Examples described herein relate to management of containers in a storage system. Examples may receive a container specification corresponding to a container image. Examples may obtain the container image from a container repository and select storage volumes based on the container specification. Examples may execute one or more containers from the container image on a controller of the storage system within resource limits. Examples may dynamically select the controllers based on resource availability at the plurality of controllers. Examples may allow scheduling the execution of the containers at a specific controller at a predetermined time. The execution may include performing one or more batch operations on the storage volumes. Examples may further enable monitoring a status of the container and providing alerts in response to a detection of a failure event associated with the container.

A system and method for memory management. In one embodiment, the method includes generating a dependency structure comprising one or more task identifiers and one or more data object identifiers. The dependency structure includes a list of one or more dependencies for a first data object identifier of the one or more data object identifiers, a first dependency of the list identifying a first task for which a data object identified by the first data object identifier is an input. The method further includes counting the number of dependencies for the first data object identifier, decrementing the count by one when the first task completes execution, and, when the count reaches zero, deallocating the first data object.

Provided are a storage device using a neural network and an operating method of the storage device for automatic redistribution of information and variable storage capacity based on accuracy-storage capacity tradeoff that may learn input information using the neural network and may store the learned information. The neural network may include a plurality of input neurons and a plurality of output neurons; at least one stable synapse configured to connect at least one of the input neurons and at least one of the output neurons, respectively; and at least one flexible synapse configured to connect at least one remaining of the input neurons and at least one remaining of the output neurons, respectively.

Storage devices can be configured to utilize one or more memory buffers located within a host-computing device. These host buffers may allow for faster access to some data, including control pages. However, host buffers are susceptible to fragmentation issues similarly to standard user memory arrays. As the data stored within the host buffers becomes more fragmented, performance can suffer. This performance loss in storage devices becomes more pronounced as the desired performance levels of these storage devices increase. Therefore, various methods and systems described herein manage fragmentation within host buffers by conducting one or more operations. These operations may include locating a continuous portion of allocated or unallocated memory within the host buffer and either swap or copy high-usage or high-priority data to those continuous portions. When continuous portions of host buffer memory are not available, relevant portions of data may be cashed within the storage device to increase performance.

A data processing method for a network adapter includes the network adapter that obtains a first input/output (I/O) command. The first I/O command instructs to write data stored in a local server to at least one remote server, and the first I/O command includes address information and length information that are of the data and that are stored in the local server. The network adapter splits the data based on the address information and the length information to obtain a plurality of groups of address information and length information. The network adapter obtains, from the local server based on the groups of address information and length information, data corresponding to the groups of address information and length information, and sends the data to the at least one remote server.

The disclosed technology relates to an electronic device. According to the disclosed technology, a memory controller for a storage device for storing data in connection with a host in communication with the storage device includes a recommendation signal manager configured to store a plurality of recommendation signals that recommends activating a memory area of the host that stores mapping information in the memory area of the host, and a host controller configured to provide at least one of the plurality of recommendation signals to the host according to whether a number of recommendation signals provided to the host is less than a threshold value.

Disclosed herein are system, method, and computer program product aspects for managing a storage system. In an aspect, a host device may generate a configuration corresponding to a file and transmit the configuration to a memory device, such as 3D NAND memory. The configuration instructs the memory device to refrain from transmitting a logic-to-physical (L2P) dirty entry notification to the host device. The L2P dirty entry notification corresponds to the file. The host device may also generate a second configuration corresponding to the file and transmit the second configuration to the memory device. The second configuration instructs the memory device to resume transmitting the L2P dirty entry notification corresponding to the file to the host device.

A data processing method for a log structured merge (LSM) tree includes selecting SST files to be compressed and merged in a current layer and a next layer, sequentially reading the SST files to be compressed and merged in the current layer and the next layer from a first storage device and sequentially writing the SST files in a second storage device, randomly reading the SST files to be compressed and merged from the second storage device into a memory according to key sequence numbers of data blocks included in the SST files to be compressed and merged, and performing compression and merge processing on the SST files to be compressed and merged. Sequential and random read and write speed of the second storage device is higher than that of the first storage device

A storage device includes; a memory, a management circuit configured to manage an offloading program table and a count table, and a computing circuit configured to perform a processing operation using the offloading program table, the count table, and the memory. The management circuit is further configured to, in response to a first offloading program and a first offloading request, selectively store the first offloading program in the offloading program table in accordance with a determination of whether an offloading program identical to the first offloading program is stored in the offloading program table, and update the count table storing a first count indicating a remaining number of processing operations using the first offloading program.

In creating an extent array in a storage system, in response to receiving a request to generate an extent array using idle extents in storage devices, a width of an extent stripe is determined, and a size of the extent array is designated by the storage system. A first extent group and a second extent group are respectively selected from the storage devices based on the width to form a first extent stripe and a second extent stripe, and a first extent at a given position in the first extent group and a second extent at a given position in the second extent group are respectively located in different storage devices. Based on the first extent stripe and the second extent stripe, an address mapping representing the extent array is generated. The address mapping includes association between extent identifiers of extents and extent indexes of the extents.