nvidia

问题 I've installed the latest CUDA and driver for my GPU. I'm using Python 2.7.10 on Win7 64bit. I tried installing pyopencl from: a . the unofficial windows binaries at http://www.lfd.uci.edu/~gohlke/pythonlibs/#pyopencl b . by compiling my own after getting the sources from https://pypi.python.org/pypi/pyopencl The installation was successful on both cases but I get the same error message once I try to import it: >>> import pyopencl Traceback (most recent call last): File "<stdin>", line 1, in

问题 I have installed tensorflow using the anaconda environment as mentioned in the tensorflow website and after doing my python installation path changed. dennis@dennis-HP:~$ which python /home/dennis/anaconda2/bin/python And Jupyter was installed. I assumed that if I was able to import and use tensorflow in the conda environment that I will be able to do the same in Jupyter. But that was not the case - Importing tensorflow in my system (without activating the environment) dennis@dennis-HP:~$

问题 I am tring to open an OpenGL full screen window using GLFW on linux red-hat. I have a desktop that spans two monitors with total resolution of 3840*1080. I have two problems: 1. The window is opened just on one monitor with maximum window width of 1920 (the width of a single monitor). 2. The maximum height of the window is 1003 (which I think is the height of the screen minus the height of the task bar and the top bar). This is the code I use to open the window: if (glfwInit() == GL_FALSE)

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 4 years ago . Microsoft creates their windows and MFC DLL library, etc. An open source develop write a new MFC application and release the source code as GPL. The app has to link with the MS DLL/libraries to run in Windows, but I don't think anyone can argue that we now have the right to force the Microsoft's GPL their DLL.

问题 I'm just starting out with CUDA. Is there a way of getting the card specs programmatically? 回答1: You can use the cudaGetDeviceCount and cudaGetDeviceProperties APIs. void DisplayHeader() { const int kb = 1024; const int mb = kb * kb; wcout << "NBody.GPU" << endl << "=========" << endl << endl; wcout << "CUDA version: v" << CUDART_VERSION << endl; wcout << "Thrust version: v" << THRUST_MAJOR_VERSION << "." << THRUST_MINOR_VERSION << endl << endl; int devCount; cudaGetDeviceCount(&devCount);

问题 Can anyone give me a good explanation as to the nature of CUDA C and C++? As I understand it, CUDA is supposed to be C with NVIDIA's GPU libraries. As of right now CUDA C supports some C++ features but not others. What is NVIDIA's plan? Are they going to build upon C and add their own libraries (e.g. Thrust vs. STL) that parallel those of C++? Are they eventually going to support all of C++? Is it bad to use C++ headers in a .cu file? 回答1: CUDA C is a programming language with C syntax.

问题 Closed . This question needs details or clarity. It is not currently accepting answers. Want to improve this question? Add details and clarify the problem by editing this post. Closed 9 days ago . I am reading NCCL code on Nvidia Github, it is to hard to understand how topology is build. Is there any material or paper can explain this process. I think maybe Nvidia has released some paper before is also helpful for me. Is there any reference paper can explain function ncclTopoCompute(). Thanks

问题 This question already has an answer here : How to copy the memory allocated in device function back to main memory (1 answer) Closed 3 years ago . I need to use polymorphism in my kernels. The only way of doing this is to create those objects on the device (to make a virtual mehod table available at the device). Here's the object being created class Production { Vertex * boundVertex; } class Vertex { Vertex * leftChild; Vertex * rightChild; } Then on the host I do: Production* dProd;

问题 We are trying to connect our Tobii Eye Tracker to our Ubuntu OS 16.04.6 LTS Nvidia Jetson TX2 module. However, when we want to pip install tobii_research we keep getting an error that says that there are not matching distributions found for it. Has anyone had any success doing this? We are using a virtual environment for python 3.5 and we are trying to install psychopy but it keeps saying that it is failing with error code 1 in /tmp/pip-install-cdg_if0d/psychopy. Do we need psychopy inorder

问题 I'm working on a "fujitsu" machine. It has 2 GPUs installed: Quadro 2000 and Tesla C2075. The Quadro GPU has 1 GB RAM and Tesla GPU has 5GB of it. (I checked using the output of nvidia-smi -q). When I run nvidia-smi, the output shows 2 GPUs, but the Tesla ones display is shown as off. I'm running a memory intensive program and would like to use 5 GB of RAM available, but whenever I run a program, it seems to be using the Quadro GPU. Is there some way to use a particular GPU out of the 2 in a