Samsung Electronics Co., Ltd.

Praveen Krishnamoorthy

Changho Choi

Jianjian Huo

Hingkwan Huen

Derrick Tseng

Yang Seok Ki

Andrew Zhenwen Chang

Hui Zhang

Joo Hwan Lee

Armin Haj Aboutalebi

Sompong Paul Olarig

Ramdas P Kachare

Ramzi Ammari

Xiaodong Zhao

Manali Sharma

Sahand Salamat

Chandranil Chakraborttii

Mukesh Garg

Yiqun Zhang

An interface for enabling a computer device to utilize data property-based data placement inside a nonvolatile memory device comprises: executing a software component at an operating system level in the computer device that monitors update statistics of all data item modifications into the nonvolatile memory device, including one or more of update frequencies for each data item, accumulated update and delete frequencies specific to each file type, and an origin of the data item; storing the update statistics of each of the data items and each of the data item types in a database; and intercepting all operations, including create, write, and update, of performed by applications to all the data items, and automatically assigning a data property identifier to each of the data items based on current update statistics in the database, such that the data items and assigned data property identifiers are transmitted over a memory channel.

Heuristic interface for enabling a computer device to utilize data property-based data placement inside a nonvolatile memory device

A method includes receiving, at a hardware circuit of a device, a target value corresponding to a target data. The method further includes outputting, from the hardware circuit, a first indicator that source data corresponds to the target value. The method further includes, based on the first indicator, outputting, from software executing at the device, a result indicator that the source data corresponds to the target data.

Systems and methods for data comparison

A storage device may include storage for data. A host interface may receive a write request from a host at the storage device. The write request may include a data chunk and a data identifier (ID). A class ID determiner circuitry may determine a class ID for the data chunk. A mapping table may map the data ID to the class ID.

Dynamic quantization in storage devices using machine learning

An interface for enabling a computer device to utilize data property-based data placement inside a nonvolatile memory device comprises: executing a software component at an operating system level in the computer device that monitors update statistics of all data item modifications into the nonvolatile memory device, including one or more of update frequencies for each data item, accumulated update and delete frequencies specific to each file type, and an origin of the data item; storing the update statistics of each of the data items and each of the data item types in a database; and intercepting all operations, including create, write, and update, of performed by applications to all the data items, and automatically assigning a data property identifier to each of the data items based on current update statistics in the database, such that the data items and assigned data property identifiers are transmitted over a memory channel to the non-volatile memory device.

An accelerator is disclosed. The accelerator may include a memory that may store a dictionary table. An address generator may be configured to generate an address in the dictionary table based on an encoded value, which may have an encoded width. An output filter may be configured to filter a decoded value from the dictionary table based on the encoded value, the encoded width, and a decoded width of the decoded data. The accelerator may be configured to support at least two different encoded widths.

Near-storage acceleration of dictionary decoding

A method of processing data in a system having a host and a storage node may include performing a shuffle operation on data stored at the storage node, wherein the shuffle operation may include performing a shuffle write operation, and performing a shuffle read operation, wherein at least a portion of the shuffle operation is performed by an accelerator at the storage node. A method for partitioning data may include sampling, at a device, data from one or more partitions based on a number of samples, transferring the sampled data from the device to a host, determining, at the host, one or more splitters based on the sampled data, communicating the one or more splitters from the host to the device, and partitioning, at the device, data for the one or more partitions based on the one or more splitters.

Systems, methods, and devices for storage shuffle acceleration

Example embodiments are described for data property-based data placement inside a nonvolatile memory device performed by a storage controller of the nonvolatile memory device. In one aspect, the embodiments include: executing a software component on the computer device that detects at least one of an executing application and a hardware device connecting to the computing device; responsive to detecting the at least one executing application and the hardware device, searching, by the software component, a workflow repository to find a predetermined workflow associated with the at least one executing application and the hardware device, wherein the predetermined workflow associates predefined data property identifiers to different types of data items written to the nonvolatile memory device by the executing application or the hardware device; comparing, by the software component, activities of the at least one executing application and the hardware device to the predetermined workflow; and using the predetermined workflow to automatically assign the data property identifiers to the data items used by the application or the hardware device, such that the data items and assigned data property identifiers are transmitted over a channel to the nonvolatile memory device for storage wherein the nonvolatile memory device reads the data property identifiers and identifies which blocks of the nonvolatile memory device to store the corresponding data items, such that the data items having the same data property identifiers are stored in a same block.

Data property-based data placement in a nonvolatile memory device

A programmable data storage device configured to process images via an embedded processor is disclosed. The processor identifies luminance and chrominance data of a received image, and retrieves a first machine learning model stored in the storage device. The first model is applied for making a first prediction about the image based on luminance data, and a first determination is made in regards to a criterion. In response to making the first determination, a first label associated with the first prediction is returned. A second determination is also made in regards to the criterion. In response to making the second determination, a second machine learning model stored in the storage device is retrieved. The second machine learning model is applied for making a second prediction about the image based on the color data associated with the image, and a second label associated with the second prediction is determined.

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Sunnyvale, CA, United States of America

Praveen Krishnamoorthy