![]() ![]() Just like said, this issue occurs on fresh installed Ubuntu 18.04.2. The error is not observed on systems that are upgraded from 18.04.1 to 18.04.2. Note: This error is only observed on systems with a new install of Ubuntu 18.04.2. To recover from this error, install the xserver-xorg-core package and proceed with the installation of CUDA. On systems with a new install of Ubuntu 18.04.2, note that the installation of CUDA 10.1 and NVIDIA 418 drivers may result in the following error: The following packages have unmet dependencies: The CUDA 10.1 release notes also specify : The following packages have unmet dependencies:Ĭuda : Depends: cuda-10-1 (>= 10.1.105) but it is not going to be installedĮ: Unable to correct problems, you have held broken packages. The following information may help to resolve the situation: Requested an impossible situation or if you are using the unstableĭistribution that some required packages have not yet been created | 0 GeForce GTX 760 Off | 00000000:02:00.Neither local nor network installer succeed to install. | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. Then install the graphics driver: sudo apt install nvidia-driver-396Īfter a reboot, you can run nvidia-smi to see if it is installed: nvidia-smi In a terminal window, type in: sudo apt-add-repository ppa:graphics-drivers/ppa To install the NVIDIA graphics drivers in 18.04LTS, follow the steps below: ) Success ĬlCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) No platformĬlCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices found in platformĬlCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) No platformĬlCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No devices found in platformĬlCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) Invalid device type for platformĬlCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) No platform ) NVIDIA CUDAĬlGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL. Max size of kernel argument 4352 (4.25KiB)Ĭoncurrent copy and kernel execution (NV) Yesĭevice Extensions cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_bufferĬlGetPlatformInfo(NULL, CL_PLATFORM_NAME. Max 1D or 2D image array size 2048 images Max size for 1D images from buffer 134217728 pixels Minimum alignment for any data type 128 bytesĪlignment of base address 4096 bits (512 bytes) ![]() Single-precision Floating-point support (core)Ĭorrectly-rounded divide and sqrt operations Yesĭouble-precision Floating-point support (cl_khr_fp64) Half-precision Floating-point support (n/a) Platform Extensions cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer ![]() Then you should get something similar to the following: clinfo ![]() Just install clinfo and run it to see: sudo apt install clinfo The toolkit also installs the necessary drivers and support for OpenCL. You should see something similar to this: nvcc -VĬopyright (c) 2005-2017 NVIDIA CorporationĬuda compilation tools, release 9.1, V9.1.85 Run the following from a terminal window: sudo apt install nvidia-cuda-toolkitĪfter it is installed run nvcc -V to confirm. It looks as though the CUDA 9.1 is actually in the official 18.04 repositories now. ![]()
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