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    DATA STORING SYSTEMS, DATA STORING METHODS, AND ELECTRONIC DEVICES
    2.
    发明公开
    DATA STORING SYSTEMS, DATA STORING METHODS, AND ELECTRONIC DEVICES 审中-公开

    公开(公告)号：US20240311300A1

    公开(公告)日：2024-09-19

    申请号：US18470346

    申请日：2023-09-19

    Applicant: ZHEJIANG LAB ,  Huazhong University of Science and Technology

    Inventor： Zhan ZHANG ,  Yu ZHANG ,  Jin ZHAO ,  Haifei WU

    IPC: G06F12/0804

    CPC classification number: G06F12/0804 ,  G06F2212/1032

    Abstract: The present disclosure provides a data storage system, including data cache module, data processing module, and a persistent memory. The data cache module includes an on-chip mapping data cache and an on-chip counter cache, where the mapping data cache is configured to cache mapping data, and when the free space of the mapping data cache is less than a preset threshold, the least recently used mapping data cache line will be evicted from the cache and written back to the persistent memory. The data processing module encrypts/decrypts persistent memory data by using their counters, and accesses the persistent memory blocks indicated by their corresponding mapping data. The persistent memory comprises the first and second storage regions for the latest checkpoint data and modified working data in the current checkpoint interval respectively.

    GRAPH DATA PROCESSING
    4.
    发明公开
    GRAPH DATA PROCESSING 审中-公开

    公开(公告)号：US20240303277A1

    公开(公告)日：2024-09-12

    申请号：US18396493

    申请日：2023-12-26

    Applicant: ZHEJIANG LAB ,  Huazhong University of Science and Technology

    Inventor： Yu ZHANG ,  Hao QI ,  Kang LUO ,  Jin ZHAO ,  Zhan ZHANG

    IPC: G06F16/901

    CPC classification number: G06F16/9024

    Abstract: Systems, methods, devices and storage media for graph data processing are provided. In one aspect, a graph data processing system includes a memory and a plurality of processing units, and each processing unit is provided with a decision module. Each processing unit is configured to determine set operations required for extracting one or more subgraphs matching a specified graph pattern from target graph data according to a preset graph pattern matching algorithm. Then, for each set operation, the decision module is configured to determine a cost value corresponding to a performance of the processing unit occupied to execute the set operation in accordance with different execution policies, and further select a target execution policy with a smallest cost value to execute the set operation.

    ENERGY-EFFICIENT HARDWARE-SOFTWARE COLLABORATIVE METHOD AND APPARATUS FOR GRAPH PROCESSING
    5.
    发明公开
    ENERGY-EFFICIENT HARDWARE-SOFTWARE COLLABORATIVE METHOD AND APPARATUS FOR GRAPH PROCESSING 审中-公开

    公开(公告)号：US20230367815A1

    公开(公告)日：2023-11-16

    申请号：US17945792

    申请日：2022-09-15

    Applicant: Huazhong University Of Science And Technology

    Inventor： Yu ZHANG ,  Jin ZHAO ,  Qiange SHEN ,  Xinyu JIANG ,  Hui YU ,  Hao QI ,  Yun YANG ,  Shijun LI ,  Xiaofei LIAO ,  Hai JIN

    IPC: G06F16/901

    CPC classification number: G06F16/9024

    Abstract: The present invention relates to energy-efficient collaborative method and apparatus for graph processing, wherein the apparatus comprises at least: a dependency path prefetching unit for receiving active vertex information and prefetching an edge of graph partition along a dependency path, starting with an active vertex in a circular queue; and a direct dependency managing unit for converting dependency relationship between head and tail vertices of a core dependency path into direct dependency and managing it in a cache, and updating dependency indexes according to dynamic changes in graph structure during dynamic graph processing, so as to ensure accurate results of graph processing. The accelerator of the present invention is capable of being integrated into a multi-core processor, thereby processing multiple paths on multiple processor kernels with high concurrency, and in turn accelerating dissemination of vertex states in a graph to speed convergence during graph processing.

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