D 2012

GPU-specific reformulations of image compression algorithms

MATELA, Jiří, Petr HOLUB, Martin JIRMAN and Martin ŠROM

Basic information

Original name

GPU-specific reformulations of image compression algorithms

Authors

MATELA, Jiří (203 Czech Republic, guarantor, belonging to the institution), Petr HOLUB (203 Czech Republic, belonging to the institution), Martin JIRMAN (203 Czech Republic) and Martin ŠROM (203 Czech Republic)

Edition

8499. vyd. BELLINGHAM, WA 98227-0010 USA, Proceedings of Applications of Digital Image Processing XXXV, p. nestránkováno, 8 pp. 2012

Publisher

SPIE-INT SOC OPTICAL ENGINEERING

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/12:00057518

Organization unit

Faculty of Informatics

ISBN

978-0-8194-9216-6

ISSN

UT WoS

000312200600040

Keywords in English

GPU; parallel; reformulation; JPEG; JPEG2000; Context Modeling; Arithmetic coding; MQ-Coder; Huffman coding

Tags

Tags

International impact, Reviewed
Změněno: 22/4/2013 14:20, doc. RNDr. Petr Holub, Ph.D.

Abstract

V originále

Image compressions have a number of applications in various fields where the processing throughput and/or latency is a crucial attribute and the main limitation with state of the art implementations of compression algorithms. At the same time the contemporary GPUs provide a tremendous processing power applicable to the image compression acceleration but it calls for a specific algorithm design. We discuss the key components of successful GPU algorithm design and demonstrate this on JPEG2000 compression chain, which contains several types of algorithms: from DWT which is inherently well suited to GPU, through context modeling requiring reformulation in order to perform well on GPU, to arithmetic coding which does not fit the paradigm well but can be optimized to perform faster than CPU versions. Performance evaluation of the optimized JPEG2000 chain will be used to demonstrate the importance of various aspects of GPU programming, especially with respect to real-time applications.

Links

GAP202/12/0306, research and development project
Name: Dyschnet - Dynamické plánování a rozvrhování výpočetních a síťových zdrojů (Acronym: Dyschnet)
Investor: Czech Science Foundation
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
MUNI/A/0914/2009, interní kód MU
Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Acronym: SV-FI MAV)
Investor: Masaryk University, Category A