GPU implementation of kNN and SNN
- GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors
- Supported by
numba cudaandfaisslibrary
Env Initialization & Activation
Prior to the import and execution of main source code (knnsnn.py), a conda envrionment should be set. Execute following commands to set the envrionment.
conda env create --file ksnn_env.yaml
conda activate gpu-knn-snn
Import & Execution
Place knnsnn.py in the working directory, and import the within class using
from knnsnn import KnnSnn as ks
Afterwards, you can create an instance and runn knn and snn by
KSnn = ks(k)
knn_indices = KSnn.knn(sample_data)
snn_results = KSnn.snn(knn_indices)
Refer to test.py to know the way to use knnsnn.py in detail.
