nvidia

问题 I use: Single CPU (Intel Core i7-4820K Ivy Bridge-E) 40 Lanes of PCIe 3.0 + MotherBoard MSI X79A-GD65 (8D) WindowsServer 2012, MSVS 2012 + CUDA 5.5 and compiled as 64-bit application GPUs nVidia Quadro K4000 and K2000 All Quadros in TCC-mode (Tesla Compute Cluster) nVidia Video Driver 332.50 simpleP2P-test shown that, all Quadros K4000 and K4000 - IS capable of Peer-to-Peer (P2P), but Peer-to-Peer (P2P) access - Quadro K4000 (GPU0) <-> Quadro K2000 (GPU1) : No. Can I use Quadro K4000 and

问题 I want to get driver version of nVidia video card. So I used WMI and get data from "DriverVersion" obejct of "Win32_VideoController" class. But it was like "9.18.13.1106"(file version) and what I wanted is something like "311.06"(treiber version). Where can I get that information? If it is impossible on WMI, I want to know other way to get that. Thanks. 回答1: You can do this using NVML from nVidia's Tesla Deployment Kit. You can retrieve the internal driver version (the one you're accustomed

问题 I am using the open source haptics and 3D graphics library Chai3D running on Windows 7. I have rewritten the library to do stereoscopic 3D with Nvidia nvision. I am using OpenGL with GLUT, and using glutInitDisplayMode(GLUT_RGB | GLUT_DEPTH | GLUT_DOUBLE | GLUT_STEREO) to initialize the display mode. It works great on Quadro cards, but on GTX 560m and GTX 580 cards it says the pixel format is unsupported. I know the monitors are capable of displaying the 3D, and I know the cards are capable

问题 I am learning CUDA with trying to solve some standard problems. As a example, I am solving the diffusion equation in two dimensions with the following code. But my results are different than the standard results and I am not able to figure that out. //kernel definition __global__ void diffusionSolver(double* A, double * old,int n_x,int n_y) { int i = blockIdx.x * blockDim.x + threadIdx.x; int j = blockIdx.y * blockDim.y + threadIdx.y; if(i*(n_x-i-1)*j*(n_y-j-1)!=0) A[i+n_y*j] = A[i+n_y*j] +

问题 I have a Intel Xeon machine with NVIDIA GeForce1080 GTX configured and CentOS 7 as operating system. I have installed NVIDIA-driver 410.93 and cuda-toolkit 10.0. After compiling the cuda-samples, i tried to run ./deviceQuery. But it throws like this ./deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount returned 30 -> unknown error Result = FAIL some command outputs lspci | grep VGA 01:00.0 VGA compatible controller: NVIDIA Corporation

问题 const char programSource[] = "__kernel void vecAdd(__global int *a, __global int *b, __global int *c)" "{" " int gid = get_global_id(0);" "for(int i=0; i<10; i++){" " a[gid] = b[gid] + c[gid];}" "}"; The kernel above is a vector addition done ten times per loop. I have used the programming guide and stack overflow to figure out how global memory works, but I still can't figure out by looking at my code if I am accessing global memory in a good way. I am accessing it in a contiguous fashion

问题 I'm a newbie in OpenCL. From yesterday, I'm trying to use OpenCL for parallel programming instead of CUDA which is more familiar for me and experienced before. Now I have NVIDIA GTX 580 GPU, Ubuntu Linux 12.04 OS and CUDA SDK 4.1 (already installed before because of CUDA programming). In CUDA SDK folder, Some OpenCL header file and library are already included. So I just downloaded OpenCL examples from NVIDIA's Developer zone. (Here is the link! https://developer.nvidia.com/opencl) And I'm

问题 Trying to run docker command : nvidia-docker run -d -p 8888:8888 -e PASSWORD="123abcChangeThis" theano_secure start-notebook.sh # Then open your browser at http://HOST:8888 taken from https://github.com/nouiz/Theano-Docker returns error : Error: image library/theano_secure:latest not found Appears the theano_secure image is not currently available ? Searching for theano_secure : $ nvidia-docker search theano_secure:latest NAME DESCRIPTION STARS OFFICIAL AUTOMATED The return of this command is

问题 I've been googling around and have only been able to find a trivial example of the new dynamic parallelism in Compute Capability 3.0 in one of their Tech Briefs linked from here. I'm aware that the HPC-specific cards probably won't be available until this time next year (after the nat'l labs get theirs). And yes, I realize that the simple example they gave is enough to get you going, but the more the merrier . Are there other examples I've missed? To save you the trouble, here is the entire

问题 I have followed all the instructions from https://datanoord.com/2016/02/01/setup-a-deep-learning-environment-on-windows-theano-keras-with-gpu-enabled/ but can't seem to get it work. I have added C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin to my PATH variable Every time I run the code from the Theano website to test whether a CPU or GPU is used, it gives me a fatal error of "nvcc fatal : Cannot find compiler 'cl.exe' in PATH" Here is the code I use to test: from theano import