Efficient JPEG2000 EBCOT Context Modeling for Massively
Parallel Architectures

D 2011

Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures

MATELA, Jiří, Vít RUSŇÁK and Petr HOLUB

Basic information

Original name

Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures

Authors

MATELA, Jiří (203 Czech Republic, guarantor, belonging to the institution), Vít RUSŇÁK (203 Czech Republic, belonging to the institution) and Petr HOLUB (203 Czech Republic, belonging to the institution)

Edition

Washington, DC, USA, Data Compression Conference (DCC), 2011, p. 423-432, 10 pp. 2011

Publisher

IEEE Computer Society

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/11:00049671

Organization unit

Faculty of Informatics

ISBN

978-0-7695-4352-9

ISSN

DOI

http://dx.doi.org/10.1109/DCC.2011.49

UT WoS

000298610800043

Keywords in English

JPEG2000; EBCOT; Parallel; Contex Modeling; GPU; GPGPU; CUDA

Abstract

V originále

Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. In this paper, we present a reformulation of the context modeling of EBCOT that allows full parallelization for massively parallel architectures such as GPUs with their single instruction multiple threads architecture. We prove that the reformulation is equivalent to the EBCOT specification in JPEG2000 standard. Behavior of the reformulated algorithm is demonstrated using NVIDIA CUDA platform and compared to other state-of-the-art implementations.

Links

GD102/09/H042, research and development project

Name: Matematické a inženýrské metody pro vývoj spolehlivých a bezpečných paralelních a distribuovaných počítačových systémů

Investor: Czech Science Foundation

MSM0021622419, plan (intention)

Name: Vysoce paralelní a distribuované výpočetní systémy

Investor: Ministry of Education, Youth and Sports of the CR, Highly Parallel and Distributed Computing Systems

MUNI/A/0057/2011, interní kód MU

Name: Posílení zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity (Acronym: SKONF)

Investor: Masaryk University, Category A

MUNI/A/0914/2009, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Acronym: SV-FI MAV)

Investor: Masaryk University, Category A

Citovat

MATELA, Jiří, Vít RUSŇÁK and Petr HOLUB. Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures. In Storer, James A. and Marcellin, Michael W. Data Compression Conference (DCC), 2011. Washington, DC, USA: IEEE Computer Society, 2011, p. 423-432. ISBN 978-0-7695-4352-9. Available from: https://dx.doi.org/10.1109/DCC.2011.49.

@inproceedings{916772,
   author = {Matela, Jiří and Rusňák, Vít and Holub, Petr},
   address = {Washington, DC, USA},
   booktitle = {Data Compression Conference (DCC), 2011},
   doi = {http://dx.doi.org/10.1109/DCC.2011.49},
   editor = {Storer, James A. and Marcellin, Michael W.},
   keywords = {JPEG2000; EBCOT; Parallel; Contex Modeling; GPU; GPGPU; CUDA},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Washington, DC, USA},
   isbn = {978-0-7695-4352-9},
   pages = {423-432},
   publisher = {IEEE Computer Society},
   title = {Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures},
   year = {2011}
}

TY  - JOUR
ID  - 916772
AU  - Matela, Jiří - Rusňák, Vít - Holub, Petr
PY  - 2011
TI  - Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures
PB  - IEEE Computer Society
CY  - Washington, DC, USA
SN  - 9780769543529
KW  - JPEG2000
KW  - EBCOT
KW  - Parallel
KW  - Contex Modeling
KW  - GPU
KW  - GPGPU
KW  - CUDA
N2  - Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. In this paper, we present a reformulation of the context modeling of EBCOT that allows full parallelization for massively parallel architectures such as GPUs with their single instruction multiple threads architecture. We prove that the reformulation is equivalent to the EBCOT specification in JPEG2000 standard. Behavior of the reformulated algorithm is demonstrated using NVIDIA CUDA platform and compared to other state-of-the-art implementations.
ER  -

MATELA, Jiří, Vít RUSŇÁK and Petr HOLUB. Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures. In Storer, James A. and Marcellin, Michael W. \textit{Data Compression Conference (DCC), 2011}. Washington, DC, USA: IEEE Computer Society, 2011, p.~423-432. ISBN~978-0-7695-4352-9. Available from: https://dx.doi.org/10.1109/DCC.2011.49.

Detailed Information on Publication Record