Open Source Distributed Workflow Orchestration for Quantum & HPC
Make your experiments more manageable, scalable and reproducible.
Manage, deploy & scale workloads across the world’s most advanced computing hardware
Code
UI
import covalent as ct @ct.electron def hello(): return "Hello " @ct.electron def moniker(name): return name+" " @ct.electron def join(*a): return "".join(a) @ct.lattice def workflow(name): result=join(hello(),moniker(name)) return result+" !!" id=ct.dispatch(workflow)(name="shore") ct.get_result(id,wait=True)
Why Covalent?
Covalent is purpose-built for heterogeneous workflows



Covalent makes workflows scalable
- Serverless HPC: don’t waste resources while waiting in queue
- Code locally and scale anywhere from on prem HPC to the cloud
- Native parallelization across diverse hardware types
Covalent makes workflows manageable
- Visualize and monitor workflows in Covalent’s browser-based UI
- Manage experiments across heterogeneous hardware and software
- Write in Python, not YAML
Covalent makes workflows reproducible
- Version your experiments just as you would version your code.
- Easily store and retrieve past runs and share with colleagues
- Built-in checkpointing capabilities to prevent re-runs
Who is Covalent for?
Academics
Computational scientists running large-scale experiments
Individuals
ML and Data Scientists dealing with heterogeneous computing tasks
Enterprises & Teams
Enterprises and research labs working across hardware types and clouds