International Business Machines Corporation

Michael Feiman

Zhenhua Hu

Alicia Elena Chin

Zhimin Lin

Li Feng Zhang

Jian Tan

Lior Aronovich

Lei Su

Jason T S Lam

Hao Zhou

Xiaoqiao Meng

Yonggang Hu

Shicong Meng

Khalid Ahmed

Vincenzo Pasquantonio

Ting Xue

A system for resolving a resource deadlock between processes. A shared data structure is maintained that includes process records of the processes. Process states and process priorities are defined for each of the processes. A respective state of the process is determined for each process based on the process states and process priorities of the process records maintained in the shared data structure. The respective state is used to allocate and deallocate resources to the process to mitigate and resolve the resource deadlock between the processes.

Deadlock resolution between distributed processes

Embodiments for automatic diagonal scaling of workloads in a distributed computing environment. For each of a plurality of resources of each of a plurality of application instances, a determination as to whether a change in allocation of at least one of the plurality of resources is required. Operations requirements are computed for each of the plurality of application instances, the computed requirements including vertical increase and decrease operations, and horizontal split and collapse operations. The vertical decrease and horizontal collapse operations are first processed, the vertical increase and horizontal split operations are ordered, and the vertical increase and horizontal split operations are subsequently processed based on the ordering, thereby optimizing application efficiency and utilization of the plurality of resources in the distributed computing environment.

Automatic diagonal scaling of workloads in a distributed computing environment

Implementing a fair share of resources among one or more scheduling peers. Resource allocations are received for a plurality of scheduling peers. For each scheduling peer, a usage percentage difference is determined between their respective usage percentage and configured share ratio. For a first competing peer that is served more than a second competing peer, resource allocation is adjusted such that resources from the first competing peer are allocated to the second competing peer based, at least in part, on a time decay factor function that gives less weight to the usage percentage difference as an age of the usage percentage difference increases.

Hierarchical fairshare of multi-dimensional resources

A method to determine a hierarchical fair share of resources among one or more scheduling peers. The method determines a greatest fairness difference between the usage percentage difference of a most-served competing peer and that of a least-served competing peer. The method determines a greatest accumulated fairness difference between the accumulated usage percentage difference of the most-served competing peer and that of the least-served competing peer. The method adjusts a resource allocation such that resources from the most-served competing peer are allocated to the least-served competing peer if an adjustment condition is met, wherein the adjustment condition is based on one or both of i) the greatest fairness difference, and ii) whether the greatest accumulated fairness difference exceeds at least one threshold.

Methods and arrangements for assembling tasks in a progressive queue. At least one job is received, each job comprising a dependee set of tasks and a depender set of at least one task. The dependee tasks are assembled in a progressive queue for execution, and the dependee tasks are executed. Other variants and embodiments are broadly contemplated herein.

Interleave-scheduling of correlated tasks and backfill-scheduling of depender tasks into a slot of dependee tasks

Embodiments of the present invention provide systems and methods for allocating multiple resources. In one embodiment, a configured resource plan is used to construct a hierarchical tree. The system then identifies a set of unowned resources from the configured resource plan and sends the set of unowned resource to a share pool. The share pool is either a global or local pool and can be accessed by one or more consumers. In response to changes in workload demands, a set of unused resources are lent to a global or local pool.

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Richmond Hill, Canada

Michael Feiman