GPU implementation of kNN and SNN
- GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors
- Supported by
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
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)
test.py to know the way to use
knnsnn.py in detail.