Dataflow Programming Using AGAPIA
Ciprian Păduraru
Abstract
Ciprian Păduraru
Abstract
As distributed applications became more commonplace and more sophisticated, new programming languages and models for distributed programming were created. In the context of continuously increasing data flows in parallel applications, there is a renewed interest in the dataflow paradigm. This paper shows why AGAPIA language is suitable for dataflow programming. AGAPIA is capable of expressing massive parallelism in a manageable way for programmers, allowing building dynamic nodes and links in the data flow graph at runtime. The nodes of the dataflow graph, also called programs, are modular and reusable. The communication is transparent for users allowing them to concentrate on the high level flow and algorithm. A complete application and an analysis in terms of productivity and performance are presented in order to demonstrate the AGAPIA's capabilities.
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As distributed applications became more commonplace and more sophisticated, new programming languages and models for distributed programming were created. In the context of continuously increasing data flows in parallel applications, there is a renewed interest in the dataflow paradigm. This paper shows why AGAPIA language is suitable for dataflow programming. AGAPIA is capable of expressing massive parallelism in a manageable way for programmers, allowing building dynamic nodes and links in the data flow graph at runtime. The nodes of the dataflow graph, also called programs, are modular and reusable. The communication is transparent for users allowing them to concentrate on the high level flow and algorithm. A complete application and an analysis in terms of productivity and performance are presented in order to demonstrate the AGAPIA's capabilities.
Key concepts: Dataflow, Computer science, Dataflow architecture, Programming language, Programming paradigm, Graph, Parallel computing, Modular design