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We improve on GenASM, a recent algorithm for genomic sequence alignment, bysignificantly reducing its memory footprint and bandwidth requirement. Ouralgorithmic improvements reduce the memory footprint by 24$\times$ and thenumber of memory accesses by 12$\times$. We efficiently parallelize thealgorithm for GPUs, achieving a 4.1$\times$ speedup over a CPU implementationof the same algorithm, a 62$\times$ speedup over minimap2's CPU-based KSW2 anda 7.2$\times$ speedup over the CPU-based Edlib for long reads.

Algorithmic Improvement and GPU Acceleration of the GenASM Algorithm