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parallelcomputing
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)
- 2010-06-18 22:24:03下载
- 积分：1
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PI
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)
- 2012-05-31 16:19:51下载
- 积分：1
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The-OpenCL-Chinese-tutorial(AMD)
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)
- 2013-05-15 13:28:48下载
- 积分：1
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CPPAMP
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)
- 2013-07-10 20:47:20下载
- 积分：1
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Matrix_mulitiple
使用CUDA并行语言编写的矩阵乘法，与串行语句的对比试验，主要检测出CPU与GPU运行的时间，通过比较时间，达到比较效果。另外此程序可以随意更改矩阵的维数，增强程序的移植性。(CUDA parallel language use matrix multiplication, and serial statement comparison test, the main test of CPU and GPU to run time, by comparing the time, to compare results. Also this program can change the dimension of the matrix, and enhanced portability of the program.)
- 2020-12-11 21:49:17下载
- 积分：1
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MergeSort
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)
- 2020-11-20 14:59:38下载
- 积分：1
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NVIDIA_CUDA_1
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.)
- 2020-12-11 21:39:18下载
- 积分：1
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cppfrance_MINI-COMPILATEUR-CPLUSPLUS-ANALYSE-LEXI
compilateur de code source
- 2011-12-30 07:19:40下载
- 积分：1
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MyTest
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)
- 2013-10-14 09:45:06下载
- 积分：1
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Mars_v2
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.)
- 2009-03-17 11:22:47下载
- 积分：1
