Hybrid Dataflow/von-Neumann Architectures

General purpose hybrid dataflow/von-Neumann architectures are gaining attraction as effective parallel platforms. Although different implementations differ in the way they merge the conceptually different computational models, they all follow similar principles: they harness the parallelism and data...

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Vydané v:IEEE transactions on parallel and distributed systems Ročník 25; číslo 6; s. 1489 - 1509
Hlavní autori: Yazdanpanah, Fahimeh, Alvarez-Martinez, Carlos, Jimenez-Gonzalez, Daniel, Etsion, Yoav
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.06.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Attraction
Classification
Computation
Computational modeling
Computer architecture
Data models
Dataflow architectures
Evolution
Exploration
Harnesses
hybrid systems
Instruction sets
Mathematical models
Parallel processing
parallel processors
scheduling and task partitioning
Synchronization
von-Neumann model
ISSN:1045-9219, 1558-2183
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Shrnutí:General purpose hybrid dataflow/von-Neumann architectures are gaining attraction as effective parallel platforms. Although different implementations differ in the way they merge the conceptually different computational models, they all follow similar principles: they harness the parallelism and data synchronization inherent to the dataflow model, yet maintain the programmability of the von-Neumann model. In this paper, we classify hybrid dataflow/von-Neumann models according to two different taxonomies: one based on the execution model used for inter- and intrablock execution, and the other based on the integration level of both control and dataflow execution models. The paper reviews the basic concepts of von-Neumann and dataflow computing models, highlights their inherent advantages and limitations, and motivates the exploration of a synergistic hybrid computing model. Finally, we compare a representative set of recent general purpose hybrid dataflow/von-Neumann architectures, discuss their different approaches, and explore the evolution of these hybrid processors.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2013.125