ASAP: Accelerated Short Read Alignment on Programmable Hardware (Abstract Only)

The proliferation of high-throughput sequencing machines allows for the rapid generation of billions of short nucleotide fragments in a short period. This massive amount of sequence data can quickly overwhelm today's storage and compute infrastructure. This poster explores the use of hardware acceleration to significantly improve the runtime of short-read alignment (SRA), a crucial step in pre-processing sequenced genomes. It presents the design and implementation of ASAP, an accelerator for computing Levenshtein distance (LD) in the context of the SRA problem. LD computation is a prominent underlying mathematical kernel that is common to a large number of SRA tools (e.g., BLAST, BWA, SNAP) and is responsible for 50-70% of their runtime. These algorithms mentioned above calculate the exact value of LD between nucleotide strings but only use them to build a total ordering (an ordered list) of the most likely point of origin in the genome. ASAP computes an approximation of LD by encoding computation in propagation delay of circuit elements. This approximation is calculated in an accelerated fashion in hardware and preserves the original total ordering of LDs produced by the traditional algorithms. This computation is performed by constructing circuits that comprise the recursive definition of the LD computation and measuring propagation delay of a signal entering and leaving the circuit. Additionally, ASAP can explore large portions of the search space (substrings of the strings being compared) within one clock cycle, and ignore parts of the search space that does not contribute to an answer. Our design is implemented on an Altera Stratix V FPGA in an IBM POWER8 system using the CAPI interface for cache coherence across the CPU and FPGA. Our design is 200x faster (median measurement) than the equivalent C implementation of the kernel running on the host processor and 2.2x faster for an end-to-end alignment tool for 120-150bp short-read sequences.