Accelerating BP Neural Network-Based Image Compression by CPU and GPU Cooperation

Author

Lin, Jinxian ; Lin, Jianghong

Author_Institution

Network Inf. Center, Fuzhou Univ., Fuzhou, China

fYear

2010

fDate

29-31 Oct. 2010

Firstpage

1

Lastpage

4

Abstract

Recently, GPU has evolved into a highly parallel, multithreading, many core processor with tremendous computational capability and very high memory bandwidth. At the same time, multi-core CPU evolution continued and today´s CPUs have 4-8 cores which offer dramatically increased performance and power savings characteristics. We are aware of very few works that consider both devices cooperating to solve general computations. The article tries to bring forward a method of similar master/ worker GPU-CPU cooperative computing to improve efficiency of Back-Propagation neural network-based image compression application even further than using either device independently.

Keywords

backpropagation; computer graphic equipment; coprocessors; data compression; image coding; multiprocessing systems; neural nets; CPU-GPU cooperative computing; backpropagation neural network; graphics processing unit; image compression; multicore CPU evolution; Artificial neural networks; Central Processing Unit; Computer architecture; Graphics processing unit; Image coding; Instruction sets; Parallel processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Technology (ICMT), 2010 International Conference on

Conference_Location

Ningbo

Print_ISBN

978-1-4244-7871-2

Type

conf

DOI

10.1109/ICMULT.2010.5629832

Filename

5629832