Embodiments of systems and methods for platform framework orchestration and discovery are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: receive, by a service within a platform framework through an Application Programming Interface (API), a discovery request; in response to the discovery request, convey an inquiry for capability information from the service to a participant registered with the platform framework through the API; receive, by the service from the participant through the API, the capability information; and fulfill, by the service through the API, the discovery request using at least a portion of the capability information.

Examples include techniques to enable quality of service (QoS) control for an accelerator device. Circuitry at an accelerator device implements QoS control responsive to receipt of a submission descriptor for a work request to execute a workload for an application hosted by a compute device coupled with the accelerator device. An example QoS control includes accepting the submission descriptor to a work queue at the accelerator device based on a work size of submission descriptor submissions of the application to the work queue over a unit of time not exceeding a submission rate threshold. The work queue is associated with an operational unit at the accelerator device to execute the workload based on information included in the submission descriptor. The work queue to be shared with at least one other application hosted by the compute device.

In one example in accordance with the present disclosure, an electronic device is described. An example electronic device includes a processor and memory storing executable instructions that when executed cause the processor to determine availability of memory resources and processing resources of multiple computing devices. The instructions also cause the processor to form a computing cluster based on the availability of the memory resources and the processing resources. The instructions further cause the processor to assign a computing task to the computing cluster to replace a cloud service.

interface circuitry to detect a request to obtain a resource request from a workload and processor circuitry including one or more of: at least one of a central processing unit, a graphic processing unit or a digital signal processor, the at least one of the central processing unit, the graphic processing unit or the digital signal processor having control circuitry, arithmetic and logic circuitry, and one or more registers, the processor circuitry to execute instructions to: determine if resources are available for the workload on an infrastructure processing unit managed system; negotiate with the infrastructure processing unit to determine if an executing workload can be migrated; in response to determining that an executing workload can be migrated, cause the executing workload to be migrated; and cause the workload to execute on the resource.

This application provides a method for adjusting a resource of an intelligent analysis device and an apparatus. The method includes: obtaining status information of an intelligent analysis device that accesses a surveillance platform and application information deployed on the intelligent analysis device, where the status information includes resource usage and a quantity of bound cameras; after a camera accesses the surveillance platform, selecting a to-be-bound intelligent analysis device for the camera based on the status information and the application information of the intelligent analysis device that accesses the surveillance platform; and sending, to the selected intelligent analysis device, a command for binding the camera. In this way, the resource of the intelligent analysis device may be automatically allocated. This improves processing efficiency and avoids low efficiency caused by manual processing.

A software defined (SD) process control system (SDCS) implements controller and other process control-related business logic as logical abstractions (e.g., application layer services executing in containers, VMs, etc.) decoupled from hardware and software computing platform resources. An SD networking layer of the SDCS utilizes process control-specific operating system support services to manage the usage of the computing platform resources and the creation, deletion, modifications, and networking of application layer services with devices disposed in the field environment and with other services, responsive to the requirements and needs of the business logic and dynamically changing conditions of SDCS hardware and/or software assets during run-time of the process plant (such as performance, faults, addition/deletion of hardware and/or software assets, etc.). Thus, dynamic (re-)allocation of hardware/software resources is primarily, if not entirely, and continually governed in real-time by present requirements and needs of application layer services as well as dynamically changing SDCS conditions.

Disclosed are various implementations of approaches for reassigning hosts between computing clusters. A computing cluster assigned to a first queue is identified. The first queue can include a first list of identifiers of computing clusters with insufficient resources for a respective workload. A host machine assigned to a second queue can then be identified. The second queue can include a second list of identifiers of host machines in an idle state. A command can then be sent to the host machine to migrate to the computing cluster. Finally, the host machine can be removed from the second queue.

A method for creating a container, an apparatus for creating a container, a device, a medium, and a program product are provided. The method includes: acquiring a description file of a to-be-scheduled container group (Pod), where the description file of the Pod is used for describing resource demand information; determining, based on the description file of the to-be-scheduled Pod and idle resource information of each of work nodes, a target work node from the work nodes, and binding the to-be-scheduled Pod to the target work node; and sending a container runtime interface (CRI) request to a container engine, where the CRI request is used for instructing node to create a target container at the target work based on configuration information in the CRI request, and the configuration information is used for limiting an authority of the target container.

A method for performing a distributed computation on a computing system using computational resources dynamically allocated using a computational resource manager includes storing information specifying quantities of computational resources associated with respective ones of a number of program portions of the program, where the program portions perform successive transformations of data and each program portion uses computational resources granted by the computational resource manager enabling computation associated with that program portion to be performed in the computing system, requesting a first quantity of computational resources associated with a first program portion of the number of program portions from the computational resource manager, receiving a second quantity of computational resources from the computational resource manager, less than the requested first quantity of computational resources, performing computation associated with the first portion of the program using the second quantity of computational resources, while performing the computation associated with the first portion of the program using the second quantity of computational resources, receiving an additional quantity of computational resources from the computational resource manager, and performing an additional computation associated with the first portion of the program using the additional quantity of computational resources while performing the computation associated with the first portion using the second quantity of computational resources.

The present invention provides a method for allocating and managing a cluster resource on a cloud platform, the method comprising the steps of: generating service group information, by means of a cloud platform system, when a cluster resource allocation request is input; adding/deleting a user of the service group; selecting a cluster to be allocated to the user of the service group and inputting allocation information; querying a cluster resource availability; registering resource allocation information in the service group and allocating a resource to complete cluster resource allocation, when the resource is available as a result of the querying of the cluster resource availability; checking whether a cluster resource can be added when the resource is insufficient as a result of the querying of the cluster resource availability; registering the further cluster resource when the cluster resource can be added; registering resource allocation information in the service group and allocating the resource to complete cluster resource allocation; and reselecting an available cluster when the cluster resource cannot be added.