A guide to running computational workflows on DesignSafe, from interactive exploration in a Jupyter notebook to production-scale simulations on TACC supercomputers.
- How It Works The DesignSafe portal, compute environments, storage, and workflow design
- Compute Environments JupyterHub, VMs, HPC systems, queues, and allocations
- Storage and File Management Storage areas, paths across environments, file staging, and dapi file operations
- Submitting a Job Through the Portal Step-by-step walkthrough with screenshots
- Running HPC Jobs Job submission with dapi, resource parameters, and parallel execution
- Debugging Failed Jobs Job states, output files, and common failure patterns
- Parameter Sweeps Running hundreds of independent simulations with PyLauncher
- DesignSafe Applications Catalog of 45+ available tools
- Advanced Topics Tapis internals, execution strategies, and custom app development
Submit and monitor an HPC job from a Jupyter notebook using dapi:
from dapi import DSClient
ds = DSClient()
input_uri = ds.files.to_uri("/MyData/analysis/input/")
job_request = ds.jobs.generate(
app_id="opensees-mp-s3",
input_dir_uri=input_uri,
script_filename="model.tcl",
max_minutes=60,
allocation="your_allocation",
)
job = ds.jobs.submit(job_request)
job.monitor()For dapi installation, authentication, and API reference, see the dapi documentation.