Files
serverAppConfigs/docs/index.md
T
Frank 993b6af576 docs: add DFlash/DSpark speculative decoding research + quantization-by-hardware guide
- DFlash DSpark Speculative Decoding.md: verified method details (DFlash
  block diffusion from Z Lab arXiv:2602.06036; DSpark semi-autoregressive from
  DeepSeek arXiv:2607.05147), runtime support matrix (vLLM/llama.cpp/SGLang),
  exact vLLM --speculative-config recipes (incl. dflash/dspark), llama.cpp
  --spec-type recipes with sidecar auto-discovery, draft model table
  (z-lab Qwen3.6-27B-DFlash 2B, Qwen3.6-35B-A3B-DFlash 0.4B), deployment
  guidance for RTX 3090 (AWQ+Dflash) and Strix Halo (ROCmFPX MTP), measured
  45-50 t/s MTP decode on Strix Halo
- Quantization by Hardware Architecture.md: FP8/INT8/INT4/GPTQ/AWQ/GGUF/FP4/
  ROCmFP4 support per NVIDIA (Turing/Ampere/Ada/Hopper/Blackwell), AMD
  (CDNA MI250/MI300/MI350, RDNA 3/3.5/4), and CPU; recommended picks per
  Dankserver (AWQ/GPTQ 4-bit) and Dankclaw (ROCmFP4/Q4_K_M)
- index.md: link both new pages under Speculative Decoding & Quantization
2026-08-10 21:09:17 -07:00

2.2 KiB

vLLM Scripts — Knowledge Base

Documentation for running vLLM inference on two local machines.

Deployment Topology

graph LR
    subgraph Dankserver[NVIDIA Dankserver - Ubuntu 24.04]
        A[RTX 3090 24GB + 62GB RAM]
        B[vLLM 0.26.0 in Podman\nvllm-qwen36-dflash]
        C[Qwen3.6-35B-A3B-FP8\n+ DFlash draft, port 8000]
        A --> B --> C
    end

    subgraph Dankclaw[AMD Strix Halo - Ubuntu 26.04]
        D[gfx1151 APU 30GiB phys / 96GiB GPU-visible]
        E[ROCmFPX llama.cpp\n/ROCmFPX/build-strix-rocmfp4]
        F[Ling-3.0-flash ROCmFP4-MTP\ndraft-mtp, port 8080]
        D --> E --> F
    end

    G[LLM Clients / API] -->|HTTP :8000| B
    G -->|HTTP :8080| E

Servers

Server GPU VRAM / Memory OS
Dankserver System Specs NVIDIA RTX 3090 24 GB VRAM, 62 GB RAM Ubuntu 24.04
Dankclaw System Specs AMD Radeon 8060S (Strix Halo) 30 GiB physical / 96 GiB GPU-visible Ubuntu 26.04

vLLM Reference

  • VLLM Overview — installation, CLI, API, architecture, quantization, parallelism
  • VLLM Index — quick reference with commands, endpoints, and parameter table
  • deployment — deploy and update process for both servers

Memory Management

Model Deployment

Speculative Decoding & Quantization