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Hardcore Project for Internships
·
Module 5
ANN with Navigable Small World (NSW) Graphs
1
Understanding NSW Graph Structure
Describe the data structure of an NSW graph, including nodes, edges, and the concept of 'long' vs. 'short' range links.
2
Graph Data Structures in C
Design C structs for graph nodes and edges, allocated from a contiguous memory pool for data locality.
3
Greedy Search for Approximate Nearest Neighbor
Implement the greedy search algorithm to traverse the graph and find an approximate nearest neighbor.
4
Graph Algorithms: K-Nearest Neighbor Insertion
Implement the algorithm for inserting a new vector into the graph by connecting it to its `k` nearest existing neighbors.
5
Graph Construction: Iterative Vector Insertion
Implement the full graph construction process by iteratively inserting all vectors from a dataset.
Benchmarking NSW Search Performance
Benchmark the search speed and recall of the NSW implementation against the exact k-NN search baseline.
Previous module
Data Layout and Exact k-NN Search
Next module
HNSW: Hierarchical Structure and Search