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Motivation: Seed filtering is critical in DNA read mapping, a process wherebillions of DNA fragments (reads) sampled from a donor are mapped onto areference genome to identify genomic variants of the donor. Read mappers 1)quickly generate possible mapping locations (i.e., seeds) for each read, 2)extract reference sequences at each of the mapping locations, and then 3) checksimilarity between each read and its associated reference sequences with acomputationally expensive dynamic programming algorithm (alignment) todetermine the origin of the read. Location filters come into play beforealignment, discarding seed locations that alignment would have deemed a poormatch. The ideal location filter would discard all poor matching locationsprior to alignment such that there is no wasted computation on poor alignments.  Results: We propose a novel filtering algorithm, GRIM-Filter, optimized toexploit emerging 3D-stacked memory systems that integrate computation within astacked logic layer, enabling processing-in-memory (PIM). GRIM-Filter quicklyfilters locations by 1) introducing a new representation of coarse-grainedsegments of the reference genome and 2) using massively-parallel in-memoryoperations to identify read presence within each coarse-grained segment. Ourevaluations show that for 5% error acceptance rates, GRIM-Filter eliminates5.59x-6.41x more false negatives and exhibits end-to-end speedups of1.81x-3.65x compared to mappers employing the best previous filteringalgorithm.

GRIM-filter: fast seed filtering in read mapping using emerging memory technologies