Proceedings of the fourteenth annual ACM symposium on Parallel algorithms and architectures
Non-blocking steal-half work queues
Proceedings of the twenty-first annual symposium on Principles of distributed computing
Bounds for the convergence rate of randomized local search in a multiplayer load-balancing game
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
A model-driven environment for the deployment of pervasive service-oriented applications
Proceedings of the 2009 international conference on Pervasive services
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
Performance Evaluation of Work Stealing for Streaming Applications
OPODIS '09 Proceedings of the 13th International Conference on Principles of Distributed Systems
Load balancing: toward the infinite network and beyond
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
Performance driven multi-objective distributed scheduling for parallel computations
ACM SIGOPS Operating Systems Review
A step-by-step extending parallelism approach for enumeration of combinatorial objects
ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Work-stealing with configurable scheduling strategies
Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming
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In this paper we analyse a very simple dynamic workstealing algorithm. In the work-generation model, there are n generators which are arbitrarily distributed among a set of n processors. During each time-step, with probability \lambda, each generator generates a unit-time task which it inserts into the queue of its host processor. After the new tasks are generated, each processor removes one task from its queue and services it. Clearly, the work-generation model allows the load to grow more and more imbalanced, so, even when \lambda