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mdouze
2017-02-25 08:17:11 +01:00
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@@ -310,5 +310,21 @@ The same script generates the KNN-graph on Deep1B. Note that the inverted file f
```
python bench_gpu_1bn.py Deep1B OPQ20_80,IVF262144,PQ20 -nnn 10 -altadd -knngraph -R 2 -noptables -tempmem $[1<<30] -ngpu 4
...
CPU index contains 1000000000 vectors, move to GPU
Copy CPU index to 2 sharded GPU indexes
dispatch to GPUs 0:2
IndexShards shard 0 indices 0:500000000
IndexIVFPQ size 500000000 -> GpuIndexIVFPQ indicesOptions=0 usePrecomputed=0 useFloat16=0 reserveVecs=0
IndexShards shard 1 indices 500000000:1000000000
IndexIVFPQ size 500000000 -> GpuIndexIVFPQ indicesOptions=0 usePrecomputed=0 useFloat16=0 reserveVecs=0
dispatch to GPUs 2:4
IndexShards shard 0 indices 0:500000000
IndexIVFPQ size 500000000 -> GpuIndexIVFPQ indicesOptions=0 usePrecomputed=0 useFloat16=0 reserveVecs=0
IndexShards shard 1 indices 500000000:1000000000
IndexIVFPQ size 500000000 -> GpuIndexIVFPQ indicesOptions=0 usePrecomputed=0 useFloat16=0 reserveVecs=0
move to GPU done in 151.535 s
search...
999997440/1000000000 (8389.961 s, 0.3379) probe=1 : 8389.990 s rank-10 intersection results: 0.3379
999997440/1000000000 (9205.934 s, 0.4079) probe=2 : 9205.966 s rank-10 intersection results: 0.4079
999997440/1000000000 (9741.095 s, 0.4722) probe=4 : 9741.128 s rank-10 intersection results: 0.4722
```