We propose a novel generic inverted index framework on the GPU (called
GENIE), aiming to reduce the programming complexity of the GPU for parallel
similarity search of different data types. Not every data type and similarity
measure are supported by GENIE, but many popular ones are...
We present the
system design of GENIE, and demonstrate similarity search with GENIE on several
data types along with a theoretical analysis of search results. A new concept
of locality sensitive hashing (LSH) named $\tau$-ANN search, and a novel data
structure c-PQ on the GPU are also proposed for achieving this purpose. Extensive experiments on different real-life datasets demonstrate the
efficiency and effectiveness of our framework. The implemented system has been
released as open source.