DKPN: A Composite Dataflow/Kahn Process Networks Execution Model

被引：4
|
作者：
Arras, Paul-Antoine [1 ,2 ,3 ]
Fuin, Didier [3 ]
Jeannot, Emmanuel [2 ]
Thibault, Samuel [2 ,4 ]
机构：
[1] CEA, LIST, Gif Sur Yvette, France
[2] Inria Bordeaux Sud Ouest, LaBRI, Bordeaux, France
[3] STMicroelect, Grenoble, France
[4] Univ Bordeaux, LaBRI, Bordeaux, France
来源：
2016 24TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, AND NETWORK-BASED PROCESSING (PDP) | 2016年
关键词：
DEADLOCK DETECTION;
D O I：
10.1109/PDP.2016.34
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
To address the high level of dynamism and variability in modern streaming applications (e.g. video decoding) as well as the difficulties in programming heterogeneous MPSoCs, we propose a novel execution model based upon both dataflow and Kahn process networks. This paper presents the semantics and properties of this hierarchical and parametric model, called DKPN. Parameters are classified and it is shown that hints can be derived to improve the execution. A scheduler framework and policies to back the model are also exposed. Experiments illustrate the benefits of our approach.
引用
收藏
页码：27 / +
页数：9
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