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Code Review
This pull request introduces experimental support for FP4 activations in DeepSeek-V4 MegaMoE by adding new environment variables and logic to conditionally use an external deep_gemm library. Review feedback identifies a critical memory corruption risk because the input staging kernel still processes data as FP8 while the buffer sizing is updated for FP4. Additionally, it is recommended to move environment variable modifications to the model initialization phase to ensure thread safety and to add validation logic for the new configuration flags.
| if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS: | ||
| import deep_gemm | ||
| else: | ||
| import vllm.third_party.deep_gemm as deep_gemm |
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The implementation is incomplete and will lead to memory corruption when VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS is enabled. While get_symm_buffer is updated to use the external deep_gemm for FP4-aware sizing, the _run_mega_moe function (lines 665-701) still calls the Triton staging kernel _stage_deepseek_v4_mega_moe_inputs, which writes FP8 data (1 byte per element) into the buffer. This will overflow the FP4-sized buffer. Furthermore, _run_mega_moe still imports and uses the vendored vllm.third_party.deep_gemm for the kernel call, which does not support the FP4 activation layout. You must update _run_mega_moe to use deep_gemm.mega_moe_pre_dispatch and the external deep_gemm kernel when the flag is set.
if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS:
try:
import deep_gemm
except ImportError:
raise ImportError(
"sgl-deep-gemm is required when "
"VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS is enabled. "
"Please install it with `pip install sgl-deep-gemm>=0.1.0`."
) from None
else:
import vllm.third_party.deep_gemm as deep_gemm| def _apply_mega_moe_dg_env() -> None: | ||
| """Forward VLLM_DEEPGEMM_MEGA_MOE_* env vars to DeepGEMM internals. | ||
|
|
||
| Experimental: uses external deep_gemm (sgl-deep-gemm) for FP4 acts. | ||
| TODO(upstream): remove once vendored deep_gemm includes | ||
| mega_moe_pre_dispatch and FP4-aware buffer sizing. | ||
| """ | ||
| global _MEGA_MOE_DG_ENV_APPLIED | ||
| if _MEGA_MOE_DG_ENV_APPLIED: | ||
| return | ||
| if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS: | ||
| os.environ.setdefault("DG_USE_FP4_ACTS", "1") | ||
| if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND: | ||
| os.environ.setdefault("DG_USE_MXF4_KIND", "1") | ||
| _MEGA_MOE_DG_ENV_APPLIED = True |
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_apply_mega_moe_dg_env modifies os.environ globally and is called during the forward pass via get_symm_buffer. Modifying environment variables at runtime is generally thread-unsafe and can lead to race conditions. This configuration should be applied once during model initialization, for example in DeepseekV4MegaMoEExperts.__init__. Additionally, you should add a check to ensure that VLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND is only enabled when VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS is also set, as the former requires the latter.
| def _apply_mega_moe_dg_env() -> None: | |
| """Forward VLLM_DEEPGEMM_MEGA_MOE_* env vars to DeepGEMM internals. | |
| Experimental: uses external deep_gemm (sgl-deep-gemm) for FP4 acts. | |
| TODO(upstream): remove once vendored deep_gemm includes | |
| mega_moe_pre_dispatch and FP4-aware buffer sizing. | |
| """ | |
| global _MEGA_MOE_DG_ENV_APPLIED | |
| if _MEGA_MOE_DG_ENV_APPLIED: | |
| return | |
| if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS: | |
| os.environ.setdefault("DG_USE_FP4_ACTS", "1") | |
| if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND: | |
| os.environ.setdefault("DG_USE_MXF4_KIND", "1") | |
| _MEGA_MOE_DG_ENV_APPLIED = True | |
| def _apply_mega_moe_dg_env() -> None: | |
| """Forward VLLM_DEEPGEMM_MEGA_MOE_* env vars to DeepGEMM internals. | |
| Experimental: uses external deep_gemm (sgl-deep-gemm) for FP4 acts. | |
| TODO(upstream): remove once vendored deep_gemm includes | |
| mega_moe_pre_dispatch and FP4-aware buffer sizing. | |
| """ | |
| global _MEGA_MOE_DG_ENV_APPLIED | |
| if _MEGA_MOE_DG_ENV_APPLIED: | |
| return | |
| if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS: | |
| os.environ.setdefault("DG_USE_FP4_ACTS", "1") | |
| if envs.VLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND: | |
| if not envs.VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS: | |
| raise ValueError("VLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND requires " | |
| "VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS=1") | |
| os.environ.setdefault("DG_USE_MXF4_KIND", "1") | |
| _MEGA_MOE_DG_ENV_APPLIED = True |
|
This pull request has merge conflicts that must be resolved before it can be |
Add two opt-in env vars (both default off) to control FP4 activation packing in DeepSeek V4 MegaMoE: - VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS: enables E2M1 packing path - VLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND: switches to mxf4 mainloop Also add the required imports (os, vllm.envs) to deepseek_v4.py in preparation for subsequent patches. Signed-off-by: wuddiz <wuddiz@users.noreply.github.com>
…mm import in get_symm_buffer Add _apply_mega_moe_dg_env() which forwards VLLM_DEEPGEMM_MEGA_MOE_* env vars to DeepGEMM internals via os.environ.setdefault, ensuring explicit DG_USE_* overrides still win. The once-only guard prevents double-application. In get_symm_buffer(), call the helper then conditionally import the external deep_gemm (sgl-deep-gemm) for FP4-aware buffer sizing, or fall back to the vendored path when FP4 acts are disabled. TODO: collapse import branches to vendored path once upstream deepseek-ai/DeepGEMM merges FP4 buffer layout support. Signed-off-by: wuddiz <wuddiz@users.noreply.github.com>
…experimental) When VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS=1, replace the Triton _stage_deepseek_v4_mega_moe_inputs staging kernel with deep_gemm.mega_moe_pre_dispatch(), which packs activations as FP4 (E2M1) instead of FP8 (E4M3). This halves the symmetric buffer footprint and, combined with VLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND=1, unlocks the MXF4 mainloop (K=64 dense vs K=32 padded) on Blackwell. Accuracy (GSM8K, 1319 samples, greedy): V4-Flash: w4a8 93.86% -> w4a4 94.39% (+0.53%, within noise) V4-Pro: w4a8 91.81% -> w4a4 91.13% (-0.68%, within noise) When disabled (default), the original vendored path is used unchanged. TODO: collapse import branches to vendored path once upstream deepseek-ai/DeepGEMM merges mega_moe_pre_dispatch and FP4 buffer layout support. Signed-off-by: wuddiz <wuddiz@users.noreply.github.com>
…p-gemm dependency Update docstring and inline comments to more accurately describe the transitional status: upstream DeepGEMM accepts use_fp8_dispatch but does not yet wire it end-to-end; sgl-deep-gemm is used as a PoC bridge until upstream support lands. Signed-off-by: wuddiz <wuddiz@users.noreply.github.com>
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seealso: #42845 deepseek-ai/DeepGEMM#338
Purpose
MegaMoE currently packs activations as FP8 (E4M3) in the symmetric buffer before dispatch. On Blackwell (SM100), FP4 (E2M1) packing would halve the buffer footprint and unlock the MXF4 mainloop (K=64 dense vs K=32 padded) in DeepGEMM.
However, upstream DeepGEMM does not yet support FP4 activations end-to-end. The
fp8_fp4_mega_moekernel hardcodesa_dtype_t = float_e4m3_t,get_symm_buffer_size_for_mega_moeallocates input token buffers at FP8 width (hiddenbytes/token), and the dispatch stage TMA loads assume FP8 layout. Theuse_fp8_dispatchparameter exists in the API signature but is not wired through to the buffer sizing or kernel logic. An RFC has been filed at deepseek-ai/DeepGEMM to track this.This PR provides a proof-of-concept using
sgl-deep-gemm>=0.1.0, which ships amega_moe_pre_dispatch()CUDA kernel that handles E2M1 packing + FP4-aware buffer allocation. Two opt-in env vars, both default off:VLLM_DEEPGEMM_MEGA_MOE_USE_FP4_ACTS-- usedeep_gemm.mega_moe_pre_dispatch()for E2M1 activation packing instead of the Triton staging kernelVLLM_DEEPGEMM_MEGA_MOE_USE_MXF4_KIND-- switches tokind::mxf4mainloop, requires FP4 actsWhen enabled, imports external
deep_gemmfor buffer allocation and pre-dispatch. When disabled, vendoredvllm.third_party.deep_gemmis used as before -- zero change to default path.Flags forwarded to the external deep_gemm via
os.environ.setdefault("DG_USE_FP4_ACTS", ...)so explicitDG_USE_*overrides still win.Files:
vllm/envs.py,vllm/model_executor/models/deepseek_v4.pyUpstream Gap Analysis
Checked deepseek-ai/DeepGEMM (latest, identical to vendored commit 891d57b for the mega module):
csrc/apis/mega.hpp:get_symm_buffer_size_for_mega_moeacceptsuse_fp8_dispatchbut ignores it --input_token_bufferis alwayslayout::Data(hidden)(FP8, 1 byte/element)sm100_fp8_fp4_mega_moe.cuhline 162-163:a_dtype_t = cutlass::float_e4m3_t-- UMMA configured for FP8 activations onlykHiddenbytes per token (FP8 width)slice_input_buffersreturnsxas[tokens, hidden]float8,x_sfas[tokens, hidden/128]None of these support FP4 activations. Full FP4 activation support requires changes at the C++/CUDA kernel level (buffer sizing, TMA load widths, UMMA A-matrix dtype), which is being tracked via the upstream RFC.
Test Plan
Hardware: 8x B200 (SM100, 183GB). Accuracy: GSM8K full test set (1319 samples), greedy decoding, max_tokens=2048, concurrency=32.
Dep:
pip install sgl-deep-gemm==0.1.0V4-Flash (256 experts, hidden=4096, 43 layers), DP=4:
V4-Pro (384 experts, hidden=7168, 61 layers), TP=8:
Eval: hit
/v1/chat/completions, extract final number after####, compare against reference.Test Result
Accuracy (GSM8K, 1319 samples, greedy)
V4-Flash: w4a8 93.86% (1238/1319) -> w4a4 94.39% (1245/1319), delta +0.53%
V4-Pro: w4a8 91.81% (1211/1319) -> w4a4 91.13% (1202/1319), delta -0.68%
Both within noise. No meaningful accuracy degradation from FP4 activation packing.
Performance (V4-Flash, DP=4, 8×B200)
Benchmark config: 500 prompts, input_len=1024, output_len=8, max-concurrency=64, request-rate=inf,
--max-cudagraph-capture-size 512, random dataset.Key takeaway: ~58% throughput improvement, ~52% mean TTFT reduction. The gain is dominated by prefill (MXF4 mainloop K=64 dense vs K=32 padded). Decode TPOT improves ~8% from reduced buffer bandwidth.
What Happens When Upstream Supports FP4 Acts
Once deepseek-ai/DeepGEMM wires
use_fp8_dispatch=Falsethrough to buffer sizing + kernel:cmake/external_projects/deepgemm.cmakesgl-deep-gemmpath with a Triton FP4 staging kernel (~40 lines, E2M1 bucketize + pack) or use whatever staging API upstream providesget_symm_buffer_for_mega_moe(..., use_fp8_dispatch=False)-- the parameter already existssgl-deep-gemmdepDG_USE_FP4_ACTS/DG_USE_MXF4_KINDenv forwarding likely becomes unnecessary -- remove_apply_mega_moe_dg_envEssential Elements of an Effective PR Description Checklist
supported_models.mdandexamplesfor a new model.