A method for executing a task by a scheduling device, belonging to the technical field of electronics. The method includes: acquiring a target algorithm corresponding to a target task to be executed; acquiring an execution environment condition for a target algorithm, and current execution environment information of various execution devices; in the execution devices, determining a target execution device of which the execution environment information satisfies the execution environment condition; and sending a control message for executing the target task to the target execution device.

In accordance with an embodiment, described herein is a system and method for use in a distributed computing environment, for automatically scaling a cluster based on metrics being monitored. A cluster that comprises a plurality of nodes or brokers and supports one or more colocated partitions across the nodes, can be associated with an exporter process and alert manager that monitors metrics associated with the cluster. Various metrics can be associated with user-configured alerts that trigger or otherwise indicate the cluster should be scaled. When a particular alert is raised, a callback handler associated with the cluster, for example an operator, can automatically bring up one or more new nodes, that are added to the cluster, and then reassign a selection of existing colocated partitions to the new nodes/brokers, such that computational load can be distributed within the newly-scaled cluster environment.

[Problem] Available resources are efficiently used even in a case in which continuous available resources cannot be secured on a cloud. [Solution] A resource reservation management apparatus 10 includes: a storage unit that stores a resource capacity and resource reservation information of a computing machine; a reservation notification unit 11 that receives, from a user terminal, reservation request information including an operating requested time period, an operating time, and a requested specification as a reservation of a master lease; a scheduling unit 12 that creates slave leases by splitting the operating time of the master lease in accordance with times corresponding to available resources indicated in the resource reservation information and sets the slave leases in the resource reservation information; a reservation management unit that detects occurrence of predetermined events including stop, shift, restart, and deletion of the created instances by referring to the resource reservation information; and an instance management unit 15 that transmits instruction information in accordance with an instance creation instruction and the detected predetermined events to the computing machine 15.

A method and system for processing media content in Moving Picture Experts Group (MPEG) Network Based Media Processing (NBMP) includes receiving, from an NBMP source, a first message including a workflow descriptor document corresponding to a workflow for processing the media content; obtaining, based on the workflow, a task having a task template; obtaining, based on the task, a function having a function template; and managing the processing of the media content by transmitting, to a media processing entity, a second message instructing the media processing entity to perform the function based on the task. The first message, the workflow descriptor document, the task template, the function template, and/or the second message may be used to signal a scheme for processing the media content.

In a real-time system having first and second processor systems, cooperative dynamic clock and voltage scaling (“DCVS”) may include a first processor system monitoring a condition indicative of first processor workload, adjusting a first processor operating frequency in response to a detected amount of change in the first processor workload, and providing an indication based on the detected amount of change in the first processor workload to the second processor contemporaneously with providing first processor output data to the second processor. The cooperative DCVS may further include the second processor system adjusting a second processor operating frequency in response to the indication.

A method for processing a touch signal includes: detecting, through an event dispatch process, a full-screen gesture touch signal, determining whether the full-screen gesture touch signal conforms to a full-screen gesture trajectory determination rule; and sending, based on a result of the determining, the full-screen gesture touch signal or a part of events of the full-screen gesture touch signal to a gesture processing process or an application processing process.

A computer implemented system is described for assigning executable jobs to pipeline sets, whereby the jobs may be network based computer jobs. The assigning includes generating a weight for each pipeline set of multiple pipeline sets to obtain multiple weights. Generating a weight includes obtaining duty cycle metrics for pipeline software threads in the pipeline set. The duty cycle metrics include a measure of an amount of time that a corresponding pipeline thread is executing and actively processing data. Generating the weight further includes determining the weight for the pipeline set based at least in part on the duty cycle metrics. The method further includes assigning a job request to a target pipeline set selected from the pipeline sets according to a weighted random algorithm, wherein the weighted random algorithm uses the weights.

This application provides an application program management method and apparatus. The method is performed in a database cluster system including at least two database nodes, at least one database object is stored in each database node, and the method includes: running an application program on a first database node in a first time period; determining a target database node based on at least one historical database object accessed by the application program in the first time period, where the target database node stores the historical database object; and running the application program on the target database node in a second time period. According to this application, a database node on which an application program runs can be dynamically adjusted, to avoid overload of the database node.

An apparatus and method for scheduling threads on local and remote processing resources. For example, one embodiment of an apparatus comprises: a local graphics processor to execute threads of an application; graphics processor virtualization circuitry and/or logic to generate a virtualized representation of a local processor; a scheduler to identify a first subset of the threads for execution on a local graphics processor and a second subset of the threads for execution on a virtualized representation of a local processor; the scheduler to schedule the first subset of threads on the local graphics processor and the second subset of the threads by transmitting the threads or a representation thereof to Cloud-based processing resources associated with the virtualized representation of the local processor; and the local graphics processor to combine first results of executing the first subset of threads on the local graphics processor with second results of executing the second subset of threads on the Cloud-based processing resources to render an image frame.

An analysis processing apparatus (100) includes a reception unit (110) for receiving a plurality of analysis requests requesting any of a plurality of types of analysis processing for media data, an estimation unit (120) for estimating a processing time according to the type of the analysis processing corresponding to the analysis request from an analysis condition of each analysis request for each of the plurality of analysis requests, a priority determination unit (130) for determining a priority of processing of each analysis request based on relative positioning of the estimated processing time in past records of the processing time for the type of the analysis processing corresponding to the analysis request, and an execution unit (140) for executing the analysis processing in the type corresponding to each analysis request in accordance with an order corresponding to the priority determined by the priority determination unit (130).