Abstract: One or more aspects of the present disclosure relate to allocating virtual memory to one or more virtual machines (VMs). The one or more VMs can be established by a hypervisor of a storage device. The virtual memory can be allocated to the established one or more VMs. The virtual memory can correspond to non-volatile (NV) memory of a global memory of the storage device.

Abstract: Techniques for allocating resources in a system may include: monitoring, using a first proportional-integral-derivative (PID) controller, a size of a pool of free shared resources of a first type; responsive to determining the size of the pool of the free shared resources is at least a minimum threshold, providing the size of the pool of free shared resources as an input to a second PID controller; monitoring, using the second PID controller, a total amount of resources of the first type that are available; determining, using the second PID controller and in accordance with one or more resource policies for one or more applications, a deallocation rate or amount; deallocating, using the second PID controller and in accordance with the deallocation rate or amount, resources of the first type; and allocating a least a first of the deallocated resources for use by one of the applications.

Abstract: A method for managing data includes obtaining, by a hypervisor on a host computing device, a write request for storing first data, and in response to the write request: identifying a first set of memory segments associated with the first data using a memory mapper, wherein the first set of memory segments is associated with a memory device, making a first determination that the memory device is local to the host computing device, and in response to the first determination: storing the first data in the first set of memory segments.

Abstract: Techniques for data deduplication may include: receiving write operations that write first data; partitioning the first data into a plurality of data portions; generating, using a first hash function, a plurality of data deduplication hash values for the plurality of data portions, wherein a first data deduplication hash value of the plurality of data deduplication hash values is produced by said generating for a first of the plurality of data portions; performing first processing using a Bloom filter to determine whether the first data deduplication hash value has a corresponding first entry in a data store of deduplication hash values; and responsive to the first processing determining the first data deduplication hash value does not have the corresponding first entry in the data store of deduplication hash values, performing second processing, said second processing including adding the corresponding first entry in the data store of deduplication hash values.

Abstract: Techniques for allocating resources in a system may include: monitoring, using a first proportional-integral-derivative (PID) controller, a size of a pool of free shared resources of a first type; responsive to determining the size of the pool of the free shared resources is at least a minimum threshold, providing the size of the pool of free shared resources as an input to a second PID controller; monitoring, using the second PID controller, a total amount of resources of the first type that are available; determining, using the second PID controller and in accordance with one or more resource policies for one or more applications, a deallocation rate or amount; deallocating, using the second PID controller and in accordance with the deallocation rate or amount, resources of the first type; and allocating a least a first of the deallocated resources for use by one of the applications.

Abstract: A method for managing data includes obtaining, by a hypervisor on a host computing device, a write request for storing first data, and in response to the write request: identifying a first set of memory segments associated with the first data using a memory mapper, wherein the first set of memory segments is associated with a memory device, making a first determination that the memory device is local to the host computing device, and in response to the first determination: storing the first data in the first set of memory segments.

Abstract: First and second virtual storage controllers represent first and second physical storage controllers that provide access to different physical storage devices that back first and second virtual disks. One or more computing nodes host a virtual storage array that includes paired virtual storage directors. Each virtual storage director has access to both the first and second virtual storage controllers. Thus, the virtual disks may be presented to the storage directors as dual-ported disks even if the physical storage devices are single-ported. The virtual storage directors and virtual storage controllers may each be hosted by a separate virtual machine or instantiated in a separate container.

Abstract: The system and methods disclosed herein relate to an improvement in automated data tiering technology. The systems and methods disclosed herein enhance database storage performance characteristics in myriad ways. First, the speed with which data can be relocated from one tier to another in a tiered data storage system is increased by reducing the number of sort cycles required to perform data relocation. In addition, data relocation among the tiers is performed on the backend by an offload engine, which results in uninterrupted access to read/write commands within the data storage system from a user's perspective on the frontend. Third, users are able to adjust the percentages of hot or cold data that are relocated within the database without having to alter the service level agreements. In this way, users can make spontaneous changes to performance characteristics related to the promotion and demotion of data stored within a tiered data storage system.

Abstract: One or more aspects of the present disclosure relate to allocating virtual memory to one or more virtual machines (VMs). The one or more VMs can be established by a hypervisor of a storage device. The virtual memory can be allocated to the established one or more VMs. The virtual memory can correspond to non-volatile (NV) memory of a global memory of the storage device.

Abstract: A storage array is implemented as a virtual machine on a server. The virtual storage array includes a virtual engine with virtual directors and virtualized processor and memory resources. Embedded storage software converts Input/Output requests into Input/Output requests that can be serviced by the virtual machine. A virtual backend driver enables the virtual storage directors to access a set of virtual drives. A virtualized shared memory driver provides emulated input/output, XOR, direct memory access and copy services for send and receive threads.

Abstract: A method and computing system for sorting position-dependent data arrays. Specifically, the method and computing system disclosed herein entail: first, sorting one position-dependent data array according to a desired sorting order; and second, permuting the remaining position-dependent data arrays, based on the sorted position-dependent data array, in order to maintain the same relative positions of the various data stored across the position-dependent data arrays. Through this aforementioned sorting of position-dependent data arrays, a GPU may produce sorted structure of arrays from unsorted structure of arrays.

Abstract: Techniques for data deduplication may include: receiving write operations that write first data; partitioning the first data into a plurality of data portions; generating, using a first hash function, a plurality of data deduplication hash values for the plurality of data portions, wherein a first data deduplication hash value of the plurality of data deduplication hash values is produced by said generating for a first of the plurality of data portions; performing first processing using a Bloom filter to determine whether the first data deduplication hash value has a corresponding first entry in a data store of deduplication hash values; and responsive to the first processing determining the first data deduplication hash value does not have the corresponding first entry in the data store of deduplication hash values, performing second processing, said second processing including adding the corresponding first entry in the data store of deduplication hash values.

Abstract: Techniques for data deduplication may include: receiving write operations that write first data; partitioning the first data into a plurality of data portions; generating, using a first hash function, a plurality of data deduplication hash values for the plurality of data portions, wherein a first data deduplication hash value of the plurality of data deduplication hash values is produced by said generating for a first of the plurality of data portions; performing first processing using a Bloom filter to determine whether the first data deduplication hash value has a corresponding first entry in a data store of deduplication hash values; and responsive to the first processing determining the first data deduplication hash value does not have the corresponding first entry in the data store of deduplication hash values, performing second processing, said second processing including adding the corresponding first entry in the data store of deduplication hash values.

Abstract: Embodiments are described for a executing a processing job using one or more nodes of a storage area network using computing resources on the SAN that are predicted to be idle. A predictive model is generated by monitoring idle states of resources of nodes of the SAN and using machine learning to build the predictive model. A scheduler executes jobs on one or more nodes of the SAN with sufficient predicted idle resources to process the job, in accordance with resource requirements and job attributes in a manifest of the job. If a job cannot be completed during a window of time that the necessary resources are predicted to be idle, or if one or more resources become unavailable, the job can be paused and resumed, migrated to another node, or restarted at a later time when the required resources to complete the job are predicted to be idle.

Abstract: The system and methods disclosed herein relate to an improvement in automated data tiering technology. The systems and methods disclosed herein enhance database storage performance characteristics in myriad ways. First, the speed with which data can be relocated from one tier to another in a tiered data storage system is increased by reducing the number of sort cycles required to perform data relocation. In addition, data relocation among the tiers is performed on the backend by an offload engine, which results in uninterrupted access to read/write commands within the data storage system from a user's perspective on the frontend. Third, users are able to adjust the percentages of hot or cold data that are relocated within the database without having to alter the service level agreements. In this way, users can make spontaneous changes to performance characteristics related to the promotion and demotion of data stored within a tiered data storage system.

Abstract: The system and methods disclosed herein relate to an improvement in automated data tiering technology. The systems and methods disclosed herein enhance database storage performance characteristics in myriad ways. First, the speed with which data can be relocated from one tier to another in a tiered data storage system is increased by reducing the number of sort cycles required to perform data relocation. In addition, data relocation among the tiers is performed on the backend by an offload engine, which results in uninterrupted access to read/write commands within the data storage system from a user's perspective on the frontend. Third, users are able to adjust the percentages of hot or cold data that are relocated within the database without having to alter the service level agreements. In this way, users can make spontaneous changes to performance characteristics related to the promotion and demotion of data stored within a tiered data storage system.

Abstract: The system and methods disclosed herein relate to an improvement in automated data tiering technology. In these embodiments, users are able to weigh the importance of read, write, and pre-fetch operations in terms of tier placement within the data storage system. Data relocation evaluations are performed by an off-load engine, e.g., a graphics processing unit, which utilizes parallel processing on data arrays/vectors/extents. The data relocation candidates are identified via calculating a mobility score on an extent-by-extent basis. Data are then relocated within the various tiers of the data storage system.