Merge nucleic/sleek-ember-seal-uady into dev

2026-07-30 05:04:34 -07:00
parent 9c43be6df1
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+# Purpose-classifier energy and accelerator-residency check
+
+This is the required per-model-version hardware spot check from
+`docs/PURPOSE_CLASSIFIER.md` §8.5. It is deliberately not CI: the numbers are meaningful
+only on named physical hardware with a stable power source, thermal state, and runtime
+placement.
+
+## Common protocol
+
+1. Record the artifact SHA-256, app/build commit, machine model, OS build, battery/AC
+   state, ambient power mode, and runtime compute policy.
+2. Warm the model with 100 batch-one classifications, then classify the same fixed
+   1,000-prompt sequence. Tokenization is included. Disable network activity and other
+   foreground workloads.
+3. Run at least five trials per compute policy, alternating policy order. Report median
+   wall time, p95 inference latency, average package power, and joules per inference.
+4. Capture the runtime placement evidence alongside the power trace. A fast CPU fallback
+   is still a residency failure for `purpose-deep`.
+
+## macOS
+
+- Run the release Core ML artifact once with `.cpuAndNeuralEngine`, recording the
+  `MLComputePlan` ANE operation share and the artifact's required floor.
+- Repeat with a diagnostic CPU-only configuration on the same Mac and power source.
+- Sample the 1,000-inference region with `sudo powermetrics --samplers cpu_power,gpu_power`
+  at one-second intervals. Store the raw trace outside git and put its summarized table in
+  the model metrics report.
+- The default ANE policy is accepted only when it uses less average power and fewer joules
+  per inference than CPU-only. On AC, a `.all` GPU retry must separately meet its declared
+  GPU operation-share floor before it can activate a deep model.
+
+## Windows
+
+- Record the Windows ML execution provider and assigned device after AOT compilation.
+  Deep requires QNN NPU, OpenVINO NPU/GPU, NvTensorRT-RTX, or MIGraphX; bare CPU is only
+  valid for lite.
+- On battery compare `MAX_EFFICIENCY` with an explicit CPU session. On AC compare the
+  selected NPU, otherwise the validated vendor GPU EP, with CPU.
+- Capture the 1,000-inference window with HWiNFO sensor logging or the vendor's documented
+  NPU/GPU telemetry. Include package/device average power and energy per inference in the
+  model metrics report.
+- Verify that unplugging skips the discrete-GPU rung and that an idle session unloads
+  without keeping the dGPU awake.
+
+The report is incomplete if it gives latency without placement evidence and energy, or if
+it compares different prompt sequences between policies.