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: 8.3.2.49
* TensorRT: 8.4.0.11
* 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.
or :
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