficiently called by the large model operator; then, based on the sub-tensor data size and the mapping relation between operators and instructions, the target calculation task is split into sub-tasks and distributed to a target calculation unit, and accurate matching of calculation unit resources and task types is achieved; and finally, generating an equipment executable instruction stream according to an allocation result to ensure that storage, instructions and computing unit resources of the computing equipment in the optimized memory are all adaptive to large model computing requirements, so that the utilization rate of the equipment resources can be improved.

A system or method for preventing or mitigating malicious processes in a computing environment having one or more processors and memory operatively coupled to the one or more processors can include computer instructions which when executed causes the one or more processors to perform certain operations. The operations can include the steps of obtaining all file system input and output paths using a kernel driver, performing a normalized entropy quantification calculation on data found on the file system input and output paths, determining an inverse density from the normalized entropy calculation, and flagging any data or data segment found having a difference in inverse densities of read and write volume equal to or higher than a predetermined threshold.

Methods and systems for implementing division of process resources of running processes into individually locked partitions, and indirect mapping of keys to process resources to locks of each partition, are provided. In computing systems implementing concurrent processing, applications may generate and destroy concurrently running processes with high frequency. Real-time security monitoring may cause the computing system to run monitoring processes collecting large volumes of data regarding system events occurring in context of various other processes, causing threads of processes of the security monitoring application to make frequent write access and read access to resources of those processes in memory. Indirect mapping of lock acquisition across locks provides scalable alleviation of lock contention and thread blocking that result from computational concurrency, while handling read and write requests which arise at unpredictable times from kernel-space monitoring processes, and which request unpredictable resources of monitored user-space processes.

The invention discloses a multi-platform PFS management method, device and equipment and a storage medium, and relates to the technical field of cloud computing infrastructure, and the method comprises the steps: detecting a working node of a container pointed by a storage volume mounting request, and judging whether the working node is provided with a native client of a parallel file system PFS or not; if a native client is provided with the PFS, creating an isolation mounting point directory on the working node, directly mounting the PFS, and mapping the isolation mounting point directory to the container; if the container does not have the native client of the PFS, a unified NFS access address corresponding to the PFS provided by an NFS virtualization gateway is returned to the container, and the NFS virtualization gateway is configured to mount a back-end PFS and execute conversion from a PFS protocol to an NFS protocol. The efficiency of the multi-cloud environment can be improved, and the operation and maintenance pressure can be reduced.

A method, a non-transitory computer-readable medium, and a system for optimizing storage in a cloud computing environment that comprises receiving, by a processor, a persistent volume claim (PVC) for storage by a workload; automatically providing, by the processor, a storage class to the PVC for storage provisioning; dynamically creating, by the processor, a persistent volume (PV) based on the storage class; and automatically binding, by the processor, the PV to the PVC, wherein the PV is formatted with a B-tree file system (Btrfs).

The multi-thread partitioning method under the storage-computation integrated structure disclosed in the present invention includes: splitting the parallel nodes in the annotation call graph into multiple basic blocks, running them on multiple threads, and running the data set to calculate the data transmission volume between the basic blocks; selecting the thread with the highest number of executions to execute in the in-memory computing unit, using the partitioning result as the initial solution, and calculating the total execution time of the partitioning scheme; in each iteration, screening out the threads with the execution times exceeding the threshold T H The threads are distributed to the set of threads executed by the in-memory computing unit. In the current optimal solution {I} opt Based on the random inversion of the threads in the thread set, the i-th feasible solution {I} i ; Calculate the partitioning scheme corresponding to the feasible solution {I} i Execution time T i , calculate the execution time T i and the execution time T of the current optimal solution opt If the difference ΔT is positive, the feasible solution {I} i As the current optimal solution and update the current optimal execution time T i . Divide the parallel basic blocks to reduce the waiting time between programs.

The invention relates to the technical field of data security, in particular to a data security storage method and system in big data transaction. According to the method, physical characteristics such as the number of data blocks, the number of key segments and the number of deleted entries are extracted, and hardware reference parameters and environment correction factors are combined, so that file volume is mapped to CPU estimation time consumption; the method comprises the following steps: constructing a virtual scheduler in a memory and simulating task allocation of a background thread pool to predict the latest completion time of a system and a thread load unbalance ratio; a suggested delay coefficient is generated based on the prediction result, and a lockless hibernation operation is performed before the write request acquires the mutex lock resource. According to the method, the hidden overhead of the computing power of the CPU is analyzed, the task allocation is simulated by means of the virtual scheduler, the thread load state is pre-judged in advance, and flow control is implemented before the storage engine mutual exclusion lock is obtained by the write-in request through lock-free delay execution, so that the deadlock risk is reduced, and the stability and throughput capacity of the system in a compliance encryption scene are improved.

Systems and methods are provided for data migration including cloning a multiple-logical unit number (LUN) volume into a plurality of cloned single-LUN volumes on a first storage node of a computing system; creating a plurality of new volumes on a second storage node of the computing system based at least in part on the plurality of cloned single-LUN volumes; selectively copying snapshot data from the plurality of cloned single-LUN volumes to the plurality of new volumes; establishing snapshot mirror relationships between the plurality of cloned single-LUN volumes and the plurality of new volumes; synchronizing the plurality of cloned single-LUN volumes and the plurality of new volumes; and performing a migration of data logical interface failovers (LIFs) from the plurality of cloned single-LUN volumes to the plurality of new volumes.

The embodiment of the invention provides a data processing method, system and device, equipment, a storage medium and a program product, and relates to the field of big data. The method is applied to any mother computer node in a mother confidential environment cluster, the mother computer node is provided with a confidential environment, and the method comprises the following steps: initiating a data use request to a sub-company node, and receiving a sub-company key sent by the sub-company node; combining the mother company secret key with the subsidiary company secret key to obtain a disk dropping secret key; decrypting the storage data of the subsidiary company node stored in the confidential environment by using the storage key; and carrying out distributed processing on the decrypted disk data in a confidential environment to obtain a processing result, and sending the processing result to the sub-company node. According to the method, the risk of data leakage is reduced, and the data protection requirement is met; the distributed processing tasks are processed through the mother company computing nodes, and the problems of large data volume and high processing timeliness requirement are solved at the same time.

A computing device comprising a storage device and processing circuitry may perform the techniques of this disclosure. The storage device may have a plurality of blocks forming a volume. The processing circuitry may obtain volume changed block tracking (CBT) information identifying one or more of the blocks storing updated data that has changed relative to a previous backup of the one or more blocks, and determine file mapping information identifying one or more blocks of the plurality of blocks that store file data associated with a file. The processing circuitry may also determine, based on the volume CBT information and the file mapping information, file system CBT information identifying whether at least one of the one or more blocks store file data associated with the file have changed, and initiate, based on the file system CBT information, a subsequent backup of at least a portion of the file data.

Systems and methods are provided for data migration including cloning a multiple-logical unit number (LUN) volume into a plurality of cloned single-LUN volumes on a first storage node of a computing system; creating a plurality of new volumes on a second storage node of the computing system based at least in part on the plurality of cloned single-LUN volumes; selectively copying snapshot data from the plurality of cloned single-LUN volumes to the plurality of new volumes; establishing snapshot mirror relationships between the plurality of cloned single-LUN volumes and the plurality of new volumes; synchronizing the plurality of cloned single-LUN volumes and the plurality of new volumes; and performing a migration of data logical interface failovers (LIFs) from the plurality of cloned single-LUN volumes to the plurality of new volumes.

A method facilitating soft deletion and restoration of clustered file systems includes, in response to receiving an instruction to temporarily disable a computing cluster, creating, by a system including at least one processor, snapshots of volumes associated with a virtual machine (VM) of the computing cluster; generating, by the system, mapping data representative of a mapping between snapshot identifiers, of the snapshots of the volumes associated with the VM, and an instance identifier of the VM; and, in response to the mapping data being determined to have been successfully generated, deleting, by the system, the VM.