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Reserving resources in an on-demand compute environment

  • US 10,333,862 B2
  • Filed: 01/14/2014
  • Issued: 06/25/2019
  • Est. Priority Date: 03/16/2005
  • Status: Active Grant
First Claim
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1. A system comprising:

  • a processor; and

    a computer-readable storage medium storing code which, when executed by the processor, cause the processor to perform operations comprising;

    receiving instructions from a local resource broker based on a submission by a user, wherein the instructions are associated with compute resources to be used to process user workload, wherein the local resource broker, an on-demand compute environment and a local compute environment are each separate environments, wherein the local compute environment comprises a multiple node environment and includes an associated provider resource broker configured to manage compute resources of each node of the multiple node environment available to the user based on the submission by the user, wherein a specification of resources associated with the instructions is one of fully explicit, partially explicit, or fully implicit based on workload, and includes provisioning a support environment and adjustments to resource request timeframes including pre-allocation, allocation duration, and post-allocation timeframe adjustments;

    determining a time duration, the time duration including at least a provisioning time duration allocated for provisioning overhead, a resource consumption time duration allocated for consuming compute resources in the on-demand compute environment based on the instructions, and a clean-up time duration allocated for cleaning up the on-demand compute environment after consuming the compute resources;

    reserving, at a first time, the compute resources in the on-demand compute environment based on the instructions for use for the time duration; and

    receiving a transfer of the user workload from the local compute environment to the on-demand compute environment such that the user workload consumes the reserved compute resources in the on-demand compute environment, the user workload having been submitted to the local compute environment.

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