Hi! I recently bought a new Jetson TX1. According to the user guide, I’ve installed Jetpack 2.3 and L4T R24.2 on the TX1. Unfortunately, when I ran any sample with CUDA, it always showed an error code 35 (CUDA driver version is insufficient for CUDA runtime version). I also typed command ‘nvidia-detector’, but shows ‘none’. I’ve no idea which part goes wrong.
Thanks.
Were you using the program remotely, or directly from the Jetson? If remote, then it may have been talking about your host instead of the Jetson. CUDA itself could have been installed with the Jetson flash, but it is possible you just missed that when installing the extra packages.
Actually, I used the program directly from the Jeston. I’m sure that CUDA 8 has been installed through Jetpack.run on host (Linux mint). Any cues for this issue? @linuxdev
I use Fedora, so debugging JetPack is difficult. What shows up under:
sudo dpkg --list | egrep -i '(nvidia|cuda)'
sudo ldconfig -p | egrep -i '(nvidia|cuda)'
EDIT: Last night the forum was timing out…I guess posts got in, but response never made it back.
sudo dpkg --list | egrep -i ‘(nvidia|cuda)’
ii cuda-command-line-tools-8-0 8.0.34-1 arm64 CUDA command-line tools
ii cuda-core-8-0 8.0.34-1 arm64 CUDA core tools
ii cuda-cublas-8-0 8.0.34-1 arm64 CUBLAS native runtime libraries
ii cuda-cublas-dev-8-0 8.0.34-1 arm64 CUBLAS native dev links, headers
ii cuda-cudart-8-0 8.0.34-1 arm64 CUDA Runtime native Libraries
ii cuda-cudart-dev-8-0 8.0.34-1 arm64 CUDA Runtime native dev links, headers
ii cuda-cufft-8-0 8.0.34-1 arm64 CUFFT native runtime libraries
ii cuda-cufft-dev-8-0 8.0.34-1 arm64 CUFFT native dev links, headers
ii cuda-curand-8-0 8.0.34-1 arm64 CURAND native runtime libraries
ii cuda-curand-dev-8-0 8.0.34-1 arm64 CURAND native dev links, headers
ii cuda-cusolver-8-0 8.0.34-1 arm64 CUDA solver native runtime libraries
ii cuda-cusolver-dev-8-0 8.0.34-1 arm64 CUDA solver native dev links, headers
ii cuda-cusparse-8-0 8.0.34-1 arm64 CUSPARSE native runtime libraries
ii cuda-cusparse-dev-8-0 8.0.34-1 arm64 CUSPARSE native dev links, headers
ii cuda-documentation-8-0 8.0.34-1 arm64 CUDA documentation
ii cuda-driver-dev-8-0 8.0.34-1 arm64 CUDA Driver native dev stub library
ii cuda-license-8-0 8.0.34-1 arm64 CUDA licenses
ii cuda-misc-headers-8-0 8.0.34-1 arm64 CUDA miscellaneous headers
ii cuda-npp-8-0 8.0.34-1 arm64 NPP native runtime libraries
ii cuda-npp-dev-8-0 8.0.34-1 arm64 NPP native dev links, headers
ii cuda-nvgraph-8-0 8.0.34-1 arm64 NVGRAPH native runtime libraries
ii cuda-nvgraph-dev-8-0 8.0.34-1 arm64 NVGRAPH native dev links, headers
ii cuda-nvml-dev-8-0 8.0.34-1 arm64 NVML native dev links, headers
ii cuda-nvrtc-8-0 8.0.34-1 arm64 NVRTC native runtime libraries
ii cuda-nvrtc-dev-8-0 8.0.34-1 arm64 NVRTC native dev links, headers
ii cuda-repo-l4t-8-0-local 8.0.34-1 arm64 cuda repository configuration files
ii cuda-samples-8-0 8.0.34-1 arm64 CUDA example applications
ii cuda-toolkit-8-0 8.0.34-1 arm64 CUDA Toolkit 8.0 meta-package
ii libcudnn5 5.1.5-1+cuda8.0 arm64 cuDNN runtime libraries
ii libcudnn5-dev 5.1.5-1+cuda8.0 arm64 cuDNN development libraries and headers
ii libcudnn5-doc 5.1.5-1+cuda8.0 arm64 cuDNN documents and samples
ii libgie-dev 1.0.0-1+cuda8.0 arm64 GIE development libraries and headers
ii libgie1 1.0.0-1+cuda8.0 arm64 GIE runtime libraries
ii libvisionworks 1.5.3.71n arm64 NVIDIA’s VisionWorks Library and supplemental data
ii libvisionworks-dev 1.5.3.71n all Development files for NVIDIA’s VisionWorks Library
ii libvisionworks-docs 1.5.3.71n all Documentation for NVIDIA’s VisionWorks Library
ii libvisionworks-nvxio 1.5.3.71n arm64 NVIDIA’s VisionWorks Library and supplemental data
ii libvisionworks-nvxio-dev 1.5.3.71n all NVIDIA’s VisionWorks Library and supplemental data
ii libvisionworks-repo 1.5.3.71n arm64 NVIDIA VisionWorks computer vision library.
ii libvisionworks-samples 1.5.3.71n arm64 Samples for NVIDIA’s VisionWorks Library
ii libvisionworks-sfm 0.88.0 arm64 SFM module for NVIDIA’s VisionWorks Library
ii libvisionworks-sfm-dev 0.88.0 arm64 Development files for SFM module for NVIDIA’s VisionWorks Library
ii libvisionworks-sfm-docs 0.88.0 all Documentation for SFM module for NVIDI’s VisionWorks Library
ii libvisionworks-sfm-repo 0.88.0 arm64 Package repository for NVIDIA’s VisionWorks SFM module.
ii libvisionworks-tracking 0.84.0 arm64 Tracking module for NVIDIA’s VisionWorks Library
ii libvisionworks-tracking-dev 0.84.0 arm64 Development files for Tracking module for NVIDIA’s VisionWorks Library
ii libvisionworks-tracking-docs 0.84.0 all Documentation for Tracking module for NVIDIA’s VisionWorks Library
ii libvisionworks-tracking-repo 0.84.0 arm64 Package repository for NVIDIA’s VisionWorks Tracking module.
ii nv-gie-repo-ubuntu1604-6-rc-cuda8.0 1.0.2-1 arm64 nv-gie repository configuration files
sudo ldconfig -p | egrep -i ‘(nvidia|cuda)’
libnvsample_cudaprocess.so (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/libnvsample_cudaprocess.so
libnvrtc.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvrtc.so.8.0
libnvrtc.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvrtc.so
libnvrtc-builtins.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvrtc-builtins.so.8.0
libnvrtc-builtins.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvrtc-builtins.so
libnvidia-tls.so.24.2.1 (libc6,AArch64, OS ABI: Linux 2.3.99) => /usr/lib/aarch64-linux-gnu/tegra/libnvidia-tls.so.24.2.1
libnvidia-rmapi-tegra.so.24.2.1 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libnvidia-rmapi-tegra.so.24.2.1
libnvidia-ptxjitcompiler.so.24.2.1 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libnvidia-ptxjitcompiler.so.24.2.1
libnvidia-glsi.so.24.2.1 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libnvidia-glsi.so.24.2.1
libnvidia-glcore.so.24.2.1 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libnvidia-glcore.so.24.2.1
libnvidia-fatbinaryloader.so.24.2.1 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libnvidia-fatbinaryloader.so.24.2.1
libnvidia-eglcore.so.24.2.1 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libnvidia-eglcore.so.24.2.1
libnvgraph.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvgraph.so.8.0
libnvgraph.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvgraph.so
libnvblas.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvblas.so.8.0
libnvblas.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvblas.so
libnvToolsExt.so.1 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvToolsExt.so.1
libnvToolsExt.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnvToolsExt.so
libnpps.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnpps.so.8.0
libnpps.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnpps.so
libnppitc.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppitc.so.8.0
libnppitc.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppitc.so
libnppisu.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppisu.so.8.0
libnppisu.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppisu.so
libnppist.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppist.so.8.0
libnppist.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppist.so
libnppim.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppim.so.8.0
libnppim.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppim.so
libnppig.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppig.so.8.0
libnppig.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppig.so
libnppif.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppif.so.8.0
libnppif.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppif.so
libnppidei.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppidei.so.8.0
libnppidei.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppidei.so
libnppicom.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppicom.so.8.0
libnppicom.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppicom.so
libnppicc.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppicc.so.8.0
libnppicc.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppicc.so
libnppial.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppial.so.8.0
libnppial.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppial.so
libnppi.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppi.so.8.0
libnppi.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppi.so
libnppc.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppc.so.8.0
libnppc.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libnppc.so
libicudata.so.55 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/libicudata.so.55
libicudata.so (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/libicudata.so
libcusparse.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcusparse.so.8.0
libcusparse.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcusparse.so
libcusolver.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcusolver.so.8.0
libcusolver.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcusolver.so
libcurand.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcurand.so.8.0
libcurand.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcurand.so
libcuinj64.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcuinj64.so.8.0
libcuinj64.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcuinj64.so
libcufftw.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcufftw.so.8.0
libcufftw.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcufftw.so
libcufft.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcufft.so.8.0
libcufft.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcufft.so
libcudart.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcudart.so.8.0
libcudart.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcudart.so
libcuda.so.1 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libcuda.so.1
libcuda.so (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/libcuda.so
libcuda.so (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra/libcuda.so
libcublas.so.8.0 (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcublas.so.8.0
libcublas.so (libc6,AArch64) => /usr/local/cuda-8.0/targets/aarch64-linux/lib/libcublas.so
libEGL_nvidia.so.0 (libc6,AArch64) => /usr/lib/aarch64-linux-gnu/tegra-egl/libEGL_nvidia.so.0
Any cues from these?
That confirms that CUDA 8 is installed on the Jetson, and that the linker has access to the dynamic libraries. I am wondering if this is a permissions issue. Were you running as user ubuntu? If not, you need to add the other user to group “video”:
sudo usermod -a -G video <username>
If this isn’t the issue, then lets see what the application wanted to link against. I don’t know the application’s name, but it would go like this:
ldd </full/path/to/app/name>
I login as user ubuntu. So, I tried the command ‘ldd ’. The application is from NVIDIA-8.0_Samples, e.g., vectorAdd.
It shows that
linux-vdso.so.1 => (0x0000007fb7feb000)
librt.so.1 => /lib/aarch64-linux-gnu/librt.so.1 (0x0000007fb7fb3000)
libpthread.so.0 => /lib/aarch64-linux-gnu/libpthread.so.0 (0x0000007fb7f87000)
libdl.so.2 => /lib/aarch64-linux-gnu/libdl.so.2 (0x0000007fb7f73000)
libc.so.6 => /lib/aarch64-linux-gnu/libc.so.6 (0x0000007fb7e2d000)
/lib/ld-linux-aarch64.so.1 (0x000000556cab3000)
Verify the existence of each of those files from the ldd output. If named file is a symbolic link, then it needs to be verified that it points at an actual file. It looks like they are all there though, so perhaps there is something more subtle than just a missing dependency.
Can someone look up the meaning of the “error code 35”, and why it may claim insufficient CUDA version despite having CUDA 8? I do not have an Ubuntu host, so I am unable to install via JetPack…and it looks like CUDA 8 is not available separately. Would it be possible to get a download URL for CUDA 8 separate from JetPack?
Hi marshallixp and linuxdev,
The “error code 35” means the build being used is incorrect.
Please be sure only Ubuntu 14.04 for Jetpack as that is what we explicitly offer for public - [url]https://developer.nvidia.com/embedded/jetpack[/url]
Thanks
Thanks for your reply. Finally, I managed to use a virtual machine with ubuntu 14.04 instead of real host with linux mint (although both are regarded as same core). Everything is all right, even there is no need to install CUDA on virtual machine (host). I have still no idea why installation based on linux mint generates issues.
Thanks
The URL [url]https://developer.nvidia.com/cuda-downloads[/url] only makes CUDA 8 available on desktops…it is missing the arm64/aarch64 architecture required for L4T on JTX1s. So far as I know the only way of installing CUDA 8 (or ‘cuda-repo--8.0.44-1.’) on a JTX1 is to use JetPack…which of course won’t run on my Fedora host (I have no trouble installing CUDA 8 on the host, what I need is to install it on the JTX1 L4T R24.2). I’d really like to see Linux arm64 added to the CUDA downloads page.
Hi linuxdev,
The Jetpack_2.3 downloads and installs “cuda-repo-l4t-8-0-local_8.0.34-1_arm64.deb” only to the target.
Sorry for bringing the wrong information previously.
Regarding the download for CUDA 8 separate from JetPack, we’re investigating this issue, and will do the update once it’s ready, please stay tuned.
Thanks
CUDA 8 for embedded is downloaded only through JetPack. It’s not planned to be a separate download, due to dependency restrictions.
Thanks
I am having similar issues.
New TX1, just used JetPack 2.3 to download, and install all drivers and selecting “full” under the component manager.
When I try and run the examples “simpleGL”, “stereoDisparity” or “clock”, on the TX1, I get the same error:
CUDA error at ../../common/inc/helper_cuda.h:1133 code=35(cudaErrorInsufficientDriver) "cudaGetDeviceCount(&device_count)"
I am not using remote desktop or ssh’d in.
Any solutions?
Thanks