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2D CUDA-based bilinear interpolation
- This MEX performs 2d bilinear interpolation using an NVIDIA graphics chipset. To compile and run this software, one needs the NVIDIA CUDA Toolkit (http://www.nvidia.com/object/cuda_get.html) and, of course, an NVIDIA graphics card of reasonably moder
CUDA_Match
- 基于NVIDIA CUDA GPU计算开发环境的双目视觉匹配程序，用于立体视觉的识别，同时可用于三维重建。主要算法在显卡上进行，需要NVIDIA的支持CUDA的显卡-NVIDIA CUDA GPU-based computing development environment to match the binocular vision procedures, for three-dimensional visual recognition, can be used for three-dimen
CPURayCasting
- 在CPU做的Ray-Casting代码，仿写CUDA的VolumeRender. -In the CPU to do Ray-Casting code, Imitative CUDA' s VolumeRender.
CUDA
- 学习NVIDIA公司GPU平台CUDA开发环境的好资料，可以大体上了解CUDA的运行环境和编程技巧-NVIDIA' s GPU platform to learn CUDA development environment good information, you can generally understand the CUDA runtime environment and programming skills
cksc2.0
- nvidia CUDA 2.0 SDK 中文版本,翻译率大概为95％-nvidia CUDA 2.0 SDK Chinese version, the translation rate of about 95
UIUC_CudaProgrammingGuide
- UIUC的工程院在全美堪称至尊级，这是UIUC推出的CUDA学习教程，非常系统地讲述其特点及应用。很好，很强大！-UIUC' s at the National Academy of Engineering called Extreme class, This is UIUC Study launched CUDA tutorial, very systematically about their characteristics and applications. Very good, v
NVCC_1.0
- CUDA s Compiler NVCC descr iption, very important t o CUDA developers
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 p
cuda
- cuda的教程，cuda是在nvdia的GT80以上显卡支持的Gpu编程的c语言环境-cuda' s Guide, cuda is the GT80 in nvdia above Gpu graphics support c programming language environment
mpeg2dec
- MEPG2 dec 优化代码。 可运行于nvidia 的CUDA平台中-MEPG2 dec opt code it can running in nvidia s cuda chip
cuSVMVCcode
- 基于GPU计算的SVM，VC++源码，包括详细文档说明文件。借用了GPU编程的优势，该代码据作者说比常规的libsvm等算法包的训练速度快13-73倍，预测速度快22-172倍。希望对大家有用-cuSVM is a software package for high-speed (Gaussian-kernelized) Support Vector Machine training and prediction that exploits the massively parallel proc
40e87b3a-0df7-43ec-8729-916b7c6ea92fR
- 基于CUDA的立体视觉 在本文中，我们提出了一个基于GPU的加速方法，以加快计算量图像配准 统一设备架构（CUDA技术）。一种新颖的CUDA技术为基础的联合直方图计算方法介绍 在这个文件，该文件还对二维图像配准和其他应用程序的一般图形宝贵。此外， 1算法的改进，提出改进FMRIB广泛使用的线性图像注册工具 （调情）。虽然采取了额外的时间是通过应用该算法的改进，我们的实现表明， 能够执行一个完整的12个自由度（自由度）的两个脑容量图像配准在近35秒， 时间大约是10比本
cuda
- 深入浅出谈CUDA CUDA 是 NVIDIA 的 GPGPU 模型，它使用 C 语言为基础，可以直接以大多数人熟悉的 C 语言，写出在显示芯片上执行的程序，而不需要去学习特定的显示芯片的指令或是特殊的结构。-Visitors to learn about CUDA CUDA is NVIDIA s GPGPU model, which uses the C language-based, most people directly familiar with the C language
CUDA_Developer_Guide_for_Optimus_Platforms
- CUDA开发者程序优化指南！NVIDIA公司最新规范！不可多得的程序规范指南！-CUDA Developer Program Optimization Guide! NVIDIA' s latest specification! Rare procedural norms guide!
cuda_wordpassword_crack
- 暴力破解word2003所需的计算量极其大，耗费时间长！本作品利用CUDA的高速并行能力进行破解，以时间换空间及成本， 适合普通用户使用。-Word2003 brute force computation required is extremely large, time-consuming long! This works using CUDA' s ability to break high-speed parallel to the time for space and cost,
CUDA
- 面向大学的课件，介绍NVIDIA公司GPU在CDUA平台下的编程方法，是快速进入研究计算机并行计算的优秀课件，全英文的-For university courseware to introduce NVIDIA' s GPU programming platform in CDUA method is quick access to the best of parallel computing research computer courseware, all in English
cuda-radar-signal-process
- 基于cuda的软件雷达信号处理的多GPU并行技术-Multi- GPU Parallel Technology Based on cuda s Software Radar Signal Processing
CUDA code
- CUDA(Compute Unified Device Architecture)，是显卡厂商NVIDIA推出的运算平台。 CUDA?是一种由NVIDIA推出的通用并行计算架构，该架构使GPU能够解决复杂的计算问题。(CUDA (Compute Unified Device Architecture), is the graphics platform NVIDIA's computing platform. CUDA is a general purpose parallel computi
FDTD-Mur-CUDA-master
- 基于CUDA的FDTD模拟二维TM波在真空中的传播，基于Mur边界条件(FDTD-Mur-CUDA ============= 2D FDTD solution for Mur's Absorbing Boundary Condition using CUDA acceleration.)
simulink&&CUDA
- 利用simulink的自动生成代码功能生成代码后，在VC2013上进行编译，然后调用CUDA程序(After generating code from Simulink's automatic generation of code, compiling on VC2013, then calling the CUDA program)