Garden's Almanac of Matter Models AllScAIP
March 2026
| Checkpoint | Params | Polaris | Sophia | Perlmutter | Delta | Frontier | Della |
|---|---|---|---|---|---|---|---|
| allscaip-md-conserving-all-omol | — | — | ● | ● | — | ● | |
| allscaip-md-direct-all-omol | — | — | — | — | — | ● | |
| allscaip:custom | — | — | — | — | — | — |
● verified, last 30 days ○ installed, not recently verified — not installed
No cluster has installed any checkpoint of this model yet.
Running this model
1# from a job or interactive session on a supported cluster:
2from rootstock import RootstockCalculator
3
4# this model accepts charge and spin
5atoms.info["charge"] = -1
6atoms.info["spin"] = 2
7
8with RootstockCalculator(
9 cluster=YOUR_CLUSTER_ID, # eg, "perlmutter", "delta"
10 checkpoint="allscaip-md-conserving-all-omol",
11 device="cuda",
12) as calc:
13 # model is now running in subprocess on compute node
14 atoms.calc = calc
15 atoms.get_potential_energy()
Environments
Rootstock runs each model family inside an isolated Python environment defined by a single file. This environment file includes the specific dependencies needed, plus a setup() function that loads the model and returns an ASE calculator. These files are usually almost identical for a given model family, but because of cluster-specific quirks (eg, an old CUDA driver) the dependencies and setup code can vary a bit.
allscaip_env.py
1# /// script
2# requires-python = ">=3.11"
3# dependencies = [
4# "fairchem-core>=2.20",
5# "ase>=3.22",
6# "torch>=2.4.0",
7# ]
8# ///
9"""AllScAIP env — FAIRChem scalable attention MLIP trained on OMol25.
10
11allscaip-md-conserving-all-omol is an energy-conserving, all-to-all node
12attention model served through fairchem-core's get_predict_unit — the same
13API as eSEN. fairchem v2 carries the architecture in-package, so no
14flash-attention or custom CUDA kernels are needed.
15
16OMol checkpoints expect `charge` and `spin` in `atoms.info`.
17"""
18
19CHECKPOINTS = {
20 "allscaip-md-conserving-all-omol": "allscaip-md-conserving-all-omol",
21}
22
23
24def setup(checkpoint: str, device: str = "cuda"):
25 from fairchem.core import FAIRChemCalculator, pretrained_mlip
26
27 predictor = pretrained_mlip.get_predict_unit(CHECKPOINTS[checkpoint], device=device)
28 return FAIRChemCalculator(predictor)
29
30
Built on Perlmutter: 2026-05-29
Couldn't load the current environments from Rootstock.