bash nvcc --version nvidia-smi 这些命令将分别显示 CUDA 编译器的版本和 NVIDIA GPU 的状态信息。 希望这些步骤能帮助您解决“E: unable to locate package nvidia_cuda_toolkit”错误,并成功安装 CUDA Toolkit。如果问题仍然存在,请确保您的系统能够访问 NVIDIA 的存储库,并检查您的网络连接设置。
And here is my modified DockerFile per@i11quick recommendation (which did get me past the originalUnable to locate package condaerror: ARG IMAGE_TYPE=extras ARG BASE_IMAGE=ubuntu:22.04 # extras or core FROM ${BASE_IMAGE} as requirements-core ARG GO_VERSION=1.21.7 ARG BUILD_TYPE ARG CUDA...
The build succeeds when CUDA and Bazel are apt-get install'd, e.g. in a Dockerfile build environment. So it seems to be Conda that's introducing the inability to locate libcudart.so. Not sure where to go from here! Collaborator cloudhan commented Mar 8, 2024 See the toolkit detection...
Done E: Unable to locate package linux-headers-4.9.140-tegra E: Couldn't find any package by glob 'linux-headers-4.9.140-tegra' E: Couldn't find any package by regex 'linux-headers-4.9.140-tegra' I tried to get the runtime file for ubuntu x86_64 off the NVIDIA website and just...
Add the path to the CUDAbindirectory (usually something likeC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\vX.X\bin). Click OK to save and close all dialog boxes. After this, you should be able to usenvcc --versionin the terminal to confirm it's correctly set up. ...
Because now by default we use find_package to locate the dependencies first. You can set FETCHCONTENT_TRY_FIND_PACKAGE_MODE to NEVER. cyrusbehr commentedon Oct 7, 2023 cyrusbehr on Oct 7, 2023 Author AddingSET(CMAKE_SYSTEM_PROCESSOR aarch64)indeed fixes the issue for v1.15.1. Thank you...