33results about How to "Implement parallel execution" patented technology

The invention provides a cluster GPU resource scheduling system. The system comprises a cluster initialization module, a GPU master node, and a plurality of GPU child nodes, wherein the cluster initialization module is used for initializing the GPU master node and the plurality of GPU child nodes; the GPU master node is used for receiving a task inputted by a user, dividing the task into a plurality of sub-tasks, and allocating the plurality of sub-tasks to the plurality of GPU child nodes by scheduling the plurality of GPU child nodes; and the GPU child nodes are used for executing the sub-tasks and returning the task execution result to the GPU master node. The cluster GPU resource scheduling system and method provided by the invention can fully utilize the GPU resources so as to execute a plurality of computation tasks in parallel. In addition, the method can also achieve plug and play function of each child node GPU in the cluster.

The invention discloses a method for constructing a prediction and evaluation model of time series type surface water quality big data, which firstly clears the numerical value obviously contrary to common sense, then finds out the time point nearest to the Markov distance according to all the data at the time point where the vacancy value exists, and uses the data at the time point to fill the vacancy value. Then the outliers in the water quality data are detected by using the improved KMeans + + clustering algorithm and Z-fraction detection algorithm, and the outliers are filled by support vector regression. Then stochastic forest algorithm is used to extract the important characteristics of water quality indicators, and the indicators with high importance are selected to evaluate the overall state of water quality. Then the LSTM model is used to predict the time series of the whole state of water quality. Finally, the MapReduce program of Hadoop is used to realize the parallel execution of the program, which improves the execution efficiency of each algorithm, completes the final prediction and evaluation model construction, and improves the efficiency, integrity and accuracy ofwater quality big data analysis.

The invention relates to a method for routing a part entangled quantum pair bridging communication network. The method comprises the following steps: launching routing request information 1 by an original node; answering the routing request information by a destination node; launching routing request information 2 by the original node; launching routing request information 3 by a path node; answering the routing request information of each node by the destination node; and establishing routing. The routing metric of each node is updated on time by the node, wherein the routing metric is calculated through a special formula, and the node selects and determines routing according to the routing metric.

The invention provides a method and device for executing transactions in a block chain system. The method is executed by a node of a block chain, and the method comprises the following steps: determining a sequence corresponding to a plurality of transactions to be executed and each parameter accessed by each transaction; based on the sequence and each parameter accessed by each transaction, dividing the transactions to obtain a first transaction group and a second transaction group, wherein the second transaction group comprises at least one second transaction, and a random second transaction has a read-write conflict with at least one first transaction in the first transaction group, and the sequence of the second transaction is after the first transaction having the read-write conflict with the second transaction; and after the execution of each first transaction in the first transaction group is completed, executing the remaining transactions in the first transaction group and the second transaction in the second transaction group in parallel.

The invention provides a cluster GPU resource scheduling system. The system comprises a cluster initialization module, a GPU master node, and a plurality of GPU child nodes, wherein the cluster initialization module is used for initializing the GPU master node and the plurality of GPU child nodes; the GPU master node is used for receiving a task inputted by a user, dividing the task into a plurality of sub-tasks, and allocating the plurality of sub-tasks to the plurality of GPU child nodes by scheduling the plurality of GPU child nodes; and the GPU child nodes are used for executing the sub-tasks and returning the task execution result to the GPU master node. The cluster GPU resource scheduling system and method provided by the invention can fully utilize the GPU resources so as to execute a plurality of computation tasks in parallel. In addition, the method can also achieve plug and play function of each child node GPU in the cluster.

The embodiment of the present application discloses a network configuration method and a related device. The method includes: during the process of the terminal performing the first service through the first SIM card, detecting whether there is a second service and triggering the second SIM card to connect to the second network Enter; If so, then obtain the first base station that is currently connected in communication with the first SIM card in the first network; Determine whether the first base station includes the same base station with the second base station type to be accessed by the second SIM card; If so, adjusting the first base station of the current communication connection of the first SIM card to be a third base station, and controlling the second SIM card to access the second network to perform the second service, the third base station does not include the same type as the second base station base station. The implementation of the embodiment of the present application can enable the terminal to realize the function of parallel execution of services by two SIM cards, and improve the data processing efficiency of the terminal.

The disclosure relates to a test task scheduling method oriented to complex resource constraints, and relates to the field of automated testing, wherein the method includes: connecting test task nodes of the target system according to preset test task dependencies to obtain multiple test task nodes According to the target directed acyclic graph, obtain at least one test task path according to the target directed acyclic graph, and determine the node sequence of each test task node in the corresponding test task path; according to the test resource constraints and node sequence, determine at least The reference test resource of each test task node in a test task path, and execute the corresponding test script according to the reference test resource. Therefore, the execution of test tasks based on the target directed acyclic graph can realize parallel execution of test tasks, improve test efficiency and utilization of test resources, and match test resources based on test resource constraints, improving Test resource selection reliability and efficiency.

The embodiment of the invention discloses a conditional branch instruction fusion method and device and a computer storage medium. The method comprises the following steps: in a compiling stage, respectively generating corresponding code blocks from branch statements in a conditional branch statement sequence in response to detecting that the conditional branch statement sequence appears in a program; fusing the code blocks according to a set instruction fusion strategy to obtain a fusion instruction, and storing the fusion instruction in an instruction memory, wherein the branch statement corresponds to a judgment result corresponding to a conditional judgment statement in the conditional branch statement sequence; in an execution stage, decoding a fusion instruction read from the instruction memory to obtain a code block contained in the fusion instruction; scheduling code blocks obtained by decoding to corresponding execution units in parallel according to an execution result obtained by executing the conditional judgment statement; and executing the scheduled code block through the execution unit.

The invention relates to the technical field of big data, and provides a business data loading method and device, electronic equipment and a storage medium, and the method comprises the following steps: carrying out dependency analysis on preloaded data; creating a decision tree according to the preloading data and the preloading data on which each timed loading task depends; when it is detected that loading of the preloaded data depended on by the next timed loading task of the first timed loading task is completed, a second thread is started to load the preloaded data in the next timed loading task of the first timed loading task of the decision tree, controlling the first thread to load the residual preloading data in the first timed loading task; and the decision tree is loaded. According to the method and the device, when the loading of the preloading data on which the next timed loading task of the first timed loading task depends is finished, the second thread is started to load the next timed loading task of the first timed loading task, so that the data loading efficiency is improved.

The invention discloses a computing board card with an OODA multiprocessor. The computing board card comprises four processors with different computing functions of the OODA, and the four processors allocate different workflow jobs through a scheduling controller; and when one streaming job is processed, sequentially and circularly calling the four processors according to a preset calculation sequence, and executing the streaming job. When the four processors process the OODA workflow loads, four kinds of calculation algorithms including observation, adjustment, scenario and action are executed respectively, the multiple OODA workloads occupy different processors in sequence according to the characteristic that the OODA workloads occupy different processors in sequence, and the execution efficiency of a load assembly line is improved.

An IC storing card wherein the main storage unit and the programming unit employ flash memory units, two static state random memory units, and a serial input / output interfaces, when a command is inputted, the device command is temporarily stored in a command registering unit, the type A command is sent to the second control unit for execution, the type B command is sent to the first control unit for execution, in the execution term, the control signal produced by the control unit flows to the two static random storage units through data of the selector control system bus, thus preventing errors for data communication between the system resources when two commands are operated simultaneously.

The invention discloses a large-scale particle image velocimeter based on a near-infrared smart camera, which belongs to the technical field of non-contact open channel current surveying. The instrument consists of a processor module, an image sensor module, an optical system, a network communication module and a power module, wherein the processor module takes a 32-bit fixed point DSP (digital signal processor) chip as a core to replace a PC (personal computer) to finish image collection and processing as well as data transmission; the image sensor module adopts a monochrome CMOS (complementary metal oxide semiconductor) image sensor of a digital interface; and the optical system consists of a double-filter switcher, an electric three-variable lens, an infrared LED fill light, a motor driving module and an illumination control module and is used for realizing the remote control of lower optical image under a near-infrared waveband or full-spectrum waveband. The instrument adopts an Ethernet transmission image, flow field data, a state information and control command conforming to an IEEE (institute of electrical and electronic engineers) 802.3 protocol, and the instrument and data transmission can share one cable by supplying power in a PoE mode. The large-scale particle image velocimeter has the characteristics of strong anti-jamming capability, high temporal-spatial resolution and flexible and efficient system.

The invention discloses a method for realizing cloudization task arrangement and scheduling based on ZooKeeper. The method comprises: performing cloudization slice configuration on the task on a static tree according to the task requirement, and obtaining configuration information of the task slice; Slices are instantiated, pooled and configured to obtain task layout information of task slices; record the running status of task slices on the dynamic tree; record the execution status of task slices on the control tree; schedule task slices according to task layout information, and execute scheduling The final task slicing realizes the arrangement, scheduling and execution of tasks, and does not require manual intervention. The arrangement and scheduling of tasks can be realized through the cloud task arrangement and scheduling client, which improves the usability and robustness of batch tasks .

The invention discloses a method for compressing and processing YUV image Y data, which relates to the field of image processing, comprising: acquiring residual data of Y macroblocks of an input image; performing DCT transformation on the residual data of Y macroblocks to obtain AC coefficients; Add all sub-block data matrices in the residual data to obtain the DC component matrix of the macroblock residual data; perform WHT transformation on the DC component matrix to obtain the DC coefficient; quantize the AC coefficient and the DC coefficient to obtain the Y data compression data . This method can realize the parallel execution between DCT transformation and WHT transformation, improve the pipeline parallelism between modules, and improve the overall throughput performance of the WebP image lossy compression algorithm. The invention also discloses a YUV image Y data compression processing device, equipment and a YUV image-based WebP lossy compression system, which have the above beneficial effects.

The invention relates to the field of ion thruster numerical simulation, in particular to a charge exchange collision MCC method for ion thruster numerical simulation. The present invention utilizes the physical characteristics of the charge exchange collision of the ion thruster in combination with the characteristics of single instruction multi-threading of the graphics processing unit (GPU) in the computer field to realize the parallel execution of the single instruction multiple data of the charge exchange collision MCC algorithm of the ion thruster, greatly greatly The calculation efficiency is improved and the calculation time is saved.