2024-03-28T13:11:11Zhttp://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/291192021-06-23T11:18:19Zcom_10324_1165com_10324_931com_10324_894col_10324_1337
2018-03-17T11:08:57Z
urn:hdl:10324/29119
One Tier Dataflow Programming Model for Hybrid Distributed- and Shared-Memory Systems
Fresno Bausela, Javier
González Escribano, Arturo
Llanos Ferraris, Diego Rafael
Producción Científica
Dataflow programming consists in developing a program by describing its sequential stages and the interactions between them. The runtimes supporting this kind of programming are responsible of exploiting the parallelism by concurrently executing the different stages when their dependencies have been met. In this paper we introduce a new parallel programming model and framework based on the dataflow paradigm. Its features are: It is a unique one-tier model that supports hybrid shared- and distributed-memory systems; it can express activities arbitrarily linked, including cycles; it uses a distributed work-stealing mechanism to allow Multiple-Producer/Multiple-Consumer configurations; and it has a run-time mechanism for the reconfiguration of the dependences network which also allows to create task-to-task
affinities. We present an evaluation using examples of different classes of applications. Experimental results show that programs generated using this framework deliver good performance, and that the new abstractions introduce minimal overheads.
2018-03-17T11:08:57Z
2018-03-17T11:08:57Z
2016
info:eu-repo/semantics/conferenceObject
HiPEAC 2016 Workshop on High-Level Parallel Programming for GPUs (HLPGPU), Prague, Jan. 18-20 2016.
http://uvadoc.uva.es/handle/10324/29119
eng
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Sus autores
Attribution 4.0 International
Universidad de Valladolid, Escuela de Ingeniería Informática