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SIFT-1B Dataset & Disk Index
The SIFT-1B (BigANN) dataset and pre-built disk-based ANN index. Built February 2026 on Intel Xeon 8462Y+ (Sapphire Rapids) with 800GB RAM.
Build Parameters
| Parameter | Value |
|---|---|
| Dataset | SIFT-1B (1,000,000,000 vectors, 128-dim, uint8) |
| Graph R | 128 (max degree) |
| Build L | 200 (search list size during construction) |
| PQ chunks | 32 (4 dimensions per sub-quantizer) |
| Build time | ~2 days |
Files
Raw Data
| File | Size | Description |
|---|---|---|
base.bin |
120GB | Raw SIFT-1B vectors. Binary format: [uint32 num_points][uint32 dim][uint8 vectors...]. 1B x 128-dim x uint8. |
query.bin |
1.3MB | 10,000 query vectors in the same format. Standard BigANN query set. |
gt.bin |
39MB | Ground truth (100 nearest neighbors per query). Binary format: [uint32 num_queries][uint32 K][uint32 ids...]. |
Disk Index
| File | Size | Description |
|---|---|---|
disk_diskidx_parts/ |
636GB total | Sector-aligned Vamana graph, split into 250GB chunks for upload. Each 4096-byte sector contains one or more nodes. Each node stores: [float32 coords[128]][uint32 num_neighbors][uint32 neighbor_ids[R]]. Primary structure for graph-based disk ANN search. Reassemble with: cat disk_diskidx_parts/disk.diskidx.*.part > disk.diskidx |
disk.pq |
129KB | PQ codebook (trained centroids). 32 sub-quantizers, each with 256 centroids of 4 float32 values. Used to compute approximate distances without reading full vectors from disk. |
disk.pqcodes |
30GB | PQ-compressed representation of all 1B vectors. Each vector encoded as 32 bytes (one centroid ID per sub-quantizer). Loaded into memory for fast approximate distance computation during search. |
In-Memory Sample Index
| File | Size | Description |
|---|---|---|
mem |
3.2GB | In-memory Vamana graph built on a 1% sample (~10M points). Provides fast entry point discovery — search this small graph first, then jump into the full disk graph at promising locations. |
mem.data |
1.2GB | Raw vectors for the 1% sample points. Kept in memory for exact distance computation during sample graph traversal. |
mem.tags |
39MB | Maps sample graph node IDs to their corresponding IDs in the full 1B dataset, so sample graph results can be used as entry points into the disk graph. |
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