An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations

Detalhes bibliográficos
Autor(a) principal: Perleberg, Murilo Roschildt
Data de Publicação: 2020
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional da UFPel - Guaiaca
Texto Completo: http://guaiaca.ufpel.edu.br/handle/prefix/6089
Resumo: Currently, there is a growing demand for video streaming through the internet, and also a crescent number of portable devices capable of capture and reproduce those videos. Moreover, the 3D videos allow an improved user experience when compared with traditional videos, since in the 3D videos the scene is simultaneously captured from different points of view. However, due to the amount of data required to represent digital videos, compression techniques are mandatory, which are a series of tools responsible for reducing the redundancies present in video data. In the 3D-High Efficiency Video Coding (3D-HEVC) standard, the most complex tool is the Motion Estimation (ME), while it is also responsible for a huge part of the compression efficiency of this standard. The ME is divided in Integer ME (IME), which performs the comparison a block from the frame being encoded with several candidate blocks from already encoded frames, searching for the candidate block most similar with the block being encoded, and the Fractional ME (FME), which performs a refinement around the candidate result of the IME. By default, the 3D-HEVC adopts the Test Zone Search (TZS) algorithm to select the candidates to be evaluated in the IME, since the TZS evaluates a reduced number of candidates without result in huge losses in image quality when compared with a full search algorithm, which compares all possible candidate blocks. Also, in 3D-HEVC the IME was applied in up to 24 different block sizes. This implies several redundant operations, where parts from a specific candidate can be compared with part of the block being encoded several times, besides a huge memory communication to perform the processing of several block sizes of each candidate block. Aiming at reducing these operation redundancies, it is possible to reuse the operations performed to small block sizes to compose the result of higher block sizes. This strategy also allows data reuse, since it reduces the memory access needed to obtain the samples to process all block sizes. There have only a few works on literature proposing hardware architectures for the IME of the 3D-HEVC standard. Between the IME works of other video coding standards, only a few presents solutions considering data and operations reuse strategies and a fast algorithm as TZS. Therefore, this work presents an IME hardware design adopting the TZS algorithm, with support to all block sizes supported by 3D-HEVC standard and with operations and data reuse strategies to take advantage of already processed operations and reduce the memory communication. The 3D-HEVC IME algorithm was modified aiming at an efficient hardware implementation, and the evaluations show that these modifications present an increase of 9.016% in the BD-rate metric. The developed IME architecture was synthesized for an ASIC with TSMC 40nm standard cells technology, and the results show that the hardware requires 269 K gates, while dissipates 108.48 mW when processing 3 views from different cameras, where each view is composed by the video of the two channels (Texture and Depth Maps) with FHD 1920x1080p resolution with 30 frames per second. The synthesis results have also indicated that the IME hardware design can process up to 3 views with UHD 3840x2160p resolution with 60 frames per second. Moreover, an FME architecture was also presented, which is able to evaluate all possible 48 fractional blocks around the IME result.
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spelling 2020-06-29T12:49:49Z2020-06-29T12:49:49Z2020-04-06PERLEBERG, Murilo Roschildt. An Energy-Efficient Hardware Design for the 3DHEVC Motion Estimation Adopting Reuse Strategies for Data and Operations. Advisor: Marcelo Schiavon Porto. 2020. 88 f. Dissertation (Masters in Computer Science) – Technology Development Center, Federal University of Pelotas, Pelotas, 2020.http://guaiaca.ufpel.edu.br/handle/prefix/6089Currently, there is a growing demand for video streaming through the internet, and also a crescent number of portable devices capable of capture and reproduce those videos. Moreover, the 3D videos allow an improved user experience when compared with traditional videos, since in the 3D videos the scene is simultaneously captured from different points of view. However, due to the amount of data required to represent digital videos, compression techniques are mandatory, which are a series of tools responsible for reducing the redundancies present in video data. In the 3D-High Efficiency Video Coding (3D-HEVC) standard, the most complex tool is the Motion Estimation (ME), while it is also responsible for a huge part of the compression efficiency of this standard. The ME is divided in Integer ME (IME), which performs the comparison a block from the frame being encoded with several candidate blocks from already encoded frames, searching for the candidate block most similar with the block being encoded, and the Fractional ME (FME), which performs a refinement around the candidate result of the IME. By default, the 3D-HEVC adopts the Test Zone Search (TZS) algorithm to select the candidates to be evaluated in the IME, since the TZS evaluates a reduced number of candidates without result in huge losses in image quality when compared with a full search algorithm, which compares all possible candidate blocks. Also, in 3D-HEVC the IME was applied in up to 24 different block sizes. This implies several redundant operations, where parts from a specific candidate can be compared with part of the block being encoded several times, besides a huge memory communication to perform the processing of several block sizes of each candidate block. Aiming at reducing these operation redundancies, it is possible to reuse the operations performed to small block sizes to compose the result of higher block sizes. This strategy also allows data reuse, since it reduces the memory access needed to obtain the samples to process all block sizes. There have only a few works on literature proposing hardware architectures for the IME of the 3D-HEVC standard. Between the IME works of other video coding standards, only a few presents solutions considering data and operations reuse strategies and a fast algorithm as TZS. Therefore, this work presents an IME hardware design adopting the TZS algorithm, with support to all block sizes supported by 3D-HEVC standard and with operations and data reuse strategies to take advantage of already processed operations and reduce the memory communication. The 3D-HEVC IME algorithm was modified aiming at an efficient hardware implementation, and the evaluations show that these modifications present an increase of 9.016% in the BD-rate metric. The developed IME architecture was synthesized for an ASIC with TSMC 40nm standard cells technology, and the results show that the hardware requires 269 K gates, while dissipates 108.48 mW when processing 3 views from different cameras, where each view is composed by the video of the two channels (Texture and Depth Maps) with FHD 1920x1080p resolution with 30 frames per second. The synthesis results have also indicated that the IME hardware design can process up to 3 views with UHD 3840x2160p resolution with 60 frames per second. Moreover, an FME architecture was also presented, which is able to evaluate all possible 48 fractional blocks around the IME result.Atualmente existe uma grande demanda por streaming de vídeos digitais através da internet, além de um crescente número de dispositivos móveis capazes de gravar e reproduzir estes vídeos. Além disso, vídeos em 3 Dimensões (3D) permitem ainda uma experiência maior do usuário se comparado com os videos tradicionais, visto que nos videos 3D a cena é capturada de pontos de vista diferentes. Contudo, devido a grande quantidade de dados necessários para representar os vídeos digitais, técnicas de compressão se tornam obrigatórias, as quais são uma série de ferramentas responsáveis por reduzir as redundâncias presentes nos dados dos vídeos. No padrão 3D-High Efficiency Video Coding (3D-HEVC), a etapa mais complexa é a Estimação de Movimento (ME), a qual é também a etapa responsável por grande parte da eficiência de compressão deste padrão. A ME é divida em Estimação de Movimento Inteira (IME), a qual realiza a comparação de um bloco do quadro que está sendo codificado com diversos blocos candidatos de quadros já codificados em busca do bloco candidato mais similar ao bloco sendo codificado, e a Estimação de Movimento Fracionária (FME), a qual realiza um refinamento sobre o candidato resultante da IME. Por padrão, o 3D-HEVC utiliza o algoritmo Test Zone Search (TZS) para escolher os candidatos a serem avaliados pela IME, visto que o TZS realiza a avaliação de um número reduzido de candidatos sem resultar em grandes perdas na qualidade da imagem quando comparado com o algoritmo de busca completa, que avalia todos os blocos possíveis. Além disso, no 3D-HEVC a ME pode ser aplicada sobre blocos de até 24 diferentes tamanhos. Isso implica na ocorrência de diversas operações redundantes, onde uma parte de um dos blocos candidatos pode ser comparada com uma parte do bloco sendo codificado inúmeras vezes, além de uma enorme comunicação com a memória para realizar o processamento dos diferentes tamanhos de bloco de cada bloco candidato. Visando a redução das operações redundantes, é possível reutilizar as operações realizadas em blocos pequenos para compor o resultado dos blocos maiores. Esta estratégia também permite o reuso de dados, visto que será reduzindo o número de acessos a memória necessários para obter as amostras de todos os tamanhos de bloco. Existem apenas poucos trabalhos na literatura propondo arquiteturas de hardware para a IME do padrão 3D-HEVC. Dos trabalhos de IME para outros padrões de codificação, apenas poucos apresentam soluções considerando estratégias de reuso de dados e operações e um algoritmo rápido como o TZS. Portanto, este trabalho apresenta uma arquitetura de IME adotando o algoritmo TZS, com suporte a todos os tamanhos de bloco suportados pelo 3D-HEVC e utilizando estratégias de reuso de operações para obter vantagem das operações já processados. O algoritmo de IME do 3D-HEVC foi alterado visando uma implementação de hardware eficiente, e experimentos mostraram que essas modificações apresentam um aumento de 9,016% na métrica BD-rate. A arquitetura de IME desenvolvida foi sintetizada para ASIC utilizando a biblioteca de células padrão de 40nm da TSMC, e os resultados mostraram que a arquitetura requer 269 K gates, enquanto dissipa 108,48 mW quando processa 3 vistas de diferentes câmeras, sendo cada vista é composta pelo video dos 2 canais (textura e mapas de profundidade) com resolução de FHD 1920x1080p com 30 quadros por segundo. Os resultados de síntese também mostraram que a arquitetura de IME é capaz de processar até 3 vistas com resolução UHD 3840x2160p e com uma taxa de mostragem de 60 quadros por segundo. Além disso, uma arquitetura de FME também é apresentada, capaz de avaliar todos os 48 possiveis blocos fracionarios ao redor do resultado da IME.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de PelotasPrograma de Pós-Graduação em ComputaçãoUFPelBrasilCentro de Desenvolvimento TecnológicoCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOComputaçãoHardware designMotion estimation3D-HEVCOperations reuseData reuseArquitetura de hardwareEstimação de movimentoReuso de operaçõesReuso de dadosAn energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operationsUma arquitetura de Hardware Energéticamente Eficiente para a Estimação de Movimento do padrão 3D-HEVC Adotando Estratégias de Reúso de Dados e de Operações.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://lattes.cnpq.br/5865984564684903http://lattes.cnpq.br/5741927083446578Agostini, Luciano Volcanhttp://lattes.cnpq.br/9604735363839730Afonso, Vladimirhttp://lattes.cnpq.br/9414186841741820Porto, Marcelo SchiavonPerleberg, Murilo Roschildtinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFPel - Guaiacainstname:Universidade Federal de Pelotas (UFPEL)instacron:UFPELTEXTDissertacao_Murilo_Perleberg.pdf.txtDissertacao_Murilo_Perleberg.pdf.txtExtracted texttext/plain165961http://guaiaca.ufpel.edu.br/xmlui/bitstream/prefix/6089/6/Dissertacao_Murilo_Perleberg.pdf.txtd63fe66f82076637fa0978f2a5e6b9cfMD56open accessTHUMBNAILDissertacao_Murilo_Perleberg.pdf.jpgDissertacao_Murilo_Perleberg.pdf.jpgGenerated Thumbnailimage/jpeg1267http://guaiaca.ufpel.edu.br/xmlui/bitstream/prefix/6089/7/Dissertacao_Murilo_Perleberg.pdf.jpgc994f18f1d07142f0746ee5218395541MD57open accessORIGINALDissertacao_Murilo_Perleberg.pdfDissertacao_Murilo_Perleberg.pdfapplication/pdf10578369http://guaiaca.ufpel.edu.br/xmlui/bitstream/prefix/6089/1/Dissertacao_Murilo_Perleberg.pdf7583d5fe1b6ffacd33baed010f3143a3MD51open accessCC-LICENSElicense_urllicense_urltext/plain; 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dc.title.pt_BR.fl_str_mv An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
dc.title.alternative.pt_BR.fl_str_mv Uma arquitetura de Hardware Energéticamente Eficiente para a Estimação de Movimento do padrão 3D-HEVC Adotando Estratégias de Reúso de Dados e de Operações.
title An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
spellingShingle An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
Perleberg, Murilo Roschildt
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
Computação
Hardware design
Motion estimation
3D-HEVC
Operations reuse
Data reuse
Arquitetura de hardware
Estimação de movimento
Reuso de operações
Reuso de dados
title_short An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
title_full An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
title_fullStr An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
title_full_unstemmed An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
title_sort An energy-efficient hardware design for the 3D-HEVC motion estimation adopting reuse strategies for data and operations
author Perleberg, Murilo Roschildt
author_facet Perleberg, Murilo Roschildt
author_role author
dc.contributor.authorLattes.pt_BR.fl_str_mv http://lattes.cnpq.br/5865984564684903
dc.contributor.advisorLattes.pt_BR.fl_str_mv http://lattes.cnpq.br/5741927083446578
dc.contributor.advisor-co1.fl_str_mv Agostini, Luciano Volcan
dc.contributor.advisor-co1Lattes.fl_str_mv http://lattes.cnpq.br/9604735363839730
dc.contributor.advisor-co2.fl_str_mv Afonso, Vladimir
dc.contributor.advisor-co2Lattes.fl_str_mv http://lattes.cnpq.br/9414186841741820
dc.contributor.advisor1.fl_str_mv Porto, Marcelo Schiavon
dc.contributor.author.fl_str_mv Perleberg, Murilo Roschildt
contributor_str_mv Agostini, Luciano Volcan
Afonso, Vladimir
Porto, Marcelo Schiavon
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
topic CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
Computação
Hardware design
Motion estimation
3D-HEVC
Operations reuse
Data reuse
Arquitetura de hardware
Estimação de movimento
Reuso de operações
Reuso de dados
dc.subject.por.fl_str_mv Computação
Hardware design
Motion estimation
3D-HEVC
Operations reuse
Data reuse
Arquitetura de hardware
Estimação de movimento
Reuso de operações
Reuso de dados
description Currently, there is a growing demand for video streaming through the internet, and also a crescent number of portable devices capable of capture and reproduce those videos. Moreover, the 3D videos allow an improved user experience when compared with traditional videos, since in the 3D videos the scene is simultaneously captured from different points of view. However, due to the amount of data required to represent digital videos, compression techniques are mandatory, which are a series of tools responsible for reducing the redundancies present in video data. In the 3D-High Efficiency Video Coding (3D-HEVC) standard, the most complex tool is the Motion Estimation (ME), while it is also responsible for a huge part of the compression efficiency of this standard. The ME is divided in Integer ME (IME), which performs the comparison a block from the frame being encoded with several candidate blocks from already encoded frames, searching for the candidate block most similar with the block being encoded, and the Fractional ME (FME), which performs a refinement around the candidate result of the IME. By default, the 3D-HEVC adopts the Test Zone Search (TZS) algorithm to select the candidates to be evaluated in the IME, since the TZS evaluates a reduced number of candidates without result in huge losses in image quality when compared with a full search algorithm, which compares all possible candidate blocks. Also, in 3D-HEVC the IME was applied in up to 24 different block sizes. This implies several redundant operations, where parts from a specific candidate can be compared with part of the block being encoded several times, besides a huge memory communication to perform the processing of several block sizes of each candidate block. Aiming at reducing these operation redundancies, it is possible to reuse the operations performed to small block sizes to compose the result of higher block sizes. This strategy also allows data reuse, since it reduces the memory access needed to obtain the samples to process all block sizes. There have only a few works on literature proposing hardware architectures for the IME of the 3D-HEVC standard. Between the IME works of other video coding standards, only a few presents solutions considering data and operations reuse strategies and a fast algorithm as TZS. Therefore, this work presents an IME hardware design adopting the TZS algorithm, with support to all block sizes supported by 3D-HEVC standard and with operations and data reuse strategies to take advantage of already processed operations and reduce the memory communication. The 3D-HEVC IME algorithm was modified aiming at an efficient hardware implementation, and the evaluations show that these modifications present an increase of 9.016% in the BD-rate metric. The developed IME architecture was synthesized for an ASIC with TSMC 40nm standard cells technology, and the results show that the hardware requires 269 K gates, while dissipates 108.48 mW when processing 3 views from different cameras, where each view is composed by the video of the two channels (Texture and Depth Maps) with FHD 1920x1080p resolution with 30 frames per second. The synthesis results have also indicated that the IME hardware design can process up to 3 views with UHD 3840x2160p resolution with 60 frames per second. Moreover, an FME architecture was also presented, which is able to evaluate all possible 48 fractional blocks around the IME result.
publishDate 2020
dc.date.accessioned.fl_str_mv 2020-06-29T12:49:49Z
dc.date.available.fl_str_mv 2020-06-29T12:49:49Z
dc.date.issued.fl_str_mv 2020-04-06
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv PERLEBERG, Murilo Roschildt. An Energy-Efficient Hardware Design for the 3DHEVC Motion Estimation Adopting Reuse Strategies for Data and Operations. Advisor: Marcelo Schiavon Porto. 2020. 88 f. Dissertation (Masters in Computer Science) – Technology Development Center, Federal University of Pelotas, Pelotas, 2020.
dc.identifier.uri.fl_str_mv http://guaiaca.ufpel.edu.br/handle/prefix/6089
identifier_str_mv PERLEBERG, Murilo Roschildt. An Energy-Efficient Hardware Design for the 3DHEVC Motion Estimation Adopting Reuse Strategies for Data and Operations. Advisor: Marcelo Schiavon Porto. 2020. 88 f. Dissertation (Masters in Computer Science) – Technology Development Center, Federal University of Pelotas, Pelotas, 2020.
url http://guaiaca.ufpel.edu.br/handle/prefix/6089
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Pelotas
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Computação
dc.publisher.initials.fl_str_mv UFPel
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Centro de Desenvolvimento Tecnológico
publisher.none.fl_str_mv Universidade Federal de Pelotas
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFPel - Guaiaca
instname:Universidade Federal de Pelotas (UFPEL)
instacron:UFPEL
instname_str Universidade Federal de Pelotas (UFPEL)
instacron_str UFPEL
institution UFPEL
reponame_str Repositório Institucional da UFPel - Guaiaca
collection Repositório Institucional da UFPel - Guaiaca
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repository.name.fl_str_mv Repositório Institucional da UFPel - Guaiaca - Universidade Federal de Pelotas (UFPEL)
repository.mail.fl_str_mv rippel@ufpel.edu.br || repositorio@ufpel.edu.br || aline.batista@ufpel.edu.br
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