Abstract: Embodiments described herein relate to systems and methods for identifying virtual machines in a network. The systems and methods comprise a virtual asset tool that can interface with a virtualization manager to receive metadata identifying virtual machines hosted by a plurality of physical machines. The virtual asset tool can subscribe to updates associated with the virtual machines, such as changes to the virtual machines, or additions or deletions of virtual machines. In response to receiving an update, the virtual asset tool can modify an asset record associated with the virtual machines and any corresponding descriptions. In embodiments, the virtual asset tool can schedule vulnerability scans for any or all of the virtual machines.

Abstract: The present subject matter relates to categorizing virtual machines of a virtual machine environment into predefined service level buckets. The predefined service level buckets are indicative of different levels of application based services that are to be applied to the virtual machines. In one implementation, specifications of information technology (IT) resources allocated to each of the virtual machines are obtained. A weighted average score for each virtual machine with respect to each of the specifications of IT resources is determined. The weighted average score is indicative of a relative level of importance of the corresponding virtual machine with respect to the corresponding specification of IT resource for providing at least one business service using the virtual machine environment. Each virtual machine is assigned to one of the predefined service level buckets based on a total weighted average score for the each virtual machine.

Abstract: A snapshot of a remote virtual machine within a cluster of nodes is taken by using an image writer with a snapshot provider. A set of backup components is recorded by using a cluster interface. The remote virtual machine is reconstructed by using the snapshot and a framework with the set of backup components.

Abstract: In one embodiment, a method includes empirically analyzing a set of active reservations and a current set of consumable resources belonging to a class of consumable resources. Each active reservation is of a managed task type and includes a group of one or more tasks requiring access to a consumable resource of the class. The method further includes, based on the empirically analyzing, clocking the set of active reservations each clocking cycle. In addition, the method includes, responsive to the clocking, sorting a priority queue of the set of active reservations.

Abstract: Systems and methods for improving response times in based on application states. In some embodiments, an Information Handling System (IHS) may include a Central Processing Unit (CPU) and a hardware memory storage device coupled to the CPU, the hardware memory storage device having program instructions stored thereon that, upon execution by the CPU, configure the IHS to: identify a first state of an application being executed by the CPU at runtime; identify a trigger event configured to cause the IHS to change from the first state to a second state; in response to the trigger event, switch from the first state to a second state, wherein the first state is associated with first hardware configuration and the second state is associated with a second hardware configuration; and in response to the trigger event, switch the first hardware configuration to the second hardware configuration.

Abstract: A method, system, and computer program product for automatically generating service definitions for application clients of a message broker is provided. The method includes retrieving a trace of interactions between different application instances and corresponding message queues in a message brokering system. Thereafter, messages in the trace can be analyzed to identify the application instances and related message exchange data. Finally, a service definition document can be generated for each identified application instance using the related message exchange data to describe computational services provided by the identified application instance.

Abstract: A method and apparatus for batch-processing multiple data in an electronic device are provided. A method for batch-processing multiple data in a first processor includes transmitting batching data configuration information to a second processor of the electronic device according to batching option information of at least one application; receiving, from the second processor, batching data including at least one data acquired via at least one sensor of the electronic device based on the batching data configuration information; and batch-processing the received batching data according to the batching option information, for the at least one application.

Abstract: A system may perform work stealing using a dynamically configurable separation between stealable and non-stealable work items. The work items may be held in a double-ended queue (deque), and the value of a variable (index) may indicate the position of the last stealable work item or the first non-stealable work item in the deque. A thread may steal a work item only from the portion of another thread's deque that holds stealable items. The owner of a deque may add work items to the deque and may modify the number or percentage of stealable work items, the number or percentage of non-stealable work items, and/or the ratio between stealable and non-stealable work items in the deque during execution. For example, the owner may convert stealable work items to non-stealable work items, or vice versa, in response to changing conditions and/or according to various work-stealing policies.

Abstract: The present disclosure provides modular electronic devices that are capable of predicting future availability of module combinations and associated computing resources and/or capable of predicting future tasks. Based on such predictions, the module or modular electronic device can choose to schedule or delay certain tasks, alter resource negotiation behavior/strategy, or select from among various different resource providers. As an example, a modular electronic device of the present disclosure can identify one or more computing tasks to be performed; predict one or more future sets of computing resources that will be respectively available to the modular electronic device at one or more future time periods; and determine a schedule for performance of the one or more computing tasks based at least in part on the prediction of the one or more future sets of computing resources that will be respectively available at the one or more future time periods.

Abstract: A technique for managing distributed computing resources in a virtual computing environment is disclosed. In an embodiment, a method includes receiving a recommended change to a virtual architecture of a virtual computing environment; determining an impact on current workload in the virtual computing environment if the recommended change is performed; determining an impact on future workload in the virtual computing environment if the recommended change is performed; calculating a combined impact on current and future workload; determining if the combined impact is above or below a threshold; if the combined impact on current and future workload is below the threshold, do not perform the recommended change; and if the combined impact on current and future workload is above the threshold, perform the recommended change.

Abstract: Embodiments include computing devices, apparatus, and methods implemented by the apparatus for implementing speculative loop iteration partitioning (SLIP) for heterogeneous processing devices. A computing device may receive iteration information for a first partition of iterations of a repetitive process and select a SLIP heuristic based on available SLIP information and iteration information for the first partition. The computing device may determine a split value for the first partition using the SLIP heuristic, and partition the first partition using the split value to produce a plurality of next partitions.

Abstract: Embodiments are provided that include the use of a cancellable command application programming interface (API) framework that provides cooperative multitasking for synchronous and asynchronous operations based in part on a command timing sequence and a cancellable command API definition. A method of an embodiment enables a user or programmer to use a cancellable command API definition as part of implementing a responsive application interface using a command timing sequence to control execution of active tasks. A cancellable command API framework of an embodiment includes a command block including a command function, a task engine to monitor the command function, and a timer component to control execution of asynchronous and synchronous tasks based in part on first and second control timing intervals associated with a command timing sequence. Other embodiments are also disclosed.

Abstract: In one embodiment, a method includes calculating ideal resource apportionments from a current set of consumable resources for each of a plurality of reservations. Each reservation corresponds to one of a plurality of customers. The method further includes running an apportionment process relative to the plurality of reservations. The running includes attempting to apportion to each reservation its ideal resource apportionment. The running yields an actual resource apportionment for each reservation. Each customer's actual resource apportionment comprises a sum of the actual resource apportionments for the customer's reservations. In addition, the method includes, responsive to an indication of unapportioned resources following the running, performing a first optimization to increase resource utilization by at least one needy customer.

Abstract: A parallel arithmetic device includes a plurality of computing nodes; and a management node coupled to the plurality of computing nodes and including a computer, the management node being configured to calculate a degree of increasing a priority of each of a plurality of users, based on a degree of increasing the priority of the user depending on resource distribution to the user as time elapses and a difference between a current time instant and a future time instant, the priority being to be used in determining one of the plurality of users that has a job to which a computing resource at a first time instant being later than the current time instant is to be allocated.

Abstract: Aspects include computing devices, systems, and methods for implementing scheduling and execution of lightweight kernels as simple tasks directly by a thread without setting up a task structure. A computing device may determine whether a task pointer in a task queue is a simple task pointer for the lightweight kernel. The computing device may schedule a first simple task for the lightweight kernel for execution by the thread. The computing device may retrieve, from an entry of a simple task table, a kernel pointer for the lightweight kernel. The entry in the simple task table may be associated with the simple task pointer. The computing device may directly execute the lightweight kernel as the simple task.

Abstract: A set of like tasks to be performed is organized into a first group. A last used processing group assigned to the set of like tasks is stored. The set of like tasks is reassigned to an additional group having a minimal queue length upon a determination that the difference between the queue lengths of the additional processing group and the stored processing group is greater than a predetermined threshold.

Abstract: The efficient use of threads that issue calls to log events. While waiting for the call to return or complete, the threads are put to work on other tasks that are not part of the process that generated the event. This can occur without context switching of the thread, especially when the task to be performed is state-less or context free. In the efficient thread diversion process, the thread calls a logging component to log an event. This blocks the thread from continuing work on a process that the event is part of until the event is logged. The thread then performs a diversion task that is not part of the processing unit that the event is part of. After detecting that the event has logged, the thread continues work on the processing unit that the event is part of.

Abstract: A system includes a plurality of physical calculation nodes and a controller. The controller is configured to execute a process including: determining a type of a target job based on a processing load for execution of the target job, first instructing a first physical calculation node among the plurality of physical calculation nodes to execute the target job when it is determined that the type of the target job is a first type, and second instructing a virtual machine running on a second physical calculation node among the plurality of physical calculation nodes to execute the target job when it is determined that the type of the target job is a second type, a job of the second type being required a lower processing load for the execution of the job than a job of the first type.