Arthur Nádas
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.
Arthur Nádas
IEEE Transactions on Neural Networks
George Saon
SLT 2014
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023