dspark: rowwise-fp8 draft lm_head (VLLM_DSPARK_FP8_DRAFT_HEAD, opt-in)

[bird]

Summary

DSpark's draft base logits are a full [hidden, vocab] bf16 GEMM through the
shared target lm_head (4096 x 64640 for DS4-Flash), computed once per draft
step purely to propose tokens. On bandwidth-bound GPUs the weight read
dominates the draft loop.

With VLLM_DSPARK_FP8_DRAFT_HEAD=1, attach_target_modules materializes a
one-time rowwise-fp8 (e4m3) copy of the local lm_head shard — w8 = w * (448 / rowmax) stored fp8, row_scale = rowmax / 448 — and
compute_logits runs dynamic per-token activation quant +
torch._scaled_mm, scales applied in the epilogue:

logits = _scaled_mm(a8, w8.T, out_dtype=bf16) * row_scale * (amax / 448)

Halves lm_head weight traffic in the draft step. Env unset: zero behavior
change. Mirrors the existing VLLM_DSPARK_FP32_LM_HEAD pattern (eager copy
at attach, branch in compute_logits); FP32 takes precedence if both are
set.

Numbers

Production A/B, DeepSeek-V4-Flash-DSpark on DGX Spark (GB10, ~235 GB/s):

• draft-head GEMM 2.73 -> 1.45 ms per draft step
• +3–5% end-to-end single-stream decode
• draft argmax-identical to the bf16 head on our eval set; per-position
  acceptance unchanged

Win scales with how bandwidth-bound the part is; GB10 is the extreme case,
expect less on B300/RTX 6000 Pro — hence opt-in.

Why it's safe

• Draft-time only: compute_logits lives on the draft model; the verify
  pass never sees the fp8 copy, so accepted outputs are bit-identical.
• Rowwise scaling bounds per-logit error to ~e4m3 half-ulp of each row's
  max; a rare near-tie argmax flip costs one rejected draft token, never a
  wrong output.
• TP: quantizes the local vocab shard with per-local-row scales, then the
  same _gather_logits + vocab_size slice as the FP32 branch — argmax
  semantics unchanged.
• Capture-safe: materialized eagerly at attach (before draft-step FULL
  graph capture); the fp8 branch has no data-dependent control flow and no
  allocations beyond the GEMM output.

Scope

One file, vllm/models/deepseek_v4/nvidia/dspark.py (+54): fp8 buffers in
attach_target_modules, fp8 branch in compute_logits. No collision with
#71 — its dspark.py hunks touch _dspark_attention, the forward_head
confidence skip, and forward_spec, not attach_target_modules /
compute_logits; the two compose (this removes half the head GEMM cost,
#71's confidence skip removes the other lm-head-sized projection).

Validation

• python3 -m py_compile vllm/models/deepseek_v4/nvidia/dspark.py
• git diff --check lil/dev/eldritch-enlightenment..HEAD
• Kernel math validated on GB10 (torch 2.11 cu130 container): real
  torch._scaled_mm path matches a float32 emulation bitwise; rowwise
  quant roundtrip within the analytic half-ulp bound; bf16-vs-fp8 argmax
  flips occur only on near-ties (top-2 margin within fp8 error scale) on
  i.i.d.-Gaussian worst-case logits.
• E2E: same patch (V1-lineage overlay) in production on our 2x DGX Spark
  cluster since 2026-06; A/B numbers above, 30k-token coherence clean.

Upstream port of the same change: vllm-project#47584

🤖 Generated with Claude Code

Summary by CodeRabbit

• New Features

  • Added an optional FP8 draft-time path for generating logits, enabled through an environment setting.
  • When turned on, the model can use a quantized weight format for the final projection step during draft generation.

• Performance

  • Improves draft-time inference efficiency while preserving the existing default behavior when the option is not enabled.

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📥 Commits

Reviewing files that changed from the base of the PR and between 281febd5e4e398105d1e729a9094c1c527237ff8 and 91d495e.

📒 Files selected for processing (1)

• vllm/models/deepseek_v4/nvidia/dspark.py

📝 Walkthrough

Walkthrough

Adds an environment-gated (VLLM_DSPARK_FP8_DRAFT_HEAD=1) FP8 rowwise-quantized draft lm_head path to DeepSeekV4DSparkDraft. attach_target_modules() materializes and registers FP8 E4M3 weight and scale buffers; compute_logits() adds a branch performing per-token activation quantization and torch._scaled_mm-based logits computation with dequant scaling.

Changes

FP8 Draft Head

Layer / File(s)	Summary
FP8 weight materialization and quantized logits path vllm/models/deepseek_v4/nvidia/dspark.py	Adds env-gated FP8 E4M3 quantization of lm_head weights with row/unit scale buffers in attach_target_modules(), and a matching compute_logits() branch that quantizes activations per-token, runs torch._scaled_mm, applies dequant scaling, then reuses existing _gather_logits/vocab slicing.

Estimated code review effort: 3 (Moderate) | ~20 minutes

Sequence Diagram(s)

sequenceDiagram
  participant Draft as DeepSeekV4DSparkDraft
  participant AttachFn as attach_target_modules
  participant ComputeFn as compute_logits
  participant ScaledMM as torch._scaled_mm

  Draft->>AttachFn: attach_target_modules()
  AttachFn->>AttachFn: compute per-row max, quantize lm_head to FP8 E4M3
  AttachFn->>Draft: register fp8_weight, row_scale, unit_scale buffers

  Draft->>ComputeFn: compute_logits(hidden_states)
  ComputeFn->>ComputeFn: compute per-token activation max, quantize activations to FP8
  ComputeFn->>ScaledMM: scaled_mm(quantized_activations, fp8_weight, scales)
  ScaledMM-->>ComputeFn: raw logits
  ComputeFn->>ComputeFn: apply activation and rowwise dequant scaling
  ComputeFn->>ComputeFn: _gather_logits and vocab slicing
  ComputeFn-->>Draft: logits

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Title check	✅ Passed	The title clearly identifies the DSpark rowwise-FP8 draft lm_head change and the opt-in environment flag.
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[voipmonitor]

Closing this old dev/eldritch-enlightenment PR as superseded by the Fathomless Firmament port.

The feature is preserved in the new FF DSpark stack as commit d20d103bc ([Spec Decode][Perf] Rowwise-fp8 draft lm_head for DSpark (opt-in)). The port keeps VLLM_DSPARK_FP8_DRAFT_HEAD, moves the implementation into a reusable fp8_draft_head helper, registers the environment variable normally, initializes the FP8 copy before CUDA graph capture, and adds dedicated tests. Authorship from this PR is retained.

It will be submitted against dev/fathomless-firmament as part of the new non-draft DSpark PR.