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Dataflow architecture

About: Dataflow architecture is a(n) research topic. Over the lifetime, 1400 publication(s) have been published within this topic receiving 23800 citation(s).

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Journal ArticleDOI: 10.1109/5.381846
Edward A. Lee1, T.M. Parks1Institutions (1)
01 May 1995-
Abstract: We review a model of computation used in industrial practice in signal processing software environments and experimentally and other contexts. We give this model the name "dataflow process networks," and study its formal properties as well as its utility as a basis for programming language design. Variants of this model are used in commercial visual programming systems such as SPW from the Alta Group of Cadence (formerly Comdisco Systems), COSSAP from Synopsys (formerly Cadis), the DSP Station from Mentor Graphics, and Hypersignal from Hyperception. They are also used in research software such as Khoros from the University of New Mexico and Ptolemy from the University of California at Berkeley, among many others. Dataflow process networks are shown to be a special case of Kahn process networks, a model of computation where a number of concurrent processes communicate through unidirectional FIFO channels, where writes to the channel are nonblocking, and reads are blocking. In dataflow process networks, each process consists of repeated "firings" of a dataflow "actor." An actor defines a (often functional) quantum of computation. By dividing processes into actor firings, the considerable overhead of context switching incurred in most implementations of Kahn process networks is avoided. We relate dataflow process networks to other dataflow models, including those used in dataflow machines, such as static dataflow and the tagged-token model. We also relate dataflow process networks to functional languages such as Haskell, and show that modern language concepts such as higher-order functions and polymorphism can be used effectively in dataflow process networks. A number of programming examples using a visual syntax are given. >

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Topics: Dataflow programming (77%), Dataflow (74%), Signal programming (68%) ...read more

946 Citations


Journal ArticleDOI: 10.1109/MC.1980.1653418
Dennis1Institutions (1)
01 Nov 1980-IEEE Computer
Abstract: Programmability with increased performance? New strategies to attain this goal include two approaches to data flow architecture: data flow multiprocessors and the cell block architecture.

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Topics: Cellular architecture (69%), Dataflow architecture (67%), Unconventional computing (63%) ...read more

550 Citations


Proceedings ArticleDOI: 10.1109/ICASSP.1993.319147
J.T. Buck1, Edward A. Lee1Institutions (1)
27 Apr 1993-
Abstract: The authors build upon research by E. A. Lee (1991) concerning the token flow model, an analytical model for the behavior of dataflow graphs with data-dependent control flow, by analyzing the properties of cycles of the schedule: sequences of actor executions that return the graph to its initial state. Necessary and sufficient conditions are given for the existence of a bounded cyclic schedule as well as sufficient conditions for execution of the graph in bounded memory. The techniques presented apply to a more general class of dataflow graphs than previous methods. >

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Topics: Dataflow architecture (61%), Dataflow (60%), Bounded function (56%)

507 Citations


Journal ArticleDOI: 10.14778/1687553.1687568
Alan Gates1, Olga Natkovich1, Shubham Chopra1, Pradeep Kamath1  +5 moreInstitutions (1)
01 Aug 2009-
Abstract: Increasingly, organizations capture, transform and analyze enormous data sets. Prominent examples include internet companies and e-science. The Map-Reduce scalable dataflow paradigm has become popular for these applications. Its simple, explicit dataflow programming model is favored by some over the traditional high-level declarative approach: SQL. On the other hand, the extreme simplicity of Map-Reduce leads to much low-level hacking to deal with the many-step, branching dataflows that arise in practice. Moreover, users must repeatedly code standard operations such as join by hand. These practices waste time, introduce bugs, harm readability, and impede optimizations.Pig is a high-level dataflow system that aims at a sweet spot between SQL and Map-Reduce. Pig offers SQL-style high-level data manipulation constructs, which can be assembled in an explicit dataflow and interleaved with custom Map- and Reduce-style functions or executables. Pig programs are compiled into sequences of Map-Reduce jobs, and executed in the Hadoop Map-Reduce environment. Both Pig and Hadoop are open-source projects administered by the Apache Software Foundation.This paper describes the challenges we faced in developing Pig, and reports performance comparisons between Pig execution and raw Map-Reduce execution.

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Topics: Dataflow programming (69%), Dataflow (63%), Dataflow architecture (63%) ...read more

444 Citations


Journal ArticleDOI: 10.1109/12.48862
Arvind1, Rishiyur S. Nikhil1Institutions (1)
Abstract: The MIT Tagged-Token Dataflow Project has an unconventional, but integrated approach to general-purpose high-performance parallel computing. Rather than extending conventional sequential languages, Id, a high-level language with fine-grained parallelism and determinacy implicit in its operational semantics, is used. Id programs are compiled to dynamic dataflow graphs, which constitute a parallel machine language. Dataflow graphs are directly executed on the MIT tagged-token dataglow architecture (TTDA), a multiprocessor architecture. An overview of current thinking on dataflow architecture is provided by describing example Id programs, their compilation to dataflow graphs, and their execution on the TTDA. Related work and the status of the project are described. >

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Topics: Dataflow architecture (73%), Dataflow (70%), Signal programming (63%) ...read more

435 Citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202114
202020
201916
201824
201755
201656

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Topic's top 5 most impactful authors

Shuvra S. Bhattacharyya

29 papers, 999 citations

Marco Mattavelli

20 papers, 224 citations

Ali R. Hurson

17 papers, 249 citations

Krishna M. Kavi

16 papers, 196 citations

Guang R. Gao

15 papers, 236 citations

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