Squash history after dataset card cleanup

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.avro filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
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+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
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+*.jpg filter=lfs diff=lfs merge=lfs -text
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README.md

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+# deep-100m-static-search-eval
+
+Static 100M search-evaluation dataset with original vectors, original query/ground-truth files, a rebuilt hnswlib HNSW index, and generated PQ artifacts.
+
+## Files
+
+- Base: `base.fbin`
+- HNSW index: `index_m_32_ef_500`
+- Query: `orig_query_10k.fbin`
+- Ground truth: `groundtruth.bin`
+- Checksums: `checksums.sha256`
+- Kaggle metadata is provided via `dataset-metadata.json` during upload and is stored by Kaggle as dataset configuration, not as a listed data file.
+
+## Data Sources
+
+- `base.fbin` -> `base.fbin`
+- `unif_query_10k.fbin` -> `orig_query_10k.fbin`
+- `GT_100M/deep-100M` -> `groundtruth.bin` from https://dl.fbaipublicfiles.com/billion-scale-ann-benchmarks/GT_100M/deep-100M
+
+Source license/terms note: Original source terms apply; Kaggle metadata uses license other.
+
+## Dataset Properties
+
+- Vector count: `100000000`
+- Dimension: `96`
+- Dtype: `float32`
+- Metric: `l2`
+- Query count label: `10k`
+- Query count: `10000`
+
+## Environment
+
+- CPU threads used: `96`
+- Python: `Python 3.10.12`
+- hnswlib package version: `unknown`
+- hnswlib git commit: `fe873b1cee484795bd254088c0d4579f567f1979`
+- faiss: `1.14.3`
+- numpy: `2.2.6`
+- kaggle: `unknown`
+- kagglehub: `1.0.2`
+- vectordb-cxl commit: `73e82318a4c346b64b8c645d030ac86696351632`
+
+## HNSW Index
+
+- Parameters: `M=32`, `ef_construction=500`
+- Index dtype: `float32`
+- hnswlib space: `l2`
+- Thread count: `96`
+- Build start: `2026-07-05 15:07:30 UTC`
+- Build end: `2026-07-05 17:39:00 UTC`
+- Build elapsed seconds: `9090.091`
+- Built from original base vectors: `true`
+- Prebuilt Kaggle index reused: `false`
+
+## Primary Search
+
+- Parameters: `ef_search=150`, `k=10`
+- Thread count: `96`
+- Recall@10: `0.975170`
+- Batch throughput qps: `8784.062140`
+- Latency mean_ms: `10.821620`
+- Latency p50_ms: `2.060002`
+- Latency p95_ms: `18.078470`
+- Latency p99_ms: `38.452937`
+- Instrumented latency from batch run: `True`
+- Search elapsed seconds: `1.138425`
+
+## Optional ef_search Sweep
+
+Not run unless a `search_sweep.json` file is included and referenced in the status log.
+
+## PQ
+
+Implementation path: `cpp`
+
+Fallback used: `False`
+
+Thread count: `96`
+
+Elapsed seconds: `2811.184`
+
+Final `m` values: `m24`, `m48`, `m96`
+
+Kaggle upload file names: `pq_m24.pqcodes/.pqmeta/.pqcodebook`, `pq_m48.pqcodes/.pqmeta/.pqcodebook`, `pq_m96.pqcodes/.pqmeta/.pqcodebook`
+

base.fbin

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checksums.sha256

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groundtruth.bin

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index_build.json

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+  "command": [
+    "/home/cc/workspace/vectordb-cxl/venv/bin/python",
+    "/home/cc/workspace/vectordb-cxl/scripts/datasets/general/build_initial_update_index.py",
+    "--base-fbin-path",
+    "/home/cc/workspace/static-search-eval-datasets/deep-100m-static-search-eval/base.fbin",
+    "--data-type",
+    "float32",
+    "--output-index-path",
+    "/home/cc/workspace/static-search-eval-datasets/deep-100m-static-search-eval/index_m_32_ef_500",
+    "--initial-active",
+    "100000000",
+    "--space",
+    "l2",
+    "--m",
+    "32",
+    "--ef-construction",
+    "500",
+    "--ef-search",
+    "150",
+    "--num-threads",
+    "96",
+    "--batch-size",
+    "100000"
+  ],
+  "dataset": "deep",
+  "dtype": "float32",
+  "ef_construction": 500,
+  "elapsed_seconds": 9090.091,
+  "end_time": "2026-07-05 17:39:00 UTC",
+  "index_bytes": 66025692572,
+  "index_path": "/home/cc/workspace/static-search-eval-datasets/deep-100m-static-search-eval/index_m_32_ef_500",
+  "sidecar": null,
+  "space": "l2",
+  "start_time": "2026-07-05 15:07:30 UTC",
+  "threads": 96
+}

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pq_manifest.json

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+  "end_time": "2026-07-05 19:09:07 UTC",
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+  "start_time": "2026-07-05 18:22:16 UTC",
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search_ef150.json

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+  "dataset": "deep",
+  "ef_search": 150,
+  "end_time": "2026-07-05 17:47:58 UTC",
+  "instrumented_latency": true,
+  "k": 10,
+  "latency_mean_ms": 10.8216196164,
+  "latency_p50_ms": 2.060002,
+  "latency_p95_ms": 18.078470449999994,
+  "latency_p99_ms": 38.45293692000009,
+  "query_count": 10000,
+  "recall_at_10": 0.97517,
+  "start_time": "2026-07-05 17:47:58 UTC",
+  "threads": 96,
+  "throughput_qps": 8784.062139982418
+}

source_manifest.json

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+  "dataset": "deep",
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+  "folder": "deep-100m-static-search-eval",
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+      "kaggle_dataset": "shurangwu/deep-100m",
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+      "url": "https://dl.fbaipublicfiles.com/billion-scale-ann-benchmarks/GT_100M/deep-100M"
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+  "started_at": "2026-07-05 10:50:25 UTC"
+}