Abstract: Content object operations over content objects of a content management system are prioritized to be performed immediately, or at a later time. The immediate scheduling of an operation is determined by policies, rules, and/or predictive model outcomes. The determination for later time scheduling is based on analysis of a history of events on content objects. If the content object operation is deemed to be at least potentially delayable to a later time, then a scheduling model is consulted to determine an urgency of performing the content object operation on the content object. The urgency value resulting from consulting the scheduling model is combined with then-current resource availability to determine a timeframe for performance of the content object operation on the content object relative to other entries in a continuously updated list of to-be-performed operations. The performance of the content object operation on the content object is initiated in due course.

Abstract: A method, a computer program product, and a system for pre-pooling virtual machine components prior to application startup. The method includes reading a virtual machine pool manifest by a virtual machine pool manager. The virtual machine pool manifest includes an initial number of virtual machines to launch, how many virtual machines to allocate resources to, and an amount of resources to allocate based on a virtual machine resource definition. The method also includes launching a plurality of base virtual machines into a virtual machine pool and based on the initial number provided by the virtual machine pool manifest. The base virtual machines lack initial application assignments. The method further includes allocating initial resources to a portion of the base virtual machines based on a virtual machine resource definition in the virtual machine pool manifest. The method includes loading core program packages into the portion of the base virtual machines.

Abstract: Techniques regarding the management of computational resources based on clinical priority associated with one or more computing tasks are provided. For example, one or more embodiments described herein can regard a system comprising a memory that can store computer-executable components. The system can also comprise a processor, operably coupled to the memory, that executes the computer-executable components stored in the memory. The computer-executable components can include a prioritization component that can prioritize computer applications based on a clinical priority of tasks performed by the computer applications. The clinical priority can characterize a time sensitivity of the tasks. The computer-executable components can also include a resource pool component that can divide computational resources across a plurality of resource pools and can assign the computer applications to the plurality of resource pools based on the clinical priority.

Abstract: Various methods, apparatuses/systems, and media for automatically controlling operating state of one or more applications in a distributed operating system are disclosed. A processor creates a filesystem that contains a script configured for interacting with a distributed operating system application programming interface (API); and integrates the filesystem with a scheduler module to be run on a predefined schedule. The processor also creates a container, in response to the predefined schedule, in the distributed operating system, the container having the script installed therein; calls the distributed operating system API to obtain a list of applications in the distributed operating system based on the script; automatically controls the operating state of the corresponding one or more applications in the distributed operating system in response to the predefined schedule and the script; and destroys the container after controlling the operating state of the corresponding one or more applications.

Abstract: The present disclosure relates to a method, device and computer program product for processing a job. In a method, a first group of tasks in a first portion of the job are obtained, the first group of tasks being executable in parallel by a first group of processing devices. A plurality of priorities are set to a plurality of processing devices, respectively, based on a state of a processing resource of a processing device among the plurality of processing devices in a distributed processing system, the processing resource comprising at least one of a computing resource and a storage resource. The first group of processing devices are selected from the plurality of processing devices based on the plurality of priorities. The first group of tasks are allocated to the first group of processing devices, respectively, which process the first group of tasks for generating a first group of task results.

Abstract: Techniques are provided for allocating resources for one or more workloads. One method comprises obtaining a current performance of a workload; determining an adjustment to a current allocation of a resource allocated to the workload by evaluating a representation of a relationship between: (i) the current allocation of the resource allocated to the workload, (ii) a performance metric, and (iii) the current performance of the workload; and initiating an application of the determined adjustment to the current allocation of the resource for the workload. The performance metric may comprise a nominal value of a predefined service metric and the current performance of the workload may comprise a current value of a variable that tracks a given predefined service metric of the workload. An amount (or percentage) of the adjustment permitted for each iteration may be controlled. A sum of allocated resources can be constrained to an amount of available resources.

Abstract: A system and method for dynamically determining parameters of crafting activities for individual users in a virtual space are disclosed. The crafting activity parameters may be determined based on rate of usage of the virtual space by the users. In some examples, a user usage rate of the virtual space may be determined to measure an amount of time a user spend in the virtual space during a period of real-world time. Based on the determined user usage rate of the virtual space, crafting activity parameters may be determined, for example, to balance differences in time spent in the virtual space by the users. In some implementations, for such determinations of the crafting activity parameters, one or more user normalization standards may be obtained.

Abstract: Example methods are provided for a first node to perform identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node. The method may comprise retrieving, from a pool of IDs associated with the cluster, a batch of IDs to a cache associated with the first node. The pool of IDs may be shared within the cluster and the batch of IDs retrieved for subsequent ID allocation by the first node. The method may also comprise, in response to receiving a request for ID allocation from an ID consumer, allocating one or more IDs from the batch of IDs in the cache to respective one or more objects for unique identification of the one or more objects across the cluster; and sending, to the ID consumer, a response that includes the allocated one or more IDs.

Abstract: A method and apparatus controls power management of a graphics processing core when multiple virtual machines are allocated to the graphics processing core on a much finer-grain level than conventional systems. In one example, the method and apparatus processes a plurality of virtual machine power control setting requests to determine a power control request for a power management unit of a graphics processing core. The method and apparatus then controls power levels of the graphics processing core with the power management unit based on the determined power control request.

Abstract: A cloud resource audit system includes a plurality of datacenter hardware resources and a cloud resource management controller that is coupled to the plurality of datacenter hardware resources and that allocates a first portion of the plurality of datacenter hardware resources to run one or more workloads for a first end user on the first portion of the plurality of datacenter hardware resources. The cloud resource management controller then executes a first set of audit instructions to performs a first audit action on one or more datacenter hardware resources included in the first portion of the plurality of datacenter hardware resources, and provides, in response to the first set of audit instructions being executed and the first audit action being performed, a first set of audit results to an audit terminal device.

Abstract: Managing concurrent accesses by a set of tasks to a shared resource of a computer system. Synchronizing the set of tasks for assigning and releasing a resource according to a predefined access period with flexibility of providing an extended access period where an external task is not detected during the predefined access period. Where an extended access period is provided, resynchronizing is performed, and the external task is identified and access is prevented when the external task is determined to be a particular type of task.

Abstract: A computing resource allocation method comprises beginning a first performance of a first task; determining, using a task manager circuit during the first performance of the first task, that a first operation from among the first plurality of operations requires a resource, wherein the resource is external to the processor; determining, using a spinlock circuit, that the resource is unavailable for use; pausing, under control of the task manager, the first performance of the first task at the processor; beginning, using the processor, a second performance of a second task, the second task comprising a second plurality of operations; receiving, at the task manager, a notice from the spinlock that the resource is currently available for use by the processor; and resuming, under control of the task manager, the first performance of the first task at the processor starting with the first operation from among the first plurality of operations.

Abstract: Harvesting the high performance computing capabilities of vehicle processors while the vehicles are parked and/or charging may provide use to otherwise unused resources as well as offer a way to discount parking and/or charging costs for the vehicle owner/driver. To harvest the computing capabilities, a dispatcher is utilized that receives incoming complex processing requests and parses the requests into tasks. The dispatcher dispatches the tasks to vehicle processors that are within, for example, a parking garage to which the dispatcher has access. The dispatcher may prioritize requests and/or prioritize the vehicle processors to distribute the tasks to optimize the power consumption, time, and processing capabilities used. When the vehicle processors complete the tasks and return results to the dispatcher, the dispatcher finalizes the job results and provides the results to the requestor. The dispatcher may discount the parking and/or charging costs for the vehicles that performed the computational tasks.

Abstract: An image of a virtualization software and firmware in a plurality of hosts are upgraded by performing the steps of: validating a desired image of the virtualization software by extracting dependencies and conflicts defined in metadata of all payloads of the desired image of the virtualization software, and confirming there are no violations of the extracted dependencies and conflicts; performing a pre-check of the desired image of the virtualization software against a current image of the virtualization software and a pre-check of the desired version of the firmware against a current version of the firmware; and upon determining from results of the pre-check that the virtualization software can be upgraded to the desired image and the firmware can be upgraded to the desired version, upgrading the current image of the virtualization software to the desired image and upgrading the current version of the firmware to the desired version.

Abstract: A first set of requirements of a first set of computing tasks for computing resources in a computing system is acquired respectively. Based on a determination that the requirement of a computing task in the first set of computing tasks for a computing resource satisfies a resource threshold condition, the computing task is divided into a plurality of sub-tasks. The resource threshold condition describes the threshold of a computing resource provided by a computing device in a plurality of computing devices in the computing system. A merging task for merging a plurality of sub-results of the plurality of sub-tasks into a result of the computing task is generated. Based on other computing tasks than the computing task in the set of computing tasks, the plurality of sub-tasks, and the merging task, a second set of computing tasks of the computing job is determined so as to process the computing job.

Abstract: A system and method that enables resource analysis within an intelligent content absorption network with autonomous mobility implementations includes generating a prioritization model, training the prioritization model on a data corpus to generate a prioritization schedule, deploying the prioritization schedule to one or more autonomous vehicles, offloading data at a local content absorption node, processing data at the local content absorption node, and optionally transmitting data results from the processed data.

Abstract: A service partitioned into service components requiring different resources is assigned to at least one cloud of a set of clouds. With interdependent service components, a service-placement engine is configured to coordinate assignments of individual service components. The service-placement engine receives from a client a definition of each service component and indications of components interdependence. Each cloud that satisfies compliance requirements, capability requirements, and resource requirements of a service component is considered eligible to host the service component. Selection of a specific eligible cloud is based on an overall cloud merit which depends on the service-component definition and the location of the client.

Abstract: A device may receive a job request associated with a data processing job, including job timing data specifying a time at which the data processing job is to be executed by a virtual computing environment. The device may receive user data associated with the job request and validate the data processing job based on the user data. In addition, the device may identify a priority associated with the data processing job, based on the user data and the job timing data. The device may provide, to a job queue, job data that corresponds to the data processing job, and monitor the virtual computing environment to determine when virtual resources are available. The device may also determine, based on the monitoring, that a virtual resource is available and, based on the determination and the priority, provide the virtual resource with data that causes execution of the data processing job.

Abstract: One or more aspects of the present disclosure relate to service level input/output scheduling to control central processing unit (CPU) utilization. Input/output (I/O) operations are processed with one or more of a first CPU pool and a second CPU pool of two or more CPU pools. The second CPU pool processes I/O operations that are determined to stall any of the CPU cores.

Abstract: Disclosed are methods, systems and computer program products for optimizing computer system resource utilization during in-game resource farming. In some non-limiting embodiments or aspects, the present disclosure describes a method for optimizing computer system resource utilization during in-game resource farming, the method including detecting a gameplay state associated with an executing instance of a gaming application and based on the detected gameplay state selecting a gaming application mode from among a plurality of available gaming application modes. In some non-limiting embodiments or aspects, the method may also include implementing the selected gaming application mode for subsequent execution of the gaming application on the computing system.