The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: Research Posters
Author: YuTsen Tseng (Tohoku University, Graduate School of Information Sciences), Masatoshi Kawai (Tohoku University), Keichi Takahashi (University of Osaka), Hiroyuki Takizawa (Tohoku University)
Supervisor:
Abstract: HPC workloads are increasingly data-intensive, with contention on shared storage emerging as a primary bottleneck. Existing I/O-aware job schedulers rely on static bandwidth assumptions that overlook time-varying I/O behavior, leading to inefficient utilization and unpredictability.
This work introduces the Contention-Avoiding Temporal I/O-aware job Scheduling (CATIOS) framework, which considers temporal I/O behavior in scheduling decisions to address these issues. CATIOS first matches incoming jobs with similar historical profiles semantically and resource-wise, who serve as proxies and are evaluated sequentially in time-resolved contention-aware simulation after being reprioritized by configurable scheduling policies. These enable CATIOS to avoid overlapping bursts according to objectives.
Evaluations with Blue Waters workloads on a SimGrid-based platform show that CATIOS reduces makespan while maintaining controlled average wait times, achieving a balanced trade-off of approximately 1:1.3 between makespan reduction and average wait time increase. These results demonstrate CATIOS’s capability to improve data-intensive HPC systems with mixed workloads.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF