Abstract: A system, apparatus, and method are directed to enabling a user to analyze real-time scheduling decisions of resources in a computing environment. A scheduler component maps jobs to resources, and schedule jobs for execution. In one embodiment, the scheduler component continually iterates, based on job characteristics, available resources, required resources, policies, or other constraints. While the scheduler component performs its tasks, a scheduling trace interface (STI) component may perform a trace of decisions made by the scheduler component, as well as collect static and/or dynamic state information used by the scheduler component. In one embodiment, the STI component may generate a snapshot of the scheduling decisions, and state information. A user interface may be employed to query the scheduling snapshots to monitor and analyze the scheduling decisions, and state information. In one embodiment, the user may then modify a job, the job's requirements, or the like, based on the analysis.

Abstract: Systems, methods and apparatuses (i.e., utilities) for use in performing dynamic cost model (DCM)-based scheduling of resources of a distributed computing system (e.g., server farms, computing clouds, and the like). In one arrangement, cost for consumption of a resource or type of resource of the system may be dynamically determined as a function of both a demand for and an availability of the resource. In this regard, changing demand for and/or availability of the resource over time can also adjust a cost for consumption of the resource. For instance, assigning a lower consumption cost to utilizing of a resource in low demand can benefit system operators by realizing increased use on little-used resources as well as users by allowing the users to take advantage of lower usage costs.

Abstract: Disclosed herein is a method for scheduling computing jobs for a compute farm. The method includes: receiving a plurality of computing jobs at a scheduler; assigning a signature to each computing job based on at least one computing resource requirement of the computing job; storing each computing job in a signature classification corresponding to the signature of the computing job; and scheduling at least one of the plurality of computing jobs for processing in the compute farm as a function of the signature classification.

Abstract: Systems, methods and apparatuses (i.e., utilities) for use in performing dynamic cost model (DCM)-based scheduling of resources of a distributed computing system (e.g., server farms, computing clouds, and the like). In one arrangement, cost for consumption of a resource or type of resource of the system may be dynamically determined as a function of both a demand for and an availability of the resource. In this regard, changing demand for and/or availability of the resource over time can also adjust a cost for consumption of the resource. For instance, assigning a lower consumption cost to utilizing of a resource in low demand can benefit system operators by realizing increased use on little-used resources as well as users by allowing the users to take advantage of lower usage costs.

Abstract: Disclosed herein is a method for scheduling computing jobs for a compute farm. The method includes: receiving a plurality of computing jobs at a scheduler; assigning a signature to each computing job based on at least one computing resource requirement of the computing job; storing each computing job in a signature classification corresponding to the signature of the computing job; and scheduling at least one of the plurality of computing jobs for processing in the compute farm as a function of the signature classification.

Abstract: A mechanism is provided for estimating the amount of time needed to execute a job. The mechanism receives a request to execute a new job. The mechanism processes the request to determine the job profile signature for the new job, which is based on a set of job characteristics of the new job. The mechanism also selects a candidate machine from a plurality of machines in a computing grid which contains an available time slot, and determines a machine profile signature for the candidate machine based on a set of machine characteristics of the candidate machine. The mechanism accesses and obtains from a database execution estimation information based on actual execution information associated with previously executed jobs having identical job profile signatures as the new jobs and which have been executed on machines having identical machine profile signatures as the candidate machine.

Abstract: A system, apparatus, and method are directed to enabling a user to analyze real-time scheduling decisions of resources in a computing environment. A scheduler component maps jobs to resources, and schedule jobs for execution. In one embodiment, the scheduler component continually iterates, based on job characteristics, available resources, required resources, policies, or other constraints. While the scheduler component performs its tasks, a scheduling trace interface (STI) component may perform a trace of decisions made by the scheduler component, as well as collect static and/or dynamic state information used by the scheduler component. In one embodiment, the STI component may generate a snapshot of the scheduling decisions, and state information. A user interface may be employed to query the scheduling snapshots to monitor and analyze the scheduling decisions, and state information. In one embodiment, the user may then modify a job, the job's requirements, or the like, based on the analysis.