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公开(公告)号：US20200278795A1
公开(公告)日：2020-09-03
申请号：US16750655
申请日：2020-01-23
Inventor： Haikun Liu , Xiaofei Liao , Hai Jin , Yuanyuan Ye
Abstract: The present disclosure involves a hard-ware-supported 3D-stacked NVM data compression method and system, involving setting a first identifier to mark a compression state of written-back data, the method at least comprising steps of: dividing the written-back data into a plurality of sub-blocks and acquiring a plurality of first output results through OR operations among the sub-blocks, respectively, or acquiring a plurality of second output results through exclusive OR operations among the sub-blocks, and determining a compression strategy for the written-back data based on the first output results or the second output results; and setting a second identifier to mark a storing means of the written-back data so that the second identifier is in pair with the first identifier, and configuring a storage strategy for the written-back data that includes at least rotating the second identifier.
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公开(公告)号：US10749880B2
公开(公告)日：2020-08-18
申请号：US16109846
申请日：2018-08-23
Inventor： Hai Jin , Weiqi Dai , Yan Xia , Deqing Zou
Abstract: The present invention involves with a cloud tenant oriented method and system for protecting privacy data. The method comprises at least the following steps: analyzing event handler information and/or behavioral signature information of request information and determining an execution mode, selecting at least one node without a behavioral signature plot to execute the tenant request and recording an execution result, generating a behavioral signature plot based on the execution result, and dynamically detecting security-sensitive behavior based on the behavioral signature plot. The present invention ensures data security during processing of security-sensitive data for cloud services by adopting a technology based on behavioral signatures, and prevents attackers from exploiting vulnerabilities and bypassing security control to conduct malicious operations.
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公开(公告)号：US10719370B2
公开(公告)日：2020-07-21
申请号：US16180460
申请日：2018-11-05
Abstract: The present invention involves with a dynamic distributed processing method for stream data, at least comprising: analyzing and predicting an execution mode of at least one data feature block of the data of a user stream data processing program; dynamically adjusting the execution mode based on an average magnitude of queue latency and a threshold of queue latency of the stream data; and processing corresponding said at least one data feature block based on the execution mode. By associating and combining the irrelevant data stream mode and micro-batch mode of stream data computing, the present invention successfully releases automatic shift and data process between the two modes, which advantageously has both the high throughput property and the low latency property.
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公开(公告)号：US20190294643A1
公开(公告)日：2019-09-26
申请号：US16284611
申请日：2019-02-25
Inventor： Xuanhua Shi , Hai Jin , Wenke Li , Ying Yang , Wei Liu
IPC: G06F16/953 , G06F9/50 , G06F16/901
Abstract: A GPU-based system for optimizing rich metadata management and a method thereof are disclosed. The system includes: a search engine for converting rich metadata information into traversal information and/or search information of a property graph, and providing at least one API according to a traversal process and/or a search process; a mapping module for detecting relationships among entity nodes in the property graph by means of mapping; a management module for activating a GPU thread group and allotting video memory blocks, so as to store the property graph in a GPU as a mixed graph; and a traversal module for activating a traversal program and performing detection and gathering on stored property arrays for iteration, so as to feed back a result of the iteration to the search engine. The system and the method are efficient in rich metadata search while having good scalability and compatibility.
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25.发明授权公开(公告)号：US12287719B2
公开(公告)日：2025-04-29
申请号：US17247237
申请日：2020-12-04
Inventor： Jiang Xiao , Huichuwu Li , Minrui Wu , Hai Jin
Abstract: The present invention relates to an activity recognition system balanced between versatility and individuation, comprising a communication framework jointly formed by a data collecting terminal, a computing device, and a cloud computing platform, the activity recognition system uses the communication framework to conduct personnel activity recognition and model updating, and the edge computing device further comprises a model training module and an activity recognition module, and the model training module retrieves a local activity recognition model by continuously verifying user IDs, and uses the first data to train a versatile network structure and an individualized network structure of the local activity recognition model in a way that individuation features of the user and versatility features of the model are fused with each other, so that the personnel activity recognition process conducted by the activity recognition module.
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Patent Agency Ranking
公开(公告)号：US12242877B2
公开(公告)日：2025-03-04
申请号：US17661991
申请日：2022-05-04
Inventor： Song Wu , Hang Huang , Kun Wang , Honglei Wang , Hai Jin
Abstract: The present invention relates to a container-oriented Linux kernel virtualizing system, at least comprising: a virtual kernel constructing module, being configured to provide a virtual kernel customization template for a user to edit and customize a virtual kernel of a container, and generate the virtual kernel taking a form of a loadable kernel module based on the edited virtual kernel customization template; and a virtual kernel instance module, being configured to reconstruct and isolate a Linux kernel, and operate a virtual kernel instance in a separate address space in response to a kernel request from a corresponding container. The container-oriented Linux kernel virtualizing system of the present invention is based on the use of a loadable module.
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公开(公告)号：US12189950B2
公开(公告)日：2025-01-07
申请号：US18145552
申请日：2022-12-22
Inventor： Long Zheng , Qinggang Wang , Xiaofei Liao , Zhaozeng An , Hai Jin
IPC: G06F3/06
Abstract: The present invention relates to a dynamic memory management apparatus and method for HLS, the apparatus has several searching and caching modules and several modifying and writing-back modules, the searching and caching modules are in connection with a DRAM storing module and a BRAM buffer, respectively, and the modifying and writing-back modules are in connection with the DRAM storing module and the BRAM buffer, respectively, the BRAM buffer is for caching information about nodes on a search path and registering information about modification made to the nodes. To remedy the defect that the traditional operating system is directly transplanted to the FPGA and has low execution efficiency, the present invention utilizes the advantage of the large capacity of the DRAM on the FPGA to realize efficient dynamic memory allocation and deallocation, and improve the usability and code reusability of HLS.
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公开(公告)号：US11792105B2
公开(公告)日：2023-10-17
申请号：US17249838
申请日：2021-03-16
Inventor： Jiang Xiao , Shijie Zhang , Jiajie Zeng , Hai Jin , Chen Yu
IPC: H04L45/02 , H04L45/12 , H04L45/48 , H04L45/74 , G06F18/243
CPC classification number: H04L45/02 , G06F18/24323 , H04L45/123 , H04L45/48 , H04L45/74
Abstract: The present invention relates to a method of building a dynamic overlay network topology based on cross-chain interaction between blockchains, at least comprising: selecting at least one gateway node and at least one ordinary node from at least one cross-chain interaction node; clustering the ordinary nodes into ordinary node clusters based on a clustering algorithm; building a structured network topology and cross-chain connections between the cross-chain interaction nodes based on the gateway node; performing topology building on the ordinary node clusters based on a breadth-first spanning tree algorithm.
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公开(公告)号：US11714836B2
公开(公告)日：2023-08-01
申请号：US17455502
申请日：2021-11-18
Inventor： Jiang Xiao , Jian Chang , Rui Han , Xiaohai Dai , Hai Jin
IPC: G06F16/2457 , G06F16/248 , G06F16/28 , G06Q20/38
CPC classification number: G06F16/288 , G06F16/248 , G06F16/24575 , G06F16/285 , G06Q20/3823 , G06Q20/3827
Abstract: The present invention relates a method for high-performance traceability query oriented to multi-chain data association, comprising: identifying a target transaction needing the traceability query; searching out all corresponding target chains based on cross-chain transaction data association; making query requests parallelly; and executing the query among the target chains according to a key value of the target transaction and returning query results. The blockchain traceability query method proposed by the present invention is different from serialized block data query conducted in the chain-type structure, and the disclosed cross-chain query operation can be parallelly executed, leading to improved efficiency of traceability query. Opposite to the conventional blockchain where blocks are used as nodes of chains, the present invention directly uses sub blockchains as nodes of the SRB. Since sub blockchains can be dynamically added or removed, the present invention enhances the scalability of the entire system.
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公开(公告)号：US11609787B2
公开(公告)日：2023-03-21
申请号：US16947055
申请日：2020-07-16
Inventor： Xiaofei Liao , Yicheng Chen , Yu Zhang , Hai Jin , Jin Zhao , Xiang Zhao , Beibei Si
Abstract: The present disclosure relates to an FPGA-based dynamic graph processing method, comprising: where graph mirrors of a dynamic graph that have successive timestamps define an increment therebetween, a pre-processing module dividing the graph mirror having the latter timestamp into at least one path unit in a manner that incremental computing for any vertex only depends on a preorder vertex of that vertex; an FPGA processing module storing at least two said path units into an on-chip memory directly linked to threads in a manner that every thread unit is able to process the path unit independently; the thread unit determining an increment value between the successive timestamps of the preorder vertex while updating a state value of the preorder vertex, and transferring the increment value to a succeeding vertex adjacent to the preorder vertex in a transfer direction determined by the path unit, so as to update the state value of the succeeding vertex.
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