lsqrf90-v2

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)

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.)

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)

cuda_by_example 原版 中文版 程例(cuda by example)

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)

mpi的源码，示例程序等，主要用于对mpi并行编程程序的研究。(mpi source code, sample programs, mainly for mpi parallel programming procedures.)

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的基礎的矩陣相乘法，包含CPU版本以及GPU版本(CUDA Matrix)

采用改进的三维Hasin准则，考虑基体和纤维损伤，以及复合材料分层损伤( U91C7 u7539 u659 u8F09 u7F4 u7R4 u7354 u03 U6599 u5206 u5C42 u635F u4F24)

calculate the circle surface using parallel mpi