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HitFlow: A Dataflow Programming Model for Hybrid Distributed- and Shared-Memory Systems

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Abstract

Dataflow programming consists in developing a program by describing its sequential stages and the interactions between them. The runtime systems supporting this kind of programming are responsible for exploiting the parallelism by concurrently executing the different stages as soon as their dependencies are met. In this paper we introduce a new parallel programming model and framework based on the dataflow paradigm. It presents a new combination of features that allows to easily map programs to shared or distributed memory, exploiting data locality and affinity to obtain the same performance than optimized coarse-grain MPI programs. These features include: It is a unique one-tier model that supports hybrid shared- and distributed-memory systems with the same abstractions; it can express activities arbitrarily linked, including non-nested cycles; it uses internally a distributed work-stealing mechanism to allow Multiple-Producer/Multiple-Consumer configurations; and it has a runtime mechanism for the reconfiguration of the dependences and communication channels which also allows the creation of task-to-task data affinities. We present an evaluation using examples of different classes of applications. Experimental results show that programs generated using this framework deliver good performance in hybrid distributed- and shared-memory environments, with a similar development effort as other dataflow programming models oriented to shared-memory.

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Notes

  1. In the current implementation, MPI communications are always used to move tokens from queue to queue, even when the queue objects are mapped into the same MPI process. Although this simplifies the implementation and MPI communications are highly optimized in shared-memory, this decision clearly opens possibilities for further optimization.

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Acknowledgements

This research has been partially supported by MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys Project (TIN2014-58876-P), PCAS Project (TIN2017-88614-R), CAPAP-H6 (TIN2016-81840-REDT), and COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS). By Junta de Castilla y León, Project PROPHET (VA082P17). And by the computing facilities of Extremadura Research Centre for Advanced Technologies (CETA- CIEMAT), funded by the European Regional Development Fund (ERDF). CETA-CIEMAT belongs to CIEMAT and the Government of Spain.

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Authors and Affiliations

  1. Departamento de Informática, Universidad de Valladolid, Valladolid, Spain

    Javier Fresno, Daniel Barba, Arturo Gonzalez-Escribano & Diego R. Llanos

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  1. Javier Fresno
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  2. Daniel Barba
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  3. Arturo Gonzalez-Escribano
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  4. Diego R. Llanos
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Correspondence to Arturo Gonzalez-Escribano.

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Fresno, J., Barba, D., Gonzalez-Escribano, A. et al. HitFlow: A Dataflow Programming Model for Hybrid Distributed- and Shared-Memory Systems. Int J Parallel Prog 47, 3–23 (2019). https://doi.org/10.1007/s10766-018-0561-2

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