Nemo Mbridge Perf Tp Dp Comm Overlap
NVIDIAOfficialPublished by NVIDIA
- Skill
- Tool integration
- Software development
- Apache-2.0
- Medium risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a comprehensive guide for enabling and tuning communication overlap (TP, DP, and PP) within the Megatron-Bridge framework. It covers essential configuration knobs, code-level gating mechanisms, common pitfalls to avoid, and verification procedures to ensure optimal performance during large-scale model training.
What it does
- Provides configuration templates for enabling TP, DP, and PP communication overlap.
- Identifies key code anchors that control overlap gating and P2P communication logic.
- Highlights common pitfalls regarding sequence parallelism, Transformer Engine dependencies, and bucket sizing.
- Details environment variable tuning for launch-time performance optimization.
- Outlines verification steps using unit tests to confirm overlap configuration success.
When to use it
- When configuring communication overlap for Megatron-Bridge training jobs.
- When investigating throughput regressions related to communication overlap settings.
- When troubleshooting why TP or PP overlap features are not activating as expected.
- When tuning environment variables like CUDA_DEVICE_MAX_CONNECTIONS for performance.
Advantages
- Centralizes configuration knowledge for complex parallel training setups.
- Provides clear guidance on the interaction between model parallelism and overlap features.
- Includes specific verification commands to validate configuration integrity.
- Warns against common misconfigurations in mixed precision and environment settings.
Usage examples
- “How do I enable TP communication overlap in my Megatron-Bridge config?”
- The skill provides the CommOverlapConfig snippet to set tp_comm_overlap=True and notes the requirement for sequence_parallel=True and Transformer Engine availability.
- “Why is my PP overlap not working?”
- The guide explains that PP overlap is only auto-selected when pipeline_model_parallel_size > 1 and virtual_pipeline_model_parallel_size > 1.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/nvidia/nemo-mbridge-perf-tp-dp-comm-overlap/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip nemo-mbridge-perf-tp-dp-comm-overlap.zip -d .agents/skills
Documentation by NVIDIA
TP / DP / PP Communication Overlap Skill
For stable background and recommendation level, see:
@docs/training/communication-overlap.md
Enablement
Minimal Bridge override:
from megatron.bridge.training.comm_overlap import CommOverlapConfig
cfg.model.tensor_model_parallel_size = 4
cfg.model.sequence_parallel = True
cfg.model.pipeline_model_parallel_size = 4
cfg.model.virtual_pipeline_model_parallel_size = 2
cfg.comm_overlap = CommOverlapConfig(
tp_comm_overlap=True,
)
cfg.ddp.use_distributed_optimizer = True
cfg.ddp.overlap_grad_reduce = True
cfg.ddp.overlap_param_gather = TrueOptional TP preset:
from megatron.bridge.training.comm_overlap import userbuffers_bf16_h100_h12288_tp4_mbs1_seqlen2048
cfg.comm_overlap.tp_comm_overlap_cfg = userbuffers_bf16_h100_h12288_tp4_mbs1_seqlen2048Precision knobs belong to mixed precision:
cfg.mixed_precision.grad_reduce_in_fp32 = False
cfg.mixed_precision.fp8_param_gather = FalseCode Anchors
Bridge overlap gating:
if self.user_comm_overlap_cfg.tp_comm_overlap is True:
if model_cfg.tensor_model_parallel_size < 2:
...
elif not model_cfg.sequence_parallel:
...
elif not HAVE_TE:
...PP overlap selection:
if model_cfg.pipeline_model_parallel_size > 1:
if vp_size > 1:
comm_overlap_cfg.overlap_p2p_comm = True
comm_overlap_cfg.batch_p2p_comm = False
else:
comm_overlap_cfg.overlap_p2p_comm = False
comm_overlap_cfg.batch_p2p_comm = TrueDP overlap defaults:
if self.data_parallel_size > 1:
comm_overlap_cfg.bucket_size = 128 * 1024 * 1024
comm_overlap_cfg.overlap_grad_reduce = True
comm_overlap_cfg.overlap_param_gather = TrueLaunch-time env tuning:
executor.env_vars["CUDA_DEVICE_MAX_CONNECTIONS"] = str(cuda_device_max_connections)
...
executor.env_vars["NVTE_FWD_LAYERNORM_SM_MARGIN"] = str(self.layernorm_sm_margin)
executor.env_vars["NVTE_BWD_LAYERNORM_SM_MARGIN"] = str(self.layernorm_sm_margin)Pitfalls
TP overlap silently disables itself if
sequence_parallel=Falseor Transformer Engine is unavailable.PP overlap is not enabled for all PP cases. Bridge only auto-selects
overlap_p2p_comm=TruewhenPP > 1andVPP > 1.bucket_sizeis a parameter-count knob, not a byte-size knob.grad_reduce_in_fp32andfp8_param_gathershould be set through mixed precision, not as standalone DDP tuning first.CUDA_DEVICE_MAX_CONNECTIONSand LayerNorm SM margin are launch-time plugin settings, notCommOverlapConfigfields.
Verification
Use the checked-in overlap unit coverage first:
uv run python -m pytest tests/unit_tests/training/test_comm_overlap.py -qOptional second check if nemo_run is available:
uv run python -m pytest tests/unit_tests/recipes/test_run_plugins.py -qSuccess criteria:
first command reports
26 passedsecond command validates plugin-owned env wiring when not skipped
Files
- ATTRIBUTION.mdAdded by AutoGineer871 B
- BENCHMARK.md4.3 KiB
- LICENSELicence file added by AutoGineer11.2 KiB
- SKILL.md3.6 KiB
- card.yaml2.1 KiB
- evals/evals.json1.4 KiB
- skill-card.md3.7 KiB
- skill.oms.sig4.7 KiB
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Attribution and licence
- Published by
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- NVIDIA (Official)
- Source
- NVIDIA/skills · skills/nemo-mbridge-perf-tp-dp-comm-overlap · commit fce3cca
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE-APACHE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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