From 3e16c33da45580730444e414bbee54bb830a2604 Mon Sep 17 00:00:00 2001
From: gspark <gspark@etri.re.kr>
Date: Sat, 24 Oct 2026 02:46:28 +0900
Subject: [PATCH 1/5] feat: prefill one queued request during B1 ATOM decode
 (#253)

---
 opt_prime/examples/pd/http_matrix/STATUS.md   |  4 +
 .../evidence253/atom253-cli-red.log           | 38 +++++++++
 .../evidence253/atom253-focused.log           |  2 +
 .../http_matrix/evidence253/atom253-full.log  | 21 +++++
 .../atom253-pipeline-hypothesis.json          | 26 +++++++
 .../http_matrix/evidence253/atom253-red.log   | 38 +++++++++
 .../pd/http_matrix/evidence253/events.jsonl   |  2 +
 .../2026-10-24-atom-prefetch253.md            | 53 +++++++++++++
 opt_prime/examples/pd/serve_batched.py        |  8 +-
 .../accel/platforms/atom/batching.py          | 44 ++++++++++-
 opt_prime/tests/test_atom_batching.py         | 77 +++++++++++++++++++
 opt_prime/tests/test_serving_prefill_cache.py | 15 ++++
 12 files changed, 323 insertions(+), 5 deletions(-)
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-cli-red.log
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-focused.log
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-full.log
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-pipeline-hypothesis.json
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-red.log
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/events.jsonl
 create mode 100644 opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md

diff --git a/opt_prime/examples/pd/http_matrix/STATUS.md b/opt_prime/examples/pd/http_matrix/STATUS.md
index ce8ca12f..fdfd45f7 100644
--- a/opt_prime/examples/pd/http_matrix/STATUS.md
+++ b/opt_prime/examples/pd/http_matrix/STATUS.md
@@ -37,3 +37,7 @@ A real terminated subprocess producer previously left /ready200 and new requests
 ## Batched producer timing (#249)
 
 Candidate exports airm_pd_producer_seconds_total{stage="prefill"|"transfer"} from existing accumulated batcher durations. Repeated scrapes do not add observations; missing timing keys are omitted. Tiny real-model admission test covers fixed worker-reported durations and legacy omissions. These counters are worker-reported admitted-handoff sums, not request latency or proof of zero cost for workers that do not measure stages. Full CPU suite:467passed,17skipped,135subtests,1existing warning. See pd-stage-metrics249 experiment.
+
+## B1 next-request prefill (#253), 2026-10-24
+
+Opt-in remote_prefetch / --pd-prefetch-next implemented for single-lane ATOM remote-only PD. Keep one source result reserved through owner import; cancelled writers drain before reuse. Prefix/host cache admission remains late, so early prefill transfers the full prompt.35focused tests and full511passed34skipped253subtests; real four-model hardware pipeline/performance validation pending. No speedup claim. See experiments/2026-10-24-atom-prefetch253.md.
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-cli-red.log b/opt_prime/examples/pd/http_matrix/evidence253/atom253-cli-red.log
new file mode 100644
index 00000000..318622e9
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-cli-red.log
@@ -0,0 +1,38 @@
+F
+=================================== FAILURES ===================================
+__ test_next_prefill_rejects_unsupported_route_before_load[torch-1-True-True] __
+
+monkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x75d4cb85d2d0>
+backend = 'torch', slots = 1, remote = True, worker = True
+
+    @pytest.mark.parametrize('backend,slots,remote,worker', [('torch',1,True,True),('atom',2,True,True),
+                                                            ('atom',1,False,True),('atom',1,True,False)])
+    def test_next_prefill_rejects_unsupported_route_before_load(monkeypatch,backend,slots,remote,worker):
+        path=Path(__file__).parents[1]/'examples/pd/serve_batched.py'
+        spec=importlib.util.spec_from_file_location('serve_prefetch_test',path)
+        factory=importlib.util.module_from_spec(spec);spec.loader.exec_module(factory)
+        args=SimpleNamespace(model='must-not-load',backend=backend,slots=slots,pd_prefetch_next=True,
+                             pd_remote_only=remote,pd_prefill_python='python' if worker else None,pd_prefill_device=None)
+        def unexpected_load(*args,**kwargs):
+            pytest.fail('unsupported prefetch route reached model loading')
+        monkeypatch.setattr(factory.AutoTokenizer,'from_pretrained',unexpected_load)
+        with pytest.raises(ValueError,match='single-lane'):
+>           factory.build(args)
+
+opt_prime/tests/test_serving_prefill_cache.py:89:
+_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
+opt_prime/examples/pd/serve_batched.py:69: in build
+    tok = AutoTokenizer.from_pretrained(a.model)
+_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
+
+args = ('must-not-load',), kwargs = {}
+
+    def unexpected_load(*args,**kwargs):
+>       pytest.fail('unsupported prefetch route reached model loading')
+E       Failed: unsupported prefetch route reached model loading
+
+opt_prime/tests/test_serving_prefill_cache.py:86: Failed
+=========================== short test summary info ============================
+FAILED opt_prime/tests/test_serving_prefill_cache.py::test_next_prefill_rejects_unsupported_route_before_load[torch-1-True-True]
+!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!
+1 failed, 4 deselected in 2.58s
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-focused.log b/opt_prime/examples/pd/http_matrix/evidence253/atom253-focused.log
new file mode 100644
index 00000000..c85ad178
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-focused.log
@@ -0,0 +1,2 @@
+...................................                                      [100%]
+35 passed in 4.39s
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-full.log b/opt_prime/examples/pd/http_matrix/evidence253/atom253-full.log
new file mode 100644
index 00000000..a5356909
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-full.log
@@ -0,0 +1,21 @@
+.sssssss.....................ssssssssss........................................................... [ 18%]
+s.............................................................s.s....... [ 31%]
+..........ss.....................ss....s................................ [ 44%]
+........................................................................ [ 57%]
+..........s.s...........................................s............... [ 71%]
+.....................................................................s.s...............................................................................s. [ 99%]
+...                                                                      [100%]
+=============================== warnings summary ===============================
+tests/test_kvstore.py::test_second_engine_reuses_chunks_from_the_store[lmcache]
+  /home/gspark/venvs/pt213/lib/python3.10/site-packages/torch/nn/attention/flex_attention.py:2481: UserWarning: flex_attention called without torch.compile() - this will use an unfused implementation that materializes the full scores matrix instead of generating a fused kernel.
+
+  SOLUTION: Use torch.compile(flex_attention)(...)
+
+  If you want to debug your score_mod/mask_mod, you can set:
+  torch.nn.attention.flex_attention._FLEX_ATTENTION_DISABLE_COMPILE_DEBUG = True
+
+  This will allow you to use print statements or breakpoints. Note: This doesn't work with the backwards pass and may produce incorrect results.
+    _warn_once(
+
+-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
+511 passed, 34 skipped, 1 warning, 253 subtests passed in 150.28s (0:02:30)
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-pipeline-hypothesis.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-pipeline-hypothesis.json
new file mode 100644
index 00000000..6bee03e0
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-pipeline-hypothesis.json
@@ -0,0 +1,26 @@
+{
+  "warning": "Heuristic only: first SSE includes queueing and KV import, not a pure producer stage. Assumes perfect overlap of first-SSE and remaining decode, ignores import contention and shared resources. Not a throughput prediction or hardware result.",
+  "rows": [
+    {
+      "model": "qwen06b",
+      "first_sse_s": 2.6405895240604877,
+      "e2e_s": 2.9849001180846244,
+      "post_first_sse_s": 0.34431059402413666,
+      "optimistic_pipeline_ratio": 1.1303915625230094
+    },
+    {
+      "model": "qwen4b",
+      "first_sse_s": 4.540284454007633,
+      "e2e_s": 5.850550717907026,
+      "post_first_sse_s": 1.3102662638993934,
+      "optimistic_pipeline_ratio": 1.288586822515678
+    },
+    {
+      "model": "koni",
+      "first_sse_s": 4.553356555989012,
+      "e2e_s": 6.776184441987425,
+      "post_first_sse_s": 2.222827885998413,
+      "optimistic_pipeline_ratio": 1.4881734734950058
+    }
+  ]
+}
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-red.log b/opt_prime/examples/pd/http_matrix/evidence253/atom253-red.log
new file mode 100644
index 00000000..34a6aa29
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-red.log
@@ -0,0 +1,38 @@
+F
+=================================== FAILURES ===================================
+_ test_b1_prefetch_overlaps_decode_and_holds_source_until_import[False-success] _
+
+fake_rebel = {'model': <test_atom_batching.FakeBlocks object at 0x77747516d4e0>}
+outcome = 'success', cache = False
+
+    @pytest.mark.parametrize('outcome', ['success', 'cancel', 'error'])
+    @pytest.mark.parametrize('cache', [False, True])
+    def test_b1_prefetch_overlaps_decode_and_holds_source_until_import(fake_rebel, outcome, cache):
+        """A reserved prefill must neither wait for the decode lane nor reuse a still-written source slot."""
+        import copy
+        from concurrent.futures import Future
+        from opt_prime.accel.pd.pd_batching import TorchPrefillEngine
+
+        class ControlledProducer:
+            def __init__(self):
+                self.calls = []
+
+            def submit(self, request, send_from=0, slot=None):
+                assert send_from == slot == 0
+                future = Future()
+                self.calls.append((request, future))
+                return future
+
+        model = _llama()
+        fake = _blocks_model(fake_rebel, model, batch=1, blocks=3 if cache else 1)
+        producer = ControlledProducer()
+        engine = TorchPrefillEngine(copy.deepcopy(model), max_context=128, chunk=16, page_size=16)
+>       b = AtomBatcher(fake, prefix_cache=cache, host_kv_gib=1.0 if cache else 0,
+                        prefill_worker=producer, local_prefill=False, remote_prefetch=True)
+E       TypeError: AtomBatcher.__init__() got an unexpected keyword argument 'remote_prefetch'
+
+opt_prime/tests/test_atom_batching.py:461: TypeError
+=========================== short test summary info ============================
+FAILED opt_prime/tests/test_atom_batching.py::test_b1_prefetch_overlaps_decode_and_holds_source_until_import[False-success]
+!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!
+1 failed, 21 deselected in 2.74s
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/events.jsonl b/opt_prime/examples/pd/http_matrix/evidence253/events.jsonl
new file mode 100644
index 00000000..c632df6c
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/events.jsonl
@@ -0,0 +1,2 @@
+{"id": "ebfa7b30c08f4fe0af8effefe012382b", "ts": "2026-10-24T02:30:43+09:00", "task": "B1 ATOM prefetch (aicomp #253)", "result": "Prepared6regressions in own worktree;not run yet, no production changes. Source design uses one retained shared-slot reservation after current KV import, with cancellation writer lifetime preserved.", "next": "After quiet GPU measurement window, run RED and implement bounded next-request prefill; real four-model validation", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-pipeline-hypothesis.json", "size": 912, "sha256": "cdfbe1aa8d44b972"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["analysis"], "review": false, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
+{"id": "e4869f8d099b4b33aafcafe632019406", "ts": "2026-10-24T02:46:11+09:00", "task": "B1 ATOM prefetch (aicomp #253)", "result": "Implemented opt-in next-request prefill with retained single-slot ownership;35 focused tests pass. Full suite511 passed34 skipped253 subtests in150.28s; cancellation/orphan drain and cache/failure reuse covered. Hardware validation pending.", "next": "Publish draft, then paired real RNGD-ATOM four-model pipeline tests with worker kept warm", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-full.log", "size": 1619, "sha256": "31a4984744eead95"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["experiment"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
diff --git a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
new file mode 100644
index 00000000..a541a6f0
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
@@ -0,0 +1,53 @@
+# B1 ATOM next-request prefill pipeline hypothesis (#253)
+
+- **Date**: 2026-10-24
+- **Task**: B1 ATOM prefetch (aicomp #253)
+- **Host / device**: Analysis of existing RNGD+ATOM host data; no new hardware run
+- **Commit**: aicomp273952a; own worktree perf/253-atom-prefetch; implementation and regression tests added after RED
+
+## Question
+
+Can a bounded next-request prefill overlap current B1 decode without reusing a still-written shared source buffer?
+
+## Setup
+
+Source inspection: AtomBatcher._pd_step submits only while a decode lane is free. A B1 next-request reservation can reuse the existing single shared slot after the current request has been imported; an extra slab is not inherently required. Hold the reservation until import or acknowledged producer completion after cancellation. Admit decoder blocks only on the owner thread after the lane is free. Early prefill uses send_from=0 because the final cache state is not yet known; prefix hits can still be used during late admission but full transfer is required. Keep opt-in and remote-only for the first B1 implementation.
+
+## Command
+
+```bash
+# RED first, then focused and full CPU validation after the GPU queue completed:
+cd /home/gspark/workspace/aicomp-atom-prefetch-253
+CUDA_VISIBLE_DEVICES='' PYTHONPATH=opt_prime /home/gspark/venvs/pt213/bin/python -m pytest opt_prime/tests/test_atom_batching.py -k b1_prefetch -xq
+```
+
+## Results
+
+| config | metric | value | vs. baseline |
+|---|---|---:|---:|
+| scheduler regressions | RED | missing remote_prefetch option | reproduced before implementation |
+| focused AtomBatcher + public factory tests | tests | 35 passed, 4.39s | CPU fake SDK with real tiny LM/KV |
+| full opt_prime suite | tests | 511 passed,34 skipped,253 subtests,150.28s | one existing flex-attention warning |
+| Qwen0.6B | first SSE / rest | 2.641s / 0.344s | heuristic pipeline ratio1.13 |
+| Qwen4B | first SSE / rest | 4.540s / 1.310s | heuristic pipeline ratio1.29 |
+| KONI8B | first SSE / rest | 4.553s / 2.223s | heuristic pipeline ratio1.49 |
+
+Analysis: analysis/serving-matrix-201/atom253-pipeline-hypothesis.json, derived from existing #248 c1/input8192/output32 medians.
+
+## Conclusion
+
+The opt-in implementation and tests check second prefill starts during first decode, exact real-model outputs, reservation bound, cancellation without falsely releasing the writer, producer failure, and safe subsequent request reuse. Heuristic ratios assume perfect overlap and ignore import/resource contention; first SSE is not a pure producer stage, so these are not throughput predictions. Even ideal request pipelining is unlikely to close the Qwen0.6B measured gap by itself. Larger models offer more decode work to overlap. RED was observed before production changes. Real four-model RNGD-to-ATOM validation remains pending.
+
+## Implemented behavior and verification
+
+`AtomBatcher(remote_prefetch=True)` / `serve_batched.py --pd-prefetch-next` is opt-in, single-lane ATOM and remote-only. One queued request may start on the existing source slot while the current request decodes. Decoder cache admission/import remains owner-controlled. The prefetched result stays reserved until import; cancelling a client does not cancel its producer future or falsely release a still-written slot. The owner keeps draining an orphaned producer even when all clients have left. Unsupported routes are rejected before model loading. Default behavior is unchanged. No transport protocol changes or extra slab slot are required.
+
+Commands after RED:
+```bash
+cd /home/gspark/workspace/aicomp-atom-prefetch-253
+CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=2 MKL_NUM_THREADS=2 PYTHONPATH=opt_prime /home/gspark/venvs/pt213/bin/python -m pytest opt_prime/tests/test_atom_batching.py opt_prime/tests/test_serving_prefill_cache.py -q
+cd opt_prime
+CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=2 MKL_NUM_THREADS=2 PYTHONPATH=. /home/gspark/venvs/pt213/bin/python -m pytest -q
+```
+
+The full run includes the added cancellation assertion that an orphaned producer keeps the batcher non-idle, followed by safe request-ID and source-slot reuse. Tests use a controlled future boundary to expose ordering, real TorchPrefillEngine KV, a fake Rebellions SDK import, and independent greedy outputs. Hardware throughput and a real producer/decode timeline remain unmeasured; no speedup claim. Logs: atom253-{red,cli-red,focused,full}.log in analysis/serving-matrix-201.
diff --git a/opt_prime/examples/pd/serve_batched.py b/opt_prime/examples/pd/serve_batched.py
index 5f3f38cf..e3d2b926 100644
--- a/opt_prime/examples/pd/serve_batched.py
+++ b/opt_prime/examples/pd/serve_batched.py
@@ -66,6 +66,10 @@ def remote_tier(a, model):
 
 
 def build(a):
+    prefetch = getattr(a, "pd_prefetch_next", False)
+    if prefetch and (a.backend != "atom" or a.slots != 1 or not a.pd_remote_only or
+                     not (a.pd_prefill_device or a.pd_prefill_python)):
+        raise ValueError("next prefill requires single-lane ATOM remote-only PD")
     tok = AutoTokenizer.from_pretrained(a.model)
     events = None
     if a.kv_events:
@@ -87,7 +91,7 @@ def build(a):
         engine.start(a.model)
         b, model = engine.batcher(prefix_cache=a.prefix_cache, host_kv_gib=a.kv_host_memory_gb, kv_events=events,
                                   prefill_worker=prefill_worker(a, a.slots, engine.model.config),
-                                  local_prefill=not a.pd_remote_only), engine.model
+                                  local_prefill=not a.pd_remote_only, remote_prefetch=prefetch), engine.model
     else:
         model = AutoModelForCausalLM.from_pretrained(a.model, dtype=getattr(torch, a.dtype)).to(a.device).eval()
         kw = dict(slots=a.slots, max_context=a.max_context, kv=a.kv, page_size=a.page_size,
@@ -132,6 +136,8 @@ def build(a):
     ap.add_argument("--pd-prefill-pythonpath", default=None)
     ap.add_argument("--pd-remote-only", action="store_true",
                     help="PD on ATOM: every prompt is prefilled by the PD prefill side (no cost routing to ATOM)")
+    ap.add_argument("--pd-prefetch-next", action="store_true",
+                    help="B1 ATOM remote-only PD: prefill one queued prompt while the current request decodes")
     ap.add_argument("--remote-kv", default=None, help="JSON with Mooncake store setup arguments (shared KV, #128)")
     ap.add_argument("--remote-kv-keys", default="lmcache", choices=["lmcache", "optimus"])
     ap.add_argument("--remote-kv-model", default=None, help="model name in the keys (the vLLM/LMCache side's name)")
diff --git a/opt_prime/opt_prime/accel/platforms/atom/batching.py b/opt_prime/opt_prime/accel/platforms/atom/batching.py
index 1fa67d0b..53c1815d 100644
--- a/opt_prime/opt_prime/accel/platforms/atom/batching.py
+++ b/opt_prime/opt_prime/accel/platforms/atom/batching.py
@@ -288,7 +288,7 @@ class AtomBatcher(ContinuousBatcher):
     supports_sampling = True          # the decode graph returns logits; sampling runs on the host
 
     def __init__(self, model, *, pad_token_id=None, prefix_cache=False, host_kv_gib=0.0, kv_events=None,
-                 prefill_worker=None, remote_inflight=None, local_prefill=True):
+                 prefill_worker=None, remote_inflight=None, local_prefill=True, remote_prefetch=False):
         """prefix_cache / host_kv_gib need a model compiled with kv_blocks > batch_size (own block tables;
         prefix_cache needs kv_blocks >= batch_size + 2).
         prefill_worker (PD, #120): prompts are prefilled elsewhere (`pd.pd_batching.PrefillWorker` and engines) and their
@@ -298,12 +298,17 @@ def __init__(self, model, *, pad_token_id=None, prefix_cache=False, host_kv_gib=
         (in-flight remote prefills + 1) x remote time per prompt (prefill + KV import) against local (prompts
         queued here + 1) x ATOM prefill time; local prefills run one per iteration, as in aggregated serving. A
         slow prefill device is therefore used only for overflow, and a fast one takes most prompts.
-        local_prefill=False keeps every prefill remote (decode never stalls on a prompt; TPOT first)."""
+        local_prefill=False keeps every prefill remote (decode never stalls on a prompt; TPOT first).
+        remote_prefetch=True (B1 remote-only): keep one full-prompt result ahead of decode. Cache admission still
+        happens on the owner after the lane is free; early prefills cannot omit a cached prefix from transfer."""
         rc = model.rbln_config
         self.hybrid_cache = getattr(rc, "cache_impl", None) == "hybrid"
         if self.hybrid_cache and (prefix_cache or host_kv_gib):
             raise ValueError("hybrid sliding cache restoration is not implemented for prefix/host cache")
         self.lanes = rc.batch_size
+        if remote_prefetch and (self.lanes != 1 or prefill_worker is None or local_prefill):
+            raise ValueError("remote_prefetch requires single-lane remote-only PD")
+        self.remote_prefetch, self._prefetched = remote_prefetch, None
         decoders = getattr(model, "decoders", None) or {}
         if self.lanes not in decoders:
             raise ValueError(f"no compiled decode graph for batch {self.lanes} (have {sorted(decoders)})")
@@ -343,6 +348,10 @@ def __init__(self, model, *, pad_token_id=None, prefix_cache=False, host_kv_gib=
                 for lane in range(self.lanes):         # every lane owns a page before the B-lane graph runs
                     self._prefill(lane, [self.pad])
 
+    @property
+    def idle(self):
+        return super().idle and self._prefetched is None
+
     @property
     def hit_tokens(self):
         return self.blocks.hit_tokens if self.blocks else 0
@@ -432,6 +441,8 @@ def _decode_step(self):
         self._decoded(rows, [self.kv.length[r.slot] for r in rows], logits)
 
     def _finish(self, r, error):
+        if self._prefetched is r and (r.pending is None or r.pending.done()):
+            self._prefetched = None
         if self.blocks is not None and r.slot >= 0:
             self.blocks.release(r.slot, r.request.input_ids if getattr(r, "admitted", False) else None)
         super()._finish(r, error)
@@ -440,10 +451,14 @@ def _finish(self, r, error):
     def _pd_step(self):
         from concurrent.futures import FIRST_COMPLETED, wait
         with self._lock:
+            if self._prefetched is not None and self._prefetched.future.done() and self._prefetched.pending.done():
+                self._prefetched = None                     # cancelled writer has now relinquished the source slot
             admitted, local = [], None
             remote = sum(1 for r in self.prefilling if r.pending is not None)
             queued = 0                                 # prompts that will be prefilled here before this one
             while self.free and self.waiting:
+                if self._prefetched is not None and self.waiting[0] is not self._prefetched:
+                    break                                  # a cancelled producer still owns its source buffer
                 go_remote = remote < self.remote_inflight or not self.local_prefill
                 if not self.local_prefill:
                     pass
@@ -468,14 +483,17 @@ def _pd_step(self):
             for r in admitted:                       # decode-side prefix (device copy / host reload) is not sent
                 start = self.blocks.admit(r.slot, r.request.input_ids)
                 r.admitted = True
-                r.pending = self.worker.submit(r.request, send_from=start, slot=r.slot)
-                self.stats_pd["remote"] += 1
+                if r.pending is None:
+                    r.pending = self.worker.submit(r.request, send_from=start, slot=r.slot)
+                    self.stats_pd["remote"] += 1
             if local is not None:
                 self.stats_pd["local"] += 1
                 t0 = time.perf_counter()
                 self._prefill_request(local)
                 self._local_s = _ema(self._local_s, time.perf_counter() - t0)
             pending = [r for r in self.prefilling if r.pending is not None]
+            if self._prefetched is not None and self._prefetched.future.done():
+                pending.append(self._prefetched)              # wait for a cancelled writer without busy-spinning
             if pending and not self.decoding:
                 wait([r.pending for r in pending], timeout=0.05, return_when=FIRST_COMPLETED)
             for r in pending:
@@ -503,6 +521,8 @@ def _pd_step(self):
                     with self._lock:
                         self._finish(r, error)
                     continue
+                if self._prefetched is r:
+                    self._prefetched = None                 # only release after the owner has imported the KV
                 if self.hybrid_cache:
                     self.decoder.dec_attn_mask[r.slot].zero_()
                     self.decoder.dec_attn_mask[r.slot, :len(ids)] = 1
@@ -515,6 +535,8 @@ def _pd_step(self):
                     self.decoding.append(r)
             if self.decoding:
                 self._decode_step()
+            if self.remote_prefetch:
+                self._prefetch_next()
         except BaseException:
             self.poisoned = True
             raise
@@ -522,3 +544,17 @@ def _pd_step(self):
             events = self.blocks.drain_events()
             if events:
                 self.kv_events.publish(events)
+
+    def _prefetch_next(self):
+        from concurrent.futures import Future
+        with self._lock:
+            if self._prefetched is not None or not self.decoding or not self.waiting:
+                return
+            r = self._prefetched = self.waiting[0]
+        try:
+            # Cache admission waits for the decode lane; reserve one full-prompt result in the existing source slot.
+            r.pending = self.worker.submit(r.request, send_from=0, slot=0)
+        except BaseException as error:
+            r.pending = Future()
+            r.pending.set_exception(error)
+        self.stats_pd["remote"] += 1
diff --git a/opt_prime/tests/test_atom_batching.py b/opt_prime/tests/test_atom_batching.py
index 2434a808..dd3523d0 100644
--- a/opt_prime/tests/test_atom_batching.py
+++ b/opt_prime/tests/test_atom_batching.py
@@ -434,3 +434,80 @@ def submit(self, request, send_from=0, slot=None):
     assert good.result() == _greedy(model,q,5)
     assert b.blocks.free == [0] and b.blocks.lane_block == [None]
     assert not b.by_id and not b.poisoned
+
+
+@pytest.mark.parametrize('outcome', ['success', 'cancel', 'error'])
+@pytest.mark.parametrize('cache', [False, True])
+def test_b1_prefetch_overlaps_decode_and_holds_source_until_import(fake_rebel, outcome, cache):
+    """A reserved prefill must neither wait for the decode lane nor reuse a still-written source slot."""
+    import copy
+    from concurrent.futures import Future
+    from opt_prime.accel.pd.pd_batching import TorchPrefillEngine
+
+    class ControlledProducer:
+        def __init__(self):
+            self.calls = []
+
+        def submit(self, request, send_from=0, slot=None):
+            assert send_from == slot == 0
+            future = Future()
+            self.calls.append((request, future))
+            return future
+
+    model = _llama()
+    fake = _blocks_model(fake_rebel, model, batch=1, blocks=3 if cache else 1)
+    producer = ControlledProducer()
+    engine = TorchPrefillEngine(copy.deepcopy(model), max_context=128, chunk=16, page_size=16)
+    b = AtomBatcher(fake, prefix_cache=cache, host_kv_gib=1.0 if cache else 0,
+                    prefill_worker=producer, local_prefill=False, remote_prefetch=True)
+    p, q = _prompts(2, 40, 41, seed=253)
+    first = b.submit(PDRequest('first', p, 8))
+    second = b.submit(PDRequest('second', p, 5))
+    third = b.submit(PDRequest('third', q, 5))
+    b.step()
+    request, pending = producer.calls[0]
+    pending.set_result(engine.prefill(request))
+    b.step()
+    assert not first.done() and b.decoding
+    assert len(producer.calls) == 2, 'next producer must start before the first decode finishes'
+    request, pending = producer.calls[1]
+    if outcome == 'success':
+        pending.set_result(engine.prefill(request))
+    elif outcome == 'error':
+        pending.set_exception(RuntimeError('producer failed'))
+    else:
+        assert b.cancel('second')
+        assert b.cancel('third')
+        b.step()
+        with pytest.raises(RequestCancelled):
+            second.result()
+        with pytest.raises(RequestCancelled):
+            third.result()
+        assert not pending.cancelled(), 'cancellation must not imply that the remote writer has stopped'
+    while not first.done():
+        assert len(producer.calls) == 2, 'one retained prefill must bound producer reservations'
+        b.step()
+    assert first.result() == _greedy(model, p, 8)
+    if outcome == 'cancel':
+        assert not b.idle, 'the owner must keep draining an orphaned producer after every client has left'
+        third = b.submit(PDRequest('third', q, 5))
+        b.step()
+        assert len(producer.calls) == 2, 'cancelled writer still owns its shared source slot'
+        pending.set_result(engine.prefill(request))
+    for _ in range(30):
+        b.step()
+        if len(producer.calls) == 3:
+            break
+    assert len(producer.calls) == 3
+    request, pending = producer.calls[2]
+    pending.set_result(engine.prefill(request))
+    b.run_until_idle()
+    if outcome == 'success':
+        assert second.result() == _greedy(model, p, 5)
+        if cache:
+            assert b.hit_tokens >= 32
+    elif outcome == 'error':
+        with pytest.raises(RuntimeError, match='producer failed'):
+            second.result()
+    assert third.result() == _greedy(model, q, 5)
+    assert b.free == [0] and not b.by_id and not b.poisoned
diff --git a/opt_prime/tests/test_serving_prefill_cache.py b/opt_prime/tests/test_serving_prefill_cache.py
index d2d4f8af..5e858acf 100644
--- a/opt_prime/tests/test_serving_prefill_cache.py
+++ b/opt_prime/tests/test_serving_prefill_cache.py
@@ -72,3 +72,18 @@ def observe(model, kv, slot, ids, start, end, device):
         args.pd_prefill_chunk = chunk
         with pytest.raises(ValueError, match="positive"):
             factory.prefill_worker(args, 1, model.config)
+
+
+@pytest.mark.parametrize('backend,slots,remote,worker', [('torch',1,True,True),('atom',2,True,True),
+                                                        ('atom',1,False,True),('atom',1,True,False)])
+def test_next_prefill_rejects_unsupported_route_before_load(monkeypatch,backend,slots,remote,worker):
+    path=Path(__file__).parents[1]/'examples/pd/serve_batched.py'
+    spec=importlib.util.spec_from_file_location('serve_prefetch_test',path)
+    factory=importlib.util.module_from_spec(spec);spec.loader.exec_module(factory)
+    args=SimpleNamespace(model='must-not-load',backend=backend,slots=slots,pd_prefetch_next=True,
+                         pd_remote_only=remote,pd_prefill_python='python' if worker else None,pd_prefill_device=None)
+    def unexpected_load(*args,**kwargs):
+        pytest.fail('unsupported prefetch route reached model loading')
+    monkeypatch.setattr(factory.AutoTokenizer,'from_pretrained',unexpected_load)
+    with pytest.raises(ValueError,match='single-lane'):
+        factory.build(args)

From a95e08f53f93f5048cd7e67a15588e23ebfb284f Mon Sep 17 00:00:00 2001
From: gspark <gspark@etri.re.kr>
Date: Sat, 24 Oct 2026 03:34:54 +0900
Subject: [PATCH 2/5] exp: verify KONI prefetch gains and live fault isolation
 (#253)

---
 .../pd/http_matrix/.research/events.jsonl     |      1 +
 opt_prime/examples/pd/http_matrix/STATUS.md   |      2 +
 .../examples/pd/http_matrix/atom_pipeline.py  |    251 +
 .../evidence253/atom253-koni-a.json           | 116840 +++++++++++++++
 .../evidence253/atom253-koni-a.producer.jsonl |    176 +
 .../evidence253/atom253-koni-summary.json     |    210 +
 .../pd/http_matrix/evidence253/llmd253.py     |    707 +
 .../evidence253/summarize_atom253.py          |     72 +
 .../pd/http_matrix/evidence253/worker253.py   |    160 +
 .../2026-10-24-atom-prefetch253.md            |     66 +
 10 files changed, 118485 insertions(+)
 create mode 100644 opt_prime/examples/pd/http_matrix/atom_pipeline.py
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-a.json
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-a.producer.jsonl
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-summary.json
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/llmd253.py
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/summarize_atom253.py
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/worker253.py

diff --git a/opt_prime/examples/pd/http_matrix/.research/events.jsonl b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
index 5f51c17b..cbab8434 100644
--- a/opt_prime/examples/pd/http_matrix/.research/events.jsonl
+++ b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
@@ -3,3 +3,4 @@
 {"id": "4c7935b757264687b1310fbe1ec6399a", "ts": "2026-10-23T21:26:38+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Production factory union of generation-config/tokenizer EOS fixes real KONI HTTP turn end: baseline length, fixed stop, ignore_eos length, streaming stop, reuse stop. Baseline factory3fail/3pass ->22related tests pass. Preserved failed initial SSE checker log.", "next": "Publish scoped serving fix; verify NPU HTTP and retain long RNGD semantic validation.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "KONI-8B", "backend": "gpu", "max_tokens": "8"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-http-final.json", "size": 5067, "sha256": "d5be9a4a52a6485f"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "e4993823527144b5a14e6441b1cd5c01", "ts": "2026-10-23T21:29:56+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Published production EOS fix and real KONI HTTP evidence in draft PR230 (e5fa087). Final factory/streaming/sampling/batched suite22passed; hardware checker5/5 cases passed; changed files sensitive-clean,4unchanged baseline findings in this branch.", "next": "Verify same HTTP factory on NPU; continue full four-model long semantic and heterogeneous PD validation.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "gpu"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-http-final.json", "size": 5067, "sha256": "d5be9a4a52a6485f"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "328b8349e9974a059ddc7e1a8a485e2c", "ts": "2026-10-23T21:32:23+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Real ATOM KONI HTTP also passes5/5 baseline/fixed/ignore/stream/reuse checks using same production factory: config-only length vs union stop. GPU+ATOM now10/10 expected outcomes; no SDK/artifact rebuild.", "next": "Update PR230 with NPU evidence; finish KONI medium-context RNGD handoff and broader PD work.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "atom", "kv_blocks": "1"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-atom-http.json", "size": 5199, "sha256": "4735255db379ff00"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
+{"id": "336aabdd36624e148ea41f974e84af8e", "ts": "2026-10-24T03:34:33+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "KONI complete: 48 batches exact, 8 fixed-output and 4 EOS groups passed; cancel/reuse and producer-exit preservation/503 gates passed. c4 median gains23.48-40.87%; c1 neutral. Qwen3-4B started.", "next": "Finish Qwen3-4B, Qwen3-0.6B and Gemma in current queue; publish KONI evidence to draft PR255", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "KONI-8B", "producer_width": "8192", "prefetch": "true"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-koni-summary.json", "size": 5612, "sha256": "b66019a0a29d1e3a"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark", "rngd"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
diff --git a/opt_prime/examples/pd/http_matrix/STATUS.md b/opt_prime/examples/pd/http_matrix/STATUS.md
index fdfd45f7..9f3ec9e4 100644
--- a/opt_prime/examples/pd/http_matrix/STATUS.md
+++ b/opt_prime/examples/pd/http_matrix/STATUS.md
@@ -41,3 +41,5 @@ Candidate exports airm_pd_producer_seconds_total{stage="prefill"|"transfer"} fro
 ## B1 next-request prefill (#253), 2026-10-24
 
 Opt-in remote_prefetch / --pd-prefetch-next implemented for single-lane ATOM remote-only PD. Keep one source result reserved through owner import; cancelled writers drain before reuse. Prefix/host cache admission remains late, so early prefill transfers the full prompt.35focused tests and full511passed34skipped253subtests; real four-model hardware pipeline/performance validation pending. No speedup claim. See experiments/2026-10-24-atom-prefetch253.md.
+
+KONI hardware prefetch validation complete:48timed batches exact,8fixed-output/4EOS groups pass, cancellation/reuse and producer-exit isolation/readiness503 pass. Same-warm-instance off/on3repeat c4 gains23.48–40.87%; c1 near-neutral. Host producer/decode overlap only in enabled mode. Remaining three models pending; no default promotion. See evidence253/atom253-koni-summary.json and experiment.
diff --git a/opt_prime/examples/pd/http_matrix/atom_pipeline.py b/opt_prime/examples/pd/http_matrix/atom_pipeline.py
new file mode 100644
index 00000000..b2697287
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/atom_pipeline.py
@@ -0,0 +1,251 @@
+"""Warm-engine HTTP A/B and lifecycle validation for B1 ATOM remote prefetch (#253).
+All configuration changes happen only between drained batches. No control endpoint is exposed.
+"""
+import argparse
+from concurrent.futures import ThreadPoolExecutor
+import importlib.util
+import json
+import os
+from pathlib import Path
+import socket
+import statistics
+import sys
+import threading
+import time
+import traceback
+import urllib.error
+import urllib.request
+
+
+def load_module(name, path):
+    spec = importlib.util.spec_from_file_location(name, path)
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[name] = module
+    spec.loader.exec_module(module)
+
+
+def main():
+    p = argparse.ArgumentParser(description=__doc__)
+    for name in ['model', 'cache-dir', 'batching', 'pd-module', 'service-module', 'http-module',
+                 'worker-python', 'engine-factory', 'reference', 'output']:
+        p.add_argument('--' + name, required=True)
+    p.add_argument('--kv-blocks', type=int, default=3)
+    p.add_argument('--repeats', type=int, default=3)
+    p.add_argument('--outputs', type=int, nargs='+', default=[32, 128])
+    a = p.parse_args()
+    output = Path(a.output)
+    trace_path = output.with_suffix('.producer.jsonl')
+    if output.exists() or trace_path.exists():
+        raise RuntimeError('refusing to overwrite experiment artifacts')
+    for name, path in [('opt_prime.accel.serve.llmd', a.http_module),
+                       ('opt_prime.accel.pd.pd_batching', a.pd_module),
+                       ('opt_prime.accel.platforms.atom.batching', a.batching),
+                       ('opt_prime.accel.serve.batched', a.service_module)]:
+        load_module(name, path)
+    import torch
+    from transformers import AutoTokenizer, GenerationConfig
+    from opt_prime.accel.pd.pd_batching import SubprocessPrefillWorker
+    from opt_prime.accel.platforms.atom.engine import AtomRblnEngine
+    from opt_prime.accel.serve.batched import BatchedOwner, BatchedService
+    from opt_prime.accel.serve.llmd import serve_stage
+
+    reference = json.loads(Path(a.reference).read_text())
+    prompts = reference['prompts']
+    result = dict(passed=False, stage='loading', model=a.model, runtime_commit='3e16c33',
+                  torch=torch.__version__, physical_atom=1, physical_rngd=1, slots=1,
+                  producer_width=8192, producer_cache=False, decoder_cache=False, prompts=prompts,
+                  checks=[], normal_eos=[], batches=[], lifecycle={}, submissions=[], decode_calls=[])
+    def save():
+        output.write_text(json.dumps(result, indent=2) + '\n')
+    save()
+    nodes = list(Path('/dev').glob('rbln[0-9]*'))
+    assert len(nodes) == 1, 'requires exactly one assigned ATOM'
+    engine = AtomRblnEngine(devices=[int(nodes[0].name[4:])], max_seq_len=9216, batch_size=1,
+                           kv_blocks=a.kv_blocks, cache_dir=a.cache_dir)
+    worker = owner = server = http = client = None
+    errors = []
+    started = time.perf_counter()
+    try:
+        engine.start(a.model)
+        c = engine.model.config.get_text_config()
+        worker = SubprocessPrefillWorker(a.worker_python,
+            ['--model', a.model, '--width', '8192', '--engine-factory', a.engine_factory],
+            slots=1, layers=c.num_hidden_layers, kv_heads=c.num_key_value_heads,
+            head_dim=getattr(c, 'head_dim', None) or c.hidden_size // c.num_attention_heads,
+            max_context=8192, env=dict(os.environ, PD_TRACE_PATH=str(trace_path.resolve())))
+        tokenizer = AutoTokenizer.from_pretrained(a.model, local_files_only=True)
+        eos = GenerationConfig.from_pretrained(a.model, local_files_only=True).eos_token_id
+        eos = list(eos) if isinstance(eos, (list, tuple)) else ([] if eos is None else [eos])
+        if tokenizer.eos_token_id is not None:
+            eos = list(dict.fromkeys(eos + [tokenizer.eos_token_id]))
+        b = engine.batcher(prefix_cache=False, prefill_worker=worker, local_prefill=False, remote_prefetch=False)
+        service = BatchedService(b, model=a.model, vocab_size=c.vocab_size, max_output=max(a.outputs),
+                                tokenizer=tokenizer, eos_token_ids=eos,
+                                render=lambda ids: tokenizer.decode(ids, skip_special_tokens=True))
+        owner = BatchedOwner(service)
+        emitted = {}
+        original_emit, original_decode, original_submit = b._emit, b._decode_step, worker.submit
+        def emit(r, token):
+            emitted.setdefault(r.request.request_id, time.perf_counter())
+            return original_emit(r, token)
+        def decode():
+            ids = [r.request.request_id for r in b.decoding]
+            t0 = time.perf_counter()
+            original_decode()
+            result['decode_calls'].append(dict(ids=ids, start_s=t0, end_s=time.perf_counter()))
+        def submit(request, send_from=0, slot=None):
+            key = worker._next  # only the owner submits, so this matches the subprocess wire ID
+            row = dict(wire_id=key, id=request.request_id, start_s=time.perf_counter(),
+                       prefetch=b.remote_prefetch, decoding=[r.request.request_id for r in b.decoding])
+            f = original_submit(request, send_from=send_from, slot=slot)
+            result['submissions'].append(row)
+            return f
+        b._emit, b._decode_step, worker.submit = emit, decode, submit
+        with socket.socket() as sock:
+            sock.bind(('127.0.0.1', 0)); port = sock.getsockname()[1]
+        server, http = serve_stage(owner, 'decode', port)
+        result.update(load_s=time.perf_counter()-started, eos_token_ids=eos, stage='running')
+        save()
+        refs = {}
+
+        def wait_for(predicate, description, timeout=240):
+            end = time.monotonic() + timeout
+            while not predicate():
+                if time.monotonic() >= end:
+                    raise TimeoutError(description)
+                time.sleep(.01)
+
+        def mode(enabled):
+            wait_for(lambda: b.idle, 'drain before mode switch')
+            with b._lock:
+                assert not (b.waiting or b.prefilling or b.decoding or b._prefetched)
+                b.remote_prefetch = enabled
+
+        def request(n, count, rid, ignore_eos=True, gate=None):
+            body = dict(model=a.model, prompt=prompts[str(n)], max_tokens=count,
+                        temperature=0, ignore_eos=ignore_eos, stream=False)
+            req = urllib.request.Request(f'http://127.0.0.1:{port}/v1/completions',
+                data=json.dumps(body).encode(), headers={'x-request-id': rid})
+            if gate: gate.wait(timeout=30)
+            t0 = time.perf_counter()
+            try:
+                with urllib.request.urlopen(req, timeout=240) as response:
+                    data = json.load(response)
+            except urllib.error.HTTPError as error:
+                return dict(id=rid, status=error.code, error=error.read().decode())
+            elapsed = time.perf_counter()-t0
+            choice = data['choices'][0]
+            return dict(id=rid, status=200, tokens=choice['token_ids'], text=choice['text'],
+                        finish=choice['finish_reason'], e2e_s=elapsed,
+                        first_token_emitted_s=emitted[rid]-t0)
+
+        def batch(n, count, concurrency, prefix, ignore_eos=True):
+            gate = threading.Barrier(concurrency+1)
+            with ThreadPoolExecutor(max_workers=concurrency) as clients:
+                fs = [clients.submit(request,n,count,f'{prefix}-{i}',ignore_eos,gate) for i in range(concurrency)]
+                t0=time.perf_counter(); gate.wait(timeout=30)
+                rows=[f.result(timeout=260) for f in fs]
+                wall=time.perf_counter()-t0
+            assert all(r['status']==200 for r in rows), rows
+            return rows,wall
+
+        def cut(tokens):
+            for i,t in enumerate(tokens):
+                if t in eos: return tokens[:i+1]
+            return tokens
+
+        def exercise():
+            try:
+                wait_for(lambda: owner.started, 'owner startup')
+                for n in [128,8192]:
+                    for count in a.outputs:
+                        r=request(n,count,f'warm-{n}-{count}')
+                        assert r['status']==200 and len(r['tokens'])==count and r['finish']=='length',r
+                        refs[f'{n}:{count}']=r['tokens']
+                result['references']=refs
+                for enabled in [False,True]:
+                    mode(enabled)
+                    for n in [128,8192]:
+                        for count in a.outputs:
+                            rows,_=batch(n,count,4,f'check-{enabled}-{n}-{count}')
+                            assert all(r['tokens']==refs[f'{n}:{count}'] for r in rows),rows
+                            result['checks'].append(dict(prefetch=enabled,input_tokens=n,output_tokens=count,rows=rows))
+                        rows,_=batch(n,32,4,f'eos-{enabled}-{n}',False)
+                        expected=cut(reference['references'][f'{n}:32']['tokens'])
+                        assert all(r['tokens']==expected for r in rows),rows
+                        assert all(r['finish']==('stop' if expected[-1] in eos else 'length') for r in rows)
+                        result['normal_eos'].append(dict(prefetch=enabled,input_tokens=n,rows=rows))
+                    save()
+                for repeat in range(a.repeats):
+                    for n in ([128,8192] if repeat%2==0 else [8192,128]):
+                        for count in a.outputs:
+                            for concurrency in [1,4]:
+                                for enabled in ([False,True] if repeat%2==0 else [True,False]):
+                                    mode(enabled)
+                                    rows,wall=batch(n,count,concurrency,f'r{repeat}-{enabled}-{n}-{count}-{concurrency}')
+                                    assert all(r['tokens']==refs[f'{n}:{count}'] for r in rows),rows
+                                    result['batches'].append(dict(repeat=repeat,prefetch=enabled,input_tokens=n,
+                                        output_tokens=count,concurrency=concurrency,wall_s=wall,
+                                        tok_s=concurrency*count/wall,median_e2e_s=statistics.median(r['e2e_s'] for r in rows),
+                                        median_first_token_s=statistics.median(r['first_token_emitted_s'] for r in rows),rows=rows))
+                                    save()
+                mode(True)
+                for fault in ['cancel','worker_exit']:
+                    with ThreadPoolExecutor(max_workers=3) as clients:
+                        first=clients.submit(request,8192,max(a.outputs),f'{fault}-first')
+                        wait_for(lambda:f'{fault}-first' in emitted,'first decode before fault')
+                        victim=clients.submit(request,8192,32,f'{fault}-victim')
+                        wait_for(lambda:any(r['id']==f'{fault}-victim' and r['decoding'] for r in result['submissions']),
+                                 'prefetched victim during first decode')
+                        if fault=='cancel':
+                            req=urllib.request.Request(f'http://127.0.0.1:{port}/v1/cancel',data=b'{}',headers={'x-request-id':f'{fault}-victim'})
+                            with urllib.request.urlopen(req,timeout=10) as response:assert response.status in [200,202]
+                            gone=victim.result(timeout=240);assert gone['status']==499,gone
+                            recovery=clients.submit(request,8192,32,'cancel-recovery')
+                            recovered=recovery.result(timeout=240)
+                            assert recovered['status']==200 and recovered['tokens']==refs['8192:32']
+                        else:
+                            worker._proc.terminate()
+                            gone=victim.result(timeout=240);assert gone['status'] in [500,503],gone
+                            rejected=request(128,32,'after-worker-exit');assert rejected['status']==503,rejected
+                            try:
+                                urllib.request.urlopen(f'http://127.0.0.1:{port}/ready',timeout=10)
+                            except urllib.error.HTTPError as error:
+                                assert error.code==503
+                            else:
+                                raise AssertionError('failed producer must fail readiness')
+                        kept=first.result(timeout=240)
+                        assert kept['status']==200 and kept['tokens']==refs[f'8192:{max(a.outputs)}'],kept
+                        wait_for(lambda:b.idle,'fault drain')
+                        assert not b.poisoned and not b.by_id and b._prefetched is None
+                        result['lifecycle'][fault]=dict(victim_status=gone['status'],first_tokens_equal=True,drained=True)
+                        save()
+                result.update(passed=True,stage='complete')
+            except BaseException:
+                result.update(error=traceback.format_exc(),stage='failed')
+                errors.append(result['error'])
+            finally:
+                save()
+                # Cancel only this harness's requests before graceful owner/worker shutdown.
+                for rid in list(b.by_id): owner.cancel_request(rid)
+                if errors and worker._proc.poll() is None:
+                    worker._proc.terminate()  # settle pending futures before owner drain; keep slab mapped until it stops
+                owner.submit('stop')
+        client=threading.Thread(target=exercise,name='pipeline-clients',daemon=True)
+        client.start()
+        owner.run()
+        client.join(10)
+        assert not client.is_alive()
+        if errors: raise RuntimeError(errors[0])
+    except BaseException:
+        result.setdefault('error',traceback.format_exc());result['stage']='failed';save()
+        raise
+    finally:
+        if server:
+            server.shutdown();server.server_close();http.join(5)
+        if worker:worker.close()
+        engine.close()
+
+
+if __name__=='__main__':
+    main()
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-a.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-a.json
new file mode 100644
index 00000000..be7016ae
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-a.json
@@ -0,0 +1,116840 @@
+{
+  "passed": true,
+  "stage": "complete",
+  "model": "KISTI-KONI/KONI-Llama3.1-8B-Instruct-20241024",
+  "runtime_commit": "3e16c33",
+  "torch": "2.11.0+cpu",
+  "physical_atom": 1,
+  "physical_rngd": 1,
+  "slots": 1,
+  "producer_width": 8192,
+  "producer_cache": false,
+  "decoder_cache": false,
+  "prompts": {
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diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-a.producer.jsonl b/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-a.producer.jsonl
new file mode 100644
index 00000000..2ad6897c
--- /dev/null
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diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-summary.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-summary.json
new file mode 100644
index 00000000..e13a743e
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-koni-summary.json
@@ -0,0 +1,210 @@
+{
+  "model": "KISTI-KONI/KONI-Llama3.1-8B-Instruct-20241024",
+  "stage": "complete",
+  "passed": true,
+  "measured_batches": 48,
+  "rows": [
+    {
+      "input_tokens": 128,
+      "output_tokens": 32,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 6.073943841983278,
+      "on_tok_s": 6.070414265717409,
+      "change_pct": -0.05811012346659261,
+      "paired_changes_pct": [
+        0.429253846452915,
+        -0.25616170152397144,
+        -1.637615769146028
+      ],
+      "off_median_first_token_s": 3.188754801056348,
+      "on_median_first_token_s": 3.193927025073208,
+      "off_median_e2e_s": 5.268300389987417,
+      "on_median_e2e_s": 5.2712739570997655
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 32,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 6.074931894517198,
+      "on_tok_s": 8.558004548525664,
+      "change_pct": 40.874082164600246,
+      "paired_changes_pct": [
+        41.36565813372377,
+        39.67913603903759,
+        39.791346198360735
+      ],
+      "off_median_first_token_s": 11.092427575553302,
+      "on_median_first_token_s": 8.075473057979252,
+      "off_median_e2e_s": 13.1734207815025,
+      "on_median_e2e_s": 10.152320401452016
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 128,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 10.939156951458127,
+      "on_tok_s": 10.936170404907761,
+      "change_pct": -0.027301432492632394,
+      "paired_changes_pct": [
+        0.15454567330028812,
+        -0.027301432492632394,
+        2.334248788126869
+      ],
+      "off_median_first_token_s": 3.1803960170364007,
+      "on_median_first_token_s": 3.1820806509349495,
+      "off_median_e2e_s": 11.700953993014991,
+      "on_median_e2e_s": 11.704154097940773
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 128,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 10.873236381775351,
+      "on_tok_s": 13.673585935946978,
+      "change_pct": 25.754517384219632,
+      "paired_changes_pct": [
+        26.026414304642852,
+        25.034643206329687,
+        25.754517384219632
+      ],
+      "off_median_first_token_s": 20.898272749502212,
+      "on_median_first_token_s": 16.07395024097059,
+      "off_median_e2e_s": 29.4168122105184,
+      "on_median_e2e_s": 24.59150394698372
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 32,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 4.740746256834072,
+      "on_tok_s": 4.731570991849313,
+      "change_pct": -0.19354052057799498,
+      "paired_changes_pct": [
+        1.297451484258505,
+        -0.6734476711597992,
+        -0.19354052057799498
+      ],
+      "off_median_first_token_s": 4.527249442064203,
+      "on_median_first_token_s": 4.5374126569367945,
+      "off_median_e2e_s": 6.749840553035028,
+      "on_median_e2e_s": 6.762957567931153
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 32,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 4.782615000060235,
+      "on_tok_s": 6.292681690716462,
+      "change_pct": 31.574080092945135,
+      "paired_changes_pct": [
+        31.574080092945135,
+        32.92212545335267,
+        30.807396360678574
+      ],
+      "off_median_first_token_s": 14.495777527976315,
+      "on_median_first_token_s": 11.292777049529832,
+      "off_median_e2e_s": 16.716965802013874,
+      "on_median_e2e_s": 13.512547572492622
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 128,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 9.398753655996774,
+      "on_tok_s": 9.39138588742765,
+      "change_pct": -0.0783909105269931,
+      "paired_changes_pct": [
+        -0.8766156933057379,
+        0.2230294446130321,
+        -0.17416525128901572
+      ],
+      "off_median_first_token_s": 4.504511486040428,
+      "on_median_first_token_s": 4.511214580037631,
+      "off_median_e2e_s": 13.618662261986174,
+      "on_median_e2e_s": 13.62934918096289
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 128,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 9.408771040749222,
+      "on_tok_s": 11.617823014785085,
+      "change_pct": 23.47864523930381,
+      "paired_changes_pct": [
+        23.513306575696056,
+        24.53418820134077,
+        22.9262445145064
+      ],
+      "off_median_first_token_s": 24.905245764006395,
+      "on_median_first_token_s": 19.68521516403416,
+      "off_median_e2e_s": 34.02811081049731,
+      "on_median_e2e_s": 28.79301679949276
+    }
+  ],
+  "latency_kind": "median of matched batch medians; first token is owner emission, not client SSE",
+  "overlap_kind": "producer prefill+export host-call versus other-request decode host-call; not device-kernel proof",
+  "overlap": {
+    "False": {
+      "completed_measured_producers": 60,
+      "with_overlap": 0,
+      "total_overlap_s": 0.0
+    },
+    "True": {
+      "completed_measured_producers": 60,
+      "with_overlap": 36,
+      "total_overlap_s": 96.42008972377516
+    }
+  },
+  "lifecycle": {
+    "cancel": {
+      "victim_status": 499,
+      "first_tokens_equal": true,
+      "drained": true
+    },
+    "worker_exit": {
+      "victim_status": 500,
+      "first_tokens_equal": true,
+      "drained": true
+    }
+  }
+}
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/llmd253.py b/opt_prime/examples/pd/http_matrix/evidence253/llmd253.py
new file mode 100644
index 00000000..52910e21
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/llmd253.py
@@ -0,0 +1,707 @@
+"""Optional local llm-d shared-storage control plane, separate from the engine.
+
+No KV bytes travel over HTTP. One serialized owner executes all device work;
+run OwnerExecutor.run on the main thread for the checked RNGD PDMA backend.
+"""
+
+from concurrent.futures import Future, TimeoutError as FutureTimeout
+from dataclasses import dataclass
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+import json
+from io import BufferedIOBase
+import queue
+import select
+import socket
+import threading
+import time
+from opt_prime.accel.pd.contracts import RetryableError, SamplingParams
+from opt_prime.accel.pd.runtime import PDRequest, PDRuntime, CancellationToken, RequestCancelled
+from opt_prime.accel.serve.metrics import StageMetrics
+
+
+class StageError(Exception):
+    """HTTP status + message. retryable: the request may be retried (here later, or on another replica)."""
+    def __init__(self, status, message, retryable=False):
+        super().__init__(message)
+        self.status, self.retryable = status, retryable
+
+
+@dataclass
+class Prepared:
+    request: PDRequest
+    result: object
+    created: float
+    spec: object
+
+    def recover(self):
+        # host-side record of a fenced prefill; the source engine's own recovery is checked by PDStageService.reset
+        return True
+
+    def prefill(self, request):
+        if (
+            request.request_id != self.request.request_id
+            or request.input_ids != self.request.input_ids
+        ):
+            raise ValueError("prepared continuation belongs to another request")
+        return self.result
+
+
+class CompletionAPI:
+    """OpenAI-style request parsing and responses shared by the stage services: token-ID / text prompts and chat
+    messages, sampling and stop fields, finish_reason and usage."""
+
+    def __init__(self, *, model, vocab_size, context, max_output, render, eos_token_ids=(), tokenizer=None):
+        if min(vocab_size, context, max_output) <= 0:
+            raise ValueError("positive service limits required")
+        self.model, self.vocab_size, self.context, self.max_output = model, vocab_size, context, max_output
+        self.render = render
+        self.eos_token_ids = tuple(eos_token_ids)
+        self.tokenizer = tokenizer          # text prompts and chat messages (token-ID prompts need none)
+        self.metrics = StageMetrics(model)
+
+    def _request(self, rid, body, chat=False):
+        allowed = {
+            "messages",
+            "stream_options",
+            "model",
+            "prompt",
+            "max_tokens",
+            "max_completion_tokens",
+            "temperature",
+            "top_p",
+            "top_k",
+            "seed",
+            "stop",
+            "ignore_eos",
+            "stream",
+            "cache_hit_threshold",
+        }
+        if not isinstance(rid, str) or not rid.strip() or len(rid) > 128:
+            raise StageError(400, "valid x-request-id required")
+        if (
+            not isinstance(body, dict)
+            or set(body) - allowed
+            or body.get("model") != self.model
+        ):
+            raise StageError(400, "invalid model or unsupported request fields")
+        prompt = self._prompt(body, chat)
+        if (
+            not isinstance(prompt, list)
+            or not prompt
+            or any(type(t) is not int or not 0 <= t < self.vocab_size for t in prompt)
+        ):
+            raise StageError(400, "one token-ID prompt required")
+        count = body.get("max_completion_tokens", body.get("max_tokens", 32))
+        if (
+            type(count) is not int
+            or not 1 <= count <= self.max_output
+            or len(prompt) + count > self.context
+        ):
+            raise StageError(400, "output or context capacity exceeded")
+        if (
+            "max_tokens" in body
+            and "max_completion_tokens" in body
+            and body["max_tokens"] != body["max_completion_tokens"]
+        ):
+            raise StageError(400, "conflicting output limits")
+        if not isinstance(body.get("stream", False), bool):
+            raise StageError(400, "stream must be a boolean")
+        stop = body.get("stop", [])
+        stop = [stop] if isinstance(stop, str) else stop
+        if (not isinstance(stop, list) or len(stop) > 4
+                or any(not isinstance(x, str) or not 0 < len(x) <= 64 for x in stop)):
+            raise StageError(400, "stop must be up to 4 non-empty strings")
+        ignore_eos = body.get("ignore_eos", False)
+        if not isinstance(ignore_eos, bool):
+            raise StageError(400, "ignore_eos must be a boolean")
+        temperature, seed = body.get("temperature", 0), body.get("seed")
+        if isinstance(temperature, bool) or isinstance(body.get("top_p", 1), bool):
+            raise StageError(400, "invalid sampling parameters")
+        try:
+            sampling = SamplingParams(float(temperature) if isinstance(temperature, (int, float)) else temperature,
+                                      body.get("top_p", 1.0), body.get("top_k", 0), seed,
+                                      () if ignore_eos else self.eos_token_ids)
+        except ValueError as error:
+            raise StageError(400, str(error))
+        if not sampling.greedy and not all(getattr(e, "supports_sampling", False) for e in self._engines()):
+            raise StageError(400, "engine supports greedy decoding only")
+        if "cache_hit_threshold" in body and body["cache_hit_threshold"] != 0:
+            raise StageError(400, "unsupported cache threshold")
+        return PDRequest(rid, tuple(prompt), count, sampling), tuple(stop)
+
+    def expire(self):
+        """Release a fenced prefill whose decode did not arrive within the TTL (owner thread only)."""
+        if self.state == "ready" and self.clock() - self.prepared.created > self.ttl:
+            old = self.prepared.request.request_id
+            self.prepared = None
+            self.state = "idle"
+            self._event("expired", old)
+            return old
+        return None
+
+    def _prompt(self, body, chat):
+        """token IDs of the request: `messages` through the chat template (chat), a text `prompt` through the
+        tokenizer, or a token-ID `prompt` as is"""
+        if chat:
+            messages = body.get("messages")
+            if "prompt" in body or not isinstance(messages, list) or not messages or any(
+                    not isinstance(m, dict) or not isinstance(m.get("role"), str)
+                    or not isinstance(m.get("content"), str) for m in messages):
+                raise StageError(400, "chat requires messages with role and text content")
+            if self.tokenizer is None:
+                raise StageError(400, "this stage has no tokenizer for chat messages")
+            ids = self.tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=True)
+            ids = ids["input_ids"] if isinstance(ids, dict) or hasattr(ids, "keys") else ids
+            return [int(t) for t in ids]
+        if "messages" in body:
+            raise StageError(400, "messages belong to /v1/chat/completions")
+        prompt = body.get("prompt")
+        if isinstance(prompt, str):
+            if self.tokenizer is None:
+                raise StageError(400, "this stage has no tokenizer for text prompts")
+            return [int(t) for t in self.tokenizer(prompt, add_special_tokens=True)["input_ids"]]
+        return prompt
+
+    def _finish(self, request, stop_strings, tokens):
+        """(tokens, text, finish_reason): cut at the first stop string (the text excludes it, the tokens end with the
+        token that completed it); 'stop' also when the last token is a stop token."""
+        text = self.render(tokens)
+        stops = [s for s in stop_strings if s in text]
+        if stops:
+            for i in range(1, len(tokens) + 1):
+                partial = self.render(tokens[:i])
+                hit = min((partial.find(s) for s in stops if s in partial), default=-1)
+                if hit >= 0:
+                    return tokens[:i], partial[:hit], "stop"
+        stop_ids = request.sampling.stop_token_ids
+        return tokens, text, "stop" if tokens and tokens[-1] in stop_ids else "length"
+
+    def _prefill_reply(self, rid, chat=False):
+        if chat:
+            return dict(id=rid, object="chat.completion", model=self.model,
+                        choices=[dict(index=0, message=dict(role="assistant", content=""), finish_reason="stop")])
+        return dict(
+            id=rid,
+            object="text_completion",
+            model=self.model,
+            choices=[dict(index=0, text="", finish_reason="stop")],
+        )
+
+    def _engines(self):
+        """the engines that must support non-greedy sampling for it to be accepted"""
+        return ()
+
+    def _response(self, rid, request, tokens, text, finish, chat):
+        usage = dict(prompt_tokens=len(request.input_ids), completion_tokens=len(tokens),
+                     total_tokens=len(request.input_ids) + len(tokens))
+        if chat:
+            choice = dict(index=0, message=dict(role="assistant", content=text), token_ids=tokens, finish_reason=finish)
+        else:
+            choice = dict(index=0, text=text, token_ids=tokens, finish_reason=finish)
+        return dict(id=rid, object="chat.completion" if chat else "text_completion", created=int(time.time()),
+                    model=self.model, choices=[choice], usage=usage)
+
+
+class PDStageService(CompletionAPI):
+    """Single prepared source slot. Cancel/TTL can release only fenced prefill."""
+
+    def __init__(
+        self,
+        prefill,
+        decode,
+        transport,
+        *,
+        model,
+        vocab_size,
+        context,
+        max_output,
+        render,
+        ttl=60,
+        clock=time.monotonic,
+        eos_token_ids=(),
+        tokenizer=None
+    ):
+        if prefill.spec != decode.spec:
+            raise ValueError("engine specifications differ")
+        if ttl <= 0:
+            raise ValueError("positive service limits required")
+        super().__init__(model=model, vocab_size=vocab_size, context=context, max_output=max_output, render=render,
+                         eos_token_ids=eos_token_ids, tokenizer=tokenizer)
+        self.prefill, self.decode, self.transport = prefill, decode, transport
+        self.ttl, self.clock = ttl, clock
+        self.prepared = None
+        self.runtime = None
+        self.state = "idle"
+        self.events = []
+
+    def _engines(self):
+        return self.prefill, self.decode
+
+    def gauges(self, waiting=0):
+        """(running, waiting, KV lane usage) for /metrics: one lane, occupied unless idle"""
+        running = 1 if self.state in ("prefilling", "decoding") else 0
+        return running, waiting, 0.0 if self.state == "idle" else 1.0
+
+    def _event(self, stage, request_id):
+        self.events.append(dict(stage=stage, request_id=request_id, time=self.clock()))
+        if len(self.events) > 1024:
+            del self.events[:-1024]
+
+    def cancel(self, rid):
+        if self.state != "ready" or self.prepared.request.request_id != rid:
+            raise StageError(409, "only a matching fenced prefill can be cancelled")
+        self.prepared = None
+        self.state = "idle"
+        self._event("cancelled", rid)
+
+    def execute(self, stage, rid, body, cancellation=None, on_token=None, chat=False):
+        """on_token(token) streams output tokens on the owner thread (first token after the fenced prefill)."""
+        if stage not in ("prefill", "decode"):
+            raise StageError(400, "unknown stage")
+        request, stops = self._request(rid, body, chat)
+        if cancellation is not None and cancellation.cancelled:
+            raise StageError(499, "request cancelled before execution")
+        if self.state == "poisoned":
+            raise StageError(503, "owner quarantined; recovery required", retryable=True)
+        self.expire()
+        if self.prepared is not None and self.prepared.request.request_id == rid:
+            if self.prepared.request.input_ids != request.input_ids:
+                raise StageError(409, "request ID reused with a different prompt")
+        if stage == "prefill":
+            if self.state == "ready" and self.prepared.request.request_id == rid:
+                return self._prefill_reply(rid, chat)
+            if self.state != "idle":
+                raise StageError(429, "single cache lane occupied")
+            self.state = "prefilling"
+            prefill_fenced = False
+            started = self.clock()
+            try:
+                result = self.prefill.prefill(request)
+                prefill_fenced = True
+                self.prepared = Prepared(
+                    request, result, self.clock(), self.prefill.spec
+                )
+                result.validate(request)
+                if result.cache.spec != self.prefill.spec:
+                    raise ValueError("prefill cache specification mismatch")
+                if cancellation is not None and cancellation.cancelled:
+                    raise RequestCancelled(rid)
+                self.state = "ready"
+                self._event("prefill_ready", rid)
+                elapsed = self.clock() - started
+                self.metrics.observe("vllm:time_to_first_token_seconds", elapsed)   # prefill emits the first token
+                self.metrics.observe("vllm:e2e_request_latency_seconds", elapsed)
+                self.metrics.finished("stop", len(request.input_ids), 1)
+                if on_token is not None:
+                    for t in result.output_prefix:
+                        on_token(t)
+                return self._prefill_reply(rid, chat)
+            except RequestCancelled:
+                if not prefill_fenced:
+                    self.state = "poisoned"
+                    raise
+                self.prepared = None
+                self.state = "idle"
+                self._event("cancelled", rid)
+                raise StageError(499, "prefill cancelled after completion")
+            except RetryableError as error:
+                self.prepared = None                      # the engine left nothing outstanding
+                self.state = "idle"
+                self.metrics.failed()
+                self._event("retryable_failure", rid)
+                raise StageError(503, f"retryable: {error}", retryable=True)
+            except BaseException:
+                self.state = "poisoned"
+                self.metrics.failed()
+                raise
+        if self.state != "ready" or self.prepared.request.request_id != rid:
+            raise StageError(409, "matching completed prefill required")
+        self.state = "decoding"
+        self._event("decode_start", rid)
+        started = self.clock()
+        try:
+            # PDRuntime reuses Prepared.prefill; the model is not prefetched again.
+            self.runtime = PDRuntime(self.prepared, self.decode, self.transport)
+            tokens = self.runtime.generate(request, cancellation=cancellation, on_token=on_token)
+            tokens, text, finish = self._finish(request, stops, tokens)
+            response = self._response(rid, request, tokens, text, finish, chat)
+            self.prepared = None
+            self.state = "idle"
+            self._event("decode_complete", rid)
+            t = self.runtime.last_timings
+            if "transfer_seconds" in t:
+                self.metrics.observe("airm_kv_transfer_seconds", t["transfer_seconds"])
+            if len(tokens) > 1 and "decode_seconds" in t:
+                self.metrics.observe("vllm:time_per_output_token_seconds", t["decode_seconds"] / (len(tokens) - 1))
+            self.metrics.observe("vllm:e2e_request_latency_seconds", self.clock() - started)
+            self.metrics.finished(finish, len(request.input_ids), len(tokens))
+            return response
+        except RequestCancelled:
+            if self.runtime.state != "idle":
+                self.state = "poisoned"
+                raise
+            self.prepared = None
+            self.state = "idle"
+            self._event("cancelled", rid)
+            raise StageError(499, "decode cancelled after drain")
+        except RetryableError as error:
+            self.prepared = None                          # runtime released the leases; retry from prefill
+            self.state = "idle"
+            self.metrics.failed()
+            self._event("retryable_failure", rid)
+            raise StageError(503, f"retryable: {error}", retryable=True)
+        except BaseException:
+            self.state = "poisoned"
+            self.metrics.failed()
+            raise
+
+    def reset(self):
+        """Recovery from quarantine: every endpoint must confirm a known-good device state (`recover() -> True`);
+        only then are the retained allocations released and the lane reopened. Owner thread only."""
+        if self.state != "poisoned":
+            raise StageError(409, "owner is not quarantined")
+        for part in (self.prefill, self.decode, self.transport):
+            fn = getattr(part, "recover", None)
+            if fn is None:
+                raise StageError(501, f"{type(part).__name__} has no recovery; restart the stage")
+            if fn() is not True:
+                raise StageError(503, f"{type(part).__name__} not known-good; still quarantined")
+        if self.runtime is not None and not self.runtime.recover():
+            raise StageError(503, "cache lane not recovered; still quarantined")
+        self.prepared = None
+        self.state = "idle"
+        self._event("recovered", None)
+        return dict(state=self.state)
+
+
+class OwnerExecutor:
+    """HTTP threads enqueue only. Timeouts never cancel or release device work.
+
+    While idle, the owner sweeps the TTL every `sweep` seconds, so an abandoned prepared prefill frees the lane
+    without waiting for the next request."""
+
+    def __init__(self, service, capacity=64, sweep=1.0):
+        self.service, self.sweep = service, sweep
+        self.queue = queue.Queue(capacity)
+        self.started = False
+        self.accepting = True
+        self._submit_lock = threading.Lock()
+        self._pending = {}
+
+    def submit(self, operation, *args, **kwargs):
+        return self.submit_async(operation, *args, **kwargs).result()
+
+    def submit_async(self, operation, *args, **kwargs):
+        future = Future()
+        token = CancellationToken() if operation == "execute" else None
+        rid = args[1] if token is not None else None
+        if token is not None and (
+            not isinstance(rid, str) or not rid.strip() or len(rid) > 128
+        ):
+            raise StageError(400, "valid x-request-id required")
+        with self._submit_lock:
+            if not self.started or not self.accepting:
+                raise StageError(503, "owner not accepting work")
+            try:
+                self.queue.put_nowait((operation, args, kwargs, future, token))
+                if token is not None:
+                    self._pending.setdefault(rid, []).append(token)
+            except queue.Full:
+                raise StageError(429, "owner command queue full")
+            if operation == "stop":
+                self.accepting = False
+        return future
+
+    def cancel_request(self, rid):
+        if not isinstance(rid, str) or not rid.strip() or len(rid) > 128:
+            raise StageError(400, "valid x-request-id required")
+        with self._submit_lock:
+            if not self.started or not self.accepting:
+                raise StageError(503, "owner not accepting work")
+            tokens = self._pending.get(rid, ())
+            if tokens:
+                for token in tokens:
+                    token.cancel()
+                return dict(id=rid, cancellation_requested=True, drained=False)
+        # No active/queued call: only the owner may release a prepared cache.
+        self.submit("cancel", rid)
+        return dict(id=rid, cancellation_requested=True, drained=True)
+
+    def run(self):
+        self.started = True
+        while True:
+            try:
+                operation, args, kwargs, future, token = self.queue.get(timeout=self.sweep)
+            except queue.Empty:
+                self.service.expire()
+                continue
+            error = None
+            stopping = operation == "stop"
+            try:
+                if stopping:
+                    if self.service.state not in ("idle", "ready"):
+                        raise StageError(409, "owner not quiescent")
+                    if self.service.state == "ready":
+                        self.service.cancel(self.service.prepared.request.request_id)
+                    self.started = False
+                    result = None
+                elif operation == "execute":
+                    result = self.service.execute(*args, cancellation=token, **kwargs)
+                elif operation == "cancel":
+                    result = self.service.cancel(*args)
+                elif operation == "reset":
+                    result = self.service.reset()
+                else:
+                    raise StageError(400, "unknown owner operation")
+            except BaseException as exc:
+                error = exc
+            # Complete pending-token bookkeeping atomically with cancellation.
+            # A cancel accepted after execute() returns must still drain a ready
+            # prefill; otherwise the client sees 202 but the slot remains occupied.
+            with self._submit_lock:
+                if token is not None:
+                    try:
+                        if error is None and token.cancelled:
+                            if (self.service.state == "ready" and
+                                    self.service.prepared.request.request_id == args[1]):
+                                self.service.cancel(args[1])
+                            error = StageError(499, "request cancelled after completion")
+                    except BaseException as exc:
+                        error = exc
+                    finally:
+                        pending = self._pending[args[1]]
+                        pending.remove(token)
+                        if not pending:
+                            del self._pending[args[1]]
+            if error is not None:
+                if stopping:
+                    self.accepting = True       # the stop was refused: reset and a retried stop must still get in
+                future.set_exception(error)
+            else:
+                future.set_result(result)
+                if stopping:
+                    return
+
+
+POLL = 0.5          # seconds between client-disconnect checks of a waiting handler (results wake it at once)
+_DONE = object()    # end-of-stream marker in a handler's token queue
+
+class _NoSignalSocketWriter(BufferedIOBase):
+    """Unbuffered HTTP writes that retain EPIPE without invoking native SIGPIPE handlers."""
+    def __init__(self, sock):
+        self._sock = sock
+
+    def writable(self):
+        return True
+
+    def write(self, data):
+        self._sock.sendall(data, getattr(socket, "MSG_NOSIGNAL", 0))
+        with memoryview(data) as view:
+            return view.nbytes
+
+    def fileno(self):
+        return self._sock.fileno()
+
+
+def serve_stage(owner, stage, port):
+    if stage not in ("prefill", "decode"):
+        raise ValueError("invalid stage")
+
+    class Handler(BaseHTTPRequestHandler):
+        def setup(self):
+            super().setup()
+            self.wfile = _NoSignalSocketWriter(self.connection)
+
+        def log_message(self, *args):
+            pass
+
+        def reply(self, status, payload, retry_after=None):
+            data = json.dumps(payload).encode()
+            self.send_response(status)
+            self.send_header("Content-Type", "application/json")
+            if retry_after is not None:
+                self.send_header("Retry-After", str(retry_after))
+            self.send_header("Content-Length", str(len(data)))
+            self.end_headers()
+            try:
+                self.wfile.write(data)
+            except (BrokenPipeError, ConnectionResetError):
+                pass  # The completed owner operation is not cancelled by disconnect.
+
+        def client_gone(self):
+            try:
+                readable, _, _ = select.select([self.connection], [], [], 0)
+                return bool(readable) and self.connection.recv(1, socket.MSG_PEEK) == b""
+            except OSError:
+                return True
+
+        def do_GET(self):
+            if self.path == "/metrics":
+                data = owner.service.metrics.render(*owner.service.gauges(owner.queue.qsize())).encode()
+                self.send_response(200)
+                self.send_header("Content-Type", "text/plain; version=0.0.4; charset=utf-8")
+                self.send_header("Content-Length", str(len(data)))
+                self.end_headers()
+                self.wfile.write(data)
+                return
+            if self.path not in ("/ready", "/health"):
+                self.reply(404, dict(error="not found"))
+                return
+            ready = (owner.started and getattr(owner, "accepting", True)
+                     and owner.service.state != "poisoned" and getattr(owner.service, "ready", True))
+            self.reply(200 if ready else 503, dict(ready=ready, stage=stage))
+
+        def cancel_if_gone(self, rid, state):
+            # A closed client connection is a cancel request through the same fenced path.
+            if not state["cancelled"] and self.client_gone():
+                state["cancelled"] = True
+                try:
+                    owner.cancel_request(rid)
+                except StageError:
+                    pass
+
+        def do_POST(self):
+            if self.path not in ("/v1/completions", "/v1/chat/completions", "/v1/cancel", "/v1/admin/reset"):
+                self.reply(404, dict(error="not found"))
+                return
+            try:
+                if self.path == "/v1/admin/reset":
+                    self.reply(200, owner.submit("reset"))
+                    return
+                if self.path == "/v1/cancel":
+                    result = owner.cancel_request(self.headers.get("x-request-id"))
+                    self.reply(200 if result["drained"] else 202, result)
+                    return
+                if not owner.started:
+                    raise StageError(503, "owner not running")
+                length = int(self.headers.get("Content-Length", "0"))
+                if not 0 < length <= 1048576:
+                    raise StageError(413, "invalid body size")
+                body = json.loads(self.rfile.read(length))
+                rid = self.headers.get("x-request-id")
+                chat = self.path == "/v1/chat/completions"
+                if isinstance(body, dict) and body.get("stream") is True:
+                    self.stream(rid, body, chat)
+                    return
+                future = owner.submit_async("execute", stage, rid, body, chat=chat)
+                state = dict(cancelled=False)
+                while True:
+                    try:
+                        response = future.result(timeout=POLL)    # returns at completion; POLL checks the client
+                        break
+                    except FutureTimeout:
+                        self.cancel_if_gone(rid, state)
+                self.reply(200, response)
+            except StageError as error:
+                self.reply(error.status, dict(error=str(error), retryable=error.retryable),
+                           retry_after=1 if error.retryable else None)
+            except (ValueError, TypeError):
+                failed = owner.service.state == "poisoned"
+                self.reply(
+                    500 if failed else 400,
+                    dict(error="engine failed" if failed else "invalid request", retryable=False),
+                )
+            except Exception:
+                self.reply(500, dict(error="engine failed; owner retained", retryable=False))
+
+        def stream(self, rid, body, chat):
+            """OpenAI-compatible SSE: a chunk per token as the owner produces it (the first right after the fenced
+            prefill), text held back while it could still be the start of a stop string, then a chunk with
+            finish_reason, a usage chunk and [DONE]. Errors before the first chunk are plain JSON replies."""
+            tokens = queue.Queue()
+            future = owner.submit_async("execute", stage, rid, body, chat=chat, on_token=tokens.put)
+            stops = body.get("stop") or []
+            stops = [stops] if isinstance(stops, str) else stops
+            hold = max((len(x) for x in stops), default=1) - 1
+            render, created = owner.service.render, int(time.time())
+            kind = "chat.completion.chunk" if chat else "text_completion"
+            state, out, sent, started = dict(cancelled=False), [], "", False
+
+            def chunk(delta=None, finish=None, usage=None):
+                if chat:
+                    choice = dict(index=0, delta={} if delta is None else delta, finish_reason=finish)
+                else:
+                    choice = dict(index=0, text="" if delta is None else delta, finish_reason=finish)
+                payload = dict(id=rid, object=kind, created=created, model=owner.service.model,
+                               choices=[] if usage else [choice])
+                if usage:
+                    payload["usage"] = usage
+                return payload
+
+            def send(payload):
+                nonlocal started
+                if not started:
+                    self.send_response(200)
+                    self.send_header("Content-Type", "text/event-stream")
+                    self.send_header("Cache-Control", "no-cache")
+                    self.end_headers()
+                    started = True
+                    if chat:
+                        send(chunk(dict(role="assistant", content="")))
+                data = payload if isinstance(payload, str) else json.dumps(payload)
+                try:
+                    self.wfile.write(f"data: {data}\n\n".encode())
+                    self.wfile.flush()
+                except (BrokenPipeError, ConnectionResetError):
+                    self.cancel_if_gone(rid, state)
+
+            def text_delta(final=None):
+                nonlocal sent
+                text = render(out) if final is None else final
+                if final is None:
+                    cut = min((text.find(x) for x in stops if x in text), default=-1)
+                    text = text[:cut] if cut >= 0 else text[:max(len(sent), len(text) - hold)]
+                if not text.startswith(sent) or len(text) == len(sent):
+                    return                                  # nothing new, or a multi-byte character still open
+                delta, sent = text[len(sent):], text
+                send(chunk(dict(content=delta) if chat else delta))
+
+            response, error = None, None
+            future.add_done_callback(lambda _f: tokens.put(_DONE))   # tokens are queued before completion
+            while True:
+                try:
+                    item = tokens.get(timeout=POLL)               # wakes on a token; POLL only checks the client
+                except queue.Empty:
+                    self.cancel_if_gone(rid, state)
+                    continue
+                done = item is _DONE
+                if not done:
+                    out.append(item)
+                while True:                                       # drain: one detokenization per wake-up
+                    try:
+                        item = tokens.get_nowait()
+                    except queue.Empty:
+                        break
+                    if item is _DONE:
+                        done = True
+                    else:
+                        out.append(item)
+                text_delta()
+                if done:
+                    try:
+                        response = future.result()
+                    except BaseException as exc:
+                        error = exc
+                    break
+            if error is not None:
+                if started:
+                    send(dict(error=str(error), status=getattr(error, "status", 500)))
+                    send("[DONE]")
+                    return
+                raise error
+            choice = response["choices"][0]
+            if "usage" in response:                         # decode stage: the final, stop-cut text
+                text_delta(choice["message"]["content"] if chat else choice["text"])
+            else:                                           # prefill stage: its token(s), cut at a stop string
+                text = render(out)
+                cut = min((text.find(x) for x in stops if x in text), default=-1)
+                text_delta(text[:cut] if cut >= 0 else text)
+            send(chunk(finish=choice["finish_reason"]))
+            if "usage" in response:
+                send(chunk(usage=response["usage"]))
+            send("[DONE]")
+
+    server = ThreadingHTTPServer(("127.0.0.1", port), Handler)
+    thread = threading.Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    return server, thread
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/summarize_atom253.py b/opt_prime/examples/pd/http_matrix/evidence253/summarize_atom253.py
new file mode 100644
index 00000000..924b7094
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/summarize_atom253.py
@@ -0,0 +1,72 @@
+"""Summarize warm paired HTTP runs and host-call overlap, including partial runs."""
+import argparse
+import json
+import statistics
+from pathlib import Path
+
+
+def summarize(data, producer):
+    groups = {}
+    for batch in data['batches']:
+        key = (batch['input_tokens'], batch['output_tokens'], batch['concurrency'])
+        groups.setdefault(key, {False: [], True: []})[batch['prefetch']].append(batch)
+    rows = []
+    for (n, out, c), modes in sorted(groups.items()):
+        off = {b['repeat']: b for b in modes[False]}
+        on = {b['repeat']: b for b in modes[True]}
+        repeats = sorted(off.keys() & on.keys())
+        if not repeats:
+            continue
+        baseline = statistics.median(off[r]['tok_s'] for r in repeats)
+        candidate = statistics.median(on[r]['tok_s'] for r in repeats)
+        row = dict(input_tokens=n, output_tokens=out, concurrency=c,
+            paired_repeats=repeats, off_tok_s=baseline, on_tok_s=candidate,
+            change_pct=100*(candidate/baseline-1),
+            paired_changes_pct=[100*(on[r]['tok_s']/off[r]['tok_s']-1) for r in repeats])
+        for field in ['median_first_token_s', 'median_e2e_s']:
+            # Median of batch medians over matched repetitions, not a pooled percentile.
+            row['off_'+field] = statistics.median(off[r][field] for r in repeats)
+            row['on_'+field] = statistics.median(on[r][field] for r in repeats)
+        rows.append(row)
+    completed = {r['wire_id']: r for r in producer}
+    overlap = {False: [], True: []}
+    for submission in data['submissions']:
+        if not submission['id'].startswith('r'):
+            continue  # Exclude warmup, correctness and fault injection.
+        interval = completed.get(submission['wire_id'])
+        if interval is None:
+            continue
+        intersections = []
+        for call in data['decode_calls']:
+            if not call['ids'] or submission['id'] in call['ids']:
+                continue
+            start = max(interval['start_s'], call['start_s'])
+            end = min(interval['end_s'], call['end_s'])
+            if end > start:
+                intersections.append((start, end))
+        # Union intervals so overlapping instrumentation cannot double-count.
+        total, end = 0., float('-inf')
+        for start, stop in sorted(intersections):
+            total += max(0., stop-max(start, end))
+            end = max(end, stop)
+        overlap[submission['prefetch']].append(total)
+    return dict(model=data['model'], stage=data['stage'], passed=data['passed'],
+        measured_batches=len(data['batches']), rows=rows,
+        latency_kind='median of matched batch medians; first token is owner emission, not client SSE',
+        overlap_kind='producer prefill+export host-call versus other-request decode host-call; not device-kernel proof',
+        overlap={str(mode): dict(completed_measured_producers=len(values),
+            with_overlap=sum(v > 0 for v in values), total_overlap_s=sum(values))
+            for mode, values in overlap.items()}, lifecycle=data['lifecycle'])
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('result', type=Path)
+    parser.add_argument('trace', type=Path)
+    parser.add_argument('--output', type=Path, required=True)
+    args = parser.parse_args()
+    data = json.loads(args.result.read_text())
+    producer = [json.loads(line) for line in args.trace.read_text().splitlines() if line.strip()]
+    result = summarize(data, producer)
+    args.output.write_text(json.dumps(result, indent=2)+'\n')
+    print(json.dumps(result, indent=2))
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/worker253.py b/opt_prime/examples/pd/http_matrix/evidence253/worker253.py
new file mode 100644
index 00000000..c2ca39ce
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/worker253.py
@@ -0,0 +1,160 @@
+"""Experimental Qwen3 implementation of SubprocessPrefillWorker's existing wire contract."""
+
+import argparse
+import contextlib
+import json
+import os
+import sys
+import time
+from pathlib import Path
+
+import numpy as np
+import torch
+
+
+def validate_request(slab, req, width, vocab_size):
+    tokens, slot, start = req["tokens"], req["slot"], req["send_from"]
+    if type(slot) is not int or not 0 <= slot < slab.shape[0]:
+        raise ValueError("invalid shared-memory lane")
+    if not 0 < len(tokens) <= min(width, slab.shape[-2]):
+        raise ValueError("prompt exceeds compiled capacity or is empty")
+    if type(start) is not int or not 0 <= start <= len(tokens):
+        raise ValueError("invalid prefix offset")
+    if any(type(t) is not int or not 0 <= t < vocab_size for t in tokens):
+        raise ValueError("invalid token ID")
+
+
+def store_result(slab, req, keys, values):
+    validate_request(slab, req, slab.shape[-2], 2**63)
+    expected = (slab.shape[2], slab.shape[3], len(req["tokens"]), slab.shape[-1])
+    if tuple(keys.shape) != expected or tuple(values.shape) != expected:
+        raise ValueError("prefill KV geometry mismatch")
+    start = req["send_from"]
+    arrays = [
+        t[:, :, start:]
+        .to("cpu", torch.bfloat16)
+        .contiguous()
+        .view(torch.int16)
+        .numpy()
+        .view(np.uint16)
+        for t in (keys, values)
+    ]
+    n = len(req["tokens"]) - start
+    dst = slab[req["slot"]]
+    dst[0, :, :, :n], dst[1, :, :, :n] = arrays
+    return n
+
+
+def cache_geometry(config):
+    head_dim = config.get("head_dim")
+    if head_dim is None:
+        heads, hidden = config["num_attention_heads"], config["hidden_size"]
+        if type(heads) is not int or heads <= 0 or hidden % heads:
+            raise ValueError("invalid implicit head dimension")
+        head_dim = hidden // heads
+    shape = (config["num_hidden_layers"], config["num_key_value_heads"], head_dim)
+    if any(type(n) is not int or n <= 0 for n in shape):
+        raise ValueError("invalid cache geometry")
+    return shape
+
+
+def engine_class(factory):
+    """Load an explicit trusted local CLI factory; never select this from request JSON."""
+    from importlib import import_module
+
+    module, separator, name = factory.partition(":")
+    if not separator or not module or not name:
+        raise ValueError("engine factory must be module:callable")
+    cls = getattr(import_module(module), name)
+    if not callable(cls):
+        raise TypeError("engine factory must be callable")
+    return cls
+
+
+def main():
+    ap = argparse.ArgumentParser(description=__doc__)
+    ap.add_argument("--model", required=True)
+    ap.add_argument("--shm", required=True)
+    for name in ("slots", "layers", "kv-heads", "head-dim", "max-context"):
+        ap.add_argument("--" + name, type=int, required=True)
+    ap.add_argument("--width", type=int, default=32)
+    ap.add_argument("--chip", type=int, default=0)
+    ap.add_argument(
+        "--engine-factory",
+        help="trusted local module:callable accepting config, weights, width, chip",
+    )
+    a = ap.parse_args()
+    from multiprocessing import resource_tracker, shared_memory
+
+    from huggingface_hub import snapshot_download
+    from opt_prime.accel.pd import SamplingParams
+    from opt_prime.accel.pd.sampling import select_token
+    from safetensors import safe_open
+
+    out = sys.stdout
+    with contextlib.redirect_stdout(sys.stderr):
+        path = (
+            Path(a.model)
+            if Path(a.model).is_dir()
+            else Path(snapshot_download(a.model, local_files_only=True))
+        )
+        config = json.loads((path / "config.json").read_text())
+        if a.engine_factory:
+            Prefill = engine_class(a.engine_factory)
+        else:
+            from prefill import Prefill
+            from spec import validate
+
+            config = validate(config)
+        shape = (a.slots, 2, a.layers, a.kv_heads, a.max_context, a.head_dim)
+        if min(shape) <= 0 or (a.layers, a.kv_heads, a.head_dim) != cache_geometry(
+            config
+        ):
+            raise ValueError("shared-memory geometry does not match checkpoint")
+        weights = {}
+        for shard in sorted(path.glob("*.safetensors")):
+            with safe_open(shard, framework="pt") as f:
+                for key in f.keys():  # noqa: SIM118 - safe_open is not iterable
+                    weights[key] = f.get_tensor(key).float()
+        engine = Prefill(config, weights, width=a.width, chip=a.chip)
+        shm = shared_memory.SharedMemory(name=a.shm)
+        # The parent owns unlinking; this child must not unlink another process's slab.
+        resource_tracker.unregister(shm._name, "shared_memory")
+        try:
+            slab = np.ndarray(shape, dtype=np.uint16, buffer=shm.buf)
+            print(json.dumps({"ready": True}), file=out, flush=True)
+            for line in sys.stdin:
+                req = {}
+                try:
+                    req = json.loads(line)
+                    validate_request(slab, req, a.width, config["vocab_size"])
+                    sampling = dict(req.get("sampling") or {})
+                    sampling["stop_token_ids"] = tuple(
+                        sampling.get("stop_token_ids", ())
+                    )
+                    sampling = SamplingParams(**sampling)
+                    t = time.perf_counter()
+                    k, v, logits = engine.prefill(list(req["tokens"]))
+                    token = select_token(logits, sampling, len(req["tokens"]))
+                    n = store_result(slab, req, k, v)
+                    result = {
+                        "id": req["id"],
+                        "token": int(token),
+                        "n": n,
+                        "cached": 0,
+                        "prefill_s": time.perf_counter() - t,
+                    }
+                    trace_path = os.environ.get("PD_TRACE_PATH")
+                    if trace_path:
+                        with open(trace_path, "a") as trace:
+                            trace.write(json.dumps(dict(wire_id=req["id"], start_s=t,
+                                end_s=t + result["prefill_s"])) + "\n")
+                except Exception as error:  # noqa: BLE001 - report errors through the worker protocol
+                    result = {"id": req.get("id"), "error": repr(error)}
+                print(json.dumps(result), file=out, flush=True)
+        finally:
+            shm.close()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
index a541a6f0..d302a7e7 100644
--- a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
+++ b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
@@ -51,3 +51,69 @@ CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=2 MKL_NUM_THREADS=2 PYTHONPATH=. /home/g
 ```
 
 The full run includes the added cancellation assertion that an orphaned producer keeps the batcher non-idle, followed by safe request-ID and source-slot reuse. Tests use a controlled future boundary to expose ordering, real TorchPrefillEngine KV, a fake Rebellions SDK import, and independent greedy outputs. Hardware throughput and a real producer/decode timeline remain unmeasured; no speedup claim. Logs: atom253-{red,cli-red,focused,full}.log in analysis/serving-matrix-201.
+
+## Live warm-engine hardware validation started
+
+New owned Pod `prefetch253` in namespace `codex-serving-matrix-201`, one RNGD and one assigned ATOM, CPU4requested/16limit,memory128Gi,4hourdeadline. Device bootstrap verified only its assigned ATOM opened. Prior matrix Pod was deleted. New physical assignment differs from the prior matrix, so off/on comparisons use the same warm instance rather than treating earlier absolute timings as a paired baseline.
+
+Core3e16c33; candidate modules copied from its AtomBatcher, SubprocessPrefillWorker and BatchedService. HTTP candidate combines the previously tested9e442cd signal-safe writer with d0f6f12 readiness condition. Worker253 preserves worker234 protocol and records completed prefill+slab-write intervals using perf_counter on the same host clock as decoder calls. These are host-call intervals, not pure device kernel traces.
+
+`atom_pipeline.py` starts the SDK/producer once, serves real nonstream HTTP, and switches remote_prefetch only between drained batches. Inputs128/8192,outputs32/128,c1/4,3repeats with off/on order alternating by repeat; no cache. Exact token references are warm off-mode outputs; native32-token references are used separately for actual normal-EOS checks. First-token timing is owner emission, not client SSE; cold load is excluded. Lifecycle tests cancel an in-flight prefetched request then check reuse, and terminate the owned producer while an already-imported request keeps decoding, checking503admission/readiness afterward.
+
+The script contains assertions for geometry/allocation, every output, stop reasons, quiescent mode switches, cancellation, producer exit, draining, and no poisoned decoder. It has passed syntax compilation and actual SDK startup; remaining checks are pending the live run, not yet a pass claim.
+
+Exact orchestrator command:
+```bash
+python3 analysis/serving-matrix-201/run_atom253.py > analysis/serving-matrix-201/atom253-queue.log 2>&1
+```
+Model order: KONI8B,Qwen3-4B,Qwen3-0.6B,Gemma3-1B. Expanded in-Pod arguments are in atom253-queue.log; remote wrapper run-pipeline253.sh uses the established bootstrap/SDK environment. Local raw outputs use atom253-<model>-a.json and .producer.jsonl.
+
+Source snapshots for reproduction:
+- `atom_pipeline253-initial.py` SHA256 `d8b7a0587afad6ef3713c35b215872d9dc685700bd317c72953b56bcb7be5ec0`
+- `worker253.py` SHA256 `b84405509d6e3e3529d6fc2ce208463a624531a4efe62097ba8590836ff44b7f`
+- `llmd253.py` SHA256 `849165a74a2046f7bc201d346201bf1fa98ef4d7ec0fe4bd71498614d5ec47fd`
+- `worker_python253.sh` SHA256 `7fe175b5c13fb8a3d913d5f42af906e7916de2d5cb1cba64905e5e2cea8ca935`
+
+## First warm KONI snapshot (incomplete)
+
+Actual run remains live in the owned benchmark Pod. Cold load 434.679s excluded. Eight fixed-output checks and four normal-EOS checks completed. Six timed batches recorded; three-repeat matrix and fault lifecycle are still pending. For input128/output32, first paired repeat c1 off6.04447/on6.07041tok_s (+0.43%); c4 off6.07493/on8.58787 (+41.37%). Input128/output128/c1 off10.95522/on10.97215 (+0.15%). Do not generalize a single repeat to the final model result.
+
+Correlated completed producer host-call intervals with decoder host-call intervals: measured off-mode 0/6 overlap, on-mode 3/6 overlap with union6.02735s. This includes prefill and KV export and is not device-kernel overlap proof. Snapshot tokens were rechecked against the warm off-mode reference. Analyzer union logic checked with overlapping intervals and exclusion of the same request. Files: atom253-koni-snapshot.json, atom253-koni-snapshot.producer.jsonl, atom253-koni-partial-summary.json; analyzer summarize_atom253.py under analysis/serving-matrix-201. Full results remain authoritative when the queue finishes.
+
+Follow-up snapshot: ten timed batches completed, run still live. Input128/output128/c4 first pair off10.84835/on13.67179tok_s (+26.03%). Input8192/output32/c1 first pair off4.73979/on4.80128 (+1.30%); long-input concurrent pair still pending. Host-call overlap totals off0/11, on6/11 with15.42060s union across completed measured producer calls. No final speedup or lifecycle pass claim.
+
+## Two-repeat KONI observation (34/48 batches)
+
+All eight conditions have at least two completed off/on pairs. At c4, per-repeat throughput changes: input128/output32 +41.37%/+39.68%; input128/output128 +26.03%/+25.03%; input8192/output32 +31.57%/+32.92%; input8192/output128 +23.51%/+24.53%. Single-request pairs remain near neutral. Off-mode measured host overlap0/41; on-mode24/41 completed producer calls overlap another request decode, union64.2031s. Run still active; final repeat and lifecycle checks pending. Partial summary updated in analysis/serving-matrix-201/atom253-koni-partial-summary.json.
+
+## Queue-latency analysis of the same 34-batch snapshot
+
+Added paired latency summaries using the median of each completed batch's request medians (not a pooled percentile). At c4, off/on first-token owner-emission and E2E seconds:
+
+| input/output | first-token off/on | E2E off/on |
+|---|---:|---:|
+|128/32|11.045/8.041|13.125/10.119|
+|128/128|20.909/16.051|29.429/24.578|
+|8192/32|14.437/11.223|16.658/13.446|
+|8192/128|25.119/19.679|34.236/28.790|
+
+These include queue waiting in the B1 decoder and two completed paired repetitions. First token is server owner emission, not client receipt/SSE. Rechecked all34timed batches' tokens against the warm off-mode references. Third-repeat/lifecycle completion remains pending.
+
+## KONI complete: performance, correctness and lifecycle
+
+The owned queue returned exit0 and advanced to Qwen3-4B. All48timed batches pass exact warm-off token parity;8fixed-output check groups and4normal-EOS groups pass. Three matched off/on repeats, alternating order, on the same loaded producer and decoder; cold434.679s excluded. Median tok/s:
+
+| input | output | concurrency | off | on | change |
+|---:|---:|---:|---:|---:|---:|
+|128|32|1|6.074|6.070|-0.06%|
+|128|32|4|6.075|8.558|+40.87%|
+|128|128|1|10.939|10.936|-0.03%|
+|128|128|4|10.873|13.674|+25.75%|
+|8192|32|1|4.741|4.732|-0.19%|
+|8192|32|4|4.783|6.293|+31.57%|
+|8192|128|1|9.399|9.391|-0.08%|
+|8192|128|4|9.409|11.618|+23.48%|
+
+Lifecycle: cancelled prefetched request499, recovery request exact; producer termination fails the prefetched request500, new admission503 and readiness503. In both cases the already-imported current request retains its full128-token output; batcher drains, has no poisoned decoder, no remaining request IDs and no reserved prefetch.
+
+Measured host-call timeline: off0/60 completed producer calls overlap another request decode; on36/60 overlap, union96.42009s. This is prefill+export host interval overlap, not device-kernel overlap proof. Raw2.23MB atom253-koni-a.json, producer trace and atom253-koni-summary.json. Analyzer rechecked all48token arrays against warm-off references. Other three models remain pending; do not generalize KONI's gain to them. B1/cache-off/width8192 research engine only; not native vendor engine.

From d8e74ffb3ab6cb8aec48e2af10df04a2c16afb0b Mon Sep 17 00:00:00 2001
From: gspark <gspark@etri.re.kr>
Date: Sat, 24 Oct 2026 04:06:25 +0900
Subject: [PATCH 3/5] exp: validate Qwen3-4B prefetch performance and fault
 isolation (#253)

---
 .../pd/http_matrix/.research/events.jsonl     |      1 +
 opt_prime/examples/pd/http_matrix/STATUS.md   |      2 +
 .../evidence253/atom253-qwen4b-a.json         | 116840 +++++++++++++++
 .../atom253-qwen4b-a.producer.jsonl           |    176 +
 .../evidence253/atom253-qwen4b-summary.json   |    210 +
 .../2026-10-24-atom-prefetch253.md            |     25 +
 6 files changed, 117254 insertions(+)
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.json
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.producer.jsonl
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-summary.json

diff --git a/opt_prime/examples/pd/http_matrix/.research/events.jsonl b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
index cbab8434..f10b0c1a 100644
--- a/opt_prime/examples/pd/http_matrix/.research/events.jsonl
+++ b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
@@ -4,3 +4,4 @@
 {"id": "e4993823527144b5a14e6441b1cd5c01", "ts": "2026-10-23T21:29:56+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Published production EOS fix and real KONI HTTP evidence in draft PR230 (e5fa087). Final factory/streaming/sampling/batched suite22passed; hardware checker5/5 cases passed; changed files sensitive-clean,4unchanged baseline findings in this branch.", "next": "Verify same HTTP factory on NPU; continue full four-model long semantic and heterogeneous PD validation.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "gpu"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-http-final.json", "size": 5067, "sha256": "d5be9a4a52a6485f"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "328b8349e9974a059ddc7e1a8a485e2c", "ts": "2026-10-23T21:32:23+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Real ATOM KONI HTTP also passes5/5 baseline/fixed/ignore/stream/reuse checks using same production factory: config-only length vs union stop. GPU+ATOM now10/10 expected outcomes; no SDK/artifact rebuild.", "next": "Update PR230 with NPU evidence; finish KONI medium-context RNGD handoff and broader PD work.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "atom", "kv_blocks": "1"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-atom-http.json", "size": 5199, "sha256": "4735255db379ff00"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "336aabdd36624e148ea41f974e84af8e", "ts": "2026-10-24T03:34:33+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "KONI complete: 48 batches exact, 8 fixed-output and 4 EOS groups passed; cancel/reuse and producer-exit preservation/503 gates passed. c4 median gains23.48-40.87%; c1 neutral. Qwen3-4B started.", "next": "Finish Qwen3-4B, Qwen3-0.6B and Gemma in current queue; publish KONI evidence to draft PR255", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "KONI-8B", "producer_width": "8192", "prefetch": "true"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-koni-summary.json", "size": 5612, "sha256": "b66019a0a29d1e3a"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark", "rngd"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
+{"id": "5ae1dbf4a057408187ad603c57f1cd7b", "ts": "2026-10-24T04:06:11+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "Qwen3-4B complete:48batches exact,8fixed/4EOS groups pass; cancel/reuse and producer-failure isolation/503 gates pass. c4 median gains21.20-41.00%; c1 near-neutral. Qwen0.6 started. Separate GPU-route numerical issue256 stays open.", "next": "Complete Qwen0.6/Gemma prefetch queue; publish Qwen4 results to PR255; run prepared forced-prefix diagnostic after local GPU matrix", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "Qwen3-4B", "producer_width": "8192"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-qwen4b-summary.json", "size": 5590, "sha256": "275d53eef400a031"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark", "rngd"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
diff --git a/opt_prime/examples/pd/http_matrix/STATUS.md b/opt_prime/examples/pd/http_matrix/STATUS.md
index 9f3ec9e4..02d153b5 100644
--- a/opt_prime/examples/pd/http_matrix/STATUS.md
+++ b/opt_prime/examples/pd/http_matrix/STATUS.md
@@ -43,3 +43,5 @@ Candidate exports airm_pd_producer_seconds_total{stage="prefill"|"transfer"} fro
 Opt-in remote_prefetch / --pd-prefetch-next implemented for single-lane ATOM remote-only PD. Keep one source result reserved through owner import; cancelled writers drain before reuse. Prefix/host cache admission remains late, so early prefill transfers the full prompt.35focused tests and full511passed34skipped253subtests; real four-model hardware pipeline/performance validation pending. No speedup claim. See experiments/2026-10-24-atom-prefetch253.md.
 
 KONI hardware prefetch validation complete:48timed batches exact,8fixed-output/4EOS groups pass, cancellation/reuse and producer-exit isolation/readiness503 pass. Same-warm-instance off/on3repeat c4 gains23.48–40.87%; c1 near-neutral. Host producer/decode overlap only in enabled mode. Remaining three models pending; no default promotion. See evidence253/atom253-koni-summary.json and experiment.
+
+Qwen3-4B also passes48timed batches,8fixed/4EOS groups and live cancellation/producer-exit isolation. c4 median gains21.20–41.00%; c1 near-neutral. Qwen0.6/Gemma remain pending. This does not resolve the separate GPU decoder pre-EOS drift in#256.
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.json
new file mode 100644
index 00000000..e917f4f9
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.json
@@ -0,0 +1,116840 @@
+{
+  "passed": true,
+  "stage": "complete",
+  "model": "Qwen/Qwen3-4B",
+  "runtime_commit": "3e16c33",
+  "torch": "2.11.0+cpu",
+  "physical_atom": 1,
+  "physical_rngd": 1,
+  "slots": 1,
+  "producer_width": 8192,
+  "producer_cache": false,
+  "decoder_cache": false,
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diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.producer.jsonl b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.producer.jsonl
new file mode 100644
index 00000000..f3f94e3f
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-a.producer.jsonl
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+{"wire_id": 105, "start_s": 756831.160497164, "end_s": 756834.506657516}
+{"wire_id": 106, "start_s": 756837.751681992, "end_s": 756841.054043812}
+{"wire_id": 107, "start_s": 756844.330583771, "end_s": 756847.683530708}
+{"wire_id": 108, "start_s": 756856.362018304, "end_s": 756859.716094068}
+{"wire_id": 109, "start_s": 756866.292346339, "end_s": 756869.613096158}
+{"wire_id": 110, "start_s": 756876.190490949, "end_s": 756879.371460051}
+{"wire_id": 111, "start_s": 756885.961764251, "end_s": 756889.313946639}
+{"wire_id": 112, "start_s": 756895.97529252, "end_s": 756898.996416853}
+{"wire_id": 113, "start_s": 756900.266260272, "end_s": 756903.274319384}
+{"wire_id": 114, "start_s": 756904.527209641, "end_s": 756907.551400738}
+{"wire_id": 115, "start_s": 756907.641821988, "end_s": 756910.604869835}
+{"wire_id": 116, "start_s": 756910.698436217, "end_s": 756913.6855553}
+{"wire_id": 117, "start_s": 756913.773881979, "end_s": 756916.782835665}
+{"wire_id": 118, "start_s": 756918.059754538, "end_s": 756921.053154777}
+{"wire_id": 119, "start_s": 756922.251227809, "end_s": 756925.250242757}
+{"wire_id": 120, "start_s": 756926.449716763, "end_s": 756929.438739791}
+{"wire_id": 121, "start_s": 756930.64044791, "end_s": 756933.618312386}
+{"wire_id": 122, "start_s": 756934.894632875, "end_s": 756937.889520605}
+{"wire_id": 123, "start_s": 756942.699546031, "end_s": 756945.705057632}
+{"wire_id": 124, "start_s": 756950.521467837, "end_s": 756953.50432429}
+{"wire_id": 125, "start_s": 756953.595136655, "end_s": 756956.539732079}
+{"wire_id": 126, "start_s": 756958.367316614, "end_s": 756961.356831137}
+{"wire_id": 127, "start_s": 756963.136808917, "end_s": 756966.14668669}
+{"wire_id": 128, "start_s": 756972.653454425, "end_s": 756975.608651144}
+{"wire_id": 129, "start_s": 756980.382825784, "end_s": 756983.345207348}
+{"wire_id": 130, "start_s": 756988.119363502, "end_s": 756991.127966129}
+{"wire_id": 131, "start_s": 756995.888891612, "end_s": 756998.890820483}
+{"wire_id": 132, "start_s": 757003.72050974, "end_s": 757006.671248592}
+{"wire_id": 133, "start_s": 757007.933974543, "end_s": 757010.883624215}
+{"wire_id": 134, "start_s": 757012.177668446, "end_s": 757015.061730141}
+{"wire_id": 135, "start_s": 757016.264757745, "end_s": 757019.239703757}
+{"wire_id": 136, "start_s": 757020.425212963, "end_s": 757023.375748038}
+{"wire_id": 137, "start_s": 757024.572508119, "end_s": 757027.891108354}
+{"wire_id": 138, "start_s": 757029.171259605, "end_s": 757032.19418951}
+{"wire_id": 139, "start_s": 757032.282731002, "end_s": 757035.281062747}
+{"wire_id": 140, "start_s": 757035.369298616, "end_s": 757038.343462236}
+{"wire_id": 141, "start_s": 757038.465397898, "end_s": 757041.445117496}
+{"wire_id": 142, "start_s": 757042.685590184, "end_s": 757045.651866695}
+{"wire_id": 143, "start_s": 757050.476672984, "end_s": 757053.420436968}
+{"wire_id": 144, "start_s": 757058.25207198, "end_s": 757061.216742689}
+{"wire_id": 145, "start_s": 757065.989973429, "end_s": 757069.023770134}
+{"wire_id": 146, "start_s": 757073.789224998, "end_s": 757076.823215628}
+{"wire_id": 147, "start_s": 757081.59704828, "end_s": 757084.631187183}
+{"wire_id": 148, "start_s": 757089.472936261, "end_s": 757092.483315474}
+{"wire_id": 149, "start_s": 757092.551364407, "end_s": 757095.575672353}
+{"wire_id": 150, "start_s": 757097.304086471, "end_s": 757100.308475485}
+{"wire_id": 151, "start_s": 757102.075919031, "end_s": 757105.091363228}
+{"wire_id": 152, "start_s": 757111.596224358, "end_s": 757114.9405311}
+{"wire_id": 153, "start_s": 757117.48405355, "end_s": 757120.836175094}
+{"wire_id": 154, "start_s": 757123.401110144, "end_s": 757126.750881315}
+{"wire_id": 155, "start_s": 757129.293237465, "end_s": 757132.659082922}
+{"wire_id": 156, "start_s": 757135.197430703, "end_s": 757138.513824787}
+{"wire_id": 157, "start_s": 757141.061789977, "end_s": 757144.391711711}
+{"wire_id": 158, "start_s": 757146.990631111, "end_s": 757150.311018779}
+{"wire_id": 159, "start_s": 757151.499758811, "end_s": 757154.674164191}
+{"wire_id": 160, "start_s": 757155.90086798, "end_s": 757159.251753981}
+{"wire_id": 161, "start_s": 757160.522678042, "end_s": 757163.855906354}
+{"wire_id": 162, "start_s": 757166.466417846, "end_s": 757169.815441471}
+{"wire_id": 163, "start_s": 757176.532482246, "end_s": 757179.895574077}
+{"wire_id": 164, "start_s": 757186.633413129, "end_s": 757190.320527497}
+{"wire_id": 165, "start_s": 757196.968147724, "end_s": 757200.304122222}
+{"wire_id": 166, "start_s": 757206.895304958, "end_s": 757209.997371412}
+{"wire_id": 167, "start_s": 757216.584267138, "end_s": 757219.774351353}
+{"wire_id": 168, "start_s": 757226.457149691, "end_s": 757229.775121773}
+{"wire_id": 169, "start_s": 757230.984163898, "end_s": 757234.342153769}
+{"wire_id": 170, "start_s": 757237.562751498, "end_s": 757240.894082128}
+{"wire_id": 171, "start_s": 757244.16376737, "end_s": 757247.51459983}
+{"wire_id": 172, "start_s": 757256.226019691, "end_s": 757259.571683391}
+{"wire_id": 173, "start_s": 757260.782079912, "end_s": 757264.12353045}
+{"wire_id": 174, "start_s": 757264.194032969, "end_s": 757267.526215023}
+{"wire_id": 175, "start_s": 757270.102636625, "end_s": 757273.359769145}
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-summary.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-summary.json
new file mode 100644
index 00000000..69ab6917
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen4b-summary.json
@@ -0,0 +1,210 @@
+{
+  "model": "Qwen/Qwen3-4B",
+  "stage": "complete",
+  "passed": true,
+  "measured_batches": 48,
+  "rows": [
+    {
+      "input_tokens": 128,
+      "output_tokens": 32,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 7.610776413776239,
+      "on_tok_s": 7.540415907125816,
+      "change_pct": -0.9244852670098669,
+      "paired_changes_pct": [
+        -1.1852556724907037,
+        -0.7112826000647776,
+        -0.6612382381502746
+      ],
+      "off_median_first_token_s": 3.0515774809755385,
+      "on_median_first_token_s": 3.0859774929704145,
+      "off_median_e2e_s": 4.20442083501257,
+      "on_median_e2e_s": 4.243688051006757
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 32,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 7.5658326411754935,
+      "on_tok_s": 9.510626920328264,
+      "change_pct": 25.70496033138012,
+      "paired_changes_pct": [
+        24.931673173126544,
+        24.52699325099992,
+        25.70570124846645
+      ],
+      "off_median_first_token_s": 9.338594853470568,
+      "on_median_first_token_s": 7.710929243534338,
+      "off_median_e2e_s": 10.488230757473502,
+      "on_median_e2e_s": 8.861569961009081
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 128,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 16.471839982412632,
+      "on_tok_s": 16.50290583935368,
+      "change_pct": 0.18859979804453086,
+      "paired_changes_pct": [
+        -0.017284937785644328,
+        0.18859979804453086,
+        0.21806065283742626
+      ],
+      "off_median_first_token_s": 3.0591373570496216,
+      "on_median_first_token_s": 3.0490428019547835,
+      "off_median_e2e_s": 7.770699504995719,
+      "on_median_e2e_s": 7.756013568956405
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 128,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 16.458474429816196,
+      "on_tok_s": 23.207025727122677,
+      "change_pct": 41.00350446260557,
+      "paired_changes_pct": [
+        40.9369138495621,
+        40.486542078446085,
+        41.36254858800778
+      ],
+      "off_median_first_token_s": 14.725914461538196,
+      "on_median_first_token_s": 10.194778928533196,
+      "off_median_e2e_s": 19.44344543851912,
+      "on_median_e2e_s": 14.908529031497892
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 32,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 5.4781721886797206,
+      "on_tok_s": 5.472463322668753,
+      "change_pct": -0.10421114587753078,
+      "paired_changes_pct": [
+        0.1688560808441597,
+        0.001406059833675144,
+        -0.4209167917773149
+      ],
+      "off_median_first_token_s": 4.521871907985769,
+      "on_median_first_token_s": 4.527103912900202,
+      "off_median_e2e_s": 5.8412074180087075,
+      "on_median_e2e_s": 5.847284951945767
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 32,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 5.4420091643113935,
+      "on_tok_s": 6.595476676396093,
+      "change_pct": 21.19561869996691,
+      "paired_changes_pct": [
+        18.348369365494932,
+        22.242063257606137,
+        21.19561869996691
+      ],
+      "off_median_first_token_s": 13.410464637505356,
+      "on_median_first_token_s": 11.281109626521356,
+      "off_median_e2e_s": 14.734865471546073,
+      "on_median_e2e_s": 12.600807979528327
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 128,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 12.802285837969874,
+      "on_tok_s": 12.786162809569582,
+      "change_pct": -0.12593866911230212,
+      "paired_changes_pct": [
+        0.5436002012014107,
+        -0.015867910530698026,
+        -0.12593866911230212
+      ],
+      "off_median_first_token_s": 4.577717315987684,
+      "on_median_first_token_s": 4.590946282958612,
+      "off_median_e2e_s": 9.998040177044459,
+      "on_median_e2e_s": 10.010684791952372
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 128,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 12.886042941691356,
+      "on_tok_s": 17.252816124655105,
+      "change_pct": 33.88761936246185,
+      "paired_changes_pct": [
+        34.24490680035752,
+        33.187079206573934,
+        33.88761936246185
+      ],
+      "off_median_first_token_s": 19.405796252482105,
+      "on_median_first_token_s": 14.367367321974598,
+      "off_median_e2e_s": 24.839708355953917,
+      "on_median_e2e_s": 19.798965742986184
+    }
+  ],
+  "latency_kind": "median of matched batch medians; first token is owner emission, not client SSE",
+  "overlap_kind": "producer prefill+export host-call versus other-request decode host-call; not device-kernel proof",
+  "overlap": {
+    "False": {
+      "completed_measured_producers": 60,
+      "with_overlap": 0,
+      "total_overlap_s": 0.0
+    },
+    "True": {
+      "completed_measured_producers": 60,
+      "with_overlap": 36,
+      "total_overlap_s": 78.42755955655593
+    }
+  },
+  "lifecycle": {
+    "cancel": {
+      "victim_status": 499,
+      "first_tokens_equal": true,
+      "drained": true
+    },
+    "worker_exit": {
+      "victim_status": 500,
+      "first_tokens_equal": true,
+      "drained": true
+    }
+  }
+}
diff --git a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
index d302a7e7..37870df2 100644
--- a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
+++ b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
@@ -117,3 +117,28 @@ The owned queue returned exit0 and advanced to Qwen3-4B. All48timed batches pass
 Lifecycle: cancelled prefetched request499, recovery request exact; producer termination fails the prefetched request500, new admission503 and readiness503. In both cases the already-imported current request retains its full128-token output; batcher drains, has no poisoned decoder, no remaining request IDs and no reserved prefetch.
 
 Measured host-call timeline: off0/60 completed producer calls overlap another request decode; on36/60 overlap, union96.42009s. This is prefill+export host interval overlap, not device-kernel overlap proof. Raw2.23MB atom253-koni-a.json, producer trace and atom253-koni-summary.json. Analyzer rechecked all48token arrays against warm-off references. Other three models remain pending; do not generalize KONI's gain to them. B1/cache-off/width8192 research engine only; not native vendor engine.
+
+Qwen3-4B advanced from loading to running with load_s801.25765 on the same owned Pod. Warmup/output checks started; no completed performance batches yet at observation. This is excluded cold initialization, not measured request latency. Prior controlled Qwen3-4B initialization810.53s provides context but is not a paired startup optimization result.
+
+Qwen3-4B off-mode prechecks completed:4fixed-output groups (16responses) match warm off-mode references;2normal-EOS groups (8responses) match nativeATOM references truncated through configured EOS. Independently rechecked snapshot token arrays. Enabled-mode prechecks and48timed batches remain pending. Producer trace advanced beyond wire_id24, confirming actual execution after initialization. Snapshot atom253-qwen4b-snapshot.json.
+
+Qwen3-4B both modes passed8fixed-output groups and4normal-EOS groups, then entered timing. Five batches captured. First input128/output32/c4 pair: off7.56043/on9.44537tok_s (+24.93%); first-token owner-emission9.43834/7.75430s and E2E10.59287/8.90573s. c1 off7.61078/on7.52057 (-1.19%). Enabled host-call overlap3/5 completed measured producer calls, off0/6. Single-repeat partial result only; long-input performance and lifecycle pending. Snapshot fixed/timed token arrays rechecked against warm-off references. Raw atom253-qwen4b-snapshot.json and producer trace; summary atom253-qwen4b-partial-summary.json.
+
+Qwen3-4B14/48batch snapshot: first c4 pairs input128/output128 off16.458/on23.196tok_s (+40.94%); input8192/output32 off5.483/on6.489 (+18.35%). These remain single-repeat observations, with long128/c4 and subsequent repetitions/lifecycle pending. Updated partial summary and raw snapshot retained.
+
+## Qwen3-4B complete: paired performance and live faults
+
+Exit0; queue advanced to Qwen3-0.6B.48timed batches exact versus warm-off reference,8fixed-output and4normal-EOS groups pass. Three alternating off/on repetitions in the same loaded engines, cold801.258s excluded.
+
+| input | output | c | off tok/s | on tok/s | change |
+|---:|---:|---:|---:|---:|---:|
+|128|32|1|7.611|7.540|-0.92%|
+|128|32|4|7.566|9.511|+25.70%|
+|128|128|1|16.472|16.503|+0.19%|
+|128|128|4|16.458|23.207|+41.00%|
+|8192|32|1|5.478|5.472|-0.10%|
+|8192|32|4|5.442|6.595|+21.20%|
+|8192|128|1|12.802|12.786|-0.13%|
+|8192|128|4|12.886|17.253|+33.89%|
+
+Cancellation: victim499, exact recovery, current128-token decode preserved. Producer termination: victim500, subsequent request503/readiness503, current decode preserved, batcher drained with no reservation or poisoned state. Measured host-call overlap off0/60 and on36/60, union78.42756s; not device-kernel proof. Raw atom253-qwen4b-a.json and trace, final atom253-qwen4b-summary.json. This validates the ATOM prefetch change; the separate RNGD-to-GPU Qwen4 pre-EOS discrepancy tracked in#256 remains unresolved.

From 4bee440a2f4e6471451dc2201ae103c17e823755 Mon Sep 17 00:00:00 2001
From: gspark <gspark@etri.re.kr>
Date: Sat, 24 Oct 2026 04:18:58 +0900
Subject: [PATCH 4/5] exp: validate Qwen3-0.6B ATOM prefetch and lifecycle
 (#253)

---
 .../pd/http_matrix/.research/events.jsonl     |      1 +
 opt_prime/examples/pd/http_matrix/STATUS.md   |      2 +
 .../evidence253/atom253-qwen06b-a.json        | 116840 +++++++++++++++
 .../atom253-qwen06b-a.producer.jsonl          |    176 +
 .../evidence253/atom253-qwen06b-summary.json  |    210 +
 .../2026-10-24-atom-prefetch253.md            |     17 +
 6 files changed, 117246 insertions(+)
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-a.json
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-a.producer.jsonl
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-summary.json

diff --git a/opt_prime/examples/pd/http_matrix/.research/events.jsonl b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
index f10b0c1a..347d09b7 100644
--- a/opt_prime/examples/pd/http_matrix/.research/events.jsonl
+++ b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
@@ -5,3 +5,4 @@
 {"id": "328b8349e9974a059ddc7e1a8a485e2c", "ts": "2026-10-23T21:32:23+09:00", "task": "Tokenizer EOS in batched serving (aicomp #229)", "result": "Real ATOM KONI HTTP also passes5/5 baseline/fixed/ignore/stream/reuse checks using same production factory: config-only length vs union stop. GPU+ATOM now10/10 expected outcomes; no SDK/artifact rebuild.", "next": "Update PR230 with NPU evidence; finish KONI medium-context RNGD handoff and broader PD work.", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"backend": "atom", "kv_blocks": "1"}, "artifacts": [{"path": "analysis/serving-matrix-201/eos229-koni-atom-http.json", "size": 5199, "sha256": "4735255db379ff00"}], "experiments": ["experiments/2026-10-23-serving-eos229.md"], "labels": ["bug"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "336aabdd36624e148ea41f974e84af8e", "ts": "2026-10-24T03:34:33+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "KONI complete: 48 batches exact, 8 fixed-output and 4 EOS groups passed; cancel/reuse and producer-exit preservation/503 gates passed. c4 median gains23.48-40.87%; c1 neutral. Qwen3-4B started.", "next": "Finish Qwen3-4B, Qwen3-0.6B and Gemma in current queue; publish KONI evidence to draft PR255", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "KONI-8B", "producer_width": "8192", "prefetch": "true"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-koni-summary.json", "size": 5612, "sha256": "b66019a0a29d1e3a"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark", "rngd"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "5ae1dbf4a057408187ad603c57f1cd7b", "ts": "2026-10-24T04:06:11+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "Qwen3-4B complete:48batches exact,8fixed/4EOS groups pass; cancel/reuse and producer-failure isolation/503 gates pass. c4 median gains21.20-41.00%; c1 near-neutral. Qwen0.6 started. Separate GPU-route numerical issue256 stays open.", "next": "Complete Qwen0.6/Gemma prefetch queue; publish Qwen4 results to PR255; run prepared forced-prefix diagnostic after local GPU matrix", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "Qwen3-4B", "producer_width": "8192"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-qwen4b-summary.json", "size": 5590, "sha256": "275d53eef400a031"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark", "rngd"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
+{"id": "28246e6d99fb4667a780a2e4750917e2", "ts": "2026-10-24T04:18:23+09:00", "task": "Four-model serving matrix (aicomp #201)", "result": "Qwen3-0.6B ATOM prefetch48 batches plus parity/EOS/lifecycle passed; 8K/output128/c4 35.016->48.231 tok/s (+37.74%). KONI GPU drift localized to pre-EOS indices64/98 at output128; output32 passes. Gemma active on both paths.", "next": "Complete Gemma matrix and GPU lifecycle; diagnose Qwen4/KONI pre-EOS drift", "state": "active", "done": false, "blocker": "", "metrics": {"tok_s": "48.23077851745031"}, "params": {"model": "Qwen3-0.6B", "input_tokens": "8192", "output_tokens": "128", "concurrency": "4"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-qwen06b-summary.json", "size": 5583, "sha256": "f420a2447bd438af"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark"], "review": false, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
diff --git a/opt_prime/examples/pd/http_matrix/STATUS.md b/opt_prime/examples/pd/http_matrix/STATUS.md
index 02d153b5..34f41cd3 100644
--- a/opt_prime/examples/pd/http_matrix/STATUS.md
+++ b/opt_prime/examples/pd/http_matrix/STATUS.md
@@ -45,3 +45,5 @@ Opt-in remote_prefetch / --pd-prefetch-next implemented for single-lane ATOM rem
 KONI hardware prefetch validation complete:48timed batches exact,8fixed-output/4EOS groups pass, cancellation/reuse and producer-exit isolation/readiness503 pass. Same-warm-instance off/on3repeat c4 gains23.48–40.87%; c1 near-neutral. Host producer/decode overlap only in enabled mode. Remaining three models pending; no default promotion. See evidence253/atom253-koni-summary.json and experiment.
 
 Qwen3-4B also passes48timed batches,8fixed/4EOS groups and live cancellation/producer-exit isolation. c4 median gains21.20–41.00%; c1 near-neutral. Qwen0.6/Gemma remain pending. This does not resolve the separate GPU decoder pre-EOS drift in#256.
+
+Qwen3-0.6B: 48 prefetch off/on batches and fixed-output/EOS/lifecycle checks passed. At 8K input/output128/c4, 35.016 -> 48.231 tok/s (+37.74%); c1 roughly neutral. Gemma hardware validation remains pending.
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-a.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-a.json
new file mode 100644
index 00000000..bed4d844
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-a.json
@@ -0,0 +1,116840 @@
+{
+  "passed": true,
+  "stage": "complete",
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+  "runtime_commit": "3e16c33",
+  "torch": "2.11.0+cpu",
+  "physical_atom": 1,
+  "physical_rngd": 1,
+  "slots": 1,
+  "producer_width": 8192,
+  "producer_cache": false,
+  "decoder_cache": false,
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diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-a.producer.jsonl b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-a.producer.jsonl
new file mode 100644
index 00000000..c5e30214
--- /dev/null
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diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-summary.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-summary.json
new file mode 100644
index 00000000..c5d3de5d
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-qwen06b-summary.json
@@ -0,0 +1,210 @@
+{
+  "model": "Qwen/Qwen3-0.6B",
+  "stage": "complete",
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+  "latency_kind": "median of matched batch medians; first token is owner emission, not client SSE",
+  "overlap_kind": "producer prefill+export host-call versus other-request decode host-call; not device-kernel proof",
+  "overlap": {
+    "False": {
+      "completed_measured_producers": 60,
+      "with_overlap": 0,
+      "total_overlap_s": 0.0
+    },
+    "True": {
+      "completed_measured_producers": 60,
+      "with_overlap": 36,
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+    }
+  },
+  "lifecycle": {
+    "cancel": {
+      "victim_status": 499,
+      "first_tokens_equal": true,
+      "drained": true
+    },
+    "worker_exit": {
+      "victim_status": 500,
+      "first_tokens_equal": true,
+      "drained": true
+    }
+  }
+}
diff --git a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
index 37870df2..c6600636 100644
--- a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
+++ b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
@@ -142,3 +142,20 @@ Exit0; queue advanced to Qwen3-0.6B.48timed batches exact versus warm-off refere
 |8192|128|4|12.886|17.253|+33.89%|
 
 Cancellation: victim499, exact recovery, current128-token decode preserved. Producer termination: victim500, subsequent request503/readiness503, current decode preserved, batcher drained with no reservation or poisoned state. Measured host-call overlap off0/60 and on36/60, union78.42756s; not device-kernel proof. Raw atom253-qwen4b-a.json and trace, final atom253-qwen4b-summary.json. This validates the ATOM prefetch change; the separate RNGD-to-GPU Qwen4 pre-EOS discrepancy tracked in#256 remains unresolved.
+
+## Qwen3-0.6B completed
+
+Runtime 3e16c33; 48 timed batches, eight fixed-output check groups and four normal-EOS groups passed; cancellation and producer-exit lifecycle passed. Cold initialization 326.490 s excluded. Input 128/8192, output32/128, concurrency1/4, three alternating repeats per condition. Raw atom253-qwen06b-a.json and producer trace; summary atom253-qwen06b-summary.json. Reproduce analysis: `python3 analysis/serving-matrix-201/summarize_atom253.py analysis/serving-matrix-201/atom253-qwen06b-a.json analysis/serving-matrix-201/atom253-qwen06b-a.producer.jsonl --output analysis/serving-matrix-201/atom253-qwen06b-summary.json`.
+
+| Input | Output | Concurrency | Off tok/s | On tok/s | Change |
+|---:|---:|---:|---:|---:|---:|
+| 128 | 32 | 1 | 24.605 | 24.618 | +0.05% |
+| 128 | 32 | 4 | 24.633 | 28.232 | +14.61% |
+| 128 | 128 | 1 | 66.049 | 65.552 | -0.75% |
+| 128 | 128 | 4 | 65.539 | 97.517 | +48.79% |
+| 8192 | 32 | 1 | 11.805 | 11.766 | -0.33% |
+| 8192 | 32 | 4 | 12.033 | 13.164 | +9.40% |
+| 8192 | 128 | 1 | 34.977 | 34.558 | -1.20% |
+| 8192 | 128 | 4 | 35.016 | 48.231 | +37.74% |
+
+Host-call overlap: off0/60, on36/60, union24.246s. Not a device-kernel trace. Single-request throughput remains approximately flat; queued requests benefit. Prefetch compares on/off identical producer, not general native GPU numerical equivalence. Gemma has now started in the existing queue.

From ffc5e6e02036e88761099bb89352340da07843fe Mon Sep 17 00:00:00 2001
From: gspark <gspark@etri.re.kr>
Date: Sat, 24 Oct 2026 04:39:45 +0900
Subject: [PATCH 5/5] exp: complete four-model ATOM prefetch validation (#253)

---
 .../pd/http_matrix/.research/events.jsonl     |      1 +
 opt_prime/examples/pd/http_matrix/STATUS.md   |      2 +
 .../evidence253/atom253-gemma-a.json          | 114982 +++++++++++++++
 .../atom253-gemma-a.producer.jsonl            |    176 +
 .../evidence253/atom253-gemma-summary.json    |    210 +
 .../2026-10-24-atom-prefetch253.md            |     17 +
 6 files changed, 115388 insertions(+)
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-a.json
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-a.producer.jsonl
 create mode 100644 opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-summary.json

diff --git a/opt_prime/examples/pd/http_matrix/.research/events.jsonl b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
index 347d09b7..653ca951 100644
--- a/opt_prime/examples/pd/http_matrix/.research/events.jsonl
+++ b/opt_prime/examples/pd/http_matrix/.research/events.jsonl
@@ -6,3 +6,4 @@
 {"id": "336aabdd36624e148ea41f974e84af8e", "ts": "2026-10-24T03:34:33+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "KONI complete: 48 batches exact, 8 fixed-output and 4 EOS groups passed; cancel/reuse and producer-exit preservation/503 gates passed. c4 median gains23.48-40.87%; c1 neutral. Qwen3-4B started.", "next": "Finish Qwen3-4B, Qwen3-0.6B and Gemma in current queue; publish KONI evidence to draft PR255", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "KONI-8B", "producer_width": "8192", "prefetch": "true"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-koni-summary.json", "size": 5612, "sha256": "b66019a0a29d1e3a"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark", "rngd"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "5ae1dbf4a057408187ad603c57f1cd7b", "ts": "2026-10-24T04:06:11+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "Qwen3-4B complete:48batches exact,8fixed/4EOS groups pass; cancel/reuse and producer-failure isolation/503 gates pass. c4 median gains21.20-41.00%; c1 near-neutral. Qwen0.6 started. Separate GPU-route numerical issue256 stays open.", "next": "Complete Qwen0.6/Gemma prefetch queue; publish Qwen4 results to PR255; run prepared forced-prefix diagnostic after local GPU matrix", "state": "active", "done": false, "blocker": "", "metrics": {}, "params": {"model": "Qwen3-4B", "producer_width": "8192"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-qwen4b-summary.json", "size": 5590, "sha256": "275d53eef400a031"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark", "rngd"], "review": true, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
 {"id": "28246e6d99fb4667a780a2e4750917e2", "ts": "2026-10-24T04:18:23+09:00", "task": "Four-model serving matrix (aicomp #201)", "result": "Qwen3-0.6B ATOM prefetch48 batches plus parity/EOS/lifecycle passed; 8K/output128/c4 35.016->48.231 tok/s (+37.74%). KONI GPU drift localized to pre-EOS indices64/98 at output128; output32 passes. Gemma active on both paths.", "next": "Complete Gemma matrix and GPU lifecycle; diagnose Qwen4/KONI pre-EOS drift", "state": "active", "done": false, "blocker": "", "metrics": {"tok_s": "48.23077851745031"}, "params": {"model": "Qwen3-0.6B", "input_tokens": "8192", "output_tokens": "128", "concurrency": "4"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-qwen06b-summary.json", "size": 5583, "sha256": "f420a2447bd438af"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark"], "review": false, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
+{"id": "082ee581602746b68a55087a6bef1646", "ts": "2026-10-24T04:39:26+09:00", "task": "ATOM next-request prefetch (aicomp #253)", "result": "Gemma48 batches and output/EOS/lifecycle passed; 8K/output128/c4 40.000->59.148tok/s (+47.87%). All4models now192timed batches passed on/off parity. Owned prefetched Pod cleanup requested; GPU corrected Gemma still running.", "next": "Publish fourth-model evidence in PR255; finish separate GPU correctness and lifecycle coverage", "state": "active", "done": false, "blocker": "", "metrics": {"tok_s": "59.147871"}, "params": {"model": "Gemma3-1B", "input_tokens": "8192", "output_tokens": "128", "concurrency": "4"}, "artifacts": [{"path": "analysis/serving-matrix-201/atom253-gemma-summary.json", "size": 5586, "sha256": "148cb39f84cb39e8"}], "experiments": ["experiments/2026-10-24-atom-prefetch253.md"], "labels": ["benchmark"], "review": false, "todos": [], "note": "", "agent": "codex", "host": "xeon-max", "branch": "main", "commit": "351d39d-dirty"}
diff --git a/opt_prime/examples/pd/http_matrix/STATUS.md b/opt_prime/examples/pd/http_matrix/STATUS.md
index 34f41cd3..792e2119 100644
--- a/opt_prime/examples/pd/http_matrix/STATUS.md
+++ b/opt_prime/examples/pd/http_matrix/STATUS.md
@@ -47,3 +47,5 @@ KONI hardware prefetch validation complete:48timed batches exact,8fixed-output/4
 Qwen3-4B also passes48timed batches,8fixed/4EOS groups and live cancellation/producer-exit isolation. c4 median gains21.20–41.00%; c1 near-neutral. Qwen0.6/Gemma remain pending. This does not resolve the separate GPU decoder pre-EOS drift in#256.
 
 Qwen3-0.6B: 48 prefetch off/on batches and fixed-output/EOS/lifecycle checks passed. At 8K input/output128/c4, 35.016 -> 48.231 tok/s (+37.74%); c1 roughly neutral. Gemma hardware validation remains pending.
+
+Gemma completed48batches and output/EOS/lifecycle checks. Allfour models192batches pass prefetch on/off parity. Gemma8K/output128/c4 +47.87%; separate GPU and native-reference numerical issues remain.
diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-a.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-a.json
new file mode 100644
index 00000000..651d41d6
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-a.json
@@ -0,0 +1,114982 @@
+{
+  "passed": true,
+  "stage": "complete",
+  "model": "unsloth/gemma-3-1b-it",
+  "runtime_commit": "3e16c33",
+  "torch": "2.11.0+cpu",
+  "physical_atom": 1,
+  "physical_rngd": 1,
+  "slots": 1,
+  "producer_width": 8192,
+  "producer_cache": false,
+  "decoder_cache": false,
+  "prompts": {
+    "128": [
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diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-a.producer.jsonl b/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-a.producer.jsonl
new file mode 100644
index 00000000..c7d4705c
--- /dev/null
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diff --git a/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-summary.json b/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-summary.json
new file mode 100644
index 00000000..ad80b4b2
--- /dev/null
+++ b/opt_prime/examples/pd/http_matrix/evidence253/atom253-gemma-summary.json
@@ -0,0 +1,210 @@
+{
+  "model": "unsloth/gemma-3-1b-it",
+  "stage": "complete",
+  "passed": true,
+  "measured_batches": 48,
+  "rows": [
+    {
+      "input_tokens": 128,
+      "output_tokens": 32,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 16.664034781989667,
+      "on_tok_s": 16.534893187265872,
+      "change_pct": -0.7749719465502403,
+      "paired_changes_pct": [
+        2.3064187126815128,
+        -1.4457731843210087,
+        0.6548186016889002
+      ],
+      "off_median_first_token_s": 1.5847949950257316,
+      "on_median_first_token_s": 1.600602606893517,
+      "off_median_e2e_s": 1.9201630890602246,
+      "on_median_e2e_s": 1.9351996519835666
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 32,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 16.743163479423025,
+      "on_tok_s": 19.10690078346424,
+      "change_pct": 14.117626617850298,
+      "paired_changes_pct": [
+        14.857688711462247,
+        15.416783086172359,
+        12.858358051546737
+      ],
+      "off_median_first_token_s": 4.456207271548919,
+      "on_median_first_token_s": 3.969341752526816,
+      "off_median_e2e_s": 4.792310332995839,
+      "on_median_e2e_s": 4.3055090790148824
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 128,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 43.41887589619983,
+      "on_tok_s": 43.44588158726574,
+      "change_pct": 0.062198042921401964,
+      "paired_changes_pct": [
+        0.062198042921401964,
+        -1.0603496378896793,
+        4.268973117613406
+      ],
+      "off_median_first_token_s": 1.5848738360218704,
+      "on_median_first_token_s": 1.5741173210553825,
+      "off_median_e2e_s": 2.94792864297051,
+      "on_median_e2e_s": 2.9460215979488567
+    },
+    {
+      "input_tokens": 128,
+      "output_tokens": 128,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 43.41029606795732,
+      "on_tok_s": 66.2926676232039,
+      "change_pct": 52.711853241970566,
+      "paired_changes_pct": [
+        52.711853241970566,
+        51.650867621294914,
+        54.10837597008997
+      ],
+      "off_median_first_token_s": 6.001600501534995,
+      "on_median_first_token_s": 3.975390726525802,
+      "off_median_e2e_s": 7.377990915032569,
+      "on_median_e2e_s": 5.351705843524542
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 32,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 14.965681039714351,
+      "on_tok_s": 14.939242891105454,
+      "change_pct": -0.17665850647716752,
+      "paired_changes_pct": [
+        -0.17665850647716752,
+        -0.15198741560102924,
+        -1.7681555265222637
+      ],
+      "off_median_first_token_s": 1.8022698720451444,
+      "on_median_first_token_s": 1.8059688119683415,
+      "off_median_e2e_s": 2.1381202850025147,
+      "on_median_e2e_s": 2.141879515023902
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 32,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 15.022300174911743,
+      "on_tok_s": 16.91094410477062,
+      "change_pct": 12.572268613118531,
+      "paired_changes_pct": [
+        12.663482646079082,
+        11.781772785534006,
+        12.028996130545178
+      ],
+      "off_median_first_token_s": 4.975554324977566,
+      "on_median_first_token_s": 4.528151432983577,
+      "off_median_e2e_s": 5.309278899978381,
+      "on_median_e2e_s": 4.865609006024897
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 128,
+      "concurrency": 1,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 39.51298149966651,
+      "on_tok_s": 40.05066375186407,
+      "change_pct": 1.360773679409899,
+      "paired_changes_pct": [
+        2.1510962011172863,
+        0.39549087245147607,
+        1.360773679409899
+      ],
+      "off_median_first_token_s": 1.8497115760110319,
+      "on_median_first_token_s": 1.808581120101735,
+      "off_median_e2e_s": 3.2393212789902464,
+      "on_median_e2e_s": 3.1957982340827584
+    },
+    {
+      "input_tokens": 8192,
+      "output_tokens": 128,
+      "concurrency": 4,
+      "paired_repeats": [
+        0,
+        1,
+        2
+      ],
+      "off_tok_s": 40.0004778242472,
+      "on_tok_s": 59.14816962472771,
+      "change_pct": 47.86865768106825,
+      "paired_changes_pct": [
+        49.438541688915635,
+        44.99690686532611,
+        47.86865768106825
+      ],
+      "off_median_first_token_s": 6.597376566496678,
+      "on_median_first_token_s": 4.537223069462925,
+      "off_median_e2e_s": 7.987403719453141,
+      "on_median_e2e_s": 5.929775572498329
+    }
+  ],
+  "latency_kind": "median of matched batch medians; first token is owner emission, not client SSE",
+  "overlap_kind": "producer prefill+export host-call versus other-request decode host-call; not device-kernel proof",
+  "overlap": {
+    "False": {
+      "completed_measured_producers": 60,
+      "with_overlap": 0,
+      "total_overlap_s": 0.0
+    },
+    "True": {
+      "completed_measured_producers": 60,
+      "with_overlap": 36,
+      "total_overlap_s": 30.107738365302794
+    }
+  },
+  "lifecycle": {
+    "cancel": {
+      "victim_status": 499,
+      "first_tokens_equal": true,
+      "drained": true
+    },
+    "worker_exit": {
+      "victim_status": 500,
+      "first_tokens_equal": true,
+      "drained": true
+    }
+  }
+}
diff --git a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
index c6600636..1d1d3ebf 100644
--- a/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
+++ b/opt_prime/examples/pd/http_matrix/experiments/2026-10-24-atom-prefetch253.md
@@ -159,3 +159,20 @@ Runtime 3e16c33; 48 timed batches, eight fixed-output check groups and four norm
 | 8192 | 128 | 4 | 35.016 | 48.231 | +37.74% |
 
 Host-call overlap: off0/60, on36/60, union24.246s. Not a device-kernel trace. Single-request throughput remains approximately flat; queued requests benefit. Prefetch compares on/off identical producer, not general native GPU numerical equivalence. Gemma has now started in the existing queue.
+
+## Gemma3-1B completed; all four prefetch models validated
+
+Runtime3e16c33.48timed batches,8fixed-output groups,4normal-EOS groups and cancellation/producer-exit checks passed. Cold858.059s excluded. Raw atom253-gemma-a.json and producer.jsonl; summarize_atom253.py generated atom253-gemma-summary.json. Same input/output/concurrency/repeat configuration as earlier models.
+
+| Input | Output | Concurrency | Off tok/s | On tok/s | Change |
+|---:|---:|---:|---:|---:|---:|
+|128|32|1|16.664|16.535|-0.77%|
+|128|32|4|16.743|19.107|+14.12%|
+|128|128|1|43.419|43.446|+0.06%|
+|128|128|4|43.410|66.293|+52.71%|
+|8192|32|1|14.966|14.939|-0.18%|
+|8192|32|4|15.022|16.911|+12.57%|
+|8192|128|1|39.513|40.051|+1.36%|
+|8192|128|4|40.000|59.148|+47.87%|
+
+Host-call overlap off0/60, on36/60, union30.108s; not device kernel tracing. All four models now have48batches each (192total) with on/off equivalence and lifecycle checks. This does not resolve old nativeATOM-vs-PD fixed-output Gemma post-EOS differences or GPU numerical/quality boundaries. Requested deletion of only the owned prefetch253 Pod after complete JSON/trace retrieval.