An Attempt of CUDA Implementation of PCA-SIFT

LanguageEnglish
TypeProceedings of Japanese Conferences
AuthorsMasakazu IWAMURA, Takayuki HONDO, Kazuto NOGUCHI, Koichi KISE
TitleAn Attempt of CUDA Implementation of PCA-SIFT
JournalIEICE Technical Report
Vol.107
No.281
Presentation numberPRMU2007-117
Pagespp.149-154
ReviewedNot reviewed
DateOctober 2007
Research fieldsPattern recognition, Object Recognition
KeyIwamura2007_IEICEPRMU_Attempt (id=997)

Abstract

GPGPU (General-Purpose computation on GPUs) is a paradigm to use GPUs (graphics processing units) for general computation. Due to recent remarkable improvement of GPU, GPU outperforms CPU in computation ability. However, most people could not use the ability for general computation because existing programming languages require knowledge about GPU hardware architectures and computer graphics for GPGPU computing. Recently, a new GPU language CUDA (Compute Unified Device Architecture) has been released from NVIDIA. The CUDA code is C language style and has less computational restriction. Thus, usual operations of C language can run on GPU without much special knowledge. In this report, we briefly introduce CUDA language programming and report a CUDA implemented of PCA-SIFT. Compared to a CPU implementation, our CUDA implementation reduced the processing time to around 1/4. In addition, we also report an interesting phenomenon results useful for practical use of CUDA.

Note

KJPR2007

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