Means for accelerating my gpu search

[KirinZzzz]

Summary

I am cerently working on a work using faiss on gpu to sove a vector search project, there is a loop in my project and each loop contains an faiss search section, I'm looking for a way to accelerate this process but have a few questions.

Platform

Faiss version: 1.7.2

Running on:

• CPU
• [✔] GPU

Interface:

• C++
• [✔] Python

#Questions
my codes are:
res = faiss.StandardGpuResources()
config = faiss.GpuIndexIVFFlatConfig()
config.use_raft = False
index = faiss.GpuIndexIVFFlat(res, 64, 10,faiss.METRIC_INNER_PRODUCT,config)
index.nprobe = 1
index.train(vecs)
index.add(vecs)
distances, indices = index.search(nq, 1000)

I find that "index = faiss.index_cpu_to_gpu(res, 2, index)" takes a lot of time to complete so I switch to " index = faiss.GpuIndexIVFFlat(res, 64, 10,faiss.METRIC_INNER_PRODUCT,config)", is there a difference?

Because initializing the index takes a lot of time in both circumstances, like I said there is a loop in my project and each loop contains an faiss search section, I want to initialize the index before going into the loop( so I can save the time for initializing ), thus i need to empty the index( reversing the add method )after each search( beacuse the vecs and nq are different in each loop ), I tried "index.remove_ids(np.arange(vecs.len))" but encounter:
RuntimeError: Error in virtual size_t faiss::Index::remove_ids(const faiss::IDSelector&) at /home/conda/feedstock_root/build_artifacts/faiss-split_1644327811086/work/faiss/Index.cpp:43: remove_ids not implemented for this type of index

Is there a way to empty the index after searching in GPU ?
Will my idea actually work?