CADM: Content addressable commodity off-the-shelf DRAM-based genome classifier

Processing using memory (PuM) leverages analog properties of memory infrastructure to implement logic and arithmetic operations. Commodity Off-The-Shelf (COTS) DRAM is particularly attractive for PuM because it requires no device modification, thereby preserving the ubiquity, availability, and cost advantages of modern DRAM while enabling massive column-level parallelism. We propose CADM (Content-Addressable DRAM), that enables exact and approximate (similarity) search in- and using- unmodified COTS DRAM. CADM targets genome classification, which is one of the most important applications in bioinformatics. Specifically, rapid and accurate detection of bacterial pathogens is critical for effective clinical decision-making, particularly in life-threatening conditions such as sepsis, where early identification of the causative agent significantly improves patient outcomes. We implement CADM in commercial DDR4 and show that it can achieve up to 185× higher throughput and 73× energy savings compared to CPU-run state-of-the-art classifier Kraken2. Using approximate search, CADM can achieve 9× higher F₁ score when matching relatively short (<32 DNA bases) ambiguous and erroneous k-mers.