AUTOMATICALLY ORCHESTRATING A COMPUTERIZED WORKFLOW

    公开(公告)号:US20230409386A1

    公开(公告)日:2023-12-21

    申请号:US17840698

    申请日:2022-06-15

    CPC classification number: G06F9/4881 G06F9/4856 G06N7/005

    Abstract: The method performs at the orchestration interface at which update information, including changes to tasks of a workflow, is received from a task manager system (TMS), where the workflow includes a set of tasks, inputs to the tasks, and outputs from the tasks. The inputs and outputs determine runtime dependencies between the tasks. Based on the update information received, the orchestration interface populates a topology of nodes and edges as a directed acyclic graph (DAG) that maps nodes to tasks and edges to runtime dependencies between tasks, based on node inputs and outputs. The orchestration interface instructs the execution of the tasks and handling dependencies by interacting with a task execution system (TES) and by traversing the DAG, the orchestration interface identifies tasks that depend on completed tasks as per the runtime dependencies and instructs the TES to execute the dependent tasks identified.

    Computing system performance adjustment via temporary and permanent resource allocations

    公开(公告)号:US11681556B2

    公开(公告)日:2023-06-20

    申请号:US16821171

    申请日:2020-03-17

    Abstract: The invention relates to a method for adjusting a performance of a computing system, the method comprising receiving by the computing system at least one command to execute a computational workload from a client, applying by the computing system an identification method identifying a first system resource of the system resources which limits an execution performance of the computational workload, performing a temporary adjustment of an allocation of the first system resource to the client and evaluating whether this improves an execution performance of the computational workload, and, if this is the case, offering to the client to permanently adjust the allocation of the first system resource to the client and adjusting the allocation of the first system resource to the client permanently in case of receiving a corresponding instruction from the client. The invention also relates to a computing system and a computer program product which implement the method.

    ADJUSTING PERFORMANCE OF A COMPUTING SYSTEM

    公开(公告)号:US20210294656A1

    公开(公告)日:2021-09-23

    申请号:US16821171

    申请日:2020-03-17

    Abstract: The invention relates to a method for adjusting a performance of a computing system, the method comprising receiving by the computing system at least one command to execute a computational workload from a client, applying by the computing system an identification method identifying a first system resource of the system resources which limits an execution performance of the computational workload, performing a temporary adjustment of an allocation of the first system resource to the client and evaluating whether this improves an execution performance of the computational workload, and, if this is the case, offering to the client to permanently adjust the allocation of the first system resource to the client and adjusting the allocation of the first system resource to the client permanently in case of receiving a corresponding instruction from the client. The invention also relates to a computing system and a computer program product which implement the method.

    SELECTING BEST CLOUD COMPUTING ENVIRONMENT IN A HYBRID CLOUD SCENARIO

    公开(公告)号:US20230259401A1

    公开(公告)日:2023-08-17

    申请号:US17651186

    申请日:2022-02-15

    Abstract: Embodiments for identifying an optimal cloud computing environment for a computing task is disclosed. Embodiments comprises receiving a computing task to be executed in a cloud computing environment, wherein the computing task requires a set of cloud computing environment parameter values of the cloud computing environment, pre-selecting a set of candidate cloud computing environments, each of which meets the set of cloud computing environment parameter values, ranking the candidate cloud computing environments using reward-based ranking parameter values of the candidate cloud computing environments as an additional selection constraint, and selecting the highest ranking cloud computing environment as the optimal cloud computing environment for the computing task. Furthermore, embodiments comprise executing the computing task in the optimal cloud computing environment, monitoring execution when executing the computing task, and updating parameter values of the reward-based ranking for the selected optimal cloud computing environment.

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