IgorGanapolsky

nvidia-specdecode-al-doctor

Fail-closed speculative-decoding AL/D doctor for ThumbGate. Checks speedup ≤ AL/(1+ρD), attention D=128/G-1, tile alignment, and maps to checkpoint-speculative-decoding-acceptance. Steal from NVIDIA co-design blog — never clone TensorRT/EAGLE/Model-Optimizer. Slash: /nvidia-specdecode-al-doctor.

IgorGanapolsky 29 7 Actualitzat fa 1 mes
GitHub

Instal·la

npx skillscat add igorganapolsky/thumbgate/nvidia-specdecode-al-doctor

Instal·la des del registre de SkillsCat.

Sobre aquest skill

The skill validates speculative decoding parameters and claimed speedup against the derived bound, attention size, tile alignment, and checkpoint acceptance criteria, rejecting configurations that violate these constraints. It is appropriate when verifying that draft‑length, draft‑depth ratio, and speedup claim satisfy the required theoretical limits before running ThumbGate.

SKILL.md

NVIDIA Speculative-Decoding AL/D Doctor

When

Speculative decoding, MTP, EAGLE, draft length, accept length, claimed speedup, SPEED-Bench AL talk.

Do

npx thumbgate nvidia-specdecode-al-doctor \
  --speculative-decoding \
  --accept-length=AL \
  --draft-length=D \
  --draft-depth-ratio=ρ \
  --claimed-speedup=X \
  --json

Pair with:

npx thumbgate deepseek-v4-runtime-guardrails \
  --speculative-decoding --accept-length=AL --draft-length=D \
  --draft-depth-ratio=ρ --claimed-speedup=X --cache-coherence-eval --json

Never

  • Claim speedup without measured AL
  • Ship TensorRT-LLM / Model-Optimizer / EAGLE training clones
  • Treat missing AL as a pass

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