Polyhedral Dataflow Programming: a Case Study

Abstract : Dataflow languages expose the application's potential parallelism naturally and have thus been studied and developed for the past thirty years as a solution for harnessing the increasing hardware parallelism. However, when generating code for parallel processors, current dataflow compilers only take into consideration the overall dataflow network of the application. This leaves out the potential parallelism that could be extracted from the internals of agents, typically when those include loop nests, for instance, but also potential application of intra-agent pipelining, or task splitting and rescheduling. In this work, we study the benefits of jointly using polyhedral compilation with dataflow languages. More precisely, we propose to expend the parallelization of dataflow programs by taking into account the parallelism exposed by loop nests describing the internal behavior of the program's agents. This approach is validated through the development of a prototype toolchain based on an extended version of the ΣC language. We demonstrate the benefit of this approach and the potentiality of further improvements on relevant case studies.
Document type :
Conference papers
International Symposium on Computer Architecture and and High-Performance Computing SBAC-PAD, Sep 2018, Lyon, France
Liste complète des métadonnées

Cited literature [6 references]  Display  Hide  Download

https://hal-cea.archives-ouvertes.fr/cea-01855997
Contributor : Lionel Morel <>
Submitted on : Thursday, August 9, 2018 - 11:19:15 AM
Last modification on : Thursday, August 16, 2018 - 1:11:26 AM

File

sbac18_cr.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : cea-01855997, version 1

Citation

Romain Fontaine, Laure Gonnord, Lionel Morel. Polyhedral Dataflow Programming: a Case Study. International Symposium on Computer Architecture and and High-Performance Computing SBAC-PAD, Sep 2018, Lyon, France. 〈cea-01855997v1〉

Share

Metrics

Record views

29

Files downloads

5