Revisiting Parameter Server in LLM Post-Training

TL;DR

This paper introduces On-Demand Communication (ODC), a novel approach that enhances parameter server robustness and efficiency in large language model post-training by replacing collective communication with direct point-to-point communication, leading to significant speedups.

Contribution

The paper proposes ODC, a new communication method that adapts Fully Sharded Data Parallelism for imbalanced workloads in LLM post-training, improving device utilization and training speed.

Findings

Up to 36% speedup over FSDP.

Reduces synchronization barriers from once per layer to once per minibatch.

Decouples device workloads for better load balancing.

Abstract

Modern data parallel (DP) training favors collective communication over parameter servers (PS) for its simplicity and efficiency under balanced workloads. However, the balanced workload assumption no longer holds in large language model (LLM) post-training due to the high variance in sequence lengths. Under imbalanced workloads, collective communication creates synchronization barriers, leading to under-utilization of devices with smaller workloads. This change in training dynamics calls for a revisit of the PS paradigm for its robustness to such imbalance. We propose \textbf{On-Demand Communication (ODC)}, which adapts PS into Fully Sharded Data Parallel (FSDP) by replacing collective all-gather and reduce-scatter with direct point-to-point communication. Compared to FSDP, ODC reduces the synchronization barrier from once per layer to once per minibatch and decouples the workload on each device so that faster workers are not stalled. It also enables simpler and more effective load balancing at the minibatch level. Across diverse LLM post-training tasks, ODC consistently improves device utilization and training throughput, achieving up to a 36\% speedup over standard FSDP. These results demonstrate that ODC is a superior fit for the prevalent imbalanced workloads in LLM post-training. Our implementation of ODC and integration with FSDP is open-sourced at https://github.com/sail-sg/odc.