MorphoCloud
MorphoCloud
GPU-enabled JetStream2 instances, pre-loaded with 3D Slicer and SlicerMorph — launched and managed entirely through GitHub Issues.
Current vacancy on JetStream2 for the flavors we offer (GPU flavors are
shared and can be scarce). Each instance includes a 100 GB persistent
data volume mounted at /media/volume/MyData.
| Flavor | vCPU | RAM | GPU | Available now |
|---|---|---|---|---|
| g3.large | 16 | 60 GB | A100 (½, 20 GB) | 86 |
| g3.xl | 32 | 120 GB | A100 (full, 40 GB) | 7 |
| g4.xl | 12 | 120 GB | L40S (48 GB) | 13 |
| m3.xl | 32 | 125 GB | — | 12 |
| r3.large | 64 | 500 GB | — | 12 |
| r3.xl | 128 | 1000 GB | — | 1 |
New to MorphoCloud? Onboard with your ORCID iD at join.morphocloud.org to get added to the MorphoCloud GitHub organization.
Already a member? Open an instance request in the
instance repository and drive it with
/create.
Browse documentation and tutorials for commands, workflows, and tips.
Every instance comes pre-loaded with 3D Slicer and a curated suite of morphometrics and imaging tools.
| Software / tool | Description |
|---|---|
| 3D Slicer | v5.10 |
| SlicerMorph | ImageStacks, GPA, ALPACA, and other tools |
| DeCA | Morphometrics via dense correspondence analysis |
| Photogrammetry | Generate textured 3D models from photographs |
| MorphoDepot | Collaborative segmentation and data sharing |
| MEMOs | AI based organ segmentation for E15 mouse embryos |
| NNInteractive | AI assisted interactive segmentation |
| PyTorch | GPU accelerated tensor library for AI tools |
| R/Rstudio | Provided by JetStream2 |
| Python3 | Provided by JetStream2 |
MorphoCloud services, including MorphoCloud On-Demand Instances, are supported by funding from the National Science Foundation (DBI/2301405) and National Institutes of Health (NICHD/HD104435). MorphoCloud runs on cyberinfrastructure that is made available by current and previous funding from the National Science Foundation (JetStream2: OAC/2005506, Exosphere: TI/2229642). Initial development of SlicerMorph was previously supported by National Science Foundation (DBI/1759883).
If you use any of the MorphoCloud services for your project, please cite our paper — Maga, A. M., & Fillion-Robin, J.-C. (2026). MorphoCloud: Democratizing Access to High-Performance Computing for Morphological Data Analysis. F1000Research. https://doi.org/10.12688/f1000research.176328.1 — and acknowledge our funders with this statement:
This study relied on cyberinfrastructure supported by grants from the National Science Foundation (MorphoCloud: DBI/2301405; JetStream2: OAC/2005506; Exosphere: TI/2229642) and the National Institutes of Health (MorphoCloud: NICHD HD104435).