32results about How to "Optimize execution time" patented technology

The invention provides an acceleration optimization method and system for parallel PME of molecular dynamics simulation software, and the method comprises the steps: a calculation task is divided intoa plurality of parts, the calculation task is distributed to all slave cores of a super calculation platform, and the calculation is carried out through the slave cores; in the fast Fourier transformin the calculation process, data replication of matrix transposition is completed by utilizing data partitioning and a slave core; and the master core obtains the calculation results of the slave cores in a DMA mode, merges and vectorizes the calculation results, and the master core uses an RDMA technology to replace a traditional MPI technology to obtain data of other master cores. According tothe method, the molecular dynamics simulation software can be smoothly loaded on the super computing platform, and meanwhile, the computing performance can be improved.

A vehicle includes a first motor generator that generates electric power using power of an engine, a battery, and a second motor generator that is connected to drive wheels and is driven by electric power supplied from the battery and the first motor generator. An ECU of the vehicle drives the first motor generator as an electric motor with a regenerative electric power, executes a braking control, in which a load of the first motor generator functions as the engine, when an SOC is equal to or more than a threshold value of a waste electric-power start, and changes the threshold of the waste electric-power start based on a running condition of the hybrid vehicle.

The invention belongs to the technical fields of cloud computing and data mining, and particularly discloses a massive high-dimension data clustering method for a MapReduce platform. In the method, each dimension of raw data is split, and clustering is performed by utilizing small split non-null grids instead of points in the raw data so as to reduce a data scale. The clustering is realized by utilizing an open source of MapReduce, so that the whole clustering process can be finished in parallel on a distributed cluster, and the limitations of a single-machine algorithm to storage and computation are broken. In the clustering process, the thought of a K-mediods algorithm is adopted, and a highly-efficient Euclidean distance computation method is put forward. The method is applied to the processing of massive high-dimension data. A user can perform manual regulation on the algorithm according to the computational capability of the cluster, the expected time of the algorithm and requirements on clustering accuracy. The needs of different users are satisfied.

An embodiment of the present application provides an image processing method and device thereof, wherein the method includes the following steps: converting the foreground image corresponding to the original image into a compressed image; estimating the first extraction time required for depth feature extraction using the original image and the second extraction time required for depth feature extraction using the compressed image; according to the first extraction time and the second extraction time, it is determined to use the original image for depth feature extraction or use the compressed image for depth feature extraction. By adopting the embodiment of the present application, the calculation amount of the image depth feature extraction process can be effectively reduced, thereby improving the execution time of video object detection.

A power outage plan optimization decision method aiming at reducing power outage time and quantity comprises the following steps: reading the topology information of a distribution network, and establishing the contact relationship between distribution network components in a region to be evaluated to form a contact matrix; reading the information of each load point in the distribution network; reading power outage event information; for each type of power outage events, reading the information of maintenance teams in the region to be evaluated (including the number BN of the maintenance teams in the region to be evaluated, the ability of the maintenance teams and the daily workload of the maintenance teams), and making clear the power outage strategy in the region to be evaluated; optimizing the power outage period; optimizing the power outage order; and displaying the result. The method takes the user's power outage time, the user satisfaction and the team's ability into full consideration, and adopts simultaneous maintenance. For different power outage events, the execution time of each power outage time is optimized based on the daily load curve of an affected region. Thus, the power outage time and power outage quantity of the system are reduced effectively, reliable power supply of the system is ensured, and the customer satisfaction is improved.

The invention provides a testing method and a testing device. The testing method includes: configuring execution sequence of a testing sample by using an automatic testing tool according to preset rules; using an industrial controlled device for controlling a Bluetooth system to be tested and an opposite terminal device to execute the testing sample according to the configured execution sequence of the testing sample, and obtaining the testing data; and comparing the testing data with preset testing standard data, and determining testing results according to the comparison results. According to the testing method and the testing device, problems that existing Bluetooth testing wastes manual power and is not high in efficiency are solved, and effects of high testing efficiency and low testing cost are achieved.

A method and apparatus for the processing of at least one command concerning at least one component of a cluster is disclosed. The cluster comprises several components, the at least one component having a dependency link, according to the at least one command, with at least one other component, is disclosed.

An electronic device is provided to enable a user to experience quick launching of applications in the electronic device. The electronic device includes a housing, a display, an input unit, a processor, a non-volatile memory storing an application program, and a volatile memory storing instructions that allow the processor to a state change loads a first portion of the application into the volatile memory, a second state change of the electronic device loads a second portion of the application into the volatile memory, and Displays the image or text resulting from the loaded first and second parts. Since at least a part of the application is preloaded before generating the second input, only the remaining part of the application has to be loaded in order to execute the application after generating the second input.

According to an embodiment, there is provided a method of generating a data structure stored in computer memory for processing a search query in a network of interconnected nodes, wherein the method comprises selecting landmark nodes by the following steps and storing the selected landmark nodes in the data structure: sampling from the network nodes a first sample of vertex pairs, computing the shortest path for each vertex pair, each shortest path comprising a set of vertices between each vertex in the vertex pair; identifying a first landmark node which occurs in more of the shortest paths more often than any other vertex; removing from the network vertices shortest paths including the first landmark node and identifying a second landmark node which occurs in more of the remaining shortest paths than any other remaining vertex.

The present invention relates to the technical field of cloud computing, in particular to a workflow scheduling and data distribution method in a cloud environment, comprising the following steps: obtaining the current workflow of the cloud platform; calculating the height of each task in the workflow according to the scheduling model, and Arrange the tasks in ascending order of height; use the particle swarm optimization algorithm to optimize the execution time and cost of the workflow to obtain the globally optimal particle code; decode the globally optimal particle code into a workflow scheduling and data allocation scheme and output. This method takes data storage into consideration, reduces the transmission time between nodes, and optimizes the task execution efficiency and execution cost of the workflow in the cloud platform.

A search query to provide a search result may be received, which identifies source and target nodes and an application for generating the search result. The application accesses a data structure holding landmark nodes, which store a shortest path tree in the form of a set of parent links. Each parent link can identify an adjacent vertex node in a shortest path between each node in the data structure and the landmark node. The location of the source node and the target node in the shortest path trees may be identified to the landmark node. For each landmark node, using the identified locations of the target node and source node, a measure of distance between the source node and the target may be generated. The landmark node with the shortest distance may be determined. A search result related to the shortest path tree of that landmark node may be provided.

The invention discloses a SIG mesh-based broadcast bearer layer message filtering strategy method, the method is based on the bluetooth SIG mesh mesh network, and the mesh mesh network includes a bearer layer, a network layer, a transport layer and an access layer, The bearer layer transmits data between mesh nodes and passes it to the network layer, and the mesh node receives broadcast messages at the bearer layer, and compares them with preset queues to realize the mesh Filtering of broadcast packets in a mesh network reduces RAM consumption and CPU execution time. The invention optimizes the consumption of RAM, CPU execution time, and BLE scanning time due to the interference of non-mesh broadcast packets in the air, and optimizes the consumption of RAM and CPU execution time caused by repeated data packets.

The present invention provides a method and system for task analysis and resource allocation based on a formal model, including: step S1: a task analysis module analyzes task requirements, and formally expresses the task requirements as a task workflow; step S2: a resource allocation module Combine the formalized task workflows to obtain a combined task workflow; step S3: abstract the resource capabilities of the mobile terminal device into a meta model, and perform service registration in the cloud; step S4: based on the combined task workflow and For the service registered in the cloud, a heuristic algorithm is used to perform task scheduling and matching; step S5 : the mobile terminal device executes the task according to the scheduling matching result.