i/o optimization

DTIO: Data Stack for AI-driven Workflows

K. Bateman, N. Rajesh, J. Cernuda, L. Logan, B. Nicolae, F. Cappello, X.-H. Sun, A. Kougkas

The 37th International Conference on Scalable Scientific Data Management (SSDBM 2025)

A scalable I/O runtime that unifies disparate I/O stacks for converged HPC, Big Data, and ML workflows.

N. Rajesh, K. Bateman, S. Byna, J. L. Bez, A. Kougkas, X.-H. Sun

The 38th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2024)

An AI-powered I/O tuning framework that reduces tuning time while achieving the same performance gain through RL-driven early stopping.

J. Cernuda, H. Devarajan, L. Logan, K. Bateman, N. Rajesh, J. Ye, A. Kougkas, X.-H. Sun

The 2021 IEEE International Conference on Cluster Computing (CLUSTER'21), September 7-10, 2021

A dynamic and elastic multi-layered data forwarding system leveraging a real-time data movement paradigm for HPC.