MajorK: Majority Based kmer Matching in Commodity DRAM

Abstract

Fast parallel search capabilities on large datasets are required across multiple application domains. One such domain is genome analysis, which requires high-performance k mer matching in large genome databases. Recently proposed solutions implemented k mer matching in DRAM, utilizing its sheer capacity and parallelism. However, their operation is essentially bit-serial, which ultimately limits the performance, especially when matching long strings, as customary in genome analysis pipelines. The proposed solution, MajorK, enables bit-parallel majority based k mer matching in an unmodified commodity DRAM. MajorK employs multiple DRAM row activation, where the search patterns (query k mers) are coded into DRAM addresses. We evaluate MajorK on viral genome k mer matching and show that it can achieve up to 2.7 $ \times $ higher performance while providing a better matching accuracy compared to state-of-the-art DRAM based k mer matching accelerators.