Local ctf refinement

Hi,

I am trying to run local ctf refinement with the refined particles and see following error. I am wondering if it is due to older version of CUDA.

[CPU: 4.33 GB] Traceback (most recent call last):
File “cryosparc2_worker/cryosparc2_compute/run.py”, line 85, in cryosparc2_compute.run.main
File “cryosparc2_worker/cryosparc2_compute/jobs/ctf_refinement/run_local.py”, line 156, in cryosparc2_compute.jobs.ctf_refinement.run_local.run
File “cryosparc2_worker/cryosparc2_compute/jobs/ctf_refinement/run_local.py”, line 182, in cryosparc2_compute.jobs.ctf_refinement.run_local.full_defocus_refine
File “cryosparc2_worker/cryosparc2_compute/jobs/ctf_refinement/run_local.py”, line 347, in cryosparc2_compute.jobs.ctf_refinement.run_local.do_defocus_refine
File “cryosparc2_worker/cryosparc2_compute/engine/newengine.py”, line 700, in cryosparc2_compute.engine.newengine.EngineThread.project_model
File “cryosparc2_worker/cryosparc2_compute/engine/newcuda_kernels.py”, line 3222, in cryosparc2_compute.engine.newcuda_kernels.slice_volumes
File “cryosparc2_worker/cryosparc2_compute/engine/cuda_core.py”, line 362, in cryosparc2_compute.engine.cuda_core.context_dependent_memoize.wrapper
File “cryosparc2_worker/cryosparc2_compute/engine/newcuda_kernels.py”, line 3193, in cryosparc2_compute.engine.newcuda_kernels.get_slice_volumes_kernel
File “/home/cryoem/software/cryosparc2_worker/deps/anaconda/lib/python2.7/site-packages/pycuda/compiler.py”, line 291, in init
arch, code, cache_dir, include_dirs)
File “/home/cryoem/software/cryosparc2_worker/deps/anaconda/lib/python2.7/site-packages/pycuda/compiler.py”, line 254, in compile
return compile_plain(source, options, keep, nvcc, cache_dir, target)
File “/home/cryoem/software/cryosparc2_worker/deps/anaconda/lib/python2.7/site-packages/pycuda/compiler.py”, line 137, in compile_plain
stderr=stderr.decode(“utf-8”, “replace”))
CompileError: nvcc compilation of /tmp/tmpoRIzLV/kernel.cu failed
[command: nvcc --cubin -arch sm_61 -I/home/cryoem/software/cryosparc2_worker/deps/anaconda/lib/python2.7/site-packages/pycuda/cuda kernel.cu]
[stderr:
kernel.cu(131): error: identifier “__shfl_down_sync” is undefined

kernel.cu(256): error: identifier “__shfl_down_sync” is undefined

kernel.cu(318): error: identifier “__shfl_down_sync” is undefined

kernel.cu(382): error: identifier “__shfl_down_sync” is undefined

kernel.cu(455): error: identifier “__ballot_sync” is undefined

5 errors detected in the compilation of “/tmp/tmpxft_000060b6_00000000-7_kernel.cpp1.ii”.

Hi @Anamika, can you please confirm which CUDA version you are using, and also which GPU(s) you have?

I am using CUDA Version 8.0.61.
GPU info is as below:
----------------------------------------------------------------------------+
| NVIDIA-SMI 384.59 Driver Version: 384.59 |
|-------------------------------±---------------------±---------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 108… Off | 00000000:02:00.0 On | N/A |
| 42% 71C P2 87W / 250W | 2491MiB / 11172MiB | 0% Default |
±------------------------------±---------------------±---------------------+
| 1 GeForce GTX 108… Off | 00000000:03:00.0 Off | N/A |
| 26% 46C P8 18W / 250W | 11MiB / 11172MiB | 0% Default |
±------------------------------±---------------------±---------------------+
| 2 GeForce GTX 108… Off | 00000000:82:00.0 Off | N/A |
| 23% 41C P8 18W / 250W | 11MiB / 11172MiB | 0% Default |
±------------------------------±---------------------±---------------------+
| 3 GeForce GTX 108… Off | 00000000:83:00.0 Off | N/A |
| 23% 42C P8 17W / 250W | 11MiB / 11172MiB | 0% Default |
±------------------------------±---------------------±---------------------+

±----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 4349 G /usr/bin/X 117MiB |
| 0 27759 C python 2359MiB |
±----------------------------------------------------------------------------+

@Anamika cryoSPARC requires a minimum CUDA version of 9.2 for worker nodes, please see: https://guide.cryosparc.com/setup-configuration-and-management/hardware-and-system-requirements#cryosparc-system-requirements