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mesh: an in-process engine is metered by this process's own CPU and GPU energy
Mesh's headline figure, microjoules per accepted token, is to be measured
at the meter. Yet every real serve through mesh was estimated: the GGUF
serving binaries were hardwired to EstimatorMeter, and HwMeter bridges
the host meter, which on macOS 27 is the estimator (IOReport's CPU rails
are frozen).

- mesh-meter `ProcessMeter`, behind `hw-meter`, for an engine that runs
  in this process. Each serve is metered by jouleclaw's ProcessSpanMeter:
  this process's own CPU energy plus its own GPU energy.
  - A span that covers the whole request is graded as its counters
    grade it: HwShunt for a live reading. Whole means the process was
    effectively the GPU's sole user and used no Neural Engine; a
    process with no GPU time spent exactly 0 J on it, so CPU-only
    engines qualify.
  - Any other span is an estimate of the whole request, Estimator: the
    reading plus EstimatorMeter for the rest of the host, as HwMeter
    bills a counter that reads part of a request. `mesh/1` has no
    coverage field.
- `Meter::open_span` and `Window`. The default is None, so existing
  meters keep snapshot semantics. ProcessMeter grades over the whole
  span, because its GPU grade depends on the process's share over it.
  Session uses a span window where a meter keeps one.
- mesh-engine-gguf, with `metal`: serve_falcon and serve_openai_falcon
  meter with ProcessMeter (the Metal liveness load comes from
  jouleclaw-backend-apple). New `serve_gemma_metered` serves Gemma 4
  through mesh with ProcessMeter.
- Fixes mesh-engine-gguf under `gguf`: it no longer compiled on main.
  ServeOutcome and ServeRequest gained a `decision` field and three
  initializers lacked it, unseen because CI never built the feature.
  standards-build now runs `cargo test -p mesh-engine-gguf --features
  gguf` on the mesh-rs leg.

Measured on an M5 Max:
- mesh-core tests/process_meter.rs: a ReferenceEngine serve sealed
  HwShunt 1,051,668 µJ (4,108 µJ per accepted token), within the
  1,090,946 µJ of this process's CPU energy the test read around the
  serve.
- serve_gemma_metered, Gemma 4 E2B on CPU, 3 x 16 tokens: HwShunt
  12.52 J, 12.16 J and 12.54 J (0.78, 0.76 and 0.78 J per accepted
  token). Every envelope verifies.

Mutation caught: billing a whole span's figure plus the rest-of-host
estimate fails the unit test and the end-to-end bracket ("the receipt
read 55691805 µJ, more than this process's 966177 µJ").

Co-Authored-By: Claude Opus 5.5 <[email protected]>
2026-10-08 20:21:15 -04:00
..
conformance/v1 wai.generate.spectral: extend the lexicon to 370 words (data-only, pin unchanged) 2026-06-27 05:33:47 -04:00
mesh-rs mesh: an in-process engine is metered by this process's own CPU and GPU energy 2026-10-08 20:21:15 -04:00
tools/joules-per-decision mesh: withdraw the GPU per-decision figure — another process held 99.5% of the GPU 2026-10-05 07:20:58 -04:00
CONTRIBUTING.md wai.generate.spectral: extend the lexicon to 370 words (data-only, pin unchanged) 2026-06-27 05:33:47 -04:00
LICENSE wai.generate.spectral: extend the lexicon to 370 words (data-only, pin unchanged) 2026-06-27 05:33:47 -04:00
LICENSE-SPEC wai.generate.spectral: extend the lexicon to 370 words (data-only, pin unchanged) 2026-06-27 05:33:47 -04:00
README.md mesh: an in-process engine is metered by this process's own CPU and GPU energy 2026-10-08 20:21:15 -04:00
SPEC.md mesh: a typed decision is a unit of work this spec could not measure 2026-10-05 07:20:58 -04:00

Mesh

Energy-accounted inference serving & routing. One of the Transaction Science open standards.

Mesh treats every inference as a metered transaction. A request declares a joule ceiling and a fidelity floor; the mesh routes it to the cheapest-sufficient model on the cheapest-sufficient backend, serves it under an energy meter, and seals a receipt whose headline figure is microjoules per accepted output token — measured at the meter, not estimated from a price list.

The serving shelf reports dollars per token and tokens per second. Mesh reports the number that is physical, comparable across hardware, and impossible to inflate: the joule.

The shape

ServeRequest ──▶ authorise (JCP grant) ──▶ route (cheapest-sufficient)
                                              │
                                              ▼
                          meter ◀── serve (engine) ──▶ tokens
                                              │
                                              ▼
                         sealed JCR-1 receipt: µJ / accepted token

Four roles — caller, router, engine, steward — and four phases per serve: authorise, route, meter, seal. See SPEC.md §2.

The reference workspace

mesh-rs/ is a pure-Rust reference implementation:

Crate What it is
mesh-schema wire types — ServeRequest, Fidelity, two-part Energy, RouteDecision, ServeOutcome
mesh-router energy-weighted cheapest-sufficient routing with a full candidate audit
mesh-engine the ServingEngine interface + a deterministic, weights-free ReferenceEngine
mesh-engine-gguf a real backend (behind gguf): wraps the family's pure-Rust GGUF/Metal inference substrate so the mesh routes and meters actual model tokens
mesh-meter the meter window; an always-available estimator + an optional bridge to the family hardware meter (RAPL / NVML / Apple) behind hw-meter, and ProcessMeter: this process's own CPU and GPU energy for an engine that runs in process, measured when a span covers the whole request
mesh-receipt the mesh/1 receipt, JCR-1 sealing (det-CBOR + COSE_Sign1), and a hash-chained log
mesh-core the orchestration that ties authorise → route → meter → seal together
mesh-conformance the deterministic reference scenario, its checks, and the gen-vectors bin

Mesh rides on JCP (a serve request is authorised by a JCP grant; receipts seal in JCR-1), dispatches to runtimes such as JouleClaw, and routes across compute described by EOC and isolated by Sandbox. It introduces no new cryptography (see SPEC.md §9).

Run it

cd mesh-rs

# all crates green
cargo test --workspace
cargo clippy --workspace --all-targets

# end-to-end: mint a JCP grant, serve, print the sealed receipt
cargo run -p mesh-core --example demo

# on Linux/RAPL or a CUDA/NVML box, meter real silicon (HwShunt provenance, where
# the counter is live; a counter that is not live falls back to the estimator)
cargo run -p mesh-core --example demo --features hw-meter-rapl

# regenerate the published conformance vectors
cargo run -p mesh-conformance --bin gen-vectors -- ../conformance/v1

# serve a REAL model end-to-end through Mesh (Falcon-H1 0.5B), seal the receipt
cargo run --release -p mesh-engine-gguf --features gguf --bin serve_falcon -- \
    /path/to/falcon-h1-0.5b-instruct 12 "The capital of France is"

The serve_falcon run demonstrates the whole standard on real model tokens: a JCP grant authorises each request (an underfunded grant is refused before any decode runs), the cheapest-sufficient backend is chosen, the decode is metered, and a mesh/1 receipt is sealed and hash-chained across the session — e.g. prompt "The capital of France is" → " Paris. It is known for its historical landmarks", prompt "Photosynthesis is the process by which" → " plants convert sunlight into chemical energy in the form of", with both seals verifying and the chain's prev-links intact.

The demo prints the route (every backend weighed, with the reason each was kept or rejected), the honest energy provenance, and the wedge metric — then verifies the sealed envelope under the steward key.

Status

v0.1.0-draft.1. Reference workspace builds and tests green (mesh-schema, mesh-router, mesh-engine, mesh-meter, mesh-receipt, mesh-core, mesh-conformance); cargo clippy --all-targets warning-free; published vectors in conformance/v1/. The reference engine is deterministic and weights-free; production backends implement the same ServingEngine interface — mesh-engine-gguf (behind gguf) is a real one over the family's pure-Rust GGUF/Metal substrate, kept out of the default build so it needs no weights.