Parallel Document Inversion using GPU

Abstract

Recent advances in the technology of the Graphics Processing Unit (GPU) has led to a surge of interest in using the GPU for general purpose applications. We can utilize the GPU in computation as a massive parallel co-processor because the GPU consists of multiple cores. The GPU is also an affordable, attractive, and user-programmable commodity. Although the inverted index is a useful data structure that can be used for full text search or document retrieval, the large number of documents will require tremendous time to create the index. The performance of document inversion can be improved by multicore GPU. Our approach is to implement a linear-time, hash-based, single program multiple data (SPMD), document inversion algorithm on the NVIDIA GPU/CUDA programming platform utilizing the huge computational power of the GPU, to develop high performance solutions for document indexing.