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Frank 327e78b950 docs(vault): destroy the dead weight — 53 pages and the change diary

The vault was 155 pages / 31,210 lines, most of it measurement ledgers for
payloads that no longer run. A throughput figure for a runtime nobody operates is
not a record: AI moves faster than the vault, so the number is wrong before
anyone reads it, and a wrong number in a runbook gets believed. Per the new
purpose test in `AGENTS.md` → *Documentation Policy*, it is destroyed.

Gone (`.AGENTTRASH/20261019-destruction/`, KILL-LIST.txt is the manifest):
- the `frank-medium` endpoint and its five era pages, `frank-npu`, FastFlowLM,
  the ikllama/kingjones/dealign/frank-redo eras, the ling/swift15/freetoken/ubatch
  campaign pages, qwen3.8 spec-matrix and strix-optimizations, the two
  "Running Qwen3.6 …" pages;
- the whole `Pipeline Parallelism/` folder (no live script passes a pipeline flag)
  and the multi-device/x4-pair/hybrid/offload experiment pages;
- every vLLM page — no vLLM endpoint exists on this fleet;
- `LLM/deployment.md` (`Architecture/Deployment Flow.md` is the test-referenced
  owner) and the external surveys (SGLang, Lemonade, llama.cpp forks/diff,
  self-hosted app census, the TTS survey) that were obsolete by construction;
- `log.md`, 2,380 lines. Git holds the chronology; a causal law belongs to the
  page that owns the thing it governs, never to a diary.

Survivors: 101 pages, 17,542 lines, 0 OKF violations, 0 unresolved links. Eras
tables keep the window, payload, runtime, reason and rollback pointer; the rate
columns are blanked. The live shapes stay verbatim — those numbers are what the
deployer and `models.yml` consume.

2026-10-19 10:56:37 -07:00

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LLM fleet — index

The three live endpoint pages are the only pages that carry a shape. Everything else here is a technique or a piece of hardware, and each of those owns exactly that one thing. There is no worklog and no era page: a payload swap is one row in the endpoint's Eras table, and the numbers a retired era measured are gone.

Live endpoints

Page	Owns
frank-archon	The radiance endpoint: live shape and harness contract, every era with its rollback path, and the laws it taught.
frank-dragoon	The iGPU endpoint: live shape, every era with its rollback path, the laws it paid for, and the files that own it.
frank-zealot	The RTX 3090 endpoint: live shape exactly as the env ships it, every era with its rollback path, and its card laws.

Retired endpoints

Page	Owns

Pipeline Parallelism (series)

Page	Owns

Techniques, hardware, trials

Page	Owns
Dankclaw Improvements	This page collects concrete, sourced recommendations to improve Dankclaw
Dankclaw System Specs	Dankclaw is an AMD APU server for CIRU ROCmFPX llama.cpp inference.
dankclaw-iommu-translation-off	Why Dankclaw boots with identity DMA, what the earlier off-era bought and cost, and which tooling owns the boot line.
Dankserver System Specs	Dankserver hardware and OS state since the board swap: board, lane topology, cards, memory, kernel posture.
DFlash DSpark Speculative Decoding	DFlash and DSpark are the two newest speculative decoding methods.
GGUF Compatibility	Answering whether an engine loads a GGUF from the file header alone, and pinning a fork build that can.
Heterogeneous Split Triage	Triage before splitting across unequal accelerators: link characterisation, real bottleneck, what placement never buys.
Llama Cpp Serving Sizing	Measurement-first sizing for llama.cpp shapes: slot pools against a headroom band, per-device accounting, prompt cache.
LLM Performance Diagnosis	Probing why a served model is slow: the flat-depth probe, offload duty-cycle arithmetic, and profiler attribution.
Model Swap and Rollback	The model-swap discipline: fit preflight, fetch verification, build and flag checks, live validation, three-pin revert.
PCIe Link and Atomics	Link probing, the streaming-versus-compute ceiling arithmetic, and the atomics wall that decides multi-GPU collectives.
Quantization by Hardware Architecture	This page maps LLM quantization formats to the GPU and CPU architectures that support them.
Quantization Production	Making a quantized payload here: the conversion recipe, the scoring gate, and the campaign ladder behind a shipped file.
RDNA4 MoE Expert Offload VRAM Budget	Expert-offload arithmetic on the RDNA4 fork: movable terms, the utilisation law, graph charge, ceilings, context ladder.
Shared Memory Architecture Dankclaw	Dankclaw uses AMD Strix Halo APU with unified memory architecture.

Pages

Page	Owns

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