  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.
