2D classification can't be run

Dear all,
I recently installed the cryosparc V3.3.2 via the single-workstation method to process negative staining data. When I ran the job of 2D classification, it gave the error as shown below.
Would you please give any suggestions?
Thanks in advance.

Best,

Welcome to the forum @amtblcd.
Please can you provide some details about your cryoSPARC worker:

Thanks for your reply.

I found that the cuda version installed on our workstation is 7.0. I will install a version 11 and reinstall cryosparc to see if this can solve the problem.

I carefully read the guide for cryosparc installation. The cuda toolkit version>=10 should be only required for installation of cryosparc_worker and lower version may cause problems in runing jobs with latest cryosparc in the single-workstation ( if munderstanding is worng, please correct me, thanks).

I’m struggling with installation of cuda >=10 on our workstation. Here I provide the information about my cryosparc worker for reference, would you please have a look and give any suggestons?

Many thanks.
Best

The output of eval ~/program/cryosparc/cryosparc_worker/bin/cryosparcw env:
export “CRYOSPARC_USE_GPU=true”
export “CRYOSPARC_CONDA_ENV=cryosparc_worker_env”
export “CRYOSPARC_DEVELOP=false”
export “CRYOSPARC_LICENSE_ID=XXXXXXXXXXXXXXXXXXXXXXXXXX”
export “CRYOSPARC_ROOT_DIR=/home/gzhu/program/cryosparc/cryosparc_worker”
export “CRYOSPARC_PATH=/home/gzhu/program/cryosparc/cryosparc_worker/bin”
export “CRYOSPARC_CUDA_PATH=/usr/local/cuda”
export “PATH=/home/gzhu/program/cryosparc/cryosparc_worker/bin:/home/gzhu/program/cryosparc/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env/bin:/home/gzhu/program/cryosparc/cryosparc_worker/deps/anaconda/condabin:/usr/local/cuda/bin:/home/gzhu/program/cryosparc/cryosparc_master/bin:/home/gzhu/program/ompi/bin:/usr/local/cuda-7.0/bin:/home/gzhu/program/EMAN2/bin:/home/gzhu/program/cryosparc/cryosparc_master/bin:/home/gzhu/program/ompi/bin:/usr/local/cuda-7.0/bin:/home/gzhu/program/EMAN2/bin:/home/gzhu/program/cryosparc/cryosparc_master/bin:/home/gzhu/program/ompi/bin:/usr/local/cuda-7.0/bin:/home/gzhu/program/EMAN2/bin:/home/gzhu/program/amber18/bin:/home/gzhu/program/HKL2000_v718-Linux-x86_64/bin:/home/gzhu/program/cns_solve_1.3/intel-x86_64bit-linux/bin:/home/gzhu/program/cns_solve_1.3/intel-x86_64bit-linux/utils:/home/gzhu/program/arp_warp_7.5/bin/bin-x86_64-Linux:/home/gzhu/program/ccp4-6.5/etc:/home/gzhu/program/ccp4-6.5/bin:/home/gzhu/program/ccp4-6.5/share/xia2/Applications:/home/gzhu/program/phenix-1.10.1-2155/build/bin:/home/gzhu/program/amber18/bin:/home/gzhu/program/HKL2000_v718-Linux-x86_64/bin:/home/gzhu/program/arp_warp_7.5/bin/bin-x86_64-Linux:/home/gzhu/program/ccp4-6.5/etc:/home/gzhu/program/ccp4-6.5/bin:/home/gzhu/program/ccp4-6.5/share/xia2/Applications:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/opt/intel/impi/5.1.3.210/bin64:/opt/intel/bin:/home/gzhu/program/autodock_x86_64Linux2:/usr/local/MGLTools-1.5.6/bin:/opt/intel/impi/5.1.3.210/bin64:/opt/intel/bin:/home/gzhu/program/autodock_x86_64Linux2:/usr/local/MGLTools-1.5.6/bin:/home/gzhu/program/ccpem-1.4.1/bin:/home/gzhu/program/ccpem-1.4.1/bin:/home/gzhu/program/ccpem-1.4.1/bin”
export “LD_LIBRARY_PATH=/home/gzhu/program/cryosparc/cryosparc_worker/cryosparc_compute/blobio:/home/gzhu/program/cryosparc/cryosparc_worker/cryosparc_compute/libs:/home/gzhu/program/cryosparc/cryosparc_worker/deps/external/cudnn/lib:/usr/local/cuda/lib64:/usr/local/lib:/usr/local/cuda-7.0/lib64:/usr/local/lib:/usr/local/cuda-7.0/lib64:/usr/local/lib:/usr/local/cuda-7.0/lib64:/home/gzhu/program/amber18/lib:/home/gzhu/program/amber18/lib”
export “LD_PRELOAD=/home/gzhu/program/cryosparc/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env/lib/libpython3.7m.so:/home/gzhu/program/cryosparc/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env/lib/libtiff.so”
export “PYTHONPATH=/home/gzhu/program/cryosparc/cryosparc_worker”
export “PYTHONNOUSERSITE=true”
export “CONDA_SHLVL=1”
export “CONDA_PROMPT_MODIFIER=(cryosparc_worker_env)”
export “CONDA_EXE=/home/gzhu/program/cryosparc/cryosparc_worker/deps/anaconda/bin/conda”
export “CONDA_PREFIX=/home/gzhu/program/cryosparc/cryosparc_worker/deps/anaconda/envs/cryosparc_worker_env”
export “CONDA_PYTHON_EXE=/home/gzhu/program/cryosparc/cryosparc_worker/deps/anaconda/bin/python”
export “CONDA_DEFAULT_ENV=cryosparc_worker_env”

The output of /usr/local/cuda/bin/nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Mon_Feb_16_22:59:02_CST_2015
Cuda compilation tools, release 7.0, V7.0.27

python -c "import pycuda.driver; print(pycuda.driver.get_version())"
(7, 0, 0)

uname -a && free -g && nvidia-smi

Linux dy024-165.ust.hk 3.13.0-170-generic #220-Ubuntu SMP Thu May 9 12:40:49 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux
total used free shared buffers cached
Mem: 31 27 3 0 0 23
-/+ buffers/cache: 3 27
Swap: 31 0 31
Thu Jul 21 11:59:20 2022
±-----------------------------------------------------+
| NVIDIA-SMI 346.46 Driver Version: 346.46 |
|-------------------------------±---------------------±---------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Quadro K4200 Off | 0000:02:00.0 On | N/A |
| 30% 30C P8 15W / 110W | 156MiB / 4095MiB | 0% Default |
±------------------------------±---------------------±---------------------+

±----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 2015 G /usr/bin/X 144MiB |
±----------------------------------------------------------------------------+

Unfortunately, this GPU model is specified with a compute capability of 3.0, but cryoSPARC requires a minimum compute capability of 3.5.

Additionally,

  • $CRYOSPARC_CUDA_PATH appears to be still pointing to an old version of the CUDA toolkit

Got it, thanks.

Best