Abstract

Decoding the human genome in the past decades has brought into focus a computationally intensive operation through DNA profiling. The typical search space for these kinds of problems is extremely large and requires specialized hardware and algorithms to perform the necessary sequence analysis. In this paper, we propose an innovative and scalable approach to exact multi-pattern matching of nucleotide sequences by harnessing the massively parallel computing power found in commodity graphical processing units. Our approach places careful consideration on preprocessing of DNA datasets and runtime performance, while exploiting the full capabilities of the heterogeneous platform it runs on. Finally, we evaluate our models against real-world DNA sequences.

中文翻译：

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使用 GPU 加速处理实现实时 DNA 生物识别

摘要

在过去的几十年中，对人类基因组的解码使通过 DNA 分析的计算密集型操作成为焦点。这类问题的典型搜索空间非常大，需要专门的硬件和算法来执行必要的序列分析。在本文中，我们提出了一种创新且可扩展的方法，通过利用商品图形处理单元中的大规模并行计算能力，对核苷酸序列进行精确的多模式匹配。我们的方法仔细考虑了 DNA 数据集的预处理和运行时性能，同时利用了它运行的异构平台的全部功能。最后，我们根据真实世界的 DNA 序列评估我们的模型。