Accelerating BP neural network-based image compression by CPU and GPU cooperation - Details

author：

Lin, Jinxian (Lin, Jinxian.) ^[1] (Scholars：林锦贤) | Lin, Jianghong (Lin, Jianghong.) ^[2]

Indexed by：

EI Scopus

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.　©2010　IEEE.

Keyword：

Application programming interfaces (API) Backpropagation Computer graphics Computer graphics equipment Graphics processing unit Image compression Image enhancement Multimedia systems Multitasking Neural networks Program processors Torsional stress

Community：

[ 1 ] [Lin, Jinxian]Network Information Center, Fuzhou University, Fuzhou, Fujian, China
[ 2 ] [Lin, Jianghong]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, Fujian, China

Reprint 's Address：

Email：

jxlin@fzu.edu.cn

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