  Recent DNA pre-alignment filter designs employ DRAM for storing the reference
genome and its associated meta-data. However, DRAM incurs increasingly high
energy consumption background and refresh energy as devices scale. To overcome
this problem, this paper explores a design with racetrack memory (RTM)--an
emerging non-volatile memory that promises higher storage density, faster
access latency, and lower energy consumption. Multi-bit storage cells in RTM
are inherently sequential and thus require data placement strategies to
mitigate the performance and energy impacts of shifting during data accesses.
We propose a near-memory pre-alignment filter with a novel data mapping and
several shift reduction strategies designed explicitly for RTM. On a set of
four input genomes from the 1000 Genome Project, our approach improves
performance and energy efficiency by 68% and 52%, respectively, compared to the
state of the art proposed DRAM-based architecture.
