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，使得快速且低成本的基因组分析应用于多种场景成为可能。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巨大挑战。为应对这些挑战，研究人员提出了多项算法-架构协同设计方案，针对基因组分析流程的不同环节进行优化。这些方案探索新兴技术，以实现快速、准确且低功耗的基因组分析。本文简要回顾了基因组分析加速领域的最新进展，涵盖基因组分析流程关键环节加速的机遇与挑战。我们的分析强调了利用合适架构整合基因组分析多个步骤的重要性，这能释放显著的性能提升，并减少数据移动与能耗。最后，我们强调需要制定新颖策略与技术，以应对基因组数据生成与分析日益增长的需求。