Detecting and reconfiguring of boot parameters of a NVMe subsystem, including identifying a mapping between local boot parameters of a NVMe subsystem and a GUID that corresponds to the NVMe subsystem; determining that the NVMe subsystem has been reset; in response to determining that the NVMe subsystem has been reset: transmitting a discovery request to the NVMe subsystem for remote boot parameters of the NVMe subsystem; comparing the local boot parameters for the GUID with the remote boot parameters for the NVMe subsystem; determining, based on the comparing, that the remote boot parameters for the NVMe subsystem do not match with the local boot parameters for the GUID, and in response, updating values of the local boot parameters for the GUID based on the remote boot parameters of the NVMe subsystem.

A method, computer program product, and computing system for dividing a plurality of volumes replicated across a pair of storage systems into one or more consistency groups. A polarization state may be defined for each consistency group. An input-output (IO) failure associated with at least one consistency group may be detected. At least a portion of the at least one consistency group may be polarized based upon, at least in part, the polarization state defined for the at least one consistency group.

Tuning information associated with a storage device of a plurality of storage devices is received. One or more characteristics associated with the storage device are determined. The tuning information and the one or more characteristics are provided to the plurality of storage devices, wherein providing the tuning information causes a set of the plurality of storage devices to apply the tuning information based on the one or more characteristics.

A method for optimizing a Polar-RNNA quantizer of MLC NAND flash based on deep learning comprises the following steps: Step S1: transforming an MLC flash detection task into a deep learning task, and obtaining three hard-decision read thresholds based on a neural network; Step S2: expanding six soft-decision read thresholds based on the three hard-decision read thresholds; Step S3: constructing an LLR mapping table, and obtaining new LLR information of MLC flash based on the LLR mapping table; Step S4: symmetrizing an MLC flash channel, and performing density evolution; and Step S5: optimizing the soft-decision read thresholds based on a genetic algorithm to obtain an optimal quantization interval. According to the invention, polar codes can be directly used for MLC flash channels without the arduous work of MLC flash channel modeling, so that the reliability of MLC flash is effectively improved.

An electronic device may include: a control pulse generation circuit configured to selectively generate one of a first control pulse and a second control pulse on the basis of a reference code during a test period; and a voltage control code generation circuit configured to perform an addition operation or subtraction operation on a logic bit set of a voltage control code to set the voltage level of an operation voltage on the basis of the first and second control pulses.

A memory management method, a memory storage device, and a memory control circuit unit are provided. The method includes: detecting a first temperature status of a rewritable non-volatile memory module; performing a first write operation on a first physical unit under the first temperature status to store first data to the first physical unit; after performing the first write operation, detecting a second temperature status of the rewritable non-volatile memory module; in response to the first temperature status and the second temperature status meeting a first condition, performing a data refresh operation on the first physical unit under the second temperature status to re-store the first data to a second physical unit different from the first physical unit.

In certain embodiments, a computer system can create first and second pluralities of disk groups in a hyperconverged infrastructure (HCI) cluster, where each disk group in the first plurality has capacity storage devices of a first type and each disk group in the second plurality has capacity storage devices of a second type. The computer system can further tag each disk group in the first plurality with a first disk group tag, tag each disk group in the second plurality with a second disk group tag, and create a storage policy that includes a placement rule identifying the first disk group tag. Then, at a time of provisioning a virtual machine (VM) in the HCI cluster that is associated with the storage policy, the computer system can place the VM on one or more of the first plurality of disk groups in accordance with the placement rule identifying the first disk group tag.

A data processing apparatus and a vehicle having the same are provided. A data processing apparatus of a vehicle includes: a first memory having a plurality of storage areas to which each address of a plurality of addresses is allocated; and a processor configured to confirm information of data received from a first device, confirm an address corresponding to the received data based on the confirmed information of data, and store the received data in a storage area of the plurality of storage areas corresponding to the confirmed address.

The efficiency of the maintenance of a storage apparatus including a plurality of flash drives can be enhanced. In a storage apparatus including a plurality of SSDs and a CPU, the CPU specifies, based on lifetimes of the SSDs depending on amounts of data written to the SSDs, the SSD to be replaced on a scheduled maintenance date, gives notice of the SSD specified to be replaced, and copies data in the SSD to be replaced to another SSD by the scheduled maintenance date on which the replacement is to be performed.

Embodiments for transferring data directly from primary storage to secondary storage in a virtualized network including virtual machine (VM) based storage, by exposing a source volume in the primary storage to a hypervisor host of the virtualized network, preparing a destination volume of the secondary storage as an empty volume and exporting it to the hypervisor host so that the host can the destination volume along with the source volume, and moving, in the hypervisor host, data from the exposed source volume to the exported empty destination volume using a combination of Storage Direct, Storage VMotion, and XCOPY or enhanced XCOPY technologies, wherein the XCOPY technology provides a direct transfer of data from the primary storage to the secondary storage.