CPPAMP

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)

fluent udf 实现动态边界条件 并行及串行程序(parallel and series udf based on facets loop)

CUDA并行计算的讲义，NVDIA培训专用，最全资料。(CUDA parallel)

Hight Performance Computing Demos

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.)

高教出版社的《并行算法实践》一书的源代码，内容为MPI程序源代码(Higher Education Publishing House s Parallel Algorithm for the practice of the book s source code, content for the MPI source code)

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.)

CUDA平行的優化，以矩陣乘法為基礎。透過ShareMemory做加速(CUDA ShareMem)

cuda资料，对于并行编程很有帮助！该资料描述了cuda的基本信息，以及重要的步骤，让您逐渐上手，轻松掌握cuda并行编程。(cuda information useful for parallel programming! The information describes the cuda s basic information, as well as an important step, so that gradually you get started, easy to master parallel programming cuda.)

多核编程，比 OPENCL 简单 可以通过类似 OPENMP 的方式，简洁的实现异构编程，使用 GPU 计算(Multicore programming than simple OPENCL)