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说明：  主要是自己学习时做的习题，希望对你有帮助(Mainly to their own learning exercises to do, want to help you)

并行归并排序算法，基于mpi的并行归并排序算法(A parallel merge sort algorithm)

CUDA代码，主要是要实现一个具体ADD操作，并且可以高速在GPU上运行(An Algorithm based on UKF)

LU算法的MPI串行实现，矩阵维数无要求，可在曙光4000A并行机运行(The LU algorithm MPI serial implementation matrix dimension requirements Dawning 4000A parallel machine running)

Hight Performance Computing Demos

清华大学郑仰东CUDA教学课件1，是很好的CUDA入门材料(Tsinghua university ZhengAngDong s CUDA teaching courseware 1,a very good CUDA introductory material)

在Isight环境中集成UG/ANSYS，将UG的prt文件先储存文x_t格式文件，然后再导入ANSYS计算，将实现一个ugupdate.exe，功能除了更新prt文件文还将prt文件另存为x_t文件，以供ANSYS调用。(The Isight environment integrated the UG/ANSYS, the UG prt files first to store text x_t format file, and then import the ANSYS calculation will achieve a ugupdate.exe, functions in addition to updated prt files text will prt files saved as files x_t, for ANSYS invoked.)

GPU实现的MapReduce framework,对于学习并行编程和cuda平台的编程方面有着极好的参考价值，里面附带论文。用户要求有NViDIA显卡，并且安装cuda编程环境。(We design and implement Mars, a MapReduce framework, on graphics processors (GPUs). MapReduce is a distributed programming framework originally proposed by Google for the ease of development of web search applications on a large number of commodity CPUs. Compared with CPUs, GPUs have an order of magnitude higher computation power and memory bandwidth, but are harder to program since their architectures are designed as a special-purpose co-processor and their programming interfaces are typically for graphics applications.)

说明：  计算π值 C++ 并行算法 分别使用方法左矩形分解、中矩形分解以及梯形分解(π C++ MPI π C++ MPI π C++ MPI π C++ MPI)

MPI编程－Nbody问题并行程序（计算1000个天体的移动，天体数据由文件sample_input.in读入，结果输出到文件result1000.data）(MPI Programming-Nbody Parallel (1000 calculated the movement of celestial bodies, Objects sample_input.in data from the document read into, Results output to a file result1000.data))