This repository is a collection of tools and demonstrations used to explore and test various technologies for implementing exascale scientific workflows. This collection of resources is not intended for production use, and is for research purposes only.
Chiltepin provides Python decorators and utilities for building scientific workflows that can execute on distributed computing resources using Parsl and Globus services.
📚 Full documentation is available at Read the Docs
Key documentation sections:
- Installation Guide - Installing Chiltepin on Linux and via Docker on macOS and Windows
- Quick Start - Your first Chiltepin workflow
- Tasks - Python, Bash, and Join task decorators
- Configuration - Configuring compute resources
- Endpoints - Managing Globus Compute endpoints
- Data Transfer - Using Globus for data movement
- Testing Guide - Running the test suite
Install Chiltepin in a Python virtual environment:
python -m venv .chiltepin
source .chiltepin/bin/activate
pip install -e .For detailed installation instructions including conda, Docker, and platform-specific guidance, see the Installation Guide.
Contributions are welcome! For information on running tests and contributing to development, see the Testing Guide.
See LICENSE for details.