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Task scheduling for highly concurrent analytical and transaction workloads

Publications associées (74)

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Scheduling in datacenters is an important, yet challenging problem. Datacenters are composed of a large number, typically tens of thousands, of commodity computers running a variety of data-parallel jobs. The role of the scheduler is to assign cluster reso ...

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Universally Scalable Concurrent Data Structures

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The increase in the number of cores in processors has been an important trend over the past decade. In order to be able to efficiently use such architectures, modern software must be scalable: performance should increase proportionally to the number of all ...

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Modern computing systems are based on multi-processor systems, i.e. multiple cores on the same chip. Hard real-time systems are required to perform particular tasks within certain amount of time; failure to do so characterises an unaccepted behavior. Hard ...

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There is a trend towards increased specialization of data management software for performance reasons. The improved performance not only leads to a more efficient usage of the underlying hardware and cuts the operation costs of the system, but also is a ga ...

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Parallel execution of parsed query based on a concurrency level corresponding to an average number of available worker threads

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Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and ...

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