An Autonomic-Computing Approach on Mapping Threads to Multi-cores for Software Transactional Memory

Abstract : A parallel program needs to manage the trade-off between the time spent in synchronisation and computation. This trade-off is significantly affected by its parallelism degree. A high parallelism degree may decrease computing time while increasing synchronisation cost. Furthermore, thread placement on processor cores may impact program performance, as the data access time can vary from one core to another due to intricacies of the underlying memory architecture. Alas, there is no universal rule to decide thread parallelism and its mapping to cores from an offline view, especially for a program with online behaviour variation. Moreover, offline tuning is less precise. We present our work on dynamic control of thread parallelism and mapping. We address concurrency issues via Software Transactional Memory (STM). STM bypasses locks to tackle synchronisation through transactions. Autonomic computing offers designers a framework of methods and techniques to build autonomic systems with well-mastered behaviours. Its key idea is to implement feedback control loops to design safe, efficient and predictable controllers, which enable monitoring and adjusting controlled systems dynamically while keeping overhead low. We implement feedback control loops to automate management of threads and diminish program execution time.
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Article dans une revue
Concurrency and Computation: Practice and Experience, Wiley, In press
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https://hal.archives-ouvertes.fr/hal-01742690
Contributeur : N Zhou <>
Soumis le : lundi 26 mars 2018 - 00:18:59
Dernière modification le : mercredi 11 avril 2018 - 01:59:25

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  • HAL Id : hal-01742690, version 1

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Naweiluo Zhou, Gwenaël Delaval, Bogdan Robu, Eric Rutten, Jean-François Méhaut. An Autonomic-Computing Approach on Mapping Threads to Multi-cores for Software Transactional Memory. Concurrency and Computation: Practice and Experience, Wiley, In press. 〈hal-01742690〉

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