How it Works
- Decorate any python function to convert it into a task / workflow
- Work locally and with the IDE of your choice, including Jupyter notebooks
- Workflows can be cross-language and cross-platform
import covalent as ct @ct.electron def spacer(word): return word+" " @ct.electron def join(*a): return "".join(a) @ct.lattice def workflow(name): return join(spacer("hello"),spacer(name)) +" !!" id=ct.dispatch(workflow)(name="Shore") ct.get_result(id,wait=True)
- Prototype your workflows locally and then run them anywhere
- Switch between hardware types and locations with a single line of code
- On-demand cloud bursting within a single hybrid workflow
- Visually engage with your workflows directly with Covalent’s browser-based UI
- Get live status updates for tasks, workflows and hardware
- Automatically add checkpoints to your workflows
- Keep track of and organize your experiments using the Covalent UI
- Automatically package experiments that can easily be shared/reproduced
Covalent supports a growing number of languages and executors
Searching for a specific plugin? Create your own or get started contributing.
Covalent automatically stores and saves the run of every experiment in a reproducible format
Gain access to features such as smart scheduling and automatic resource allocation when running quantum tasks with PennyLane
No need to learn any new syntax or mess around with YAML
Monitor the state of your workflows (electrons + lattices) in real time
Stay up to date
Yes. Covalent is an Open Source-first platform that anyone can use for free including self-hosting in their own cloud.
Covalent is used by data scientists and computational scientists across industries and disciplines, wherever there is a necessity for running experiments on advanced computing hardware such as GPUs, CPUs, QPUs and others.
While most other workflow tools are focused on the “when” (when to schedule an event), Covalent is focused on the “where” (what type of hardware, and in what modality – cloud vs. on-prem).
Gain access to features such as smart scheduling and automatic resource allocation when running quantum tasks with PennyLane. No need to learn any new syntax or mess around with YAML