Extending the Task Dataflow Model with Speculative Data Accesses
Résumé
In this paper, we describe a data-centric version-based approach to extending the task dataflow model with new access types that provide speculation capabilities to applications. We further describe the performance benefits of such a model using two scenarios that model realistic applications ; the parallelization of a finite-state machine and Monte-Carlo simulations.
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