Survey on Feasibility of Pattern Matching Techniques In Heterogeneous Architectures for Bioinformatics

Abstract

Pattern-matching techniques are very common in major areas of bioinformatics, in multiple forms: from exact (accurate) to partial matching, the process itself is vital to multiple niches of research. In this paper, we prepare a survey of recent breakthroughs in the field of pattern-matching applied to bioinformatics, from a heterogeneous implementation standpoint, focusing especially on the ones based on SIMD (Single Instruction Multiple Data) or GPGPU (General-Purpose computing on Graphics Processing Units) architectures. We focus on the most important aspects of such data processing and their effectiveness, with particular focus on the technological challenges that such heterogeneous implementations bring, while also analyzing their feasibility of application to particular research niches, such as DNA analysis and protein sequence alignment.