The landscape for understanding the complexity of life sciences is evolving at a rapid pace. Continued improvements in sequencing technology and advancements in machine learning create both improved data sources and data analysis techniques enabling the next big step in scientific discovery. With the volume of acquired data growing exponentially the need for meta-analysis across diverse population studies is the reality driving our understanding of humanity and the natural world. Underpinning all of this effort is the massive parallel processing which high performance computing affords researchers and with which further advancement and innovation in the life sciences happens.