GPU-Based Sample-Parallel Context Modeling for EBCOT in
JPEG2000

D 2011

GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000

MATELA, Jiří, Vít RUSŇÁK and Petr HOLUB

Basic information

Original name

GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000

Authors

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

Edition

Dagstuhl, Germany, Sixth Doctoral Workshop on Mathematical and Engineering Methods in Computer Science -- Selected Papers, p. 77--84, 8 pp. 2011

Publisher

Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/00216224:14330/11:00049746

Organization unit

Faculty of Informatics

ISBN

978-3-939897-22-4

ISSN

Keywords in English

EBCOT;JPEG2000;Tier-1;GPU;context modeller

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. EBCOT itself consists of two tiers. In Tier-1, image samples are compressed using context modeling and arithmetic coding. Resulting bit-stream is further formated and truncated in Tier-2. JPEG2000 has a number of applications in various fields where the processing speed and/or latency is a crucial attribute and the main limitation with state of the art implementations. In this paper we propose a new parallel approach to EBCOT context modeling that truly exploits massively parallel capabilities of modern GPUs and enables concurrent processing of individual image samples. Performance evaluation of our prototype shows speedup 12 times for the context modeller, and 1.4--5.3 times for the whole EBCOT Tier-1, which includes not yet optimized arithmetic coder.

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/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. GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000. In Sixth Doctoral Workshop on Mathematical and Engineering Methods in Computer Science -- Selected Papers. Dagstuhl, Germany: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2011, p. 77--84. ISBN 978-3-939897-22-4.

@inproceedings{934115,
   author = {Matela, Jiří and Rusňák, Vít and Holub, Petr},
   address = {Dagstuhl, Germany},
   booktitle = {Sixth Doctoral Workshop on Mathematical and Engineering Methods in Computer Science -- Selected Papers},
   keywords = {EBCOT;JPEG2000;Tier-1;GPU;context modeller},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Dagstuhl, Germany},
   isbn = {978-3-939897-22-4},
   pages = {77--84},
   publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
   title = {GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000},
   url = {http://drops.dagstuhl.de/opus/volltexte/2011/3068},
   year = {2011}
}

TY  - JOUR
ID  - 934115
AU  - Matela, Jiří - Rusňák, Vít - Holub, Petr
PY  - 2011
TI  - GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000
PB  - Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
CY  - Dagstuhl, Germany
SN  - 9783939897224
KW  - EBCOT;JPEG2000;Tier-1;GPU;context modeller
UR  - http://drops.dagstuhl.de/opus/volltexte/2011/3068
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. EBCOT itself consists of two tiers. In Tier-1, image samples are compressed using context modeling and arithmetic coding. Resulting bit-stream is further formated and truncated in Tier-2. JPEG2000 has a number of applications in various fields where the processing speed and/or latency is a crucial attribute and the main limitation with state of the art implementations. In this paper we propose a new parallel approach to EBCOT context modeling that truly exploits massively parallel capabilities of modern GPUs and enables concurrent processing of individual image samples. Performance evaluation of our prototype shows speedup 12 times for the context modeller, and 1.4--5.3 times for the whole EBCOT Tier-1, which includes not yet optimized arithmetic coder.
ER  -

MATELA, Jiří, Vít RUSŇÁK and Petr HOLUB. GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000. In \textit{Sixth Doctoral Workshop on Mathematical and Engineering Methods in Computer Science -- Selected Papers}. Dagstuhl, Germany: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2011, p.~77--84. ISBN~978-3-939897-22-4.

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