Towards Easy and Realistic Network Infrastructure Testing for Large-scale Machine Learning

This paper lays the foundation for Genie, a testing framework that captures the impact of real hardware network behavior on ML workload performance, without requiring expensive GPUs. Genie uses CPU-initiated traffic over a hardware testbed to emulate GPU to GPU communication, and adapts the ASTRA-sim simulator to model interaction between the network and the ML workload.

@article{yoo2025_2504.20854,
  title={ Towards Easy and Realistic Network Infrastructure Testing for Large-scale Machine Learning },
  author={ Jinsun Yoo and ChonLam Lao and Lianjie Cao and Bob Lantz and Minlan Yu and Tushar Krishna and Puneet Sharma },
  journal={arXiv preprint arXiv:2504.20854},
  year={ 2025 }
}