Distributed Job Scheduling With Multiple Launcher Backends

via “distributed-job-scheduling-with-multiple-launcher-backends”

The RL Bridge for LLM-based Agent Applications. Made Simple & Flexible.

Unique: Provides unified Scheduler API with pluggable launcher backends (Local, Ray, SLURM, SkyPilot) that abstract cluster-specific job submission details. Automatic shared storage validation and RPC-based engine communication enable seamless scaling from single-node to multi-node training.

vs others: More flexible than Ray's native training APIs because it supports SLURM and SkyPilot; more integrated than standalone cluster management tools because it includes training-specific features like shared storage validation and engine RPC.

via “multi-system-job-scheduling”