A Survey of Parametric Dataflow Models of Computation
Dataflow models of computation (MoCs) are widely used to design embedded signal processing and streaming systems. Dozens of dataflow MoCs have been proposed in the past few decades. More recently, several parametric dataflow MoCs have been presented as an interesting tradeoff between analyzability a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Bouakaz, Adnan [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: ACM transactions on design automation of electronic systems - New York, NY : ACM Press, 1996, 22(2017), 2, Seite 1-25 |
|---|---|
| Übergeordnetes Werk: |
volume:22 ; year:2017 ; number:2 ; pages:1-25 |
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| DOI / URN: |
10.1145/2999539 |
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| 520 | |a Dataflow models of computation (MoCs) are widely used to design embedded signal processing and streaming systems. Dozens of dataflow MoCs have been proposed in the past few decades. More recently, several parametric dataflow MoCs have been presented as an interesting tradeoff between analyzability and expressiveness. They offer a controlled form of dynamism under the form of parameters (e.g., parametric rates), along with runtime parameter configuration. This survey provides a comprehensive description of the existing parametric dataflow MoCs (constructs, constraints, properties, static analyses) and compares them using a common example. The main objectives are to help designers of streaming applications choose the most suitable model for their needs and pave the way for the design of new parametric MoCs. | ||
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10.1145/2999539 doi PQ20170206 (DE-627)OLC1989635067 (DE-599)GBVOLC1989635067 (PRQ)a519-411f6edfdcbc36d437a288cd8140d8472db8ec5a895d96ce45ffcd9ff3d52cb30 (KEY)0304613320170000022000200001surveyofparametricdataflowmodelsofcomputation DE-627 ger DE-627 rakwb eng 540 620 DE-600 54.00 bkl Bouakaz, Adnan verfasserin aut A Survey of Parametric Dataflow Models of Computation 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Dataflow models of computation (MoCs) are widely used to design embedded signal processing and streaming systems. Dozens of dataflow MoCs have been proposed in the past few decades. More recently, several parametric dataflow MoCs have been presented as an interesting tradeoff between analyzability and expressiveness. They offer a controlled form of dynamism under the form of parameters (e.g., parametric rates), along with runtime parameter configuration. This survey provides a comprehensive description of the existing parametric dataflow MoCs (constructs, constraints, properties, static analyses) and compares them using a common example. The main objectives are to help designers of streaming applications choose the most suitable model for their needs and pave the way for the design of new parametric MoCs. Dataflow graphs reconfiguration parameterization static analysis Fradet, Pascal oth Girault, Alain oth Enthalten in ACM transactions on design automation of electronic systems New York, NY : ACM Press, 1996 22(2017), 2, Seite 1-25 (DE-627)214067289 (DE-600)1325337-2 (DE-576)053039084 1084-4309 nnns volume:22 year:2017 number:2 pages:1-25 http://dx.doi.org/10.1145/2999539 Volltext http://dl.acm.org/citation.cfm?id=2999539 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 54.00 AVZ AR 22 2017 2 1-25 |
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10.1145/2999539 doi PQ20170206 (DE-627)OLC1989635067 (DE-599)GBVOLC1989635067 (PRQ)a519-411f6edfdcbc36d437a288cd8140d8472db8ec5a895d96ce45ffcd9ff3d52cb30 (KEY)0304613320170000022000200001surveyofparametricdataflowmodelsofcomputation DE-627 ger DE-627 rakwb eng 540 620 DE-600 54.00 bkl Bouakaz, Adnan verfasserin aut A Survey of Parametric Dataflow Models of Computation 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Dataflow models of computation (MoCs) are widely used to design embedded signal processing and streaming systems. Dozens of dataflow MoCs have been proposed in the past few decades. More recently, several parametric dataflow MoCs have been presented as an interesting tradeoff between analyzability and expressiveness. They offer a controlled form of dynamism under the form of parameters (e.g., parametric rates), along with runtime parameter configuration. This survey provides a comprehensive description of the existing parametric dataflow MoCs (constructs, constraints, properties, static analyses) and compares them using a common example. The main objectives are to help designers of streaming applications choose the most suitable model for their needs and pave the way for the design of new parametric MoCs. Dataflow graphs reconfiguration parameterization static analysis Fradet, Pascal oth Girault, Alain oth Enthalten in ACM transactions on design automation of electronic systems New York, NY : ACM Press, 1996 22(2017), 2, Seite 1-25 (DE-627)214067289 (DE-600)1325337-2 (DE-576)053039084 1084-4309 nnns volume:22 year:2017 number:2 pages:1-25 http://dx.doi.org/10.1145/2999539 Volltext http://dl.acm.org/citation.cfm?id=2999539 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 54.00 AVZ AR 22 2017 2 1-25 |
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Dataflow models of computation (MoCs) are widely used to design embedded signal processing and streaming systems. Dozens of dataflow MoCs have been proposed in the past few decades. More recently, several parametric dataflow MoCs have been presented as an interesting tradeoff between analyzability and expressiveness. They offer a controlled form of dynamism under the form of parameters (e.g., parametric rates), along with runtime parameter configuration. This survey provides a comprehensive description of the existing parametric dataflow MoCs (constructs, constraints, properties, static analyses) and compares them using a common example. The main objectives are to help designers of streaming applications choose the most suitable model for their needs and pave the way for the design of new parametric MoCs. |
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Dataflow models of computation (MoCs) are widely used to design embedded signal processing and streaming systems. Dozens of dataflow MoCs have been proposed in the past few decades. More recently, several parametric dataflow MoCs have been presented as an interesting tradeoff between analyzability and expressiveness. They offer a controlled form of dynamism under the form of parameters (e.g., parametric rates), along with runtime parameter configuration. This survey provides a comprehensive description of the existing parametric dataflow MoCs (constructs, constraints, properties, static analyses) and compares them using a common example. The main objectives are to help designers of streaming applications choose the most suitable model for their needs and pave the way for the design of new parametric MoCs. |
| abstract_unstemmed |
Dataflow models of computation (MoCs) are widely used to design embedded signal processing and streaming systems. Dozens of dataflow MoCs have been proposed in the past few decades. More recently, several parametric dataflow MoCs have been presented as an interesting tradeoff between analyzability and expressiveness. They offer a controlled form of dynamism under the form of parameters (e.g., parametric rates), along with runtime parameter configuration. This survey provides a comprehensive description of the existing parametric dataflow MoCs (constructs, constraints, properties, static analyses) and compares them using a common example. The main objectives are to help designers of streaming applications choose the most suitable model for their needs and pave the way for the design of new parametric MoCs. |
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| title_short |
A Survey of Parametric Dataflow Models of Computation |
| url |
http://dx.doi.org/10.1145/2999539 http://dl.acm.org/citation.cfm?id=2999539 |
| remote_bool |
false |
| author2 |
Fradet, Pascal Girault, Alain |
| author2Str |
Fradet, Pascal Girault, Alain |
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214067289 |
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n |
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false |
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| author2_role |
oth oth |
| doi_str |
10.1145/2999539 |
| up_date |
2024-07-03T22:14:06.418Z |
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1803597744879697920 |
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7.4000597 |