NDLI: Fast 3D wavelet transform on multicore and many-core computing platforms

Content Provider	Springer Nature Link
Author	Galia, V. López Granado, O. Malumbres, M. P. Migallón, H.
Copyright Year	2013
Abstract	The three-dimensional wavelet transform (3D-DWT) has focused the attention of the research community, most of all in areas such as video watermarking, compression of volumetric medical data, multispectral image coding, 3D model coding and video coding. In this work, we present several strategies to speed up the 3D-DWT computation through multicore processing. An in depth analysis of the available compiler optimizations is also presented. Depending on both the multicore platform and the GOP size, the developed parallel algorithm obtains efficiencies above 95 % using up to four cores (or processes), and above 83 % using up to 12 cores. Furthermore, the extra memory requirements is under 0.12 % for low resolution video frames, and under 0.017 % for high resolution video frames. In this work, we also present a CUDA-based algorithm to compute the 3D-DWT using the shared memory for the extra memory demands, obtaining speed-ups up to 12.68 on the many-core GTX280 platform. In areas such as video processing or ultra high definition image processing, the memory requirements can significantly degrade the developed algorithms, however, our algorithm increases the memory requirements in a negligible percentage, being able to perform a nearly in-place computation of the 3D-DWT whereas in other state-of-the-art 3D-DWT algorithms it is quite common to use a different memory space to store the computed wavelet coefficients doubling in this manner the memory requirements.
Starting Page	848
Ending Page	865
Page Count	18
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	65
Issue Number	2
e-ISSN	15730484
Language	English
Publisher	Springer US
Publisher Date	2013-01-23
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	3D wavelet transform Video coding Parallel algorithms In-place computing OpenMP CUDA GPU Programming Languages, Compilers, Interpreters Processor Architectures Computer Science
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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