Low GPU Occupancy Approach to Fast Arithmetic Coding in JPEG2000
| Autor: | í Matela, Petr Holub, Martin Šrom |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Speedup
Computer science 020206 networking & telecommunications 02 engineering and technology Parallel computing computer.file_format Arithmetic coding CUDA Lookup table JPEG 2000 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Massively parallel computer Context-adaptive binary arithmetic coding Image compression |
| Zdroj: | Mathematical and Engineering Methods in Computer Science ISBN: 9783642259289 MEMICS |
| DOI: | 10.1007/978-3-642-25929-6_13 |
| Popis: | Arithmetic coding, and especially adaptive MQ-Coding of JPEG2000, is a serial process, which does not match specifics of GPUs as massively parallel processors well. In this paper we study and evaluate several approaches to acceleration of the MQ-Coding using commodity GPU hardware, including our proposal of a new enhanced renormalization procedure. We conclude with a "low occupancy approach" and 5.6---16× average speedup when compared to the state of the art multi-threaded CPU implementations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|