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面向OpenCL模型的DCT并行化 被引量：3

Parallelization of Dct Using Opencl Model
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摘要 为了提高DCT变换的速度,文中对面向OpenCL模型的DCT并行化过程进行了研究,首先分析了GPU和OpenCL的特性和优势,研究了传统DCT变换的工作原理,然后针对CPU和GPU两种不同平台对DCT变换进行测试和结果分析,实验结果表明基于OpenCL模型的并行化能够有效地提高DCT变换的速度。 In order to improve speed up the DCT inversion, this paper analyzed characteristics and advantages of GPU and Open CL; and researched working principle of traditional DCT inversion, then tested algorithm on the different platforms, the results shows that parallelization can effectively improve the fast DCT performance.
作者 向阳霞 张惠民 王子强
机构地区 装甲兵工程学院信息工程系
出处 《电脑知识与技术（过刊）》 2013年第9X期6007-6011,共5页 Computer Knowledge and Technology
关键词 GPU处理器 OpenCL模型 离散余弦变化 并行化 Graphic Processing Unit(GPU) Open Computing Language(OpenCL) Discrete Cosine Transform(DCT) Parallelization
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献8

  • 1李焱,张云泉,王可,赵美超.异构平台上基于OpenCL的FFT实现与优化[J].计算机科学,2011,38(8):284-286. 被引量：8
  • 2陈钢,吴百锋.面向OpenCL模型的GPU性能优化[J].计算机辅助设计与图形学学报,2011,23(4):571-581. 被引量：21
  • 3阮军,韩定定.基于CUDA的DCT快速变换实现方法[J].微电子学与计算机,2009,26(8):201-205. 被引量：8
  • 4Cheong Ghil Kim,Yong Soo Choi.A high performance parallel DCT with OpenCL on heterogeneous computing environment[J].Multimedia Tools and Applications.2013(2)
  • 5Dariusz Rafal Augustyn,Sebastian Zederowski.Applying CUDA Technology in DCT-Based Method of Query Selectivity Estimation[].Advances in Intelligent Systems and Computing.2013
  • 6Wei-Jhe Hsu,Hsueh-Ming Hang,Yi-Fu Chen.Motion Estimation and DCT Coding Combined Scheme for H.264/AVC Codec[].In ternational Computer Symposium.2013
  • 7Changmin Lee,Won Woo Ro,Jean-Luc Gaudiot.Boosting CUDA Applications with CPU–GPU Hybrid Computing[].International Journal of Parallel Programming.2013
  • 8Youngsub Ko,Youngmin Yi,Soonhoi Ha.An efficient parallelization technique for x264 encoder on heterogeneous platforms consist ing of CPUs and GPUs[].Journal of Real-Time Image Processing.2013

二级参考文献38

  • 1吴恩华,柳有权.基于图形处理器(GPU)的通用计算[J].计算机辅助设计与图形学学报,2004,16(5):601-612. 被引量：226
  • 2()wens J D, Houston M, Luebke D, et al. GPU computing [J]. Proceedings of the IEEE, 2008, 96(5): 879-899.
  • 3Owens J D, Luebke D, Govindaraju N, et al. A survey of general-purpose computation on graphics hardware [J]. Computer Graphics Forum, 2007, 26(1): 80-113.
  • 4Fatahalian K, Houston M. GPUs:a closer look [J]. ACM Queue, 2008, 6(2): 18 28.
  • 5Jang B, Mistry P, Sehaa D, et al. Data transformations enabling loop vectorization on multithreaded data parallel architectures [C] //Proceedings of the 15th ACM SIGPLAN Symposium on Principles ahd Practice of Parallel Programming. New York: ACM Press, 2010:353-354.
  • 6Liu Y X, Zhang E Z, Shen X P. A cross-input adaptive framework for GPU program optimizations [C] //Proceedings of IEEE International Symposium on Parallel & Distributed Processing. Los Alamitos: IEEE Computer Society Press, 2009, 1-10.
  • 7Ryoo S, Rodrigucs C I, Stone S S, et al. Program optimization space pruning for a multithreaded GPU [C]// Proceedings of the 6th Annual IEEE/ACM International Symposium on Code Generation and Optimization. New York: ACM Press, 2008:195-204.
  • 8Ryoo S, Rodrigues C l, Stone S S, el al. Optimization principles and application performance evaluation of a multithreaded GPU using CUDA [C] //Proceedings of the 13th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. New York: ACM Press, 2008:73-82.
  • 9Jang 13, Do S, Pien H, etal. Architecture aware optimization targeting multithreaded stream computing[C] //Proceedings of the 2nd Workshop on General Purpose Processing onGraphics Processing Units, New York: ACM Press, 2009: 62-70.
  • 10Baskaran M M, Bondhugu/a U, Krishnamoorthy S, et al. A compiler framework for optimization of affine loop nests for GPGPUs [C] //Proceedings of the 22nd Annual International Conference on Supercomputing. New York: ACM Press, 2008:225-234.

共引文献31

同被引文献32

  • 1刘爱东,倪永强,王建国.一种实时剔除雷达测量数据中野值的方法分析[J].火力与指挥控制,2004,29(z1):17-19. 被引量：11
  • 2吴恩华,柳有权.基于图形处理器(GPU)的通用计算[J].计算机辅助设计与图形学学报,2004,16(5):601-612. 被引量：226
  • 3朱学锋,韩荣阁,杨若红.基于模糊预测系统的观测数据野值剔除方法[J].系统工程与电子技术,2006,28(3):478-482. 被引量：9
  • 4张帆,卢峥.自适应抗野值Kalman滤波[J].电机与控制学报,2007,11(2):188-190. 被引量：19
  • 5Dariusz Rafal Augustyn, Sebastian Zederowski. Applying CUDA Technology in DCT-Based Method of Query Selectivity Estimation [ J ]. Ad- vances in Intelligent Systems and Computing, 2013,185:3 - 12.
  • 6Owens J D, Houston M, Luebke D, et al. GPU Computing[J ]. Proceedings of the IEEE, 2008, 96(5) : 879-899.
  • 7Harris M. What is GPGPU [ EB/OL ]. http:// gpgpu, org/, 2012 - 4 - 24.
  • 8Owens J D, Luebke D, Govindaraju N, et al. A survey of general purpose computation on graphics hardware [ J ]. Computer Graphics Forum, 2007, 26(1) : 80- 113.
  • 9Michalakes J, Vaehharajani M. GPU accelera- tion of numerical weather prediction[J]. Parallel Processing Letters, 2008, 18(4) : 531-548.
  • 10Bolz J, Farmer I, Grinspun E, et al. Sparse ma- trix solvers on the GPU. Conjugate gradients and multigrid[J ]. ACM Transaction on Graph- ics, 2003, 22(3) : 917-924.

引证文献3

二级引证文献4

电脑知识与技术（过刊）
2013年 第9X期

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