Explore genomic data analysis at scale in this comprehensive lecture from the Society for Industrial and Applied Mathematics. Delve into the challenges and opportunities of mapping genomic analysis problems to petascale and exascale architectures. Learn about high-performance tools for analyzing microbial data, including alignment, profiling, clustering, and assembly. Discover common computational patterns and motifs that inform parallelization strategies and architectural requirements. Examine two general approaches to genomic analysis: asynchronous one-sided communication in UPC++ and bulk-synchronous collectives. Gain insights into specialized algorithms, GPU optimization, distributed algorithms, and communication-avoiding techniques. Understand the impact of growing genomic datasets on memory and computational requirements, and explore solutions for large-scale parallel platforms.