MajorK: Majority Based kmer Matching in Commodity DRAM

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.