A processor for supporting PIM (Processing-in-Memory) execution in a multiprocessing environment includes logic configured to: receive a request to initiate an offload of a number of PIM instructions to a PIM device. The request is issued by a first thread of a processor. The logic is also configured to reserve, based on information in the request, resources of the PIM device for execution of the plurality of instructions.

A processing system includes a service provider, such as a printing device, that receives requests to process tasks or jobs from service requesters. At times, the service provider will not be available for processing and will generate deferral responses to the service requesters. The deferral responses include a condition to be met before processing requests can be resent from the service requesters. After the condition is met, the processing requests are resent to the service provider to be fulfilled.

A system to dynamically generate, monitor and optimize an allocation of resources includes a processor-based server to process requests received from the client devices. The processor-based server includes a server processor to generate the allocation of resource sharing one or more display devices selected based on an allocation criterion defined by the information emitter, target rating point goal, a geolocation, a format, and a quality coefficient of each display device in the set of available display devices. The server processor monitors availability of previously unavailable display devices and track real-time changes to the quality coefficients for each display device in the updated set. The server processor dynamically updates and optimizes the allocation of resources based on the updated quality coefficients for the updated set of available display devices.

An open edge cloud platform (OECP) enables tenants to access resources of a pool of network operator to support tenant applications. The tenant can specify a virtual location when requesting creation of a virtual network for a tenant application. The OECP creates a virtual network for the tenant application from available resources of a pool of network operators at the virtual location specified by the tenant in the request. The flexibility of selecting resources from a pool of network operators enables the tenant to access resources closer to the end user devices that will use the tenant application and thus reduce latency for applications and increase data throughput.

A method of configuring a cloud server resource, an electronic device and a storage medium, which specifically relate to a field of artificial intelligence technology, in particular to a field of cloud computing technology. A method of configuring a cloud server resource includes: obtaining an operation index of a server instance of an object; comparing the obtained operation index with a threshold; and determining whether a configuration of the cloud server resource is to be adjusted, based on a result of the comparing.

Computing systems, devices, and associated methods of allocating computing resources in a distributed computing system to user requests are disclosed herein. In one example, a method includes when none of unallocated computing resources satisfy a constraint on a physical attribute in a received request for the computing resource, identifying one of the allocated resources in the distributed computing system that satisfies the constraint on the physical attribute and recursively determining whether one of the other allocated or unallocated resources in the distributed computing system that satisfies a constraint of a prior request. In response to determining that none of the allocated or unallocated resources satisfies the constraint of the prior request, assignment of the identified one of the allocated resources to the prior request is maintained.

A computer-implemented method according to one embodiment includes identifying a job creation request within a system; determining a current amount of available resources within the system; and conditionally deploying a reusable group of containers for the job, based on the current amount of available resources for the system.

The present disclosure relates to application startup control methods and control devices. One example method includes receiving information that is sent by a first application and that is used to trigger startup of a second application, determining, based on at least one of the information of the first application and a currently available resource amount of a system, whether to restrict the startup of the second application, where the information of the first application is used to indicate an importance degree of the first application in the system, and restricting the startup of the second application in response to determining to restrict the startup of the second application.

A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include calculating a priority factor with a node autonomous center in a node and computing a node service capability with the node autonomous center. The operations may further include selecting, with the node autonomous center, a task based on the priority factor and the node service capability. The operations may further include directing the task to the node.

A system can determine timeseries telemetry data of a first resource utilization of a data center maintained by the system. The system can predict, from the timeseries telemetry data, a second resource utilization of the data center will occur at a future time, the second resource utilization exceeding a threshold amount of resource utilization of the data center. The system can determine, based on an amount of time available until the future time, a selected location indicative of whether to install additional hardware at a first physical location of the data center, or a second physical location of the data center, wherein an amount of time associated with installing the additional hardware at the first physical location is less than an amount of time associated with installing the additional hardware at the second physical location. The system can install the additional hardware at the selected location.