Open Source Workflow Orchestration for Heterogenous Computing
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 add_space(name):
return name + ' '
@ct.electron
def join(a):
return ''.join(a)
@ct.lattice
def workflow(name):
name_space=add_space(name)
result = join('Hello', name_space)
return result + ' !!'
id = ct.dispatch(workflow)(name='Shore')
ct.get_result(id, wait=True)
Explore the demo app
Read the API docs
Why Covalent?
Covalent is purpose-built for heterogeneous workflows; hardware, software and clouds
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
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