Publish source-control KLD and route allocation inputs

reproduction/source-allocation-inputs/README.md

@@ -0,0 +1,12 @@
+# Source allocation inputs
+
+These files bind K96 tail-allocation selection to the sealed TP4/PP1/DCP1
+source-control evaluation.
+
+- `kld_sm120_tp4dcp1.json` is the untrimmed 2,047-position source KLD receipt.
+- `routed_experts_tp4dcp1.npz` contains the routed-expert assignments used by
+  the allocation objective.
+
+The distributed preparation script downloads these exact bytes before score
+selection. It does not read official BF16 routed-weight shards.
+

reproduction/source-allocation-inputs/SHA256SUMS

@@ -0,0 +1,2 @@
+5d8aedb462658c693f1ce790f48ce5ed3cd6876897b1367a5cd36e42c0e2d434  kld_sm120_tp4dcp1.json
+db43b66f74745d25dfcbe7bc4baea5960a0a6a36bd1fec21533a42a380fc4d02  routed_experts_tp4dcp1.npz

reproduction/source-allocation-inputs/kld_sm120_tp4dcp1.json

@@ -0,0 +1,2221 @@
+{
+  "complete": true,
+  "elapsed_sec": 52.813933189958334,
+  "env_mirror": {
+    "B12X_MOE_FORCE_A16": "0",
+    "B12X_MOE_FORCE_A8": "0",
+    "CUDA_DEVICE_MAX_CONNECTIONS": "32",
+    "CUDA_DEVICE_ORDER": "PCI_BUS_ID",
+    "CUTE_DSL_ARCH": "sm_120a",
+    "GLOO_SOCKET_IFNAME": "lo",
+    "NCCL_IB_DISABLE": "1",
+    "NCCL_P2P_LEVEL": "SYS",
+    "NCCL_PROTO": "LL,LL128,Simple",
+    "NCCL_SOCKET_IFNAME": "lo",
+    "OMP_NUM_THREADS": "16",
+    "PYTORCH_CUDA_ALLOC_CONF": "expandable_segments:True",
+    "SAFETENSORS_FAST_GPU": "1",
+    "TMPDIR": "/tmp",
+    "TORCH_CUDA_ARCH_LIST": "12.0a",
+    "VLLM_B12X_ABSORB_BMM": "0",
+    "VLLM_ENABLE_PCIE_ALLREDUCE": "1",
+    "VLLM_PCIE_ALLREDUCE_BACKEND": "cpp",
+    "VLLM_USE_AOT_COMPILE": "1",
+    "VLLM_USE_B12X_FP8_GEMM": "1",
+    "VLLM_USE_B12X_MOE": "1",
+    "VLLM_USE_B12X_SPARSE_INDEXER": "1",
+    "VLLM_USE_BREAKABLE_CUDAGRAPH": "0",
+    "VLLM_USE_FLASHINFER_SAMPLER": "1",
+    "VLLM_USE_MEGA_AOT_ARTIFACT": "1",
+    "VLLM_USE_V2_MODEL_RUNNER": "1",
+    "VLLM_WORKER_MULTIPROC_METHOD": "spawn",
+    "XDG_CACHE_HOME": "/cache/jit/cu133-torch213-vllm6c50b0af7c-b12x1584743fd9-lmcacheccccdfc37f"
+  },
+  "gpus": [
+    {
+      "compute_capability": [
+        12,
+        0
+      ],
+      "index": 0,
+      "name": "NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition"
+    },
+    {
+      "compute_capability": [
+        12,
+        0
+      ],
+      "index": 1,
+      "name": "NVIDIA RTX PRO 6000 Blackwell Workstation Edition"
+    },
+    {
+      "compute_capability": [
+        12,
+        0
+      ],
+      "index": 2,
+      "name": "NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition"
+    },
+    {
+      "compute_capability": [
+        12,
+        0
+      ],
+      "index": 3,
+      "name": "NVIDIA RTX PRO 6000 Blackwell Workstation Edition"
+    }
+  ],
+  "image_id": "sha256:b0fcc515e94eb75e4e62e84e036dfff2752cf89be3351d479bf0b2415308843b",
+  "image_ref": "verdictai/glm52-sqg-coupled-mixedrate-sm120:goal019ffabf-routes-v2",
+  "kernel_provenance": {
+    "schedule": {
+      "blocks_per_cta": 8,
+      "kernel": "m128n64",
+      "route_block_rows": 128,
+      "stages": 2,
+      "tile_n": 64
+    },
+    "sha256": {
+      "exl3.py": "dfe2f48aaae2f5b25b39bc27b00ddad07f41d13b7b7afbd3e2a7dea365264d2d",
+      "glm_sqg_w4a8.py": "5a83210f252cedf925f1fbb9d9bd26209c3cb72181b2f4806929888c62157893",
+      "glm_trellis_w4a8.py": "b95dde9347cf679836eedc1c76f0f569a4fb37dcc594a674e41666e4d0f162ad",
+      "trellis_linear_api.py": "91e55a4d0cce2c8816e4e2cbff1c70ef9232f226ed1ac5a5768f6d71ecb0032b",
+      "w4a16_kernel.py": "fd1b048363046ad29a4b694adce6738e5f65189b22f38e0aa7a78668a07821f8"
+    }
+  },
+  "mean_kld": 0.07583317451217256,
+  "model": "/model",
+  "model_logits_finite_values": 317039360,
+  "model_logits_nonfinite_rows": 0,
+  "model_revision": "593dd0d2de6f79ce4e65303930c22c75e1359d44",
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