Covalent is a Pythonic workflow tool for computational scientists, AI/ML software engineers, and anyone who needs to run experiments on limited or expensive computing resources including quantum computers, HPC clusters, GPU arrays, and cloud services. Covalent enables a researcher to run computation tasks on an advanced hardware platform – such as a quantum computer or serverless HPC cluster – using a single line of code. Covalent overcomes computational and operational challenges inherent in AI/ML experimentation.

Features

  • Assign functions to appropriate resources: Use advanced hardware (quantum computers, HPC clusters) for the heavy lifting and commodity hardware for bookkeeping
  • Test functions on local servers before shipping them to advanced hardware
  • Let Covalent's services analyze functions for data independence and automatically parallelize them
  • Run experiments from a Jupyter notebook (or whatever your preferred interactive Python environment is)
  • Track workflows and examine results in a browser-based GUI
  • Covalent is developed using Python version 3.8 on Linux and macOS

Project Samples

Project Activity

See All Activity >

Categories

Data Pipeline

License

Affero GNU Public License

Follow Covalent workflow

Covalent workflow Web Site

Other Useful Business Software
Stay in Flow. Let Zenflow Handle the Heavy Lifting. Icon
Stay in Flow. Let Zenflow Handle the Heavy Lifting.

Your AI engineering control center. Zenflow turns specs into shipped features using parallel agents and multi-repo intelligence.

Zenflow is your engineering control center, turning specs into shipped features. Parallel agents handle coding, testing, and refactoring with real repo context. Multi-agent workflows remove bottlenecks and automate routine work so developers stay focused and in flow.
Try free now
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Covalent workflow!

Additional Project Details

Operating Systems

Linux, Mac

Programming Language

Python

Related Categories

Python Data Pipeline Tool

Registered

2023-06-12