High-throughput sequencing (HTS) technologies have revolutionized the field of genomics, enabling rapid and cost-effective genome analysis for various applications. However, the increasing volume of genomic data generated by HTS technologies presents significant challenges for computational techniques to effectively analyze genomes. To address these challenges, several algorithm-architecture co-design works have been proposed, targeting different steps of the genome analysis pipeline. These works explore emerging technologies to provide fast, accurate, and low-power genome analysis. This paper provides a brief review of the recent advancements in accelerating genome analysis, covering the opportunities and challenges associated with the acceleration of the key steps of the genome analysis pipeline. Our analysis highlights the importance of integrating multiple steps of genome analysis using suitable architectures to unlock significant performance improvements and reduce data movement and energy consumption. We conclude by emphasizing the need for novel strategies and techniques to address the growing demands of genomic data generation and analysis.

翻译：高通量测序技术彻底改变了基因组学领域，使得针对各种应用场景能够快速且经济高效地进行基因组分析。然而，高通量测序技术产生的基因组数据量日益增长，给有效分析基因组的计算技术带来了重大挑战。为应对这些挑战，研究人员提出了多项算法-架构协同设计的工作，针对基因组分析流程的不同步骤进行优化。这些工作探索新兴技术，以提供快速、准确且低功耗的基因组分析。本文对近年来加速基因组分析的研究进展进行了简要综述，涵盖了基因组分析流程关键步骤加速中的机遇与挑战。我们的分析强调了利用合适的架构整合基因组分析多个步骤的重要性，以释放显著的性能提升、减少数据搬运和能耗。最后，我们强调需要新的策略和技术来应对基因组数据生成与分析日益增长的需求。