A batched GPU algorithm for set intersection

Abstract

Intersection of inverted lists is a frequently used operation in search engine systems. Efficient CPU and GPU intersection algorithms for large problem size are well studied. We propose an efficient GPU algorithm for high performance intersection of inverted index lists on CUDA platform. This algorithm feeds queries to GPU in batches, thus can take full advantage of GPU processor cores even if problem size is small. We also propose an input preprocessing method which alleviate load imbalance effectively. Our experimental results based on a real world test set show that the batched algorithm is much faster than the fastest CPU algorithm and plain GPU algorithm. © 2009 IEEE.