feat: initialize vLLM scripts knowledge base

- VLLM Overview: installation, CLI, API, architecture, quantization, parallelism
- VLLM Index: quick reference with commands, endpoints, parameters
- Dankserver System Specs: RTX 3090 24GB, 62GB RAM, Ubuntu 24.04
- Dankclaw System Specs: AMD Strix Halo APU, 61GB unified, ROCm 7.1
- RAM/CPU Offloading in VLLM: KV cache swap, gpu_memory_utilization, preemption
- Hybrid CPU/GPU Processing (Dankserver): NVIDIA GPU + system RAM configuration
- Shared Memory Architecture (Dankclaw): AMD unified memory and ROCm setup
- Running Qwen3.6 35B A3B FP8 on Dankserver: MoE model deployment guide
- Running Qwen3.6 27B FP8 on Dankclaw: dense model deployment guide

docs/Dankserver System Specs.md

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+# Dankserver System Specs
+
+## Server Overview
+
+Dankserver is an NVIDIA GPU server for vLLM inference. The host runs Ubuntu 24.04 with an RTX 3090 and 62 GB of system RAM.
+
+## Hardware Specifications
+
+### CPU
+
+| Property | Value |
+|----------|-------|
+| Architecture | x86_64 |
+| Vendor | AuthenticAMD |
+| Cores | 8 (1 socket) |
+| NUMA Nodes | 1 (node 0, 63503 MB) |
+
+### GPU
+
+| Property | Value |
+|----------|-------|
+| Model | NVIDIA GeForce RTX 3090 |
+| VRAM | 24576 MiB (24 GB) |
+| Driver | 595.84 |
+| CUDA Version | 13.2 |
+| CUDA Toolkit | 12.0 (nvcc) |
+
+### Memory
+
+| Property | Value |
+|----------|-------|
+| System RAM | 62 GiB |
+| Swap | 127 GiB |
+| /dev/shm | 32 GiB |
+
+### Storage
+
+| Filesystem | Size | Used | Avail | Use% |
+|------------|------|------|-------|------|
+| / (nvme0n1p2) | 915G | 849G | 20G | 98% |
+| /mnt/entropy (dm-0) | 91T | 86T | 977G | 99% |
+
+### OS and Software
+
+| Property | Value |
+|----------|-------|
+| OS | Ubuntu 24.04.4 LTS (Noble Numbat) |
+| Kernel | 7.0.0-28-generic |
+| Python | 3.12.3 |
+
+### Active Services
+
+A llama-server process occupies approximately 20 GB of the RTX 3090 VRAM.
+
+## VLLM Relevance
+
+- 24 GB VRAM limits model size. Use FP8 quantization for large models.
+- 62 GB system RAM provides ample swap space for KV cache offloading.
+- 127 GB swap supports large `--swap-space` values for CPU KV cache paging.
+- Root disk has only 20 GB free. Store models on /mnt/entropy.
+- CUDA 12.0 and Python 3.12.3 are compatible with vLLM.
+
+## See Also
+
+- [[VLLM Overview]]
+- [[Hybrid CPU GPU Processing Dankserver]]
+- [[RAM CPU Offloading in VLLM]]
+- [[Running Qwen3.6 35B A3B FP8 on Dankserver]]