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`detect_in_process_meter` is for work that runs on this process's own threads. Each caller that meters model work was checked against that, and adopted it only where it holds. - jouleclaw-harness-econ: `local_model_econ`, `swebench_local_coder` and `swebench_local_suite` meter a decode that runs in this process, on the loader's CPU kernels and rayon pool; the examples build the loader with `rayon` only, without its GPU `fabric`, and the metered window is the decode alone (the `python3` judge, a subprocess, runs outside it). They now use the in-process meter, so on macOS 27.0.1, where the host meter is the load-average estimator, a dispatch is a live hardware reading of its own CPU energy. `window_joules` already refuses a window the counter did not advance across. `meter_probe` reports both meters. Run here on a host under load average ~50: the host meter was the estimator (115.6 J over 2.89 s, Estimator, SocTotal), the in-process meter process-cpu (2.397 J over 2.84 s, HwShunt, ProcessCpu) for the same one-thread spin. - jouledesk-github stays on `detect_meter`: its model runs in a `llama-completion` subprocess, which a per-process counter would bill nothing. Its docs say so, and a test pins the meter to the host meter. - l3-jouleclaw's `run` binary stays on the host counter, and says why: `llama` is a subprocess, and the in-process `jouleclaw-runtime` engine boots the Apple backend's GPU kernels (Metal and MPS matmuls, the quantized GEMVs that serve decode), whose energy is the GPU's. - jouleclaw-loader-gguf is unchanged: its metered paths (`tune_shape_live`, `fabric_calibrate`, `mpp_energy`) compare or calibrate GPU against CPU members, so they need the whole SoC, not one process's CPU. Ran: `cargo test -p jouleclaw-harness-econ`, `cargo check` of its examples, `cargo test -p jouledesk-github` (13 passed), and `cargo test` in l3-jouleclaw. No model was loaded; the examples' model runs were not repeated. Co-Authored-By: Claude Opus 5.5 <[email protected]> |
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| .. | ||
| bin | ||
| hybrid_backend.rs | ||
| lib.rs | ||
| llama_backend.rs | ||
| runtime_backend.rs | ||