feat: checkpoint batching and release-gate stories

2026-07-16 17:24:36 +03:00
parent 737bade989
commit 02b3709311
18 changed files with 4580 additions and 1 deletions
--- a/.scratch/distributed-gguf-runtime/evidence/DGR-012/generate_evidence.py
+++ b/.scratch/distributed-gguf-runtime/evidence/DGR-012/generate_evidence.py
@@ -0,0 +1,117 @@
+"""Regenerate the DGR-012 concurrency-sweep evidence artifact.
+
+Deterministic, download-free, GPU-free. Run from the repo root with the default
+venv so the worktree ``meshnet_node`` package and the DGR-007 numpy reference
+(``tests/test_hot_kv_state``) are importable:
+
+    python .scratch/distributed-gguf-runtime/evidence/DGR-012/generate_evidence.py
+
+Writes ``results.json`` beside this script.
+"""
+
+from __future__ import annotations
+
+import json
+import pathlib
+import sys
+
+_ROOT = pathlib.Path(__file__).resolve().parents[4]
+sys.path.insert(0, str(_ROOT / "packages" / "node"))
+sys.path.insert(0, str(_ROOT / "tests"))
+
+from test_hot_kv_state import _KvDenseLlama, _KvReferenceShard  # noqa: E402
+
+from meshnet_node.batch_scheduler import (  # noqa: E402
+    ContinuousBatchScheduler,
+    GenerationRequest,
+    KvBatchEngine,
+    NodeBudget,
+    run_concurrency_sweep,
+)
+from meshnet_node.hot_kv_state import (  # noqa: E402
+    HotKvStateManager,
+    KvBoundaryAdapter,
+    kv_recipe_for,
+)
+
+MODEL = _KvDenseLlama()
+
+
+def make_engine() -> KvBatchEngine:
+    shard = _KvReferenceShard(MODEL, 0, MODEL.n_layers - 1)
+    manager = HotKvStateManager(kv_recipe_for(shard))
+    return KvBatchEngine(KvBoundaryAdapter(shard, manager))
+
+
+def main() -> int:
+    prompts = {
+        "s0": [1, 2, 3, 4], "s1": [5, 6, 7, 8], "s2": [9, 10, 11, 12],
+        "s3": [13, 14, 15, 16], "s4": [17, 18, 19, 20], "s5": [21, 22, 23, 24],
+        "s6": [25, 26, 27, 28], "s7": [29, 30, 31, 32],
+    }
+    n_new = 8
+    requests = [
+        GenerationRequest(sid, 0, tuple(p), n_new) for sid, p in prompts.items()
+    ]
+    sweep = run_concurrency_sweep(
+        make_engine, requests, concurrency_levels=(1, 2, 4, 8)
+    )
+
+    # A representative telemetry snapshot mid-run at concurrency 4 (shows the live
+    # capability signals a node advertises upward).
+    engine = make_engine()
+    scheduler = ContinuousBatchScheduler(
+        engine,
+        NodeBudget(
+            max_active_sessions=4, max_batch_size=4, max_queue_depth=8,
+            scratch_bytes_per_session=1, scratch_budget_bytes=4,
+        ),
+    )
+    for request in requests:
+        scheduler.submit(request)
+    for _ in range(6):
+        scheduler.run_tick()
+    mid_run_telemetry = scheduler.telemetry().to_dict()
+
+    artifact = {
+        "schema_version": 1,
+        "evidence_kind": "synthetic-unit",
+        "model": {
+            "reference": "pure-numpy KV-cached dense-Llama (tests/test_hot_kv_state)",
+            "n_layers": MODEL.n_layers,
+            "hidden": MODEL.hidden,
+            "n_heads": MODEL.n_heads,
+            "vocab": MODEL.vocab,
+        },
+        "workload": {
+            "sessions": len(prompts),
+            "prompt_len": 4,
+            "max_new_tokens": n_new,
+        },
+        "concurrency_sweep": sweep.to_dict(),
+        "mid_run_telemetry_concurrency_4": mid_run_telemetry,
+    }
+
+    out = pathlib.Path(__file__).with_name("results.json")
+    out.write_text(json.dumps(artifact, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+    print(f"wrote {out}")
+    print(
+        "saturation_concurrency=%d corruption_free=%s"
+        % (sweep.saturation_concurrency, sweep.corruption_free)
+    )
+    for result in sweep.results:
+        print(
+            "  c=%d ticks=%d avg_occ=%.3f tokens/tick=%.3f peak_kv=%dB"
+            % (
+                result.concurrency,
+                result.ticks,
+                result.avg_batch_occupancy,
+                result.tokens_per_tick,
+                result.peak_kv_bytes,
+            )
+        )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())