Abstract: Execution end timing of a jobnet is predicted with stable accuracy. An information processing apparatus executes jobnet execution time prediction model generation processing for generating an execution time prediction model for predicting execution time of a jobnet to be executed on the basis of information associated with execution time of each of previously executed jobnets, a prediction model accuracy determination processing for calculating prediction accuracy for the execution time of each of jobnets by the generated execution time prediction model, and delay determination processing for determining whether to predict execution end timing of a designated jobnet among a jobnet group that is a set of a plurality of jobnets currently being executed or to be subsequently executed on the basis of the execution time prediction model, on the basis of the calculated prediction accuracy for the execution time of each of the jobnets.

Abstract: A memory device may receive, from a thread, a first request to read from a location that stores a first value, and may provide, to the thread, the first value based on receiving the first request. The memory device may receive, from the thread, a second request to cause the first value to be incremented to a second value, and may determine that the first value failed to be incremented. The memory device may provide, to the thread, information indicating that the first value failed to be incremented, and may increment a counter value to generate an incremented counter value. The memory device may receive, from the thread, a third request to cause the first value to be incremented to a third value, and may attempt, when the incremented counter value fails to satisfy a threshold, to cause the first value to be incremented to the third value.

Abstract: A hypervisor communicates with a guest operating system running in a virtual machine supported by the hypervisor using a hyper-callback whose functions are based on the particular guest operating system running the virtual machine and are triggered by one or more events in the guest operating system. The functions are modified to make sure they are safe to execute and to allow only limited access to the guest operating system. Additionally, the functions are converted to byte code corresponding to a simplified CPU and memory model and are safety checked by the hypervisor when registered with the hypervisor. The functions are executed by the hypervisor without any context switch between the hypervisor and guest operating system, and when executed, provide information about the particular guest operating system, allowing the hypervisor to improve operations such as page reclamation, virtual CPU scheduling, I/O operations, and tracing of the guest operating system.

Abstract: A system including a distributed network of one or more virtual machines, having a first portion of committed virtual machines dedicated to a user and a second portion of on-demand virtual machines. The system may also include a workload scheduler configured to receive workloads associated with the user. The scheduler may determine whether to schedule a given workload to be performed by a combination of virtual machines in the first and second portions, or by virtual machines included in only the first portion. The given workload may be scheduled to be performed by virtual machines in only the first portion at a first time if a sum of an anticipated resource consumption level of the given workload and a first consumption level of the first portion of virtual machines at the first time is less than or equals a total amount of resources included in the first portion.

Abstract: Disclosed are aspects of task assignment for systems that include graphics processing units (GPUs) that are virtual GPU (vGPU) enabled. In some examples, an algorithm is determined based on predetermined virtual machine assignment algorithms. The algorithm optimizes for a predetermined cost function. A virtual machine is queued in an arrival queue for assignment. A graphics configuration of a system is determined. The graphics configuration specifies a number of graphics processing units (GPUs) in the system. The system includes a vGPU enabled GPU. The algorithm is selected based on a correlation between the algorithm and the graphics configuration of the system. The virtual machine is assigned to a run queue based on the selected algorithm.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for acquiring information. The method may include: acquiring cloud resource use information; comparing the cloud resource use information with a use rate threshold value, to obtain a comparison result; obtaining use state information of a cloud resource corresponding to the cloud resource use information according to the comparison result; and generating cloud resource state information based on the use state information.

Abstract: A computer-implemented method, a computer program product, and a computer system for placements of workloads in a system of multiple platforms as a service. A computer detects a triggering event for modifying a matrix that pairs respective workloads on respective platforms and includes attributes of running respective workloads on respective platforms. The computer recalculates the attributes in the matrix, in response to the triggering event being detected. The computer determines optimal placements of the respective workloads on the respective platforms, based on information in the matrix. The computer places the respective workloads on the respective platforms, based on the optimal placements.

Abstract: Example implementations relate to a role-based autoscaling approach for scaling of nodes of a stateful application in a large scale virtual data processing (LSVDP) environment. Information is received regarding a role performed by the nodes of a virtual cluster of an LSVDP environment on which a stateful application is or will be deployed. Role-based autoscaling policies are maintained defining conditions under which the roles are to be scaled. A policy for a first role upon which a second role is dependent specifies a condition for scaling out the first role by a first step and a second step by which the second role is to be scaled out in tandem. When load information for the first role meets the condition, nodes in the virtual cluster that perform the first role are increased by the first step and nodes that perform the second role are increased by the second step.

Abstract: Techniques for transaction tracking for a high availability architecture are described herein. An aspect includes receiving a first request from a client, the first request corresponding to a start of a transaction having transaction affinity. Another aspect includes, based on receiving the first request from the client, generating a transaction tracking token. Another aspect includes sending the first request with the transaction tracking token to a gateway. Another aspect includes receiving a first response corresponding to the first request from the gateway, the first response including middleware instance information corresponding to a middleware instance, wherein a plurality of subsequent requests from the client corresponding to the transaction are processed by the middleware instance corresponding to the middleware instance information.

Abstract: A computer-implemented method, a computer program product, and a computer system for optimizing workload placements in a system of multiple platforms as a service. A computer first places respective workloads on respective platforms that yield lowest costs for the respective workloads. The computer determines whether mandatory constraints are satisfied. The computer checks best effort constraints, in response to the mandatory constraints being satisfied. The computer determines a set of workloads for which the best effort constraints are not satisfied and determines a set of candidate platforms that yield the lowest costs and enable the best effort constraints to be satisfied. From the set of workloads, the computer selects a workload that has a lowest upgraded cost and updates the workload by setting an upgraded platform index.

Abstract: The present disclosure relates to a method for a computer system comprising a plurality of processor cores including a first processor core and a second processor core, wherein a data item is exclusively assigned to the first processor core, of the plurality of processor cores, for executing an atomic primitive by the first processor core. The method includes receiving by the first processor core, from the second processor core, a request for accessing the data item, and in response to determining by the first processor core that the executing of the atomic primitive is not completed by the first processor core, returning a rejection message to the second processor core.

Abstract: A disclosed example method to automate deployment of a software defined data center includes generating, by executing an instruction with at least one processor, a task list based on tasks provided in an automation plan to deploy the software defined data center; determining, by executing an instruction with the at least one processor, dependencies between the tasks prior to executing the tasks; determining, by executing an instruction with the at least one processor, whether a resource that is to be an output of a first one of the tasks exists before execution of the first one of the tasks; removing, by executing an instruction with the at least one processor, the first one of the tasks from the task list when the resource exists before execution of the first one of the tasks; generating an execution schedule, by executing an instruction with the at least one processor, based on the dependencies and ones of the tasks remaining in the task list; and executing, with the at least one processor, the ones of the

Abstract: Embodiments are provided for providing workflow pipeline optimization in a computing environment. Execution of a workflow containing dependencies between one or more subject nodes and one or more observer nodes may be dynamically optimized by determining a wait time between successive executions of the workflow for the one or more observer nodes.

Abstract: Disclosed in the present invention are a distributed container image construction scheduling system and method. The system includes a construction node and a management node. The construction node includes an image constructor for executing a construction task issued by the management node. The management node includes a console and a scheduler. The console is responsible for acquiring the relevant parameters such as a development dependency library and system configuration required by a user, and generating tasks with these parameters and sending same to the scheduler. The scheduler is used for receiving the tasks sent by the console, detecting the legitimacy of the tasks, and sending the tasks to the corresponding construction node to be run.

Abstract: The present disclosure relates to a method, device and computer program product for managing jobs in a processing system. The processing system comprises multiple client devices. In the method, based on a group of jobs from the multiple client devices, a current workload of the group of jobs is determined. A group of job descriptions associated with the group of jobs is determined based on configuration information of various jobs in the group of jobs. A future workload associated with the group of jobs is determined based on associations, comprised in a workload model, between job descriptions and future workloads associated with the job descriptions. The group of jobs in the processing system are managed based on the current workload and the future workload. With the foregoing example implementation, jobs in the processing system may be managed more effectively, and latency in processing jobs may be reduced.

Abstract: A multi-cloud service mesh orchestration platform can receive a request to deploy an application as a service mesh application. The platform can tag the application with governance information (e.g., TCO, SLA, provisioning, deployment, and operational criteria). The platform can partition the application into its constituent components, and tag each component with individual governance information. For first time steps, the platform can select and perform a first set of actions for deploying each component to obtain individual rewards, state transitions, and expected returns. The platform can determine a reinforcement learning policy for each component that maximizes a total reward for the application based on the individual rewards, state transitions, and expected returns of each first set of actions selected and performed for each component. For second time steps, the platform can select and perform a second set of actions for each component based on the reinforcement learning policy for the component.

Abstract: The present disclosure relates to a dataflow optimization method for low-power operation of a multicore system, the dataflow optimization method including: a step (a) of creating an FSM including a plurality of system states in consideration of dynamic factors that trigger a transition in system states for original dataflow; and a step (b) of optimizing the original dataflow through optimization of the created FSM.

Abstract: Method, device, and computer program product for managing processes are disclosed. The method may include, in response to detecting a job to be executed in a job processing system, determining attribute information related to execution of a message queue in the job processing system; and determining, based on the attribute information, allocation information for a process to execute the job. The number of processes can be dynamically adjusted according to the current processing capacity of the job processing system, thereby improving the use of the resources of the job processing system and meanwhile avoiding crashing of the job processing system.

Abstract: A system, method and computer-readable media for managing a compute environment are disclosed. The method includes importing identity information from an identity manager into a module performs workload management and scheduling for a compute environment and, unless a conflict exists, modifying the behavior of the workload management and scheduling module to incorporate the imported identity information such that access to and use of the compute environment occurs according to the imported identity information. The compute environment may be a cluster or a grid wherein multiple compute environments communicate with multiple identity managers.

Abstract: Embodiments of an invention related to compacted context state management are disclosed. In one embodiment, a processor includes instruction hardware and state management logic. The instruction hardware is to receive a first save instruction and a second save instruction. The state management logic is to, in response to the first save instruction, save context state in an un-compacted format in a first save area. The state management logic is also to, in response to the second save instruction, save a compaction mask and context state in a compacted format in a second save area and set a compacted-save indicator in the second save area. The state management logic is also to, in response to a single restore instruction, determine, based on the compacted-save indicator, whether to restore context from the un-compacted format in the first save area or from the compacted format in the second save area.