Open rmadan2 opened 2 years ago
I understand that an 801 error means that the service isn't currently supported on the NVIDIA device. but is there a work-around to it?
@rmadan2 did you resolved this issue?, I also got the same problem in Jetson Xavier AGX. Could you please help!
And when I passed --disable_vis
flag, then the new error is like this:
RuntimeError: CUDA error: no kernel image is available for execution on the device
My output for torch.cuda.is_available()
is True
My output for torch.cuda.get_arch_list()
is ['sm_53', 'sm_62', 'sm_72']
My output for torch.Tensor([10,23]).to("cuda")
is tensor([10., 23.], device='cuda:0')
Hi @surajiitd , I have not been able to resolve this issue
@surajiitd did you manage to solve this kernel image error?
Yes, you need to give appropriate compiler flags for line no. 21 and 51, instead of compiling for those 6 architectures, you need to do that for ARM architecture. I don't remember properly, for jetson orin it was '-march=armv8-a' I guess.
Thanks !! You saved many hours of misery for me. My GPU was very old for the default architectures mentioned on those lines. I had to add _50 flags.
@surajiitd Hello. Did you add only '-march=armv8-a' as the cxx option and '-gencode=arch=compute_72,code=sm_72' as the nvcc option to the setup.py file?
I wonder if I only need to modify setup.py .
@TryTwoTop Sorry, I don't remember. You can share if you managed to resolve the issue.
'-gencode=arch=compute_87,code=sm_87'
line worked in Jetson AGX Orin (it has Ampere architecture) to compile lietorch
and droid_backends
.
@surajiitd Thank you so much for your precious time !!
I would like to begin by saying that this is indeed an exceptional effort. I am impressed by the robustness and stability of DROID-SLAM in particular. I am currently trying to implement DROID-SLAM on a Jetson Xavier NX. I understand that a GPU with at least 11GB of memory is needed for inference, but I am not currently interested in real-time performance. The Jetson Xavier NX board that I am using currently is running with Python 3.6, with CUDA 10.2 and Pytorch 1.10, and I am getting the following error: