I have a Jetson Orin Nano, and I’d like to get OpenCV to use CUDA. I understand that this isn’t built in, so I followed instructions that I found at https://qengineering.eu/install-opencv-4.5-on-jetson-nano.html to install OpenCV 4.6. Since those instructions are for an older Jetson Nano, I modified the script to select the correct GPU:
CUDA_ARCH_BIN=8.0
This is specifically what I have found in forums for dealing with the error I’m getting, but it isn’t helping. Despite getting the version right, as far as I can tell, I still get this error when I try to do anything CUDA-related:
error: (-217:Gpu API call) no kernel image is available for execution on the device in function 'call' Aborted
Is 8.0 the right architecture/GPU? Are there tools I can install to diagnose this? What else can I do to figure out what’s going wrong here?
Hi @theosib, try CUDA_ARCH_BIN=8.7 for Orin instead. If you check the CUDA deviceQuery output, it is listed there:
/usr/local/cuda/samples/1_Utilities/deviceQuery$ ./deviceQuery
./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: 6434 MBytes (6746046464 bytes)
(008) Multiprocessors, (128) CUDA Cores/MP: 1024 CUDA Cores
GPU Max Clock rate: 624 MHz (0.62 GHz)
Memory Clock rate: 624 Mhz
Memory Bus Width: 64-bit
L2 Cache Size: 2097152 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
Thanks! I didn’t know about that. I guess I should spend some time looking through those samples. I’ve changed the version to 8.7 and will report back how it goes. Thanks!