Abstract: Systems and methods for managing resource availability are disclosed. In one embodiment, a method for managing resource availability may include: (1) receiving, by a deployment computer program, an identification of a rack to build; (2) retrieving, by the deployment computer program, a plurality of application placement profiles for a plurality of applications; (3) selecting, by the deployment computer program, a subset of the applications to deploy to the rack, wherein the deployment computer program optimizes the selection based on metrics in the application placement profiles and a capacity of the rack; and (4) deploying, by the deployment computer program, the subset of applications to the rack.

Abstract: Techniques for in-band modification of event notification preferences for server events are provided. One method comprises obtaining an event notification; providing the event notification to a target device based on rule-based preferences of a user associated with the target device; obtaining a reply to the event notification from the target device, wherein the reply comprises event preferences of the user; and updating the rule-based preferences of the user based on the event preferences of the user. The updating of the rule-based preferences of the user may comprise creating, modifying and/or canceling at least one event preference rule of the user. A plurality of the event preference rules matching the event notification may be resolved in an order determined by one or more event preference rule resolution criteria.

Abstract: Concepts and technologies are disclosed herein for service creation and management. A processor can detect an event relating to a service, and access a service creation database to identify a recipe associated with the service. The recipe can define a resource to be used to provide the service. The processor can access an inventory to determine if the resource is available, identify a service control to control the service, instruct an infrastructure control to allocate virtual machines to host components of the service, and issue instructions to the service control. The instructions can instruct the service control to load service functions to the virtual machines.

Abstract: A system for coordinating data offloading includes a controller. The controller is configured to at least receive a set of data metrics corresponding to a set of vehicles, generate a set of vehicle clusters based on the set of data metrics, determine a thread distribution based on the set of vehicle clusters, and transmit a data offloading control signal to each of the set of vehicles according to the thread distribution.

Abstract: A method for graphics processing, wherein a graphics processing unit (GPU) resource is allocated among applications, such that each application is allocated a set of time slices. Commands of draw calls are loaded to rendering command buffers in order to render an image frame for a first application. The commands are processed by the GPU resource within a first time slice allocated to the first application. The method including determining at least one command has not been executed at an end of the first time slice. The method including halting execution of commands, wherein remaining one or more commands are not processed in the first time slice. A GPU configuration is preserved for the commands after processing a last executed command, the GPU configuration used when processing in a second time slice the remaining commands.

Abstract: Provided are a task allocation method and system for a solid state drive, an electronic device, and a storage medium. The task allocation method includes: dividing data managers into a plurality of data management groups; determining a service scenario according working states of all sibling master data managers; when the service scenario is a high-band-width scenario, controlling the sibling master data managers and sibling slave data managers to work in corresponding Central Processing Unit (CPU) cores, and allocating tasks to all the sibling master data managers and all the sibling slave data managers; and when the service scenario is a high-quality-of-service scenario, controlling the sibling master data managers to work in corresponding CPU cores, and allocating tasks to all the sibling master data managers.

Abstract: In various embodiments, a dispatch application performs multiply-accumulate (“MAC”) computations across parallel processing elements. In operation, the dispatch application determines a first quantity of iterations associated with a given MAC computation. The dispatch application determines a maximum number of tasks that can execute concurrently across a set of parallel processing elements. Subsequently, the dispatch application causes the maximum number of tasks to be executed concurrently across the set of parallel processing elements in order to perform the MAC computation. During execution, each task performs a substantially similar number of the first quantity of iterations. Relative to conventional tile-based approaches to performing MAC computations across parallel processing elements, the dispatch application can more evenly distribute iterations across the different parallel processing elements.

Abstract: A process for facilitating autoscaling in a stateful system is described herein. In embodiments, a set of metrics associated with a set of components of a stateful service is obtained. The set of metrics may generally indicate a utilization or a load of each of the components of the set of components (e.g., message managers and/or data stores). Thereafter, it is determined to initiate a scaling event at the stateful service in association with the set of components of the stateful service based on at least a portion of the set of metrics attaining a metric threshold indicating a threshold value for determining whether to scale stateful service components. A scaling request can then be provided to the stateful service to initiate the scaling event at the stateful service in association with the set of components of the stateful service.

Abstract: The disclosed computer-implemented method may include predicting, by a machine learning model, a user action and a timing of the user action for an application on a computing device. The method may also include determining that an expected lag in executing the user action is greater than a predetermined threshold based on one or more resource constraints of the computing device and initializing a setup of the application to reduce the expected lag in executing the user action based on the predicted timing. Furthermore, the method may include prefetching one or more application components in response to initializing the setup of the application and preprocessing at least a portion of a function of the application used to execute the user action. Finally, the method may include executing the user action for the application in response to a user request. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A computer implemented method includes granting a subscriber client access to a cloud service-based resource group within a subscriber controlled computing environment. The subscriber controlled computing environment has a virtual network. A direct network connection is established via the virtual network to a domain controller in the subscriber controlled computing environment. The virtual network is extended to a subscriber client virtual machine in a producer cloud service. The subscriber client virtual machine is then joined with the virtual network. Access to the subscriber client virtual machine is provided via the subscriber controlled computing environment and virtual network.

Abstract: A post-task-completion retention period for which a computing resource is to be retained, without de-activating the resource, on behalf of a set of requesters of machine learning tasks is determined at a machine learning service. A first task, identified at the service prior to expiration of the retention period at a first computing resource at which a second task has completed, is initiated at the first computing resource. In response to obtaining an indication of a third task and determining that a threshold criterion associated with the retention period satisfies a criterion, the third task is initiated at an additional computing resource. The additional computing resource is de-activated after the third task completes, without waiting for the retention period to expire.

Abstract: Embodiments described herein are generally directed to a controller of a managed container service that facilitates autoscaling based on bare metal machines available within a private cloud. According to an example, a CaaS controller of a managed container service monitors a metric of a cluster deployed on behalf of a customer within a container orchestration system. Responsive to a scaling event being identified for the cluster based on the monitoring and an autoscaling policy associated with the cluster, a BMaaS provider associated with the private cloud may be caused to create an inventory of bare-metal machines available within the private cloud. Finally, a bare metal machine is identified to be added to the cluster by selecting among the bare-metal machines based on the autoscaling policy, the inventory and a best fit algorithm configured in accordance with a policy established by or on behalf of the customer.

Abstract: Aspects of the disclosure include a non-transitory computer-readable medium storing thereon sequences of computer-executable instructions for automatically identifying underutilized features of an electronic device, the sequences of computer-executable instructions including instructions that instruct at least one processor to determine whether at least one underutilized-feature trigger is satisfied, identify, based on determining that the at least one underutilized-feature trigger is satisfied, at least one underutilized feature of the electronic device, identify the at least one underutilized feature of the electronic device to a user of the electronic device, and store an indication of the identification of the at least one underutilized feature of the electronic device to the user.

Abstract: A non-volatile storage system includes a memory controller and multiple integrated memory assemblies separate from and in communication with the memory controller. The integrated memory assemblies each comprises a memory die and a control die. The control die is connected (e.g., bonded) to the memory die. The memory controller and the control die include separate compute resources (e.g., each includes a processor). The storage system is configured to receive a request to perform a compute task and assign that compute task to any one or more of the memory controller and the integrated memory assemblies based on anticipated amount of data to be transferred to or from non-volatile memory for the compute task, computational resource need of the compute task, and/or available bandwidth of the memory controller and the control dies.

Abstract: The invention presents methods, systems and computer program products for optimizing computer system resource utilization during in-game resource farming. The invention comprises (i) detecting a gameplay event that triggers switching from a resource farming mode to a non-resource farming mode, or for switching from a non-resource farming mode to a resource farming mode, in connection with a runtime instance of a gaining application software, (ii) identifying a guest operating system within which the runtime instance of the gaming application software is being executed, (iii) selecting a mode switching protocol implementable within the identified guest operating system, and (iv) switching the runtime instance of the gaming application software from a resource farming mode to a non-resource farming mode, or from a non-resource farming mode to a resource farming mode, by implementing the selected mode switching protocol.

Abstract: Systems, computer-implemented methods and/or computer program products are provided for facilitating time management of a quantum program at one or more nodes of a system, such as a hybrid classical/quantum system. A system, such as a classic portion of the hybrid system, can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a time management component that can communicate with a node to trigger the node to execute one or more quantum program instructions relative to a counter of the node that is advanced by the communicating. The time management component can advance the counter at the node based upon a combination of time of another node and of a determined actual propagation time for the communicating.

Abstract: Tasks of directed acyclic graphs (DAGs) may be dynamically scheduled based on a plurality of constraints and conditions, task prioritization policies, task execution estimates, and configurations of a heterogenous system. A machine learning component may be initialized to dynamically schedule the tasks of the DAGs.

Abstract: Message passing circuitry comprises lookup circuitry responsive to a producer request indicating message data provided on a target message channel by a producer node of a system-on-chip, to obtain, from a channel consumer information structure, selected channel consumer information associated with a given consumer node subscribing to the target message channel. Control circuitry writes the message data to a location associated with an address in a consumer-defined region of address space determined based on the selected channel consumer information. When an event notification condition is satisfied for the target message channel and the given consumer node, and an event notification channel is to be used, event notification data is written to a location associated with an address in a consumer-defined region of address space determined based on event notification channel consumer information associated with the event notification channel.

Abstract: For a first server virtual machine (VM) virtualizing a logical volume in a read/write mode for a client VM, a second server VM virtualizing the logical volume in an off mode is instantiated. The logical volume comprises a virtualization of a portion of physical storage. At the first server VM, the logical volume is deactivated, the deactivating disallowing the first server VM from performing a storage request from the client VM. At the second server VM, the logical volume is activated, the activating performed by causing the second VM to virtualize the logical volume in the read/write mode, the activating allowing the second server VM to perform the storage request.

Abstract: An event monitoring system includes a processor and a storage unit. The storage unit holds an event message including a character string related to an event occurring in an information system and guide information including one or more guides. The guide includes a guide message including a predetermined character string, notified in response to the event, and information regarding a coping method for the event. The processor compares the event message and the guide, associates the guide with the event in a case where the guide further includes information for identifying a variable portion of the guide message and a portion other than the variable portion of the guide message coincides with a portion other than a portion corresponding to the variable portion in the event message, and receives an input of information indicating a correct answer of a guide to be associated with the event in a case where the guide does not include the information for identifying the variable portion.