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Quick Start

Get a research workstation running in under 5 minutes.

1. Install

brew install scttfrdmn/tap/prism

scoop bucket add scttfrdmn https://github.com/scttfrdmn/scoop-bucket
scoop install prism

Download the latest tarball from the releases page, extract, and add to your PATH.

2. Connect AWS credentials

If you haven't configured the AWS CLI yet:

aws configure

Then add a Prism profile pointing to those credentials:

prism profile add

3. Launch a workspace

# See what's available
prism templates

# Launch a Python + Jupyter environment
prism workspace launch python-ml my-project

# Check it's running (takes ~2 minutes)
prism workspace list

4. Connect

prism workspace connect my-project

This prints the SSH command and any web service URLs (Jupyter, RStudio, etc.).

5. Stop when done

prism workspace stop my-project

Stopped workspaces don't cost anything. Resume later with prism workspace start my-project, or delete permanently with prism workspace delete my-project.

Common templates

Template What's included
python-ml Python, PyTorch, TensorFlow, Jupyter
r-research R, RStudio Server, Bioconductor
genomics GATK, BWA, samtools, STAR
bioinformatics Conda, Snakemake, BioPython
deep-learning CUDA, cuDNN, GPU-ready PyTorch
data-science Pandas, scikit-learn, DuckDB
hpc-base MPI, OpenMP, GCC, CMake

Run prism templates info <name> for details on any template.

What's next