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Proceedings Paper

Heterogeneous computing system with GPU-based IDWT and CPU-based SPIHT and Reed-Solomon decoding for satellite image decompression
Author(s): Changhe Song; Yunsong Li; Bormin Huang
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Paper Abstract

The discrete wavelet transform (DWT)-based Set Partitioning in Hierarchical Trees (SPIHT) algorithm is widely used in many image compression systems. In order to perform real-time Reed-Solomon channel decoding and SPIHT+DWT source decoding on a massive bit stream of compressed images continuously down-linked from the satellite, we propose a novel graphic processing unit (GPU)-accelerated decoding system. In this system the GPU is used to compute the time-consuming inverse DWT, while multiple CPU threads are run in parallel for the remaining part of the system. Both CPU and GPU parts were carefully designed to have approximately the same processing speed to obtain the maximum throughput via a novel pipeline structure for processing continuous satellite images. Through the pipelined CPU and GPU heterogeneous computing, the entire decoding system approaches a speedup of 84x as compared to its single-threaded CPU counterpart.

Paper Details

Date Published: 20 September 2011
PDF: 9 pages
Proc. SPIE 8157, Satellite Data Compression, Communications, and Processing VII, 815710 (20 September 2011); doi: 10.1117/12.895421
Show Author Affiliations
Changhe Song, Xidian Univ. (China)
Yunsong Li, Xidian Univ. (China)
Bormin Huang, Univ. of Wisconsin-Madison (United States)

Published in SPIE Proceedings Vol. 8157:
Satellite Data Compression, Communications, and Processing VII
Bormin Huang; Antonio J. Plaza; Carole Thiebaut, Editor(s)

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