RTL fast convolution using the mersenne number transform

Autores
Bria, Oscar N.; Villagarcía Wanza, Horacio A.
Año de publicación
1997
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
VHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform. For filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here. Each partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular. In this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT. This work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation.
Eje: Procesamiento distribuido y paralelo. Tratamiento de señales
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Fast Convolution
Mersenne Number Transform
Languages
RTL
Distributed
Parallel processing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23905

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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling RTL fast convolution using the mersenne number transformBria, Oscar N.Villagarcía Wanza, Horacio A.Ciencias InformáticasFast ConvolutionMersenne Number TransformLanguagesRTLDistributedParallel processingVHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform. For filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here. Each partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular. In this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT. This work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI)1997info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23905enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2026-06-23T10:18:33Zoai:sedici.unlp.edu.ar:10915/23905Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292026-06-23 10:18:33.339SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv RTL fast convolution using the mersenne number transform
title RTL fast convolution using the mersenne number transform
spellingShingle RTL fast convolution using the mersenne number transform
Bria, Oscar N.
Ciencias Informáticas
Fast Convolution
Mersenne Number Transform
Languages
RTL
Distributed
Parallel processing
title_short RTL fast convolution using the mersenne number transform
title_full RTL fast convolution using the mersenne number transform
title_fullStr RTL fast convolution using the mersenne number transform
title_full_unstemmed RTL fast convolution using the mersenne number transform
title_sort RTL fast convolution using the mersenne number transform
dc.creator.none.fl_str_mv Bria, Oscar N.
Villagarcía Wanza, Horacio A.
author Bria, Oscar N.
author_facet Bria, Oscar N.
Villagarcía Wanza, Horacio A.
author_role author
author2 Villagarcía Wanza, Horacio A.
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Fast Convolution
Mersenne Number Transform
Languages
RTL
Distributed
Parallel processing
topic Ciencias Informáticas
Fast Convolution
Mersenne Number Transform
Languages
RTL
Distributed
Parallel processing
dc.description.none.fl_txt_mv VHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform. For filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here. Each partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular. In this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT. This work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation.
Eje: Procesamiento distribuido y paralelo. Tratamiento de señales
Red de Universidades con Carreras en Informática (RedUNCI)
description VHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform. For filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here. Each partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular. In this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT. This work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation.
publishDate 1997
dc.date.none.fl_str_mv 1997
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23905
url http://sedici.unlp.edu.ar/handle/10915/23905
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
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