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CUDA_VS2010
- GPU并行计算，cuda编程在VS2010平台上的配置。系统要求：windows 7，cuda 4.0（toolkit、SDK），VS2010.-GPU parallel computing, cuda programming in VS2010 platform configuration. System Requirements: windows 7, cuda 4.0 (toolkit, SDK), VS2010.
MultiDevice
- 在学习CUDA GPU并行编程时写的，用于将应用分布到多个GPU设备进行处理的通用代码。-This program is finished when I was learning CUDA GPU parallel programming. It deploys the applications to multiple GPU devices and can be used in many environments.
MatrixMulTexture_kernel
- 基于GPU的并行编程，采用纹理实现两个矩阵相乘。自己写的程序。-This is a parallel program based GPU,which achieved two matrix multiplication with texture.It is mine.
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
gpu
- gpu编程书籍 并行计算机导论 对gpu编程者有很大的帮助-Parallel gpu computer programming books An Introduction to Programming on the gpu are of great help
GPU
- 近年来，计算机图形处理器(GI．apllics Processing Unit,GPU)得到了极大地发展，从最初局限于图形渲染的图形卡，发展为如今可编程的并行计算平台。与CPU的串行计算模式不同，GPU是一种高度并行的流处理器，具有更强的浮点计算能力，在物理模拟、信号分析等许多领域人们将高强度的计算任务以适当的方式转化为流数据计算模式，通过编程在GPU中进行加速计算，通常能获得一个数量级的速度提高，这也是当今的热点研究问题之一。-In recent years, computer graphic
CUDAGPUPatternrecognition
- 本文详细分析了Tesla GPU图形与计算架构和CUDA统一计算设备架构，详细描述了如何对计算任务进行并行分解，并通过CUDA的双层并行编程模型映射到Tesla GPU上。-This paper analyzes the Tesla GPU computing architecture and CUDA graphics and computing devices unified framework, a detailed descr iption of how parallel computi
cuda-GPU
- 本文详细分析了Tesla GPU图形与计算架构和CUDA统一计算设备架构，详细描述了如何对计算任务进行并行分解，并通过CUDA的双层并行编程模型映射到Tesla GPU上。 在本文的实现部分，以软件开发流程为主线，描述了如何利用CUDA实现模式识别中的三种常用算法-The paper analyzed the Tesla GPU computing architecture and CUDA graphics and computing devices unified architecture,
reverseArray_multiblock
- 在linux下，用gpu实现对矩阵转置的并行编程-In linux, with the gpu to achieve the matrix transpose of parallel programming
CudaTutorials
- GPU并行计算，cuda编程教程，硬件要求NVIDIA独立显卡。-GPU parallel computing, cuda programming tutorial, hardware requirements, NVIDIA discrete graphics.
opencl-parallel-programing
- opencl 并行编程，针对GPU进行并行编程。是一本入门级的并行编程教程。-opencl parallel programing for GPU
hardware-GPU
- 里面包含目前流行的nvidia的GPU的硬件体系结构简介，对于CUDA并行编程的编写与调试会有很大帮助！-Which contains the currently popular nvidia GPU hardware architecture Introduction, for the preparation of the CUDA parallel programming and debugging will be very helpful!
CUDA-programming
- 此文档讲述的事CUDA编程的基础技术，对于基于GPU 的并行编程入门学者有帮助-This document is about the basis of the CUDA programming technology, entry scholars for GPU-based parallel programming
[GPU-CUDA--C-Programming]
- GPU CUDA C并行编程是计算机实现并行高速计算的强大方式，本资料将引领你进入这个神奇的世界-GPU CUDA C parallel programming is a powerful way to achieve parallel high-speed computer, this information will lead you into the magic of the world
MatlabCuda
- 自己写的GPU并行程序和MATLAB 平台混合调用，适合初学者学习MATLAB 和GPU的并行编程(Write their own GPU parallel program and MATLAB platform mixed call, suitable for beginners to learn MATLAB and GPU parallel programming)
GPU高性能编程CUDA实战中文版
- 并行计算新手入门书籍，分析的简单透彻，实例举一反三，CUDA入门的好书(Parallel computing novice entry books, analysis of simple and thorough, examples of drawing inferences from others, CUDA entry of good books)
GPU并行编程讲义
- 基于GPU并行计算基础讲义，为程序猿打开基于GPU编程的大门(Based on GPU parallel computing basic lecture, opens the gate for GPU programming based on program ape.)
32679--GPU高性能编程CUDA实战—示例代码
- 本资料是GPU高性能编程CUDA实战—示例代码，非常完整，非常适合学习与模仿，都相应的完成书中的算法和详细的并行代码编写过程。(This data is GPU high performance programming CUDA real - example code, very complete, very suitable for learning and imitation, the corresponding completion of the book algorithm and de
GPU高性能编程CUDA实战—示例代码
- 结合GPU高性能编程，提供实战样例程序，包含矩阵乘法，原子操作，热传导，多GPU，多流的代码(Combined with GPU high performance programming, it provides actual sample program, including matrix multiplication, atomic operation, heat conduction, multi GPU, and multi stream code.)
CUDA Fortran 高效编程实践.pdf
- CUDA Fortran 高效编程实践_科学家和工程师特供 2007 年以来，以 nVidia GPU 为代表的加速器并行计算风起云涌，带有加速器的超级计 算机在 TOP500 中的份额逐年增加，支持加速器的主流应用软件也呈爆炸式增长，研究加速 器计算的技术人员数以百万计，世界范围内的大学、研究机构竞相开设相关课程。 目前流行的 GPU 通用编程语言是 CUDA C 和 OpenCL. 它们均是 C/C++语言的扩展，因 此可以方便地将 C/C++代码移植到 GPU 上。但对于科学与工程计算