I have seen a few posts about this problem, where jetson_release -v does not detect cuda, jetson-stats does not detect cuda, and neither do programs im trying to install that depend on cuda.
my jetson_release -v output:
- NVIDIA Jetson UNKNOWN * Jetpack UNKNOWN [L4T 34.1.1] * NV Power Mode: MODE_50W - Type: 3 * jetson_stats.service: active - Board info: * Type: UNKNOWN * SOC Family: tegra23x - ID: * Module: UNKNOWN - Board: P3737-000 * Code Name: concord * CUDA GPU architecture (ARCH_BIN): NONE * Serial Number: 1422022101753 - Libraries: * CUDA: NOT_INSTALLED * cuDNN: 188.8.131.52 * TensorRT: 184.108.40.206 * Visionworks: NOT_INSTALLED * OpenCV: 4.6.0 compiled CUDA: YES * VPI: ii libnvvpi2 2.0.14 arm64 NVIDIA Vision Programming Interface library * Vulkan: 1.3.203 - jetson-stats: * Version 3.1.4 * Works on Python 3.8.10
my ./deviceQuary output:
./deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "Orin" CUDA Driver Version / Runtime Version 11.4 / 11.4 CUDA Capability Major/Minor version number: 8.7 Total amount of global memory: 30623 MBytes (32110190592 bytes) (016) Multiprocessors, (128) CUDA Cores/MP: 2048 CUDA Cores GPU Max Clock rate: 1300 MHz (1.30 GHz) Memory Clock rate: 1300 Mhz Memory Bus Width: 128-bit L2 Cache Size: 4194304 bytes Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384) Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total shared memory per multiprocessor: 167936 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 1536 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 2 copy engine(s) Run time limit on kernels: No Integrated GPU sharing Host Memory: Yes Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device supports Managed Memory: Yes Device supports Compute Preemption: Yes Supports Cooperative Kernel Launch: Yes Supports MultiDevice Co-op Kernel Launch: Yes Device PCI Domain ID / Bus ID / location ID: 0 / 0 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.4, CUDA Runtime Version = 11.4, NumDevs = 1 Result = PASS
for example, my opencv cmake error output:
CMake Warning at cmake/OpenCVFindLibsPerf.cmake:45 (message): OpenCV is not able to find/configure CUDA SDK (required by WITH_CUDA). CUDA support will be disabled in OpenCV build. To eliminate this warning remove WITH_CUDA=ON CMake configuration option.
CMake Error at modules/dnn/CMakeLists.txt:36 (message): DNN: CUDA backend requires CUDA Toolkit. Please resolve dependency or disable OPENCV_DNN_CUDA=OFF
sudo apt install nvidia-jetpack returns
nvidia-jetpack is already the newest version (5.0.1-b118).
not sure what to do. maybe i have to use SDK manager although finding a compatible ubuntu PC might not be the easiest