Dataflow programming studies began in the 1970s, as the limits of von Neuman (normal) computers were found: such systems use an inherent control-driven programming model. Dataflow models are alternative to, and different from this, and are much studied and researched in many areas of basic computer science: computation models, programming languages, machine architecture, compilers, parallelism. ... [MORE] LabVIEW@ (85) Oz-Mozart@ (8) Prograph@ (24) Sisal@ (11) 1. Computation Structures Group: CSG - MIT research group which does dataflow programming research. 2. CS545S: Modular Programming - College course on basic programming concepts: modular (encapsulation, abstract data types); object-oriented (class, inheritance, polymorphism, dynamic binding); concurrent (thread, synchronization); via Java compared to Oberon, Smalltalk; then dataflow model. 3. Declarative Ada: parallel dataflow programming in a familiar context - From Proceedings of the 1995 ACM 23rd annual conference on Computer science conference. 4. Pure Data (PD) - Real-time graphical dataflow programming environment for audio, video, and graphical processing. 5. Dataflow Language - Growing article, with links to many related topics. [NodeWorks Encyclopedia] 6. ResearchIndex: Coarse-Grain Dataflow Programming of Conventional Parallel Computers - Granular Lucid, GLU: coarse-grain dataflow language for programming conventional parallel computers; based on Lucid (circa 1994) an implicitly parallel, multidimensional dataflow language. A GLU program is a Lucid program with imperatively defined data functions and data types.

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