36results about How to "Relieve memory pressure" patented technology

The invention discloses a system for settling fierce competition of memory resources in a big data processing system. A memory information feedback module is used for monitoring the memory using condition for a running thread task, converting collected memory information and then feeding back the converted memory information to an information sampling and analyzing module; the information sampling and analyzing module is used for dynamically controlling the number of sampling times of information of all working nodes, analyzing data after the assigned number of sampling times is achieved, and calculating the optimal CPU to memory proportion of the current working node; a decision making and task distributing module is used for making a decision and controlling whether new tasks are distributed to the working nodes for calculation operation according to the information obtained through analysis and the task running information of the current working node to achieve effective limit on the CPU and memory use relation. By means of the system, a memory-perceptive task distribution mechanism can be achieved on a universal big data platform, the I / O expenditure generated when data overflows to a disc due to fierce competition of memory resources can be reduced, and the integral performance of the system can be effectively improved.

The invention provides an analysis system and method for power equipment monitoring data. The analysis system comprises a cabinet, an outer server, an outer management analysis platform, and one or more power transformation equipment measuring point sensors, and further comprises a lower calculation storage server, a power supply module and a kilomega management network module, a 10-GB optical fiber network module, an upper calculation storage server and a high-performance calculation storage server, wherein the outer management analysis platform comprises a big data analysis platform and a power application analysis module; the high-performance calculation storage server comprises one graph processing unit GPU; the graph processing unit GPU is connected through a single power supply so that independent power supply is realized; and the equipment has high integrity, high availability and good expandability, and the system has stable performances and is simple and convenient to operate.

The invention relates to the technical field of data packet recombination, and provides a file restoration method and device for http multi-session in a DPI scene. The method comprises the following steps: acquiring Ack values in Response response messages of a plurality of Get requests; matching out one or more Response response messages of which the Ack values are the same as the summation result of the serial number field value seq0 and the load length dlen carried in the target Get request; wherein the Ack values are carried in the Response response messages respectively; and restoring a response file of the target Get request according to the serial number field value seq1 carried in each Response response message. According to the invention, a plurality of http sessions in the TCP session can be processed in real time, disorder or retransmission interference among different http sessions is eliminated, and the restoration efficiency is improved.

The invention relates to the technical field of grid processing, and discloses a distributed unstructured grid cross-processor-plane butt joint method and system.The butt joint method comprises the steps that a two-stage index structure is adopted for recognizing the butt joint relation of the two sides of a grid partition boundary in a parallel mode; and carrying out equivalence judgment on the centroid coordinates of any two butt joint surface elements and the normalized grid point sequence in sequence. Comprising the following steps: S1, importing basic geometric data of a distributed unstructured grid in parallel; s2, constructing a dual communication list among the sub-regions in a cross-processor manner; s3, constructing a curved surface grid discrete structure at the butt joint boundary in parallel; s4, constructing a fork tree structure of the query set family on each processor; s5, querying a pairing relationship between the docking surface elements in a cross-processor manner; and S6, exporting the butt joint information of the distributed unstructured grid in parallel. According to the method, the problems of low processing efficiency, poor data processing capability and the like during large-scale unstructured grid processing in the prior art are solved.

The invention discloses a real-time virtual machine memory scheduling method and device. The memory scheduling method comprises the steps that when the memory resource of a mainframe exceeds the preset threshold value, the memory resource of the mainframe is determined to be in a stressed state; when the memory resource of the mainframe is in a stressed state, the memory usage rate of a virtual machine is queried; the spatial memory punishment coefficient is introduced, the size of the released memory is calculated; the memory of the virtual machine is reallocated according to the calculated size of the released memory. According to the memory scheduling method, the optimization of memory allocation is achieved, and wastes of memory resources are avoided.

The invention provides a method and system for achieving a remote control function, a server and a remote control terminal. The method for achieving the remote control function comprises the steps that when remote control code requesting information including controlled product data and function data is received, the remote control code requesting information is compared with controlled product data and function data in stored remote control instruction information, and remote control instruction information matched with the remote control code requesting information is determined; instruction code data in the matched remote control instruction information is sent. By means of the scheme, the instruction code data corresponding to the corresponding function of a controlled product can be sent according to the demand of a user instead of directly releasing all instruction codes related to the controlled product to the user remote control terminal. On the premise that the demand of the user is met, the storage space of the remote control terminal is occupied as little as possible; besides, the remote control terminal only needs to process instruction code data related to the demand of the user when processing the instruction code, and the processing efficiency can be effectively improved.

The invention provides a live broadcast room admission flow data processing method and device, equipment and a storage medium, and the method comprises the steps: filtering the data of a full live broadcast room in timing synchronization, and obtaining the admission flow data of an effective live broadcast room; storing the admission flow data based on a preset survival time length and Redis, andperforming real-time updating; determining whether an ordered queue sorted according to a time window exists in an effective live broadcast room corresponding to the admission flow data or not; if so,obtaining the current latest admission flow data, placing the current latest admission flow data at the head of the ordered queue, and updating the ordered queue in real time; and if not, obtaining the current latest admission flow data, and generating an ordered queue according to the descending order of the survival duration. The data of the full live broadcast room is filtered to obtain the admission flow data of the effective live broadcast room, the ordered queue corresponding to the effective live broadcast room is stored and updated by utilizing Redis, the memory pressure caused by massive admission flow data is relieved, and the real-time processing of the admission flow data is ensured.

The invention discloses a distributed high-concurrency transaction processing method and system for a block chain, equipment and a storage medium, wherein the method comprises the steps: distributing a user request to a plurality of processing servers through employing a multi-stage load balancing and multi-stage caching mechanism, can accelerate the response speed of the user request and improves the throughput, and the situation that the processing server crashes due to sudden increase of the user request is prevented. Besides, the distributed and parallel processing is carried out on the mass data through the high-concurrency pool cluster, so that the scheduling pressure can be reduced, the large-scale scheduling problem is effectively solved, the memory pressure is relieved, and the resource utilization efficiency is improved. Finally, the data processed by the high-concurrency pool cluster is published through the distributed message system, so that persistence of the message can be realized, batch processing of the data is facilitated, and the data is written into the corresponding block chain in parallel at a high speed through the plurality of cache clusters.

The invention provides a frame animation caching method, apparatus and equipment, and a computer readable storage medium. The frame animation caching method includes the steps: acquiring the first n frames of images in a frame animation, and loading the first n frames of images into a preset bitmap cache; and successively acquiring other frames of images in the frame animation, and successively loading the other frames of images into the bitmap cache so as to replace the images which have been loaded into the bitmap cache. The frame animation caching method, apparatus and equipment can alleviate the memory pressure of the frame animation, and can avoid the problem of overflow of memory when the frame animation is carried out.

The invention provides a big data integrated machine based on electric power application. The big data integrated machine comprises a cabinet, an external server and one or more transformation equipment measuring point sensors and further comprises one or more lower calculation storage servers arranged at the lower part of the cabinet, a power module, a gigabit management network module, a 10-gigabit optical fiber data network module, one or more upper calculation storage servers, one or more high-performance calculation storage servers, fans and a fan controller, wherein the power module and the gigabit management network module are arranged in the middle of the cabinet; the 10-gigabit optical fiber data network module, the upper calculation storage servers and the high-performance calculation storage servers are arranged at the upper part of the cabinet from top to bottom in sequence; the fans and the fan controller are arranged on the back of the cabinet. The big data integrated machine is high in integration level, high in equipment usability, good in expansibility and stable in system performance.

The invention relates to the technical field of grid processing, and discloses a distributed unstructured grid cross-processor face docking method and system. The docking method uses a two-level index structure to parallelize and identify faces on both sides of the grid partition boundary. Connection relationship; for any two docking surface elements, perform equivalence judgment on their centroid coordinates and normalized grid point sequence in turn. It includes the following steps: S1, parallel import of distributed unstructured grid basic geometric data; S2, cross-processor construction of dual communication lists between sub-regions; S3, parallel construction of surface grid discrete structures at docking boundaries; S4, in Each processor constructs the fork tree structure of query set family; S5, cross-processor query pairing relationship between docking surface elements; S6, parallel export of face docking information of distributed unstructured grid. The invention solves the problems of low processing efficiency, poor data processing capability and the like in the prior art when processing large-scale unstructured grids.

The present invention provides a method, device, equipment and storage medium for processing data of entry stream data in a live broadcast room, which can filter the data of a full amount of live broadcast room synchronized with timing, and obtain the entry stream data of an effective live broadcast room; based on the preset survival time and Redis storage field flow data, and update it in real time; determine whether there is an orderly queue sorted according to the time window in the effective live broadcast room corresponding to the entry flow data; Place it at the head of the ordered queue, and update the ordered queue in real time; if it does not exist, obtain the latest current entry flow data, and generate an ordered queue according to the survival time from large to small. Filter the data of all live broadcast rooms, obtain the entry flow data of effective live broadcast rooms and use Redis to store them, update the orderly queues corresponding to effective live broadcast rooms, relieve the memory pressure caused by massive entry flow data, and ensure real-time processing of entry flow data .

The invention discloses a GPU-based high-performance graph mining method and system. The method comprises the steps: employing a GPU & CPU cooperative computing architecture, carrying out the graph mining operation through multiple threads of a GPU, improving the search efficiency, and storing a large number of intermediate sub-graphs generated in a graph mining process through a CPU memory; describing a system architecture by combining a Grow-Cull execution model: in a system operation process, copying a part of sub-graphs to a GPU each time to execute a Grow operation, judging a relationshipbetween the sub-graphs and vertexes / edges, and copying the generated candidate sub-graphs to a CPU memory; in order to check the legality of the candidate sub-graphs, the CPU multithreading technology is used for executing the Cull operation to judge the candidate sub-graphs, the qualified sub-graphs are stored in the CPU main memory. The system repeats the iteration process. By referring to thethought of a pipeline, CPU calculation and GPU calculation can be executed at the same time during iteration, bidirectional copying of data can also be executed at the same time, and calculation and transmission delay is masked.

The invention relates to the technical field of risk message interception, in particular to a method and device for intercepting risk message messages based on a Bloom filter. According to the characteristics of risk data, the memory is divided into two areas, and the data loading cost will become very low. The risk data that may be added or deleted at any time of the day is stored in the hot zone H, and the historical risk data is stored in the cold zone C. At the same time, because the data of the Bloom filter can only be increased but not decreased, and users may delete historical risk data, such deletion cannot change the cold area data. Therefore, two Bloom filters are set in the hot data area, one adds H-A for the hot area, and the other deletes H-R for the hot area. By adopting the above method, the present invention can alleviate memory pressure, improve efficiency and reduce cost.

The invention discloses a system for settling fierce competition of memory resources in a big data processing system. A memory information feedback module is used for monitoring the memory using condition for a running thread task, converting collected memory information and then feeding back the converted memory information to an information sampling and analyzing module; the information sampling and analyzing module is used for dynamically controlling the number of sampling times of information of all working nodes, analyzing data after the assigned number of sampling times is achieved, and calculating the optimal CPU to memory proportion of the current working node; a decision making and task distributing module is used for making a decision and controlling whether new tasks are distributed to the working nodes for calculation operation according to the information obtained through analysis and the task running information of the current working node to achieve effective limit on the CPU and memory use relation. By means of the system, a memory-perceptive task distribution mechanism can be achieved on a universal big data platform, the I / O expenditure generated when data overflows to a disc due to fierce competition of memory resources can be reduced, and the integral performance of the system can be effectively improved.

The present invention proposes a large volume BIM model data processing and loading method and equipment, belonging to the technical field of BIM data processing, which includes a model data import module; a data export module; a model data grouping module; a model data export module; a model data lightweight module; Model layer making module. The BIM model loading of the present invention adopts the principle of nearby loading, and can quickly display the scene model closest to the current viewing angle. When the number of models reaches a certain online level, it can automatically unload according to the loading situation.

The invention provides a network anomaly detection method and device and a server. The method comprises the following steps: receiving a data stream of predicted data of a network index corresponding to a specified time and a data stream of actual data of the network index corresponding to the specified time; and comparing the data stream of the received prediction data with the data stream of the actual data to obtain a comparison result of the network indexes. According to the method, specified time is set in advance, when the specified time is reached, a data stream of prediction data and a data stream of actual data of a network index corresponding to the specified time are received and are compared, the prediction data and the actual data are gradually extracted in the time dimension, and the comparison is carried out in the form of the data streams, and a large amount of prediction data does not need to be cached, so that memory pressure is relieved.

The embodiment of the present invention discloses a real-time positioning method and device applied to automatic driving. The method includes: acquiring inertial measurement sensor data from the built-in inertial measurement sensor of the vehicle, and recording the time point when the inertial measurement sensor data is acquired. When sensor data other than inertial measurement sensor data is obtained at this time point, the vehicle is positioned according to the inertial measurement sensor data and other sensor data, and when no other sensor data is obtained at this time point, the vehicle is positioned based on the inertial measurement sensor data Position the vehicle. By implementing the embodiment of the present invention, the time point when the inertial measurement sensor data is received can be used as the time reference, and the sensor data obtained at the time point can be used for positioning to improve the positioning accuracy of the vehicle.