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NT Nano cfg update (#2662) #2681

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Merged
malay-nagda merged 1 commit into from
Mar 6, 2026
Merged

NT Nano cfg update (#2662) #2681

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2 changes: 2 additions & 0 deletions scripts/performance/configs/nemotronh/nemotron_3_nano_llm_pretrain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,8 @@ def set_nemotron_3_nano_common_configs(cfg: ConfigContainer) -> None:
cfg.mixed_precision.grad_reduce_in_fp32 = False
cfg.ddp.grad_reduce_in_fp32 = False

cfg.model.moe_router_force_load_balancing = True


def nemotron_3_nano_pretrain_config_gb300(
precision: str = "bf16", mock: bool = True, config_variant: str = "v1"
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50 changes: 37 additions & 13 deletions scripts/performance/configs/nemotronh/nemotron_3_nano_workload_base_configs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,36 +31,60 @@
BASE_NEMOTRON_3_NANO_CONFIG = WorkloadBaseConfig(
num_gpus=8,
global_batch_size=512,
micro_batch_size=2,
tensor_model_parallel_size=1,
expert_tensor_parallel_size=1,
expert_model_parallel_size=8,
moe_flex_dispatcher_backend="hybridep",
cuda_graph_impl="transformer_engine",
cuda_graph_scope=["attn", "mamba", "moe_router", "moe_preprocess"],
)

NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_BF16_V1 = BASE_NEMOTRON_3_NANO_CONFIG
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_FP8_MX_V1 = BASE_NEMOTRON_3_NANO_CONFIG

NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB200_BF16_V1 = BASE_NEMOTRON_3_NANO_CONFIG
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB200_FP8_MX_V1 = BASE_NEMOTRON_3_NANO_CONFIG
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_BF16_V1 = replace(
BASE_NEMOTRON_3_NANO_CONFIG,
micro_batch_size=4,
)
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_FP8_MX_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_BF16_V1
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_NVFP4_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_BF16_V1

NEMOTRON_3_NANO_PRETRAIN_CONFIG_B300_BF16_V1 = BASE_NEMOTRON_3_NANO_CONFIG
NEMOTRON_3_NANO_PRETRAIN_CONFIG_B300_FP8_MX_V1 = BASE_NEMOTRON_3_NANO_CONFIG
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB200_BF16_V1 = replace(
BASE_NEMOTRON_3_NANO_CONFIG,
micro_batch_size=2,
)
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB200_FP8_MX_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB200_BF16_V1
NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB200_NVFP4_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB200_BF16_V1

NEMOTRON_3_NANO_PRETRAIN_CONFIG_B200_BF16_V1 = BASE_NEMOTRON_3_NANO_CONFIG
NEMOTRON_3_NANO_PRETRAIN_CONFIG_B200_FP8_MX_V1 = BASE_NEMOTRON_3_NANO_CONFIG
NEMOTRON_3_NANO_PRETRAIN_CONFIG_B300_BF16_V1 = replace(
BASE_NEMOTRON_3_NANO_CONFIG,
micro_batch_size=4,
)
NEMOTRON_3_NANO_PRETRAIN_CONFIG_B300_FP8_MX_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_B300_BF16_V1
NEMOTRON_3_NANO_PRETRAIN_CONFIG_B300_NVFP4_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_B300_BF16_V1

NEMOTRON_3_NANO_PRETRAIN_CONFIG_B200_BF16_V1 = replace(
BASE_NEMOTRON_3_NANO_CONFIG,
micro_batch_size=2,
)
NEMOTRON_3_NANO_PRETRAIN_CONFIG_B200_FP8_MX_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_B200_BF16_V1
NEMOTRON_3_NANO_PRETRAIN_CONFIG_B200_NVFP4_V1 = NEMOTRON_3_NANO_PRETRAIN_CONFIG_B200_BF16_V1

_NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100 = replace(
BASE_NEMOTRON_3_NANO_CONFIG,
num_gpus=16,
global_batch_size=1024,
micro_batch_size=1,
recompute_modules=["moe", "layernorm"],
cuda_graph_impl="transformer_engine",
)

NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100_BF16_V1 = _NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100
NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100_FP8_CS_V1 = _NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100
NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100_BF16_V1 = replace(
_NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100,
recompute_modules=["moe", "layernorm"],
cuda_graph_scope=["attn", "mamba"],
)
NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100_FP8_CS_V1 = replace(
_NEMOTRON_3_NANO_PRETRAIN_CONFIG_H100,
cuda_graph_scope=["mamba"],
recompute_modules=["moe", "layernorm", "core_attn", "moe_act"],
)

__all__ = [
"NEMOTRON_3_NANO_PRETRAIN_CONFIG_GB300_BF16_V1",
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3 changes: 3 additions & 0 deletions scripts/performance/perf_plugins.py
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Original file line number Diff line number Diff line change
Expand Up @@ -301,6 +301,9 @@ def _set_model_specific_environment_variables(
if gpu in ["h100"] and model_recipe_name in ["llama3_70b"] and compute_dtype == "fp8_cs":
executor.env_vars["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
executor.env_vars["NCCL_GRAPH_REGISTER"] = "0"
if model_recipe_name in ["nemotron_3_nano"]:
del_cudnn_ln = False

if del_cudnn_ln:
if "NVTE_NORM_FWD_USE_CUDNN" in executor.env_vars:
executor.env_vars.pop("NVTE_NORM_FWD_USE_CUDNN")
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