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Description: 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 modern vintage.
BUILDING INSTRUCTIONS: Change the 'MATLAB' (and if necessary, 'MEX') variables in the Makefile to appropriate values, then simply run 'make' at a prompt and an executable (mex/mexmac/mexmaci/dll?) file will be created.
This code uses your GPU's built-in bilinear texture interpolation capability, and is very fast. For reasonably sized operations (taking, say, a 50x50 matrix up to 1000x1000) CUDA-based code is 5-10x faster than linear interp2 (as tested on a MBP 2.4GHz C2D, GeForce 8600M GT).
With very (VERY) large matrices, however, it has the capability of completely crashing your computer or giving bizarre results. Be careful!
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Size: 37881 |
Author: whitewalter |
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Description: cuda加速粒子群算法的代码，非常不错哦-particle swarm algorithm to accelerate the cuda code
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Size: 104448 |
Author: wangwei |
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Description: 说明了matlab与cuda之间的关系，对于有一定基础的matlab编程人员来说，是一个可以借鉴的书-Matlab and cuda illustrates the relationship between the basis for some of the matlab programmers is a reference book
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Size: 3528704 |
Author: 胡帅 |
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Description: Matlab and CUDA program manual.
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Size: 165888 |
Author: lkdata |
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Description: Nivada之CUDA，加速Matlab运算的文档资料。-Nivada of CUDA, speed up the Matlab computing documentation.
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Size: 201728 |
Author: 睢小龙 |
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Description: 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 processing power of Graphics Processors (GPUs). cuSVM is written in NVIDIA s CUDA C-language GPU programming environment, includes implementations of both classification and regression, and performs SVM training (prediction) at 13-73 (22-172) times the rate of state of the art CPU software. Moreover, cuSVM features a Matlab MEX wrapper so that users can access the GPU s power without having to do any "real" programming.
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Size: 879616 |
Author: Sheng |
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Description: This bundle provides the source code for the INRIA Object Detection and Localization Toolkit, with various optimizations including a CUDA port that allows most of the processing to be offloaded to a CUDA-capable NVidia graphics card for substantial speedups.
-This bundle provides the source code for the INRIA Object Detection and Localization Toolkit, with various optimizations including a CUDA port that allows most of the processing to be offloaded to a CUDA-capable NVidia graphics card for substantial speedups.
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Size: 4988928 |
Author: qinlei |
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Description: 在matlab中可以调用的程序，用c语言编写，cuda求直方图-used in caculating histogram of color images ,
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Size: 1024 |
Author: li |
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Description: pdf file see Accelerating MATLAB with CUDA The MATLAB scripts solve the Euler equation in vorticitystream
function using a pseudo-spectral method
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Size: 72704 |
Author: ragunathan |
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Description: The latest generation of high-end video cards off er considerable
computing power using their 100–200 on-card processors, 0.3–1.0+ GB
of RAM, and fast inter-processor communications. One promising
application of this Graphics Processing Unit (GPU) computing
capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU. -The latest generation of high-end video cards offer considerable computing power using their 100-200 on-card processors, 0.3-1.0+ GB of RAM, and fast inter-processor communications. One promising application of this Graphics Processing Unit (GPU) computing capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU.
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Size: 166912 |
Author: charlesw0100 |
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Description: Parzer Window on CUDA for Matlab
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Size: 16384 |
Author: Dmitry |
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Description: Self organizing maps for Matlab CUDA
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Size: 76800 |
Author: Dmitry |
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Description: cuda5 and matlab code for Gaussian filtering and parallel image processing code, we hope to help
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Size: 20444160 |
Author: ye |
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Description: MATLAB平台下的CUDA加速库。运用该库可避免在MEX函数中来回拷贝GPU数据，提高MATLAB运行速率。附件给出一个简单的矩阵乘法的示例程序，该程序在GTX TITAN下运行效率比intel i7 3930k提高了10倍。-CUDA MATLAB platform acceleration libraries. Avoid the use of the library can be copied back and forth GPU MEX function data, improve MATLAB run rate. Annex gives an example of a simple matrix multiplication program that runs under the GTX TITAN 10 times more efficient than the intel i7 3930k.
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Size: 379904 |
Author: andy |
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Description: 图像处理 并行处理 matlab Since images can be represented by 2D or 3D matrices and the MATLAB processing engine
relies on matrix representation of all entities, MATLAB is particularly suitable for implemen‐
tation and testing of image processing workflows. The Image Processing Toolbox
™
(IPT)
includes all the necessary tools for general-purpose image processing incorporating more than
300 functions which have been optimised to offer good accuracy and high speed of processing.
Moreover, the built-in Parallel Computing Toolbox
™
(PCT) has recently been expanded and
now supports graphics processing unit (GPU) acceleration for some functions of the IPT.
However, for many image processing applications we still need to write our own code, either
in MATLAB or, in the case of GPU-accelerated applications requiring specific control over
GPU resources, in CUDA (Nvidia Corporation, Santa Clara, CA, USA).-the first part is dedicated to some essential tools of the IPT that can be used in
image analysis and assessment as well as in extraction of useful information for further
processing and assessment. These include retrieving information about digital images, image
adjustment and processing as well as feature extraction and video handling. The second part
is dedicated to GPU acceleration of image processing techniques either by using the built-in
PCT functions or through writing our own functions. Each section is accompanied by MAT‐
LAB example code.
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Size: 629760 |
Author: 阿新 |
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Description: 这是在Matlab软件平台下的 GPU程序，进行图像放大的并行运算，使用CUDA来编写程序。(This is in the Matlab software platform under the GPU program, image amplification parallel operation, using CUDA to write programs.)
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Size: 952320 |
Author: 仁仁
|
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Description: faster_rcnn的matlab试验资料，包括编译好的包，CUDA7.5，matlab2016a，VS2013(this is a good learning resource for object detection using deep learning.
we use faster_rcnn algorithm and matlab coder
cuda version is 7.5
VS version is 12.0
matlab version is 2016a)
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Size: 100352 |
Author: 文静静
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Description: 使用cuda对快匹配算法进行并行化处理，提高了运算速度(The fast matching algorithm is parallelized with CUDA, and the speed of operation is improved.)
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Size: 350208 |
Author: `Ban
|
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Description: It is cuda cluster pkgs
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Size: 21683200 |
Author: nandini |
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Description: 1.在MATLAB中直接实现Marching Cubes;
2.使用了向量化和预分配的概念在MATLAB中优化;
3.用c-mex函数和GPU实现.(1. Marching Cubes is realized directly in MATLAB;
2., the concepts of VQ and pre allocation are optimized in MATLAB.
3. is implemented with c-MEX function and GPU.)
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Size: 97280 |
Author: zyj0-0 |
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