Ensemble Launcher

A lightweight, scalable tool for launching and orchestrating task ensembles across HPC clusters with intelligent resource management and hierarchical execution.

Documentation | GitHub

Features

• Scalability -- Hierarchical master-worker architecture tested from 1 to 2048+ nodes
• Flexible Execution -- Support for serial, MPI, and mixed workloads with Python callables or shell commands
• Co-Scheduling -- Run heterogeneous tasks (different node counts, GPU requirements) in a single ensemble
• Custom Scheduling Policies -- Pluggable policy system with built-in bin-packing, split, and FIFO strategies, or write your own
• Actors -- Distributed actor model with async/await communication over ZMQ for long-lived stateful services
• Inference -- Actor-based vLLM wrappers for offline, online, and multi-node LLM serving on HPC clusters

Quick Example

from ensemble_launcher import EnsembleLauncher

el = EnsembleLauncher("config.json")
results = el.run()

# Or use the CLI
el start my_ensemble.json

Acknowledgments

This work was supported by the U.S. Department of Energy, Office of Science, under contract DE-AC02-06CH11357.

Citation

@article{tummalapalli2026overcoming,
  title={Overcoming Orchestration Bottlenecks at Exascale: A Decentralized, Policy-Driven Approach for Sim-AI Ensembles},
  author={Tummalapalli, Harikrishna and Simpson, Christine M and Balin, Riccardo and Morozov, Vitali A and Pham, Thang D and Keceli, Murat and Uram, Thomas D},
  journal={arXiv preprint arXiv:2607.12211},
  year={2026}
}