To check CUDA version with nvidia-smi, directly runnvidia-smiYou can see similar output in the screenshot below. The version is at the top right of the output. Here’s my version is CUDA 10.2. You may have 10.0, 10.1 or even the older version 9.0 or 9.1 or 9.2 installed....
The latest version of CUDA-MEMCHECK with support for CUDA C and CUDA C++ applications is available with the CUDA Toolkit and is supported on all platforms supported by theCUDA Toolkit. Developers should be sure to check out NVIDIA Nsight for integrated debugging and profiling.Nsight Eclipse Editio...
Controls which CUDA-MEMCHECK tool is actively running Prints the version of cuda-memcheck Table 3. Memcheck Tool Command line options Option Values check-api- memory-access yes,no check-device-heap yes,no leak-check full,no Default yes yes no report-api-errors all, explicit, no explicit...
CUDA and CUDNN are installed, however my GPU memory is 10GB/11GB when running face and hand commands. I verified my CUDA and CUDNN installations so I don't know why CUDNN is not being picked up. Executed Command (if any) Note: add --logging_level 0 --disable_multi_thread to get ...
tool memcheck, racecheck, initcheck, synccheck memcheck Controls which CUDA-MEMCHECK tool is actively running version (V) N/A N/A Prints the version of cuda-memcheck Table 3. Memcheck Tool Command line options OptionValuesDefaultDescription check-api-memory-access yes,no yes Enable checking ...
–Found CUDA: /usr/local/cuda-11.2 (found version “11.2”) –Found TensorRT headers at /usr/include/x86_64-linux-gnu finally, i built my program successfully on the basis of above enviroment, however, when i executed the program to do onnx transferring to engine file...
Hi, My environment is: windows 10, VS2017, GPU 2080Ti, GPU driver 441.12, CUDA 10.2.88, cudnn version cudnn-10.1-windows10-x64-v7.6.3.30. On my computer, I could correctly run the weights model of deep learning neura…
I realized that there was an error with my CUDA installation, specifically with the cuBLAS library. You can check if yours has the same problem by running the sample program simpleCUBLAS: cd /usr/local/cuda/samples/7_CUDALibraries/simpleCUBLAS # check if your samples are in the same direct...
My environment info is: GPU: 2080 Ti CUDA: 10.0.130 cuDNN: 7.6.0 PyTorch: 1.6.0 Thank you. Owner alexandrosstergiou commented Jan 19, 2021 Hi @rumsyx, This sounds like an NVCC/CUDA runtime version mismatch for your system. Check #62 issue in PyTorch and ensure that your NVCC and ...
I realized that there was an error with my CUDA installation, specifically with the cuBLAS library. You can check if yours has the same problem by running the sample program simpleCUBLAS: cd /usr/local/cuda/samples/7_CUDALibraries/simpleCUBLAS # check if your samples are in the same direct...