serverAppConfigs/docs/index.md

vLLM Scripts — Knowledge Base

Documentation for the LLM inference fleet on two local machines: llama.cpp production (PP head + RPC worker), the FastFlowLM NPU endpoint, plus a vLLM research archive.

Deployment Topology

graph LR
    subgraph Dankserver[NVIDIA Dankserver - Ubuntu 24.04]
        A[RTX 3090 24GB + 62GB RAM]
        B[ggml-rpc worker
frank-pp-worker, port 50052]
        A --> B
    end

    subgraph Dankclaw[AMD Strix Halo - Ubuntu 26.04]
        D[gfx1151 APU 30GiB phys / 96GiB GPU-visible]
        E[llama.cpp PP head
frank-default-large, port 7770]
        F[Qwen3.8-27B UD-Q8_K_XL
split 0.40/0.60 to worker, MTP+ngram-mod]
        D --> E --> F
        G[FastFlowLM NPU XDNA2 50 TOPS
frank-default-small, port 52625]
        H[qwen3.6-moe:35b-a3b
12.5-13.1 t/s, 262k ctx, vision]
        D --> G --> H
    end

    I[LLM Clients / API] -->|HTTP :7770| E
    I -->|HTTP :52625| G
    E -->|RPC layers 0.40| B

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

• RAM CPU Offloading in VLLM — KV cache swap between GPU VRAM and system RAM
• Hybrid CPU GPU Processing Dankserver — NVIDIA GPU compute with system RAM offload
• Shared Memory Architecture Dankclaw — AMD unified memory and ROCm configuration

Model Deployment

• Running Qwen3.6 35B A3B FP8 on Dankserver — MoE model (35B total, 3B active) on RTX 3090
• Running Qwen3.6 27B FP8 on Dankclaw — Dense model (27B) on Strix Halo APU
• frank-default-large-benchmark — backend/spec benchmark; chose MTP sidecar (2026-08-14) over DFlash (parallel premature-EOS bug)
• qwen3.8-spec-matrix — Qwen3.8-27B UD-Q8_K_XL spec history + current production state: PP head, MTP (n_max 4) over the ngram-mod fallback, 2 slots @ 200704 (2026-08-16)
• qwen3.8-strix-optimizations — Qwen3.8-27B Strix speed research: ranked levers that keep UD-Q8_K_XL (PP to 3090, MTP tuning, same-bit Q8_0 A/B, prefill path, OS), quant landscape, 2026-08-16 test matrix
• frank-default-small-benchmark — ncmoe and batch/ubatch sweep that drove the Dankserver state
• dankserver-vram-growth — VRAM/RAM growth investigation behind the recurring cuBLAS crash on frank-default-small
• Dankclaw Improvements — researched enhancements: self-hosted agentic tools, runtime tuning, server/OS settings
• FastFlowLM NPU Inference — FastFlowLM (FLM), the AMD NPU-first runtime. The 50 TOPS Strix Halo NPU on Dankclaw: model fit, vendor benchmarks, verified install state, test runbook (2026-08-16)

Speculative Decoding & Quantization

• DFlash DSpark Speculative Decoding — block diffusion (DFlash) and semi-autoregressive (DSpark) drafting on vLLM and llama.cpp
• Quantization by Hardware Architecture — which quant format fits which GPU/CPU

Pipeline Parallelism

• Pipeline Parallelism — index of multi-node inference research and sample scripts
  • Pipeline Parallelism/llama.cpp RPC — ggml-rpc-server + --rpc distributed inference
  • Pipeline Parallelism/vLLM Pipeline Parallelism — vLLM PP across machines
  • Pipeline Parallelism/Ethernet Bandwidth Math — bytes per token and link feasibility
  • Pipeline Parallelism/Mixed-Vendor Experiments — NVIDIA + Strix Halo real-world runs
  • Pipeline Parallelism/Expected Performance — estimated tok/s over 1/2.5/10 GbE
  • Pipeline Parallelism/Sample Script Set — educational two-node Qwen3.6-27B Q8 split
  • Pipeline Parallelism/Qwen3.8 PP Deployment — the production deployment (promoted 2026-08-16) + runbook: Qwen3.8-27B head (Strix) / worker (RTX 3090) over RPC, b10433, scripts in scripts/

Sibling projects

• serverAppConfigs — the Podman app stack on the same two hosts. Its OpenWebUI consumes the :7770 endpoint; its Gitea instance hosts this repository.