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Merged
erhoo82 merged 4 commits into from
Jan 28, 2026
Merged

DSV3 NVFP4 recipe on GB300 #2076

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de3d019
dsv3 nvfp4 gb300
dingqingy-nv Jan 27, 2026
daf08ab
enable fast math
dingqingy-nv Jan 27, 2026
1afc195
Merge branch 'main' into dsv3-nvfp4-recipe
ko3n1g Jan 27, 2026
0aaad4d
remove redundent override
dingqingy-nv Jan 27, 2026
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2 changes: 1 addition & 1 deletion scripts/performance/configs/deepseek/deepseek_llm_pretrain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ def deepseek_v3_pretrain_config_gb300(
pipeline_model_parallel_size=base_cfg.pipeline_model_parallel_size,
virtual_pipeline_model_parallel_size=base_cfg.virtual_pipeline_model_parallel_size,
moe_flex_dispatcher_backend=base_cfg.moe_flex_dispatcher_backend,
layout=None,
layout=base_cfg.pp_layout,
)
set_deepseek_v3_common_configs(cfg)
set_workload_base_configs(cfg, base_cfg)
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16 changes: 14 additions & 2 deletions scripts/performance/configs/deepseek/deepseek_workload_base_configs.py
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Expand Up @@ -54,7 +54,16 @@
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_BF16_V1 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V1
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_FP8_CS_V1 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V1
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_FP8_MX_V1 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V1
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_NVFP4_V1 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V1
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_NVFP4_V1 = replace(
BASE_DEEPSEEK_V3_CONFIG,
micro_batch_size=2,
pipeline_model_parallel_size=2,
virtual_pipeline_model_parallel_size=8,
pp_layout="Et*4|(t*4|)*14tmL",
expert_model_parallel_size=32,
cuda_graph_scope=[],
recompute_modules=["mla_up_proj"],
)


DEEPSEEK_V3_PRETRAIN_CONFIG_GB200_V1 = replace(
Expand Down Expand Up @@ -133,7 +142,10 @@
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_BF16_V2 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V2
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_FP8_CS_V2 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V2
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_FP8_MX_V2 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V2
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_NVFP4_V2 = DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_V2
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_NVFP4_V2 = replace(
DEEPSEEK_V3_PRETRAIN_CONFIG_GB300_NVFP4_V1,
global_batch_size=4096,
)


DEEPSEEK_V3_PRETRAIN_CONFIG_GB200_V2 = replace(
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4 changes: 4 additions & 0 deletions scripts/performance/perf_plugins.py
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Expand Up @@ -446,6 +446,10 @@ def setup(self, task: Union["run.Partial", "run.Script"], executor: "run.Executo
self.train_task,
)

# Set NVFP4-specific environment variables
if self.compute_dtype == "nvfp4":
executor.env_vars["NVTE_USE_FAST_MATH"] = "1"


@dataclass
class PyTorchProfilerPluginScriptArgs:
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2 changes: 1 addition & 1 deletion scripts/performance/utils/overrides.py
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Expand Up @@ -359,7 +359,7 @@ def set_post_overrides(
dp = int(num_gpus / (tp * pp * cp))
logger.info(f"DP: {dp}; TP: {tp}; PP: {pp}; CP: {cp}; VP: {vp}")
## NOTE: overlap_param_gather_with_optimizer_step causes NaN grad norm for fp8_mx. Disabling it until the issue is resolved.
if dp > 1 and pp > 1 and vp > 1 and compute_dtype != "fp8_mx":
if dp > 1 and pp > 1 and vp > 1 and compute_dtype not in ("fp8_mx", "nvfp4"):
recipe.optimizer.overlap_param_gather_with_optimizer_step = True
if hasattr(recipe, "comm_overlap") and isinstance(recipe.comm_overlap, CommOverlapConfig):
recipe.comm_overlap.overlap_param_gather_with_optimizer_step = True
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3 changes: 3 additions & 0 deletions scripts/performance/utils/utils.py
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Expand Up @@ -62,6 +62,9 @@ class WorkloadBaseConfig:
moe_a2a_overlap: Optional[bool] = False
peft: Optional[str] = None

# Pipeline parallelism layout
pp_layout: Optional[str] = None
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@erhoo82 erhoo82 Jan 27, 2026

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This is a nice change to make the PP layout configurable.


@property
def sequence_parallel(self) -> bool:
"""Get the sequence parallel flag."""
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