Systems and methods are disclosed including a memory device and a processing device, operatively coupled with the memory device, to perform operations comprising: receiving a write data request to store write data to the memory device; determining a physical block address associated with the write data request; performing a bitwise operation on each bit of the physical block address to generate a seed value; generating an output sequence based on the seed value; performing another bitwise operation on the output sequence and the write data to generate a randomized sequence; and storing, on the memory device, the randomized sequence.

A solid state drive (SSD) device includes a first nonvolatile memory package, a second nonvolatile memory package, and a controller. The first nonvolatile memory package includes a first buffer chip and a plurality of first nonvolatile memory chips. The second nonvolatile memory package includes a plurality of second nonvolatile memory chips. The controller controls the first nonvolatile memory package and the second nonvolatile memory package. The first buffer chip communicates a first address signal and a first data with the controller, and selectively communicates the first data with one of the plurality of first nonvolatile memory chips and the plurality of second nonvolatile memory chips based on the first address signal.

A system for communicating over a Controller Area Network (CAN) bus may include a central controller and a plurality of smart devices communicatively coupled with the central controller over the CAN bus and over an identification verification network separate from the CAN bus. Each smart device may be configured to at least one of measure various parameters and control a function based on a command received from the central controller, and then communicate one or more signals indicative of at least one of the measured parameters and the function over the CAN bus to the central controller. Each of the smart devices may include a physical input, a physical output, and at least two nonvolatile memory locations. A first of the at least two memory locations may be configured to store an identifier input signal received at the physical input from at least one of the central controller and an upstream smart device over the identification verification network, the identifier input signal being stored by the smart device as a function instance value for the smart device. The smart device may further include a source address determination module configured to determine a source address for the smart device based on the function instance value and a factory default base address for the smart device, and store the source address in a second of the at least two memory locations.

A storage device includes a memory and a controller. The controller controls the memory such that, in response to a request for a first read operation on the memory while a first write operation is performed on the memory, the first write operation is suspended, and the first read operation is performed, the suspended first write operation is resumed after the first read operation is completed, and second write operation subsequent to the first write operation is performed on the memory after the resumed first write operation is completed. The controller throttles an amount of data communicated to the memory device for the second write operation or for a second read operation subsequent to the first read operation, based on a frequency that the first write operation is suspended.

Described are a system, method, and computer program product for generating a data storage server distribution pattern. The method includes determining a set of servers and raw data to be stored. The method also includes transforming the raw data according to an error-correcting code scheme to produce distributable data. The method further includes determining a server reliability of each server in the set of servers. The method further includes generating the data storage server distribution pattern based on maximizing a system reliability relative to maximizing a system entropy. System reliability may be based on a minimum reliability of the set of servers, and system entropy may be based on a cumulated information entropy of each server of the set of servers. The method further includes distributing the distributable data to be stored across at least two servers of the set of servers according to the data storage server distribution pattern.

Systems and methods for allocating memory and redirecting data writes based on temperature of memory modules in a cloud computing system are described. A method includes maintaining temperature profiles for a first plurality of memory modules and a second plurality of memory modules, The method includes automatically redirecting a first request to write to memory from a first compute entity being executed by the first processor to a selected one of a first plurality of memory chips, whose temperature does not meet or exceed the temperature threshold, included in at least the first plurality of memory modules and automatically redirecting a second request to write to memory from a second compute entity being executed by the second processor to a selected one of the second plurality of memory chips, whose temperature does not meet or exceed the temperature threshold, included in at least the second plurality of memory modules.

A storage device includes a storage device communicably connected to a host; a nonvolatile memory configured to store calibration data of the host; and a calibration circuit configured to receive a descriptor from the host including the setting information and update the calibration data with the received setting information.

A container storage system that provides storage services to a container system provides data resiliency using storage pools based on: detecting an interruption to storage services associated with a first storage pool that includes a first plurality of storage resources on which a first set of replicas of a dataset is distributed; selecting, in response to the interruption, a second storage pool that includes a second plurality of storage resources; and generating, based on one or more replicas within the first set of replicas, a second set of replicas of the dataset distributed among the second plurality of storage resources in the second storage pool.

According to one embodiment, a memory system includes nonvolatile memory including a plurality of memory areas and a memory controller. A read operation includes a first operation of reading data from a memory cell array and a second operation of transmitting at least a part of the read data to the memory controller. The memory controller determines, when executing the read operation in a first memory area and a second memory area in parallel, priorities of the second operation in the first memory area and the second operation in the second memory area based on a result of comparison between (A) a first total time period of the read operation in the first memory area and (B) a second total time of the read operation in the second memory area.

The invention discloses an aggregation optimized processing method for time-series data, characterized by comprising the following steps: writing a time-series data record into a database, forming a time-series database file, wherein the time-series database file comprises a data file and an index file, the data file comprises multiple data blocks, the index file comprises index blocks, and each index block correspond to one data block; by scanning an index file according to a start time period and a stop time period, extracting all index blocks of the time series that need to be aggregated that meet the time period conditions, and then sorting the index blocks according to the data block offset recorded in the index block; and by scanning the data file according to a data block offset order recorded in sorted index blocks, performing specified reading and calculating on each data block, and aggregating calculation results. According to the method, the reading of a single time series data or the aggregation operation of multiple time-series data can be completed by only opening a data file once for scanning such that the overall performance is greatly improved.