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

2025 · doi:10.1101/2025.08.08.669185
preprint OA: closed
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This paper studies the compute and memory demands of FM-index–based DNA alignment and finds that data movement is a major contributor to energy consumption in genomic processing. It proposes GeneF, a processing-in-memory (PIM) accelerator using 3D-stacked memory, with a custom RISC-V-based processing element array, lightweight messaging to reduce remote access latency, and specialized prefetchers. Experiments report very large speedups over CPU implementations for counting and locating stages and show substantially lower energy use (about 25% versus CPU-DDR3). The paper does not explicitly state any limitation beyond focusing on FM-index DNA alignment workloads and demonstrating performance/energy results for that setting. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

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—1820× for counting and 1728× 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.
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Abstract 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—1820× for counting and 1728× 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. Competing Interest Statement The authors have declared no competing interest.

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