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一些关于并行计算的资料，对初学并行计算的人会有些许帮助(Information about parallel computing, parallel computing for beginners who have a little help)

格子Boltzmann方法 格子Boltzmann方法是为了保留格子气自动机方法的优点，克服其缺点而发展起来的方法。 特别是1992年，钱跃弘、陈十一等的开创性工作(提出LBGK模型方法)，使该方法广泛地应用到计算流体力学(单相流、多相流、多孔介质流、热对流、磁流体、反应-扩散等)。 (Lattice Boltzmann method of lattice Boltzmann method is to retain the lattice gas automata method has the advantage to overcome its shortcomings and has developed methods. Especially in 1992, Qian Yue-hong, Chen XI, such as the pioneering work (LBGK model proposed method), so that the method widely used in computational fluid dynamics (single-phase flow, multiphase flow, porous media flow, thermal convection, magnetic fluid, the reaction- the proliferation, etc.).)

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)

compilateur de code source

并行程序,并行离散化算法实现，粗糙集数据挖掘程序(Parallel programming, parallel discrete algorithms, rough set data mining program)

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

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.)

OpenCL中文教程(AMD),最好的OpenCL教程，介绍了AMD显卡的OpenCL编程，其中有大量例程，并介绍了OpenCL优化方法(OpenCL Chinese tutorial (AMD), the best OpenCL tutorial introduces the AMD OpenCL graphics programming, including a large number of routines, and introduces OpenCL optimization method)

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.)