45 results about "Computer Grid" patented technology

A grid computing system, method, and computer program product, adapted to execute at least one workflow having a set of predefined operating parameters and including an execution module comprising a plurality of devices having a plurality of heterogeneous resources, wherein the plurality of devices is adapted to execute the at least one job by integrating the plurality of heterogeneous resources. The system further includes at least one grid workflow module. The grid workflow module includes a graphical user interface to provide at least one user to initiate and manage the at least one workflow based on the set of predefined operating parameters and the plurality of heterogeneous resources. Furthermore, the grid workflow module includes a manager module adapted to partition the at least one workflow into multiple jobs prior to the execution of the at least one workflow.

An apparatus, program product and method for managing access to a remote computing grid that is not normally accessible to a client. A client computer may communicate with the computing grid via a dropbox configured to receive and distribute data between the client computer and the grid. The connection may remain open while multiple commands are thus communicated to the computing grid, and the identity of the client submitting the commands may be authenticated.

Methods, articles of manufacture, and systems for providing access to a grid computing environment. In one environment, requests include resource specific criteria used to identify a particular grid resource to perform the request. In another embodiment, a request includes a queue criterion used to identify one of a plurality of queues on which the request is placed.

Methods, articles of manufacture, and systems for providing access to a grid computing environment. In one environment, requests include resource specific criteria used to identify a particular grid resource to perform the request. In another embodiment, a request includes a queue criterion used to identify one of a plurality of queues on which the request is placed.

An energy-harvesting compute grid includes computing assemblies that cooperate with mobile energy harvesters configured to be deployed on a body of water. The plurality of energy harvesters are positioned on and move adjacent to an upper surface of a body of water, and the locations of the energy harvesters can be monitored and controlled. The wide-spread gathering by the harvesters of environmental data within that geospatial area permits the forecasting of environmental factors, the discovery of advantageous energy-harvesting opportunities, the observation and tracking of hazardous objects and conditions, the efficient distribution of data and / or tasks to and between the harvesters included in the compute grid, the efficient execution of logistical operations to support, upgrade, maintain, and repair the cluster, and the opportunity to execute data-gathering across an area much larger than that afforded by an individual harvester (e.g., radio astronomy, 3D tracking of and recording of the communication patterns of marine mammals, etc.). The computational tasks can be shared and distributed among a compute grid implemented in part by a collection of individual floating self-propelled energy harvesters thereby providing many benefits related to cost and efficiency that are unavailable to relatively isolated energy harvesters, and likewise unavailable to terrestrial compute grids of the prior art.

A system for sharing computer resources comprises a node in a first computer grid, and one or more processing units adapted to instantiate an information path from said node to computing resources of a plurality of other grids, said information path configured as hierarchical rings of trust such that each grid of said plurality of other grids is assigned to one of a plurality of hierarchical trust levels.

An energy-harvesting compute grid includes computing assemblies that cooperate with mobile energy harvesters configured to be deployed on a body of water. The plurality of energy harvesters are positioned on and move adjacent to an upper surface of a body of water, and the locations of the energy harvesters can be monitored and controlled. The wide-spread gathering by the harvesters of environmental data within that geospatial area permits the forecasting of environmental factors, the discovery of advantageous energy-harvesting opportunities, the observation and tracking of hazardous objects and conditions, the efficient distribution of data and / or tasks to and between the harvesters included in the compute grid, the efficient execution of logistical operations to support, upgrade, maintain, and repair the cluster, and the opportunity to execute data-gathering across an area much larger than that afforded by an individual harvester (e.g., radio astronomy, 3D tracking of and recording of the communication patterns of marine mammals, etc.). The computational tasks can be shared and distributed among a compute grid implemented in part by a collection of individual floating self-propelled energy harvesters thereby providing many benefits related to cost and efficiency that are unavailable to relatively isolated energy harvesters, and likewise unavailable to terrestrial compute grids of the prior art.

The “Grid Security Monitor” tracks the security status of resources in a grid computer system. When a client submits a job to the grid scheduler, the Grid Security Monitor creates a security contract. The security contract comprises all the security credentials needed to access the resource executing the job, as well as privacy and security requirements. The Grid Security Monitor compares the security status of the resource to the requirements of the security contract. If the security status of the resource changes or violates the security contract, then the Grid Security Monitor notifies the client. The Grid Security Monitor has a user interface that allows the client to perform a manual security validation by asking the grid management system to verify the security status of the resource.

A grid computing system and method is provided for medical data processing. The grid computing system comprises a software infrastructure, and an imaging device capable of interfacing with the software infrastructure over a distributed electronic network. Also included is a plurality of CPUs capable of interfacing with the software infrastructure over the network. The performance of the plurality of CPUs is dependent on balancing load. A large medical dataset is split onto several processing nodes of the plurality of CPUs, respectively, such that performance and power is increased. In the grid computing method, a grid is limited to a nuclear medicine or radiology network. A tight and easy configuration management of computing nodes, and a tight load balancing between standardized nodes are provided. An existing network of CPUs is utilized, such that the greatest benefit is provided at the lowest cost.

Aiming at the problem of scheduling resources in the grid computing, the invention provides a scheduling method of grid resources of multi-Qos, which selects the most economic resource to schedule when in each scheduling. Compared with the prior art, the invention can complete the task at the least scheduling driving function value while meeting the user QoS, and realizes the satisfaction of a user to the max.

A set of software programs runs in a parallel configuration on local hospital servers. The software gathers all the data directed to it from a hospital patient's data sources (including, but not limited to, data formats from patient monitor devices, HL7 feeds, and other hospital data systems). Data can be time-synchronized, transformed, and routed from both currently networked device and non-networked devices. The data is made available for redisplay and analysis to system users and program agents.

The invention discloses a semantic vision SLAM method based on probability grid filtering, and the method comprises the steps: sequentially collecting RGB images of a scene through a camera sensor, and carrying out the ORB feature point extraction, super-point segmentation and semantic segmentation on the collected images; creating and initializing a probability grid; calculating matching information of the feature points between an upper frame and a lower frame, and using the matching information to propagate the probability of the grids in the upper frame to the probability grids of the corresponding lower frame to complete probability grid updating; performing motion consistency check on the matching points, and updating the motion state of the probability grid; updating the attribute of the current probability grid by using a Bayesian probability formula according to the updated probability grid, and creating a mask of a dynamic region; according to the extracted ORB feature points, performing filtering by using a mask of a dynamic region, and detecting the dynamic feature points with relatively high probability; and using the reserved feature points for tracking, local mappingand loopback detection, and finally realizing probability grid enhanced semantic vision SLAM.

The invention discloses a grid simulation platform, which comprises a terminal user, a grid server and computing nodes. After the terminal user logs onto a grid portal through a browser, grid services, such as job submission, information inquiry and the like, can be used. The grid server comprises a Web server, a dispatch server and a database. The grid computing nodes comprise all personal computers (PC) and cluster systems participating in computing. The invention also provides a corresponding grid simulation method. According to the grid simulation platform and the grid simulation method disclosed by the invention, computing of population fitness values is reasonably parallelized, and therefore, resource sharing of distributed desktop systems and cluster systems is realized, the problem that product development and production are influenced due to the fact that a single enterprise resource is insufficient at present is solved, the resource utilization rate is effectively improved, and a large number of funds are saved for enterprises.

Methods, articles of manufacture, and systems for providing access to a grid computing environment. In one environment, requests include resource specific criteria used to identify a particular grid resource to perform the request. In another embodiment, a request includes a queue criterion used to identify one of a plurality of queues on which the request is placed.

The invention provides an arc rail armrest positioning line laying method comprising the following steps: S100, popping a construction reference line in construction field, and marking the popped construction reference line; S200, marking an interlacing point between the arc position and the construction reference line on a computer, and using marking data to measure difference value between arc theoretical value and construction field value, thus determining an arc reference base line; S300, carrying out grid segmentation for the construction reference line, and marking control coordinates corresponding to the reference base line in the grid; S400, popping a datum line on a template panel according to the control coordinates corresponding to the reference base line, and cutting the template panel along the datum line so as to form a positioning template; S500, popping grid lines corresponding to computer grid segmentation in the construction field, and fixing the positioning template according to the datum line and the grid lines. The method is wide in applicability, high in construction efficiency, and can ensure construction precision.