Hash match on GPU

Information is one of the most influential forces transforming the growth of businesses, and its amount is ever growing exponentially. There is a significant challenge to have an efficient matching tool to search for a required piece of information. String matching poses a computationally intensive challenge for massive data. In this paper, we present a comparison of an exact string matching mechanism using a Graphic Processing Unit (GPU). We progressively design the mechanism and data structure to fit on this parallel processing architecture. We then evaluate our proposed Hash Match implementation by comparing two other different mechanisms, Column Search (Brute Force) and Boyer-Moore-Horspool in two different NVIDIA cards, based on the “Fermi” architecture on C2075 and “Kepler” architecture on K20c.