AgnosticApp - How to Choose Inputs

AgnosticApp - How to Choose Inputs#

A One-Page Cheat Sheet for designsafe-agnostic-app

This app gives you a lot of power. You do not need to use most inputs for most jobs.

Use this page to answer four questions, top to bottom.

1. What am I actually running?#

Pick one executable and one main script.

If you are running…

Set BINARYNAME

Set INPUTSCRIPT

OpenSees (Tcl)

OpenSees

model.tcl

OpenSeesMP / OpenSeesSP

OpenSeesMP or OpenSeesSP

model.tcl

OpenSeesPy

python3

run.py

General Python

python3

script.py

Other executable

script

Rules of thumb

  • INPUTSCRIPT is just the filename, not a path

  • The script must live inside inputDirectory

  • For OpenSeesPy, always use python3

2. Do I need MPI?#

Answer this explicitly — the app will not guess.

If your job…

Set UseMPI

Uses OpenSeesMP / OpenSeesSP

True

Uses mpi4py

True

Is fully serial

False

Uses Python threading or concurrent.futures on one node

False

Mental model

UseMPI = True   →  ibrun <command>
UseMPI = False  →  <command>

If you’re unsure: start with False and turn it on only when needed.

3. Does my environment need anything special?#

A. Do I need modules?#

If your code needs:

  • OpenSees

  • MPI-aware HDF5

  • a specific compiler stack

Yes, you need modules

Choose one:

Use this when…

Input

You want a clean, documented stack

MODULE_LOADS_FILE

You just need a few modules quickly

MODULE_LOADS_LIST

Example mental model:

If I would type “module load …” on the command line,
I probably need to declare it here.

B. Do I need Python packages?#

If you…

Use

Have a requirements.txt

PIP_INSTALLS_FILE

Just need a couple of packages

PIP_INSTALLS_LIST

Need none

(leave blank)

Packages are installed inside the job only.

C. Am I using OpenSeesPy?#

Almost always set this to True on Stampede3

GET_TACC_OPENSEESPY = True

Why:

  • Uses the TACC-compiled OpenSeesPy.so

  • Avoids broken or incompatible PyPI wheels

4 How are my inputs structured?#

A. Is everything already in my input directory?#

If yes:

  • do nothing

  • simplest and safest case

B. Do I have ZIP bundles?#

Use when:

  • many small files

  • datasets packaged for upload

–> Set:

UNZIP_FILES_LIST = mydata,meshes

(.zip is optional)

C. Do I need large external data?#

Use when:

  • data already exists in WORK / SCRATCH / HOME

  • you don’t want to re-upload it

–> Set:

PATH_COPY_IN_LIST = /work/.../dataset1,/scratch/.../dataset2

If the copy is temporary, also set:

DELETE_COPIED_IN_ON_EXIT = True

5. Do I need pre- or post-processing?#

Need

Input

Generate inputs

PRE_JOB_SCRIPT

Post-process results

POST_JOB_SCRIPT

Organize outputs

POST_JOB_SCRIPT

Cleanup

POST_JOB_SCRIPT

Hooks:

  • run inside inputDirectory

  • may be executable or run via bash

  • failures warn by default (job continues)

6. Will my output be large or long-lived?#

A. Many output files?#

–> Enable ZIP repack:

ZIP_OUTPUT_SWITCH = True

B. Do I want results in WORK or SCRATCH immediately?#

–> Move outputs:

PATH_MOVE_OUTPUT = $WORK/MyRuns

Results land in:

$WORK/MyRuns/_<JobUUID>/

This is highly recommended for:

  • large runs

  • chained workflows

  • interactive inspection in JupyterHub

7. Minimal “starter configurations”#

* Serial OpenSees (Tcl)#

BINARYNAME   = OpenSees
INPUTSCRIPT = model.tcl
UseMPI      = False

* OpenSeesMP (MPI)#

BINARYNAME   = OpenSeesMP
INPUTSCRIPT = model.tcl
UseMPI      = True

* Python + mpi4py#

BINARYNAME   = python3
INPUTSCRIPT = run.py
UseMPI      = True
PIP_INSTALLS_LIST = mpi4py

8. Final sanity checklist#

Before submitting, ask yourself:

  • Is my script inside inputDirectory?

  • Does UseMPI match how I actually run the code?

  • Do my modules match my binary?

  • Am I relying on any absolute paths unintentionally?

  • Do I want outputs zipped or moved?

If yes → you’re good.

One-sentence takeaway#

Choose the simplest inputs that describe how you would run the job manually — the app exists to make that behavior explicit, safe, and reproducible.

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