An evaluation of medium-grain dataflow code

Najjar, Walid; Roh, Lucas; Böhm, A. P. Wim

doi:10.1007/bf02577733

Cited by 6 publications

(1 citation statement)

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“…In contrast, token-based approaches [Arvind and Nikhil 1990;Ottenstein et al 1990;Najjar et al 1994] require checking the presence of the necessary tokens on incoming edges. This means that either: (1) a scanner must periodically check the schedulability of data-flow threads, or (2) data-flow threads are suspendable.…”

Section: Feed-forward Data-flow Model and Interfacementioning

confidence: 96%

OpenStream

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Cohen

2013

ACM Trans. Archit. Code Optim.

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We present OpenStream, a data-flow extension of OpenMP to express dynamic dependent tasks. The language supports nested task creation, modular composition, variable and unbounded sets of producers/consumers, and first-class streams. These features, enabled by our original compilation flow, allow translating high-level parallel programming patterns, like dependences arising from StarSs' array regions, or universal low-level primitives like futures. In particular, these dynamic features can be embedded efficiently and naturally into an unmanaged imperative language, avoiding the complexity and overhead of a concurrent garbage collector. We demonstrate the performance advantages of a data-flow execution model compared to more restricted task and barrier models. We also demonstrate the efficiency of our compilation and runtime algorithms for the support of complex dependence patterns arising from StarSs benchmarks.

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Section: Feed-forward Data-flow Model and Interfacementioning

confidence: 96%