scheduler.Evicting wraps the Locked scheduler with the design's
LRU-with-coexistence eviction loop. main.go switches to it.
Per-job flow:
1. ensureFits — compare cons.vram_resident_mib + 256 MiB cushion against
the live nvidia-smi free reading. If insufficient, pick the LRU
loaded consumer NOT in cons.can_coexist_with, NOT VRAM-managed
(ollama is excluded from eviction by design — it runs its own LRU),
and NOT the target itself, then call its unload route. Wait 1s for
VRAM to actually free. Repeat up to 5 times.
2. ensureLoaded — if the target was previously unloaded, call its
/api/admin/load (mvoice). Consumers without a load route are
assumed to cold-start implicitly on first request.
3. inner.Run — global GPU lock + job execution.
State:
- scheduler-local 'loaded' map + scheduler-local 'lastUsed' map. The
registry's health-derived Loaded field is the source of truth for
consumers that report it, but we need our own state for the seconds
between an unload call and the next probe.
- Stats.Evictions counts successful unload calls and surfaces through
/v1/status.
LRU pick order:
- Scheduler-local lastUsed (set on successful Run completion) takes
precedence over registry.LastUsed (set on health probes) because the
former reflects real GPU work, not health chatter. Zero-time
consumers (never used) lose first.
Tests:
- Already-resident target: no eviction calls.
- 13 GiB comfyui evicted to fit 2.8 GiB mvoice → 1 unload + 1 load,
Stats.Evictions = 1.
- Coexistent consumer (ollama, in mvoice.can_coexist_with) is never
picked even if it's the LRU candidate; the non-coexistent comfyui
is unloaded instead.
Race detector clean.
Refs: m/mGPUmanager#1 (Schritt 5).
Replaces the MVP Passthrough with scheduler.Locked: a capacity-1 channel
serialises every consumer's GPU work end-to-end. main.go switches to it.
Behavioural contract:
- Jobs that arrive while another job holds the GPU block on the channel
until the holder finishes. Context cancellation aborts the wait
cleanly (no leaked tokens, queue depth decremented).
- Stats track queue_depth, in_flight, total_jobs, last_wait_ms,
last_run_ms, oldest_queued — surfaced through /v1/status.
- One lock for ALL consumers (not per-consumer): the design (§4.3) is
explicit that grobgranular > GPU-stream-granular on single-GPU
single-user hardware. mvoice + ollama + comfyui never run truly
concurrently any more, which is the whole point — that's what
produced the CUDA-OOM under load.
Tests:
- 5 goroutines hammer the scheduler concurrently → max in-flight = 1.
- Cancellation while parked on the lock returns ctx.Err() and frees
the queue slot.
- Stats reflect in-flight + queue-depth transitions correctly.
- Race detector clean.
Schritt 5 will compose this with VRAM-pressure eviction: before
acquiring the lock, check if the target consumer's resident cost fits
under the current GPU headroom; if not, unload the LRU non-coexistent
consumer first.
Refs: m/mGPUmanager#1 (Schritt 4).
Go daemon listening on :8770 that fronts mvoice (8766), whisper-server
(8178), ollama (11434), comfyui (8188) behind a single /v1 façade.
What this MVP does:
- Loads config/consumers.yaml: routing table, per-consumer URL + health +
paths + vram_resident_mib + can_coexist_with + load/unload routes.
- Background health probe (5s) on every consumer; refuses fast with a
structured 503 if the last probe failed (no Felix-Banholzer-style
silent fallback).
- POST /v1/{tts,stt,llm,image} proxies the request body + Content-Type
to the routed consumer's path and streams the response back.
- GET /audio/* proxies to audio_proxy consumer (wa.sh fetches its WAV
this way).
- GET /v1/status exposes live GPU sample (nvidia-smi every 2s),
per-consumer health/loaded/gpu_resident_mib/active/total_requests,
scheduler stats.
- GET /healthz, GET / — broker liveness.
The Scheduler interface is in place but the implementation is
'Passthrough' — every job runs immediately, no lock, no queue. Schritt 4
replaces it with a serialising mutex; Schritt 5 adds VRAM-pressure
eviction. The interface boundary means server.go stays unchanged.
Out of scope here:
- Schritt 3: wa.sh migration (parallel work in mAi).
- Schritt 4: queue + global GPU lock.
- Schritt 5: nvidia-smi-driven LRU eviction.
Tests: config validation (good/bad), proxy forwards body, audio proxy
streams bytes, unhealthy consumer returns 503, /v1/status JSON shape.
Refs: m/mGPUmanager#1
