Error in running homogeneous refinement


The homogeneous refinement was failed when running with the tutorial data with D7 symmetry. It’s cryosparc 3.3.2 on a stand alone workstation and got the following error message. Could you let me know what the problem is and how I could fix it. Thank you so much!

File “cryosparc_worker/cryosparc_compute/”, line 85, in
File 'cryosparc_worker/cryosparc_compute/jobs/refine/", line 332, in
File “/home/cryosparc_worker/cryosparc_compute/”, line 165, in align_symmetry
File “cryosparc_worker/cryosparc_compute/engine/”, line 6961, in cryosparc_compute.engine.newcuda_kernels.compute_sym_error
File “cryosparc_worker/cryosparc_compute/engine/” , line 412, in cryosparc_compute.engine.cuda_core.context_dependent_memoize.wrapper
File “cryosparc_compute/engine/”, line 6926, in cryosparc_compute.engine.newcuda_kernels.get_compute_sym_error_kernel
File “/home/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env/lib/python3.7/site-packages/pycuda/”, line 291, in init
arch, code, cache_dir, include_dirs)
File “/home/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env/lib/python3.7/site_packages/pycuda/”, line 254, in compile
return compile_plain(source, options, keep, nvcc,cache_dir, target)
File “/home/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env/lib/python3.7/site-packages/pycuda/”, line 137, in compile_plain
stderr=stderr.decode(“utf-8”, “replace”))
pycuda.driver.CompileError: mvcc compilation of /tmp/tmpg191xknw/ failed
[command: nvcc --cubin -arch sm_52 -I/home/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env/lib/python3.7/site-packages/pycuda/cuda}
[stderr: error: identifier “__shfl_down_sync” is undefined

1 error detected in the compilation of “/tmp/tmpxft_0000883c_00000000-7_kernel.cpp1.ii”.

Welcome to the forum @lix .
What version of the CUDA toolkit is configured on your cryoSPARC worker(s)?
To find out, execute these commands in a shell on the worker:

Is the installed version supported by cryoSPARC?
If not, you need to locate or install a supported version of the toolkit, and then run (under the same Linux account as the cryoSPARC instance)
/path/to/cryosparc_worker/bin/cryosparcw newcuda /path/to/cuda
(see guide).