PIM-Aligner:生物序列比对的mram处理平台

Shaahin Angizi, Jiao-Jin Sun, Wei Zhang, Deliang Fan
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引用次数: 18

摘要

在本文中,我们提出了一种基于优化和硬件友好的比对算法的高通量和节能的内存中处理加速器(PIM-Aligner)来执行DNA短读比对。我们首先基于BWT和FM-index对现有的序列比对算法进行重构,使其能够在PIM平台上完全实现。它支持精确对齐,还可以处理不匹配以减少过度回溯。然后,我们开发了PIM-Aligner平台,将SOT-MRAM阵列转换为潜在的计算存储器,以加速重构的内存校准算法,从而在原始SOT-MRAM芯片的基础上降低成本(不到芯片面积的10%)。因此,我们提出了一种局部数据分区、映射和管道技术,以最大限度地提高多计算子阵列在执行对齐任务时的并行性。仿真结果表明,PIM-Aligner优于最近基于动态规划的平台,每瓦特吞吐量提高约3.1倍。此外,与基于fm索引的ASIC和in- reram处理设计相比,PIM-Aligner将每瓦每mm2的短读校准吞吐量分别提高了约9倍和1.9倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PIM-Aligner: A Processing-in-MRAM Platform for Biological Sequence Alignment
In this paper, we propose a high-throughput and energy-efficient Processing-in-Memory accelerator (PIM-Aligner) to execute DNA short read alignment based on an optimized and hardware-friendly alignment algorithm. We first reconstruct the existing sequence alignment algorithm based on BWT and FM-index such that it can be fully implemented in PIM platforms. It supports exact alignment and also handles mismatches to reduce excessive backtracking. We then develop PIM-Aligner platform that transforms SOT-MRAM array to a potential computational memory to accelerate the reconstructed alignment-in-memory algorithm incurring a low cost on top of original SOT-MRAM chips (less than 10% of chip area). Accordingly, we present a local data partitioning, mapping, and pipeline technique to maximize the parallelism in multiple computational sub-array while doing the alignment task. The simulation results show that PIM-Aligner outperforms recent platforms based on dynamic programming with ∼ 3.1× higher throughput per Watt. Besides, PIM-Aligner improves the short read alignment throughput per Watt per mm2 by ∼ 9× and 1.9× compared to FM-index-based ASIC and processing-in-ReRAM designs, respectively.
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