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feat(telemetry): add prefill-phase attribution (#175)
Split the prompt phase into the same wall-additive terms decode already reports:
prefill_cpu_s / prefill_read_mib / prefill_io_s / prefill_stall_s / prefill_mgmt_s,
as session-level deltas of the streamer's cumulative counters across the prefill
chunks. Session layer only; the streamer is untouched. The keys ride both
BMOE_DONE and the CSV `# summary` trailer, appended so existing readers ignore them.

Closes #173.
2026-08-28 19:46:43 +02:00
..
assets feat(moe): Qwen3.8-Flash-Next support (#172) 2026-08-28 10:07:43 +02:00
bench-data docs(bench): record the 2026-07-24 desktop campaign — the bottleneck flips 2026-07-24 10:34:14 +02:00
adding-a-model.md refactor(moe): drop the llada-moe recipe (diffusion, out of scope) 2026-07-13 16:02:32 +02:00
android-memory.md feat(moe): hold back dense tensors larger than RAM under every mode (#174) 2026-08-28 10:20:13 +02:00
architecture.md feat(moe): stream split multi-shard ggufs natively + DeepSeek V4 Flash recipe (#144) 2026-08-01 23:34:35 +02:00
benchmark-method.md docs: benchmark pages as a contributor guide, and the Apple platform limits 2026-08-28 16:53:22 +02:00
benchmarks-gpt-oss.md docs: record the expert-sidecar negative result and ship the --scatter microbench 2026-07-20 17:02:48 +02:00
benchmarks.md docs: benchmark pages as a contributor guide, and the Apple platform limits 2026-08-28 16:53:22 +02:00
cache-sizing.md feat(moe): warn when the expert cache budget sits below one token's cycle (#167) 2026-08-25 12:48:22 +02:00
community-benchmarks.md docs(bench): name the app settings an in-app row has to match 2026-08-28 17:06:03 +02:00
expert-dropping.md docs: professional README and canonical AGENTS.md (#132) 2026-07-28 17:40:36 +02:00
expert-prediction.md feat(moe): measure how predictable expert routing is, then act on it — and refute it (#101) 2026-07-28 09:21:41 +02:00
limitations.md docs: benchmark pages as a contributor guide, and the Apple platform limits 2026-08-28 16:53:22 +02:00
moe-streaming.md feat(moe): --drop-cold-experts — spend quality only where it buys I/O (#95) 2026-07-22 17:21:55 +02:00
mtp.md feat(engine): self-speculative decoding — the model's own MTP head, or n-gram lookup (#134) 2026-08-02 00:09:39 +02:00
ngram.md feat(engine): self-speculative decoding — the model's own MTP head, or n-gram lookup (#134) 2026-08-02 00:09:39 +02:00
prefetch.md feat(moe): measure how predictable expert routing is, then act on it — and refute it (#101) 2026-07-28 09:21:41 +02:00
pressure.md feat(moe): --drop-cold-experts — spend quality only where it buys I/O (#95) 2026-07-22 17:21:55 +02:00
README.md docs: benchmark pages as a contributor guide, and the Apple platform limits 2026-08-28 16:53:22 +02:00
roadmap.md feat(moe): warn when the expert cache budget sits below one token's cycle (#167) 2026-08-25 12:48:22 +02:00
route-ahead.md feat(engine): --route-ahead N — commit decode routing to the N-layers-early prediction (#142) 2026-08-02 00:26:38 +02:00
seam.md feat(moe): Qwen3.8-Flash-Next support (#172) 2026-08-28 10:07:43 +02:00
session.md perf(cli): BMOE_PROGRESS carries the answer as a delta, not cumulatively (#127) 2026-07-28 15:38:34 +02:00
telemetry.md feat(telemetry): add prefill-phase attribution (#175) 2026-08-28 19:46:43 +02:00
warmup-analysis.md docs: correct the benchmark recipe, the arch list and mismatched sizes 2026-07-19 11:27:18 +02:00

Documentation

Start with architecture.md for the layer map, or moe-streaming.md for the idea the project is built on.

Understanding the design

Doc What it answers
architecture.md How the layers fit together, and why llama.cpp is not forked.
moe-streaming.md Why streaming experts from flash makes a >RAM model run at all.
seam.md The exact contract with llama.cpp's public API, and how to upgrade the submodule.
limitations.md What this does not do, what it cannot do, and the prior art it builds on.
roadmap.md Themes worth exploring next.

Using and extending it

Doc What it answers
adding-a-model.md How to support a new MoE architecture (a recipe row plus a gate).
telemetry.md The BMOE_* line protocol and CSV schema — the integration contract.
session.md Session lifecycle, KV prefix reuse, cancellation.
cache-sizing.md --cache-mb auto, the cache ceiling, and dense warm-up.
prefetch.md --prefetch K: the design and why it cannot change output (with the lossy knobs off).
expert-dropping.md --drop-cold-experts F: spending quality only where it buys a flash read, and why it is the one setting whose output is not reproducible.
mtp.md --mtp: drafting with the model's own MTP head and verifying a whole group per decode — lossless by construction, and why a wider decode can lose in the streamed regime.
ngram.md --ngram: drafting from text that repeats, with no head and no draft decode — and why a source that abstains costs exactly an unspeculated step.
expert-prediction.md --predict-log: how much of a routing can be known a layer early, measured against the predictor --prefetch already bets on — and why a good score still would not mean a faster decode.
route-ahead.md --route-ahead N: committing the routing to the N-layers-early prediction, so a prefetch of it can never miss — and what that costs in quality (experimental, lossy).
android-memory.md What reclaims the engine's memory on a phone, which levers exist (almost none), and why the cache hit rate is what the kernel judges you by.
pressure.md Cache policy under memory pressure: why an unaffordable budget starts a reclaim war, why the adaptive governor was retired, and what the fixed --cache-mb / --dense-weights levers do.

Measurements

Doc What it answers
benchmarks.md Measured results per model on Android, with device-pressure numbers.
benchmarks-gpt-oss.md gpt-oss-120b: a 58 GB model at 5.2× device RAM, and what it costs.
benchmark-method.md How to measure this engine on any machine: what each knob does, when to move it, and the rules that keep a matrix honest.
community-benchmarks.md Results on hardware we do not own, the one-command protocol (scripts/bench-report.sh), and how to submit a row.
warmup-analysis.md Why first tokens are slow, and the two regimes behind it.
bench-data/ Raw per-run CSVs and session notes. A dated archive — see its README.

Every benchmark figure in these docs is measured on the hardware named beside it. If you re-measure, update benchmark-method.md and the affected table together.