Abstract: An approach for a hypervisor to throttle CPU utilization based on a CPU utilization throttling request received for a data flow is presented. A method comprises receiving a request for a CPU utilization throttling. The request is parsed to extract a CPU utilization level and a data flow identifier of the data flow. Upon receiving a data packet that belongs to the data flow identified by the data flow identifier, a packet size of the data packet is determined, and a rate limit table is accessed to determine, based on the CPU utilization level and the packet size, a rate limit for the data packet. If it is determined, based at least on the rate limit, that the CPU utilization level for the data flow would be exceeded if the data packet is transmitted toward its destination, then a recommendation is generated to drop the data packet.

Abstract: The present invention relates to a Docker-container-oriented method for isolation of file system resources, which allocates host file system resources according to access requests from containers and checks lock resources corresponding to the access requests. The method creates a plurality of new containers; allocating the host file system resources according to file resource request parameters required by the new containers; and controlling execution of the file system operation according to an amount of the file system resources that have been allocated to the new containers.

Abstract: Embodiments for optimizing resource usage in a distributed computing environment. Resource usage of each task in a set of running tasks associated with a job is monitored to collect resource usage information corresponding to each respective task. A resource unit size of at least one resource allocated to respective tasks in the set of running tasks is adjusted based on the resource usage information to improve overall resource usage in the distributed computing environment.

Abstract: Aspects of the disclosure provide for mechanisms for memory protection of virtual machines in a computer system. A method of the disclosure includes: determining a plurality of host latency times for a plurality of processor power states of a processor of a host computer system; comparing, by a hypervisor executed on the host computer system, each of the host latency times to a target latency time associated with a virtual machine running on the host computer system; mapping the plurality of processor power states to a plurality of host power states in view of the comparison; and providing the host power states to the virtual machine.

Abstract: An agent and a configuration interface permit custom-level customizations for synchronizing a replica of an enterprise system over a network connection with a replicator. The replicator produces the replica as a Virtual Machine (VM) that is maintained on a portal server that is remote from an enterprise server that hosts the enterprise system.

Abstract: A time-aware application task scheduling system for a green data center (GDC) that includes a task scheduling processor coupled to one or more queue processors and an energy collecting processor connected to one or more renewable energy sources and a grid power source. The systems is capable of determining a service rate for a plurality of servers to process a plurality of application tasks in the GDC and scheduling, via processing circuitry, one or more of the application tasks to be executed in one or more of the servers at a rate according to a difference in an accumulated arriving rate for the plurality of application tasks into the one or more queues and a removal rate for the plurality of application tasks from the one or more queues. The system is further capable of removing the one or more application tasks from their associated queues for execution in the scheduled one or more servers.

Abstract: A computer-implemented method or system is provided to automate actions for one or more applications executed via a platform using at least one virtual machine in a guest system. Each virtual machine includes a guest operating system, a guest agent and an application to be executed on the virtual machine. The method or system stores in a memory user-defined automation actions and causal relationships between the user-defined automation actions from which an automation graph is derived for the application to be executed on the virtual machine on the guest system; launches the guest system and the virtual machine via the platform; and executes the user-defined automation actions via the guest agent of the virtual machine according to the automation graph after the guest system and the virtual machine are launched.

Abstract: A method for migrating a virtual machine (VM) includes establishing a first connection to a first cloud computing system executing a first VM, and establishing a second connection to a second cloud computing system managed by a second cloud provider, which is different form the first cloud provider. The method further includes instantiating a second VM designated as a destination VM in the second cloud computing system, and installing a migration agent on each of the first VM and the second VM. The migration agents execute a migration process of the first VM to the second VM by (1) iteratively copying guest data from the first VM to the second VM until a switchover criteria of the migration operation is met, and (2) copying a remainder of guest data from the first VM to the second VM when the switchover criteria is met.

Abstract: Methods and apparatus to customize deployment using approvals are disclosed. An example deployment approval manager can generate a first Approval Payload including an initial application component approval proposal of an application component that provides a logical template of an application. A deployment event broker can reply-back to the deployment approval manager with a second approval payload that includes a processed application component approval proposal.

Abstract: A method includes: receiving a service participation request of a target service transmitted by a user terminal, wherein the user terminal comprises an iOS operating system; obtaining target identification data from a system server according to the service participation request, wherein the target identification data comprises first identification data used for identifying whether the user terminal participates in the target service, and/or second identification data used for identifying whether the device data of the user terminal is modified, and the system server is a server corresponding to the iOS operating system; and according to the target identification data, determining whether to allow the user terminal to participate in the target service.

Abstract: This application relates to a resource scheduling method, a resource scheduling system, a server, and a storage medium. The resource scheduling method includes receiving a virtual machine application request sent by a terminal, wherein the virtual machine application request includes a target virtual machine label. The resource scheduling method further includes comparing the target virtual machine label with a current virtual machine label of each host computer in a cluster to determine a target host computer, wherein the target host computer includes no virtual machine label matching the target virtual machine label, enabling the target host computer to create a first virtual machine, and setting a label of the first virtual machine as the target virtual machine label.

Abstract: Systems and techniques are described for using virtual machines to write parallel and distributed applications. One of the techniques includes receiving a job request, wherein the job request specifies a first job to be performed by a plurality of a special purpose virtual machines, wherein the first job includes a plurality of tasks; selecting a parent special purpose virtual machine from a plurality of parent special purpose virtual machines to perform the first job; instantiating a plurality of child special purpose virtual machines from the selected parent special purpose virtual machine; partitioning the plurality of tasks among the plurality of child special purpose virtual machines by assigning one or more of the plurality of tasks to each of the child special purpose virtual machines; and performing the first job by causing each of the child special purpose virtual machines to execute the tasks assigned to the child special purpose virtual machine.

Abstract: A computer-implemented method including: obtaining resource availability data indicative of a set of one or more resources available at a future time period, wherein the set of one or more resources are allocable to a plurality of resource users; obtaining requirements data indicative of a requirement for a subset of the plurality of resource users to have access to a subset of the set of one or more resources; and generating a resource allocation plan for the future time period based on the resource availability data and the requirements data. Generating the resource allocation plan includes allocating, to the subset of the plurality of resource users, the subset of the set of one or more resources; and allocating, to one or more other resource users of the plurality of resource users, at least a portion of the resources remaining from the set of one or more resources.

Abstract: A semiconductor device containing a CPU capable of receiving an interrupt request signal and a task control circuit is provided. The semiconductor device includes a CPU (processor), a save circuit, and a task control circuit. The CPU includes a program counter that is updated when a task is executed. The semiconductor device includes an interrupt-related data save circuit that stores the data of the program counter when the CPU receives a CPU interrupt request signal. The data of the program counter stored in the interrupt-related data save circuit is stored in an save circuit and is used for restoring from the interrupt processing.

Abstract: For resource management for a parent child workload, a processor organizes a plurality of processes into a plurality of process groups. Each process group includes a given parent process and all child processes of the given parent process. Each process group has a process level. The processor further calculates a process cost for each process group and assigns a process priority to each process group based on the process cost for the process group. The processor iteratively assigns computing resources to subgroups of a given process group with a highest process priority at a given process level.

Abstract: A technique for workload processing includes receiving a request to process a workload by a scheduler. A determination is made whether multiple stages of processing are needed to process data of the workload. If so, a determination is made of a process needed for each stage and historical processing data is accessed to determine historical execution statistics associated with previous processing requests for a corresponding type of the workload. At each stage, a determination is made whether the data of the workload is available for processing and, if so, whether the respective process of the workload is available. If available, a determination is made as to resource availability on a computing platform for processing the workload and whether the resources available are sufficient to process the workload based on the historical execution statistics. If sufficient resources are available, processing of the workload is initiated for the respective stage.

Abstract: Provided are parallel computational methods and their implementation on memory-distributed architectures for a peptide identification tool, called HiCOPS, that enables more than 100-fold improvement in speed over existing HPC proteome database search tools. HiCOPS empowers the supercomputing database search for comprehensive identification of peptides and all their modified forms within a reasonable timeframe. Searching Gigabytes of experimental mass spectrometry data against Terabytes of databases demonstrates peptide identification in minutes compared to days or weeks, providing multiple orders of magnitude improvements in processing times. Also provided is a theoretical framework for a novel overhead-avoiding strategy, resulting in superior performance evaluation results for key metrics including execution time, CPU utilization, and I/O efficiency.

Abstract: Methods, systems, and computer-readable media for job execution with managed compute environments are disclosed. A specification of a managed compute environment comprises one or more constraints associated with computing resources in the managed compute environment. A queue or other data structure that is associated with the managed compute environment is monitored. The data structure is configured to store jobs. Data indicative of a job is detected in the data structure. One or more computing resources are reserved for the job from a pool of available computing resources. The one or more computing resources are selected for the job based at least in part on the one or more constraints associated with computing resources in the managed compute environment. Execution of the job using the one or more computing resources is initiated.

Abstract: Various examples are directed to systems and methods for managing resources in a multi-core computing system. A first thread executing at a first core of a multi-core processor unit may allocate a first element of a resource. The first thread may increment a first thread counter for a first metric describing the resource. The first thread may determine that the first thread counter is greater than a first thread counter threshold and update a first metric global value based at least in part on the first thread counter. The first thread may also reset the first thread counter.

Abstract: Balancing a recurring task between multiple worker processes is disclosed. Each of a plurality of worker processes attempt, over a period of time, to acquire a task lock. A first worker process of the plurality of worker processes acquires the task lock. The first worker process performs a task that is associated with the task lock and sets a timer for an amount of time that prevents acquisition of the task lock by any other worker process for the amount of time.