K-mer counting is the process of building a histogram of all substrings of length k for an input string S. The problem itself is quite simple, but counting k-mers efficiently for a very large input string is a difficult task that has been researched extensively. In recent years the performance of k-mer counting algorithms have improved significantly, and there have been efforts to use graphics processing units (GPUs) in k-mer counting. The goal for this thesis was to design, implement and benchmark a GPU accelerated k-mer counting algorithm SNCGPU. The results showed that SNCGPU compares reasonably well to the Gerbil k-mer counting algorithm on a mid-range desktop computer, but does not utilize the resources of a high-end computing platform as efficiently. The implementation of SNCGPU is available as open-source software
