Discover cuda algorithms, include the articles, news, trends, analysis and practical advice about cuda algorithms on alibabacloud.com
NVIDIA CUDA installation Guide for Linux the Nvidia CUDA installation Guide under Linux systems 1. Introduction Cuda®is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the Graphics-processing unit (GPU). Cuda® w
original articles, reproduced please indicate the source ... I. Background of the problem Recently to do a learning sharing report on Cuda, I would like to make an example of using Cuda for image processing in the report, and use shared memory to avoid the global memory not merging, improve image processing performance. But for the CUDA program how to read the
Cuda Programming (ii) CUDA initialization and kernel functionsCuda InitializationAs has been said in the last time, Cuda installation success, a new project is very simple, directly in the new project when the Nvidia Cuda project can be selected, we first create a new Mycudatest project, Delete the sample kernel.cu, an
() - start print("gpu run time %f seconds " % run_time) # cpu run start = timer() aa = (aa * 10 + 2 ) * ((b + 2) * 10 - 5 ) * 5 run_time = timer() - start print("cpu run time %f seconds " % run_time) # check result r = a - aa print( min(r), max(r) )def main(): for n in range(1, 10): N = 1024 * 1024 * (n * 10) print("------------%d---------------" % n) test(N)if __name__ == '__main__': main() Comparison Numba uses some commands to mark some functions for acceleration (you can al
CUDA and cuda ProgrammingCUDA SHARED MEMORY Shared memory has some introductions in previous blog posts. This section focuses on its content. In the global Memory section, Data Alignment and continuity are important topics. When L1 is used, alignment can be ignored, but non-sequential Memory acquisition can still reduce performance. Dependent on the nature of algorithms
One, Introduction Since the system was upgraded from Ubuntu 14.04 to 16.04, the original Cuda 6.5 could not continue to be used, so Cuda 8.0 was reinstalled. Two, uninstall Cuda 6.5 and drive The following actions are operated at the command-line interface, such as pressing CTRL+ALT+F1 into the command lineFirst stop LIGHTDM:sudo service LIGHTDM stop Uninstall n
time of the kernel function is not exactly the same. So it is recommended to use Method 3. Perform the warmup function first, in the loop 10 times the timing section. the use of NVVP and Nvprof nvprof is a command line profiler that has been in existence since cuda5.0, and you can use only nvprof to perform some of the execution details of your code. The simple usage is as follows: $ nvprof./sumarraysongpu-timer You can get the following: ./sumarraysongpu-timer Starting ... Using Device 0:tes
Ubuntu14.04 configure cuda-convnet and cuda-convnet Reprinted Please note: http://blog.csdn.net/stdcoutzyx/article/details/39722999 In the previous Link, I configured cuda and had a powerful GPU. Naturally, the resources could not be completely idle, So I configured a convolutional neural network to run the program. As for the principle of the convolutional neura
Cuda register array resolution, cuda register About cuda register array When performing Parallel Optimization on some algorithms based on cuda, in order to improve the running speed of the algorithm as much as possible, sometimes we want to use register arrays to make the a
Translated from: http://blog.csdn.net/masa_fish/article/details/51882183The installation of CUDA7.5 and CUDA8.0 is a hair-like process. So if you install CUDA8.0, just replace all of the 7.5 below with 8.0.Toss a lot of days, before and after re-installed probably 六、七次 Ubuntu, finally on the Cuda installed, was the pit several times, also took a lot of detours.The first post, also please more advice.EnvironmentNotebook: ThinkPad T450 x86_64Video card:
Operating System (OS): Windows 7 set into the development environment (IDE): Microsoft Visual Studio 2008 SP1 CUDA version (CUDA version): 3.0 Hardware that supports CUDA when CUDA programming is not necessary, and Cuda provides a way to simulate GPU operations with CPUs, so
I won't talk about the installation of Cuda and Optimus on the theme. I found that some foreigners did not succeed or there were few articles about Kali. After more than one day of repeated installation and testing, this article is the final one, the English version is also released. Install Cuda and NVIDIA driversThis step is relatively simple. Before installation, we recommend that you edit the/etc/APT/so
With the development of graphics cards, GPUs become more and more powerful, and GPU optimizes display images. Computing has surpassed general CPU. Such a powerful chip would be too wasteful if it was just a video card, so NVIDIA launched Cuda to allow the video card to be used for purposes other than Image Rendering and computing (for example, general parallel computing mentioned here ). Cuda is the compute
I won't talk about the installation of cuda and optimus on the theme. I found that some foreigners did not succeed or there were few articles about Kali. after more than one day of repeated installation and testing, this article is the final one, the English version is also released. Installing cuda and nvidia drivers is relatively simple. before installation, we recommend that you... I won't talk about the
Learning computer image processing algorithm of children's shoes, you have to learn Cuda, why. Because image processing is usually a matrix operation, it is very important to calculate the calculation time of millions at this time is essential. OPENCV itself provides a number of CUDA functions that meet the needs of most users. But not absolutely, sometimes we need to define a kernel function to optimize, o
CUDA and cuda ProgrammingIntroduction to CUDA Libraries It is the location of the CUDA library. This article briefly introduces cuSPARSE, cuBLAS, cuFFT and cuRAND will introduce OpenACC later. The cuSPARSE linear algebra library is mainly used for sparse matrices. CuBLAS is a C
We have installed winxp64 + nvidia driver19 *. * + VS2008 (sp1), and we feel very stuck, so we have been using cuda2.2. I installed win7 recently and found that the driver compatibility for Versions later than 190 is very good. I installed cuda2.3. I wanted to try VS2010 beta2, However, I learned from Microsoft's staff that MSBuild still has some bugs, so I cannot use cuda normally and cannot patch me for the moment. Switch back to VS2008. When using
When Cuda C is run in the cudart library, the application can be linked to the static library cudart. lib or libcudart. A. The dynamic library cudart. dll or libcudart. So. The Cuda dynamic link library (cudart. dll or libcudart. So) must be included in the installation package of the application. All running functions of Cuda are prefixed with
Run Devicequery error after installing CUDA8.0. CUDA Device Query (Runtime API) version (Cudart static linking)Cudagetdevicecount returned 35Cuda driver version is insufficient for CUDA runtime versionResult = FAILThere are a lot of ways to find out, Dpkg-l | grep cuda Discovery There is libcuda1-304, and the libcuda1-375 version is 375.66, above
optimization of the CPU version, the Code cannot be directly parallel. In this case, you need to modify the original program according to the requirements of the parallel algorithm, this mode can be changed to a parallel mode. Some modules can be parallel in theory, but serial algorithms cannot be directly parallelized. We need to re-design parallel algorithms. B) array Modification The array definition us
Start building with 50+ products and up to 12 months usage for Elastic Compute Service
1 on 1 presale consultation
24/7 Technical Support 6 Free Tickets per Quarter Faster Response
Alibaba Cloud offers highly flexible support services tailored to meet your exact needs.
A comprehensive suite of global cloud computing services to power your business
Payment Methods We Support
