Systems, methods and apparatus of intelligent bandwidth allocation to different types of operations to access storage media in a data storage device. For example, a data storage device of a vehicle includes: storage media components; a controller configured to store data into and retrieve data from the storage media components according to commands received in the data storage device; and an artificial neural network configured to receive, as input and as a function of time, operating parameters indicative a data access pattern, and generate, based on the input, a prediction to determine an optimized bandwidth allocation scheme for controlling access by different types of operations in the data storage device to the storage media components. The controller is configured to schedule the operations of the different types to access the one or more storage media components according to the optimized bandwidth allocation scheme.

In an embodiment, a system may support programmable hashing of address bits at a plurality of levels of granularity to map memory addresses to memory controllers and ultimately at least to memory devices. The hashing may be programmed to distribute pages of memory across the memory controllers, and consecutive blocks of the page may be mapped to physically distant memory controllers. In an embodiment, address bits may be dropped from each level of granularity, forming a compacted pipe address to save power within the memory controller. In an embodiment, a memory folding scheme may be employed to reduce the number of active memory devices and/or memory controllers in the system when the full complement of memory is not needed.

Systems and methods for automated tuning of Quality of Service (QoS) settings of volumes in a distributed storage system are provided. According to one embodiment, responsive to a predetermined event, information regarding a multiple QoS settings assigned to a volume of a distributed storage system that is being utilized by a client are obtained. A difference between a first QoS setting of the multiple QoS settings and a second QoS setting of the multiple QoS settings is determined. Responsive to determining the difference is less than a threshold a new value of the first QoS setting or a third QoS setting of the multiple QoS settings that is greater than a respective current value of the first QoS setting or the third QoS setting is determined and assigned to the volume for the client.

A system and method improve caching efficiency in a data storage system by performing machine learning processes on metadata relating to extents of data blocks, rather than individual blocks themselves. Thus, once the storage devices are divided into extents, various metadata regarding access to the blocks within each extent are aggregated, and per-extent features are extracted. These features are used to train a data regression model that is subsequently used to infer a most likely “hotness” value for each extent at a future time. These predicted values, which may be further classified as e.g. “hot”, “warm”, and “cold” using thresholds, are used to implement the cache replacement policy. Embodiments scale to large and multi-layered caches, and may avoid common caching problems like thrashing, by adjusting the extent size. Policy goal functions may be optimized by dynamically adjusting the classification thresholds.

Systems and methods provide alternative store-and-forward mechanisms to utilize a Non-Volatile Memory Express (NVMe™) drive's Controller Memory Buffer (CMB) instead of using a fabric bridge's memory resources to increase overall throughput. In various embodiment this successfully avoids performance scaling limitations of a centralized store-and-forward memory location for data input/output, within a large disk-array, that may otherwise oversubscribe the available memory space.

A storage device includes a nonvolatile memory device and a storage controller. The storage controller accesses the nonvolatile memory device based on a request of an external host device. The storage controller sends a signal to the external host device, based a throughput of accessing the nonvolatile memory device being within a specific range.

A method includes: receiving, by a storage device from a core in a host, a request to provide exclusive resource to a command of a predefined submission queue of a non-volatile memory (NVM) set in the storage device, wherein the request pertains to operating the NVM set in a deterministic state; generating a virtual NVM set identifier for a virtual NVM set based on a predefined mapping of the predefined submission queue and the NVM set; determining a storage controller associated with the NVM set based on a predefined mapping of the predefined submission queue, the NVM set, and the virtual NVM set identifier; enabling at least one core to operate in a Predictable Latency Mode; and operating the storage controller and the NVM set in the deterministic state by allocating predetermined resources to execute the command and return data with a predictable latency.

A storage device includes non-volatile memory, a storage controller including a first controller processor connected to the non-volatile memory, and a second controller processor connected to the non-volatile memory, and shared memory to store a mapping table. The shared memory may be connected to the first controller processor and the second controller processor to share mapping table information between the first controller processor and the second controller processor. The storage controller may set a power mode of the first controller processor and the second controller processor based on an input/output intensity.

An operating method for a memory, a memory, and a memory system are provided in the present application. The memory includes at least a plurality of word lines and a plurality of strings, and the plurality of word lines include a target word line, and each word line is coupled to a plurality of strings. Each string includes a plurality of memory cells. In accordance with the operating method provided by the present application, the first verification and the second verification are performed on a plurality of target memory cells with first and second verify voltages during performing a first programming operation on a plurality of target memory cells in target string coupled to the target word line, and the second start program voltage is determined based on at least the second verification result, ensuring the accuracy of the second start program voltage.

A system and method employing a distributed hardware architecture, either independently or in cooperation with an attendant data structure, in connection with various data processing strategies and data analytics implementations are disclosed. A compute node may be implemented independent of a host compute system to manage and to execute data processing operations. Additionally, an unique algorithm architecture and processing system and method are also disclosed. Different types of nodes may be implemented, either independently or in cooperation with an attendant data structure, in connection with various data processing strategies and data analytics implementations.