perf-expert-parallel-overlap

To overlap expert-parallel communication in MoE training, you can enable the overlap_moe_expert_parallel_comm configuration and run the setup script to validate and apply the optimization for reduced training step times.

MoE training throughput regressions often stem from unoptimized expert-parallel communication. This Skill traces performance bottlenecks and tunes EP overlap configurations like alltoall and flex dispatchers to improve GPU utilization.

Yes, Megatron-Bridge supports key configurations like alltoall and flex dispatchers. This Skill validates these expert-parallel communication overlap settings to ensure safe deployment and improved throughput.

You need a compatible PyTorch version and sufficient memory constraints to safely deploy MoE communication overlap. This Skill checks your environment's PyTorch version and memory limits before applying the optimization.

Expert-parallel communication overlap is a performance tuning technique that overlaps MoE network operations with computation. You need it during large-scale MoE training on GPU clusters to reduce latency and decrease step times.

You can tune MoE communication overlap configurations by using this performance Skill to enable the overlap_moe_expert_parallel_comm setting. It validates your setup and applies optimizations with minimal code changes required.