Sweeping a knob the driver ignores measures nothing but benchmark noise, and the
tuner would then confidently report 'best = the highest value tried'. On this box
(driver 595.84) nvidia-settings accepts GPUGraphicsClockOffset/GPUMemoryTransferRate
Offset and silently discards them: assigning 0 reports success and reads back 250.
The ollama profile's core_offset_mhz=35 and mem_offset_mhz=200 have therefore been
doing nothing.
- _knob_effective() applies a probe value and confirms the hardware actually moved
before any sweep starts, choosing the candidate furthest from the current reading
(probing with the maximum fails when the card already sits at its top clock).
- Adds discrete clock-lock knobs (lock_mem_mhz, lock_core_max) driven by the card's
own supported-clock list, since -lmc/-lgc do work where offsets do not.
- Reasoning models return their output in 'thinking' with an empty 'response', which
the degeneracy check was flagging as corruption. Token count is now the primary
signal.
- Separates gain-vs-current-setting from gain-vs-slowest-value-tried. Reporting the
latter as 'gain vs baseline' implied a +102% speedup that nobody would observe.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Nine changes, in rough order of how much they affect real behaviour:
1. VRAM yield is now a barrier. Posting keep_alive:0 only asks Ollama to unload;
measured here, the HTTP call returns in 63ms while the driver takes a further
77ms to release 14.9GB. Returning inside that window is how ComfyUI ends up
allocating into VRAM that is still occupied. instant_free_ollama_vram() polls
NVML until the allocation is actually gone and reports request/confirm split.
2. ComfyUI VRAM is no longer purged 1.5s after every prompt, which forced a full
checkpoint reload on each workflow iteration. It is held for 30s of genuinely
empty queue, with an immediate purge when Ollama actually asks for the memory.
3. Cache-hit classification uses achieved bandwidth (size / load duration) rather
than a fixed `load_duration < 2500ms`. That constant called a 12.9GB model read
at 2.9GB/s a cold load, and a 0.5GB model read from NVMe a cache hit.
4. Page-cache residency is measured, not assumed. mincore(2) reported 128GB
resident on a box with 46GB of page cache: the kernel only permits page-cache
introspection on files you own, and the Ollama blobs are owned by uid ollama,
for which mincore answers "all resident" instead of failing. Uses cachestat(2)
where permitted and a randomised read-rate probe elsewhere, labelling which was
used. Fixed-offset probing was self-fulfilling, so windows are random and cold
ones are returned with FADV_DONTNEED.
5. Warming is budgeted and ranked by recency/frequency instead of reading every
file top-to-bottom, which on 64GB of RAM just evicts whatever was warmed first.
6. Telemetry and events persist to SQLite (~0.38 MB/hour) instead of living in a
50-entry in-memory deque, so /api/analytics/profiles can finally answer whether
an overclock profile actually delivers more tok/s.
7. Thermal governor walks the overclock back on sustained heat or hardware
throttling, with hysteresis, fed from the existing sampler.
8. Autotune sweeps a clock offset, benchmarks decode at each step, watches for Xid
errors and degenerate output, and restores the profile in a finally block.
9. Stock clocks/power/fans are restored on shutdown and via systemd ExecStopPost.
Nothing previously undid a locked clock or a manually pinned fan.
Also: one shared 1Hz telemetry sampler fanned out to SSE subscribers rather than
every client re-running the whole snapshot; wall-clock timestamps in place of the
event loop's monotonic clock; cached nvidia-smi shell-outs; quieter httpx logging.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
