Offloading computation based on extended instruction set architecture

    公开(公告)号:US12210877B2

    公开(公告)日:2025-01-28

    申请号:US18118367

    申请日:2023-03-07

    Abstract: The present disclosure describes techniques for offloading computation based on an extended instruction set architecture (ISA). The extended ISA may be created based on identifying functions executed multiple times by a central processing unit (CPU). The extended ISA may comprise hashes corresponding to the functions and identifiers of extended operations associated with the functions. The extended operations may be converted from original operations of the functions. The extended operations may be executable by a storage device. The storage device may be associated with at least one computational core. Code may be synthesized based at least in part on the extended ISA. Computation of the synthesized code may be offloaded into the storage device.

    Offloading data processing and knowledge synthesis

    公开(公告)号:US12164920B2

    公开(公告)日:2024-12-10

    申请号:US17984191

    申请日:2022-11-09

    Abstract: The present disclosure describes techniques for offloading data processing and knowledge synthesis. A set of flags may indicate information about the memory pages in a first memory and may be manageable by at least one central processing unit (CPU). A memory page may be flushed to a second memory if the memory page is associated with a first flag. The first flag may indicate that the memory page is ready to be flushed to the second memory. The second memory may be configured to store a sequence of states of each of the memory pages. Data patterns and relations among the data patterns may be determined by data processing units (DPUs) based on the sequence of states of each of the memory pages. A knowledge base may be built in a third memory based on the data patterns and the relations among the data patterns.

    COMPUTING APPARATUS AND METHOD, ELECTRONIC DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20240345806A1

    公开(公告)日:2024-10-17

    申请号:US18630753

    申请日:2024-04-09

    CPC classification number: G06F7/5443 G06F7/4876

    Abstract: A computing apparatus and method, an electronic device and a storage medium are provided. The computing apparatus includes: a preprocessing module configured to receive N pairs of input parameters, and perform format conversion on each pair of input parameters according to the precision type of the N pairs of input parameters, and obtain N pairs of processed input parameters; and a calculation module configured to respectively compute a product of exponents and mantissas of each pair of processed input parameters, and obtain an output result based on the product of exponents and mantissas of each pair of processed input parameters. The computing apparatus supports multiply-accumulate computation of a plurality of floating-point types. The computing apparatus can multiplex the multiplication computation of the mantissa and make the computing apparatus support multiply-accumulate computations in a plurality of precision formats at the cost of lower area and power consumption.

    APPLICATION-DEFINED STORAGE ARCHITECTURE FOR OFFLOADING COMPUTATION

    公开(公告)号:US20230176921A1

    公开(公告)日:2023-06-08

    申请号:US18104947

    申请日:2023-02-02

    CPC classification number: G06F9/5061 G06F2209/509 G06F2209/5018

    Abstract: The present disclosure describes techniques for offloading computation into a storage space. A plurality of streams may be created in a storage device in response to receiving information of defining the plurality of streams from an application. Each of the plurality of streams may be configured to contain a sequence of objects of a same type among a plurality of types of objects. The plurality of types of objects may be associated with one or more applications. Each of the plurality of streams may comprise a thread descriptor indicative of at least one algorithm to be applied to the sequence of objects. Data may be added to the plurality of streams. Computation associated with the plurality of streams may be offloaded into the storage device. The storage device may be associated with at least one computational core.

    DATA CONVERSION METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20240378022A1

    公开(公告)日:2024-11-14

    申请号:US18654380

    申请日:2024-05-03

    Abstract: A data conversion method and apparatus, an electronic device and a storage medium for converting dimensions of a first data combination. The data conversion method includes: reading n elements in the first data combination according to a first-dimension direction to obtain a first processing group, a first element to an n-th element in the first processing group are arranged according to the first-dimension direction, and n is a positive integer; performing a transpose on the first dimension and the third dimension of the first processing group to obtain a second processing group, a first element to an n-th element in the second processing group are arranged in a third-dimension direction; and writing the first element to the n-th element in the second processing group to a first storage.

    ACCELERATING DATA PROCESSING BY OFFLOADING THREAD COMPUTATION

    公开(公告)号:US20240095076A1

    公开(公告)日:2024-03-21

    申请号:US17945843

    申请日:2022-09-15

    CPC classification number: G06F9/5027 G06F9/4843

    Abstract: The present disclosure describes techniques for accelerating data processing by offloading thread computation. An application may be started based on creating and executing a process by a host, the process associated with a plurality of threads. Creating a plurality of computation threads on a storage device may be requested based on determining that the storage device represents a computational storage. The plurality of computation threads may be created based on preloading a plurality of libraries in the storage device. The plurality of libraries may comprise executable codes associated with the plurality of threads. Data processing associated with the plurality of threads may be offloaded to the storage device using the plurality of computation threads. Activities associated with the plurality of computation threads may be managed by the process.

    DATA STORAGE BASED ON GEOGRAPHIC LOCATION
    8.
    发明公开

    公开(公告)号:US20240037080A1

    公开(公告)日:2024-02-01

    申请号:US17877644

    申请日:2022-07-29

    CPC classification number: G06F16/2228 G06F16/29 G06F16/248

    Abstract: A first combined key may be generated based on a geographic location, a first time, and a first user that are associated with a first event. The first combined key and first data indicating the first event may be stored in a database, the first combined key configured to identify the first data. A second combined key may be generated based on the geographic location, a second time, and a second user that are associated with a second event. The second combined key and second data indicating the second event may be stored in the database, the second combined key configured to identify the second data. A set of events associated with the geographic location and comprising the first event and the second event may be presented by retrieving the first data and the second data using the first combined key and the second combined key, respectively.

    OFFLOADING KNOWLEDGE BASE CREATION
    10.
    发明公开

    公开(公告)号:US20230281476A1

    公开(公告)日:2023-09-07

    申请号:US18098611

    申请日:2023-01-18

    CPC classification number: G06N5/022 G06N5/041

    Abstract: The present disclosure describes techniques for offloading knowledge base creation into a storage space. A sequence of patterns in a data stream may be identified based on a time dimension of the data stream by data processing units (DPUs) without an initiation from a Central Processing Unit (CPU). The DPUs may be associated with the storage space. The DPUs may recognize a plurality of information contexts corresponding to the sequence of patterns based on analyzing neighboring patterns of any particular pattern in the sequence of patterns. The DPUs may determine causal relations among the sequence of patterns based on detecting repetitions of any pair of information contexts among the plurality of information contexts. The causal relations may comprise a plurality of reason-consequence pairs. Knowledge of causal relationships associated with the data stream may be used to predict future states of the data stream.

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