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IEEE Transactions on Neural Networks
The Task-Level Dataflow Language is a graphical language for architecture-independent parallel programming and is intended for the writing of new programs and the adaptation of existing ones. It is the first coarse-grained dataflow language that supports dynamic modification of program graphs. It provides a systematic use of program constructs to support particular programming styles, such as nondeterminism, iteration, and replication. It has been used successfully in a course on parallel programming. © 1990.
Ben Fei, Jinbai Liu
IEEE Transactions on Neural Networks
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ICIN 2013