Story · Semantic Scholar
RASER: Resilient Agent Scheduling and Execution Runtime for HPC Clusters (Semantic Scholar)
paper · Story page
RASER runs agent workflows on Slurm with work stealing through shared-filesystem queues, application-level checkpointing paired with Slurm requeue, and Apptainer isolation without image changes. It reports nearly 39% lower makespan than static partitioning at near-full CPU utilization, and it tests recovery after simulated preemption.
In plain words
- Researchers built software to organize unpredictable tasks performed by artificial intelligence across groups of powerful computers.
- When one computer finishes its work, it can take waiting tasks from a shared list.
- The software saves progress so interrupted tasks can restart.
- In tests, large computing jobs took nearly 39% less time than when computers received fixed task assignments.
Appeared in
- Per-phase model routing cuts agent cost, RASER on Slurm, Amp steers mid-run
Sep 09, 2026 · in the sections
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