GeneF: A High-Performance Processing-in-Memory Accelerator for Efficient DNA Alignment

In this paper, we explore the compute and memory characteristics of the FM-index and identify data movement as a significant contributor to overall energy consumption in genomic processing. We propose GeneF, a Processing-in-Memory (PIM) accelerator designed specifically for DNA alignment tasks, leveraging 3D-stacked memory to enhance memory bandwidth and computing parallelism. Our architecture features a custom RISC-V-based processing element (PE) array, a lightweight messaging mechanism to mitigate remote access latency, and specialized prefetchers for improved efficiency. Experimental results demonstrate that GeneF achieves substantial speedups--1820x for counting and 1728x for determining stages--over traditional CPU implementations and offers remarkable energy efficiency, consuming only 25% of the energy compared to conventional CPU-DDR3 systems. The findings highlight the potential of PIM architectures in minimizing data movement and enhancing performance for genomic workloads, paving the way for more energy-efficient computing solutions in the field of bioinformatics.