PIM-Assembler: A Processing-in-Memory Platform for Genome Assembly
Shaahin Angizi, Naima Ahmed Fahmi, Wei Zhang, Deliang Fan
Abstract
In this paper, for the first time, we propose a high-throughput and energy-efficient Processing-in-DRAM-accelerated genome assembler called PIM-Assembler based on an optimized and hardware-friendly genome assembly algorithm. PIM-Assembler can assemble large-scale DNA sequence dataset from all-pair overlaps. We first develop PIM-Assembler platform that harnesses DRAM as computational memory and transforms it to a fundamental processing unit for genome assembly. PIM-Assembler can perform efficient X(N)OR-based operations inside DRAM incurring low cost on top of commodity DRAM designs ( 5% of chip area). PIM-Assembler is then optimized through a correlated data partitioning and mapping methodology that allows local storage and processing of DNA short reads to fully exploit the genome assembly algorithm-level's parallelism. The simulation results show that PIM-Assembler achieves on average 8.4× and 2.3 wise× higher throughput for performing bulk bit-XNOR-based comparison operations compared with CPU and recent processing-in-DRAM platforms, respectively. As for comparison/addition-extensive genome assembly application, it reduces the execution time and power by 5× and 7.5× compared to GPU.
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Cited by top-tier papers6
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- CASA: An Energy-Efficient and High-Speed CAM-based SMEM Seeding Accelerator for Genome AlignmentYi Huang, Lingkun Kong, Dibei Chen, Zhiyu Chen et al.MICRO 2023 · 5 citations
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