Title :
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
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;
Conference_Titel :
Multimedia Technology (ICMT), 2010 International Conference on
Conference_Location :
Ningbo
Print_ISBN :
978-1-4244-7871-2
DOI :
10.1109/ICMULT.2010.5629832
