Algorithmic Improvement and GPU Acceleration of the GenASM Algorithm

We improve on GenASM, a recent algorithm for genomic sequence alignment, by significantly reducing its memory footprint and bandwidth requirement. Our algorithmic improvements reduce the memory footprint by 24 × and the number of memory accesses by 12 ×. We efficiently parallelize the algorithm for GPUs, achieving a 4.1 × speedup over a CPU implementation of the same algorithm, a 62× speedup over minimap2's CPU-based KSW2 and a 7.2 × speedup over the CPU-based Edlib for long reads.