Methods, systems, and devices for hazard detection in a multi-memory device are described. A device may receive a first command that indicates a first bank address, a first row address, and a first column address. Based on the first bank address, the device may select a buffer for a hazard detection procedure that detects hazardous commands. The device may compare, as part of the hazard detection procedure, the first row address and the first column address from the first command with a second row address and a second column address from a second command in the buffer. The device may determine whether the first command and the second command are hazardous commands based on comparing the first row address and the first column address from the first command with the second row address and the second column address from the second command.

A method for generating a reconstructed version of a filesystem entity, the method may include (i) generating fallback retrieval metadata for a reconstructed version segment, when the reconstructed version segment is (a) associated with a corresponding intermediate version segment, and (b) the corresponding intermediate version segment is preceded by a corresponding most updated segment that does not exceed a fallback version of the filesystem entity; wherein the reconstructed version segment, the corresponding intermediate version segment and the corresponding most updated segment that does not exceed a fallback version have a same address range; (ii) generating a non-existing indicator for the reconstructed version segment, when the reconstructed version segment is (a) associated with the corresponding intermediate version segment, and (b) the corresponding intermediate version segment is not preceded by any corresponding most updated segment that does not exceed the fallback version; and (iii) maintaining intermediate metadata for retrieving one or more intermediate versions of the filesystem entity.

A flash memory device is re-partitioned over-the-air. A software component responsible for re-partitioning is received. The software component then generates a re-partitioning control structure in the flash memory device and executes re-partitioning steps. The executed re-partitioning steps and currently valid locations of data that needs to be moved in the flash memory device during re-partitioning are recorded in the re-partitioning control structure.

A method for execution by a computing device of a storage network begins by obtaining scoring information for a rebuilding encoded data slices for one or more storage units of a set of storage units of the storage network, where the scoring information includes two or more of a plurality of rebuilding rates, a plurality of input/output rates, a plurality of scores, and a plurality of selection rates. The method continues with determining a rebuilding rate of the plurality of rebuilding rates to utilize for the rebuilding based on the scoring information. The method continues by implementing the rebuilding of the encoded data slices in accordance with the rebuilding rate.

Methods and systems for index lifecycle management are provided. Exemplary methods include: receiving an ILM policy; determining a first condition and a first action for a first phase using the ILM policy; performing the first action for the first phase when the first condition is met; transition from the first phase to a second phase; determining a second condition and a second action for the second phase using the ILM policy; performing the second action for the second phase when the second condition is met; transition from the second phase to a third phase; determining a third condition and a third action for the third phase using the ILM policy; performing the third action for the third phase when the third condition is met; transition from the third phase to a fourth phase; and deleting the index during the third phase.

Methods, apparatus, and processor-readable storage media for device component management using deep learning techniques are provided herein. An example computer-implemented method includes obtaining telemetry data from one or more enterprise devices; determining, for each of the one or more enterprise devices, values for multiple device attributes by processing the obtained telemetry data; generating, for each of the one or more enterprise devices, at least one prediction related to lifecycle information of at least one device component by processing the determined attribute values using one or more deep learning techniques; and performing one or more automated actions based at least in part on the at least one generated prediction.

A semiconductor storage device includes memory cells, select transistors, memory strings, first and second blocks, word lines, and select gate lines. In the memory string, the current paths of plural memory cells are connected in series. When data are written in a first block, after a select gate line connected to the gate of a select transistor of one of the memory strings in the first block is selected, the data are sequentially written in the memory cells in the memory string connected to the selected select gate line. When data are written in the second block, after a word line connected to the control gates of memory cells of different memory strings in the second block is selected, the data are sequentially written in the memory cells of the different memory strings in the second block which have their control gates connected to the selected word line.

A method of labeling logic number units in a storage system results in the use of the same label for related LUNs in different storage arrays. A first storage array includes a first source logical unit number LUN, the second storage array includes a first target LUN, and the first source LUN and the first target LUN are a pair of active-active LUNs. The first storage array sends an assignable-address set of selectable labels for the first source LUN to the address assignment apparatus. The second storage array sends an assignable-address set of selectable labels for the first target LUN to the address assignment apparatus. The address assignment apparatus selects a label that is in both assignable-address sets of the first source LUN and first target LUN, and assign that selected label to both LUNs. Thereafter, the address assignment apparatus sends the selected label to the first storage array and the second storage array for identifying both the first source LUN and the first target LUN.

Techniques provide for managing data storage. The techniques involve in response to receiving a request for unmapping a logical storage unit associated with a first disk slice on a first physical disk and the first disk slice, determining information associated with the first disk slice; generating, based on the information, a first entry and a second entry corresponding to the first disk slice; adding the first entry into a queue of failed disk slices to enable data stored on the first disk slice to be cleared; and adding the second entry into a queue of free disk slices to enable the first disk slice to be mapped to a further logical storage unit. Accordingly, such techniques can remarkably improve the write I/O performance of the system and prolong the lifetime of the SSD.

This document describes aspects of communicating information about repair elements of a memory device. A memory device can include multiple repair elements that can each replace a defective or damaged memory element, such as a memory row, using a repair operation. By knowing a quantity of remaining available repair elements, a user of a memory device can make informed decisions about whether to make a replacement. In operation, a host device can send a command to the memory device requesting repair element information. Logic of the memory device can determine a quantity of repair elements that are available for a repair operation. In some cases, the logic may store this quantity in a register of the memory device. The memory device can signal the quantity of repair elements to the host device in response to the command.