AMBER16集群通过qsub调度提交并行任务失败求助

Hey there, sorry to hear you're stuck on this AMBER16 cluster submission issue—let's break down the most common reasons this happens and how to fix them, since it works locally but fails via qsub.

Common Causes & Fixes #

1. Environment Variables Aren't Loading in Scheduler Jobs #

qsub-submitted tasks typically run in non-interactive shell sessions, which often don't automatically source your .bashrc file. That means all the AMBER path configurations you set up locally might not be available to the compute node.

• Quick fix: Add explicit environment setup to the top of your qsub script:

  # Load your bashrc explicitly
  source ~/.bashrc
  
  # Or directly define AMBER paths if sourcing .bashrc causes issues
  export AMBERHOME=/path/to/your/amber16
  export PATH=$AMBERHOME/bin:$PATH
  export LD_LIBRARY_PATH=$AMBERHOME/lib:$LD_LIBRARY_PATH
  

• If your cluster uses a module system (e.g., module load commands), add the AMBER module load line to your script instead.

2. Compute Nodes Lack AMBER Dependencies #

Your head node might have all the required libraries (like MPI, MKL, or OpenBLAS) installed, but compute nodes often don't get the same setup.

• Debug step: Add this line to your qsub script to check for missing libraries:

  ldd $AMBERHOME/bin/sander  # Replace "sander" with your AMBER executable if different
  

  Run the job and check the output—any "not found" entries will tell you which libraries are missing.
• Fix: Reach out to your cluster admin to install the missing libraries on compute nodes, or add the library paths to your script's environment variables.

3. Incorrect Resource Allocation #

AMBER16 (especially MPI-enabled versions) needs specific CPU, memory, or process counts to run. If your qsub script doesn't request enough resources, the job might fail silently or crash.

• Check & adjust:
  1. Use top or htop on the head node while running AMBER locally to see how many CPUs/memory it uses.
  2. Add matching resource requests to your qsub script (example for PBS scheduler):

     #PBS -l nodes=1:ppn=8  # Request 1 node, 8 cores per node
     #PBS -l mem=16gb        # Request 16GB of memory
     #PBS -l walltime=24:00:00  # Request 24 hours of runtime
     

  3. If using MPI, make sure the number of processes in your mpirun command matches the cores you requested (e.g., mpirun -np 8 sander -i md.in).

4. Relative Path Issues #

When you run locally, you're in your working directory, but qsub jobs might start in a default system directory (like /var/spool/pbs). Relative paths to input/output files will break here.

• Fix:
  • Add a line to your script to switch to your actual working directory first:

    cd /absolute/path/to/your/amber/workdir
    

  • Use absolute paths for all input, output, and parameter files in your AMBER command.

If you can share the exact error message from your qsub job's output log, that would help narrow this down even more—for example, a "command not found" error points straight to environment issues, while a "segmentation fault" might hint at missing libraries or resource limits.

内容的提问来源于stack exchange，提问作者Astronomer