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Invited Keynote: Investigating Epistatic and Pleiotropic Genetic Architectures in Bioenergy and Human Health

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Invited Keynote: Investigating Epistatic and Pleiotropic Genetic Architectures in Bioenergy and Human Health
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Abstract
The new CoMet application consists of implementations of the 2-way and 3-way Proportional Similarity metric and Custom Correlation Coefficient using native or adapted GEMM kernels optimized for GPU architectures, and received the 2018 Gordon Bell Prize. Nearly 300 quadrillion element comparisons per second and over 2.3 mixed precision ExaOps are reached on Summit by use of Tensor Core hardware on the Nvidia Volta GPUs. These similarity metrics form the major parts of largescale Genome-Wide Epistasis Studies (GWES) and pleiotropy studies. These efforts seek to identify genetic variants that contribute to individual phenotypes, including susceptibility (or robustness) to disease. The team is using CoMet to investigate the genetic architectures underlying complex traits in applications from bioenergy to human clinical genomics.