Principle:Hpcaitech ColossalAI Ray Cluster Initialization
| Knowledge Sources | |
|---|---|
| Domains | Distributed_Computing, Infrastructure |
| Last Updated | 2026-02-09 00:00 GMT |
Overview
A distributed orchestration pattern using Ray to launch and coordinate producer (inference) and consumer (training) actors across a GPU cluster for reinforcement learning.
Description
Ray Cluster Initialization sets up the distributed RL training infrastructure. It allocates GPUs to producer actors (which run inference to generate experiences) and consumer actors (which train the policy model). The launch_distributed() function discovers available nodes, schedules actors based on GPU resources, and establishes communication channels between producers and consumers via Ray's object store.
Usage
Use this as the entry point for distributed GRPO training. It replaces ColossalAI's standard launch_from_torch() with Ray-based orchestration.
Theoretical Basis
The producer-consumer architecture separates concerns:
- Producers (inference workers): Generate multiple responses per prompt using the current policy
- Consumers (training workers): Update the policy using GRPO loss on collected experiences
- Synchronization: Updated weights are broadcast from consumers to producers via Ray collective operations