Im trying to install Nvidia v352.50 (i also installed virtalgl 4.2.1, latest version available) I also tried every tutorial on the web but nothing worked. I’ve searched around for this error message, there is a lot of info, but not in relation to Mxnet, so i prefer to receive guidance here before changing anything. CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount returned 35 - CUDA driver version is insufficient for CUDA runtime version Result FAIL. Nvidia console on startup tells me to update to 396.64, which i did, but error message did not change, even after reboot. I can provide more info on the dump if needed.Īfter installation I had CUDA Driver Version: 387.128 but gives me error message above. Src/storage/:119: Check failed: e = cudaSuccess || e = cudaErrorCudartUnloading CUDA: CUDA driver version is insufficient for CUDA runtime version When i try to run the test command at the end (python example/image-classification/train_mnist.py -network lenet -gpus 0), i get: But the Cuddn installation was for CUDA 9.0 or CUDA 9.2, no files for 9.1 (but all version 7.1.4 ), so i went for CUDA 9.2 I could install CUDA 9.1 driver and tool kit. Q. Q.CUDA driver version is insufficient for CUDA runtime version is displayed, and training cannot be executed. GPU 1 (GeForce GTX 1050) with CUDA compute capability -1.-1 cannot be used by iray photoreal. I could follow the instructions without any problems. To access Dirac, we first log into a machine known as Carver, which is Diracs front end. Version (CUDART static linking) cudaGetDeviceCount returned 35 -> CUDA driver version is. Trying to install Mxnet following precisely these instructions ĭual GPU -> Intel Iris Pro and NVIDIA GeForce GT 750M (CUDA compatible) Tegra-K1 deviceQuery fails: CUDA driver version is insufficient.
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