SimMS: A GPU-Accelerated Cosine Similarity implementation for Tandem Mass Spectrometry

Abstract

Untargeted metabolomics involves a large-scale comparison of the fragmentation pattern of a mass spectrum against a database containing known spectra. Given the number of comparisons involved, this step can be time-consuming. In this work, we present a GPU-accelerated cosine similarity implementation for Tandem Mass Spectrometry (MS) with approximately 1000-fold speedup compared to the MatchMS reference at a rate of 0.005% incorrect matches and a rate of 0.002% incorrect scores. We describe the underlying reasons for these errors and provide means to avoid them.