CoMet is an application for calculating vector similarity metrics on large-scale parallel accelerated computing systems to solve problems in computational genomics. Currently the 2-way and 3-way Proportional Similarity (Czekanowski) metrics, Custom Correlation Coefficient and DUO method are supported. Currently the OLCF Summit and Titan systems are supported. Dependencies include GCC, CUDA, MAGMA, MPI, CMake and googletest.
See the file Quick_Start.txt for a step-by-step guide to building and running CoMet on the OLCF Summit system.
W. Joubert, J. Nance, D. Weighill, D. Jacobson, "Parallel Accelerated Vector Similarity Calculations for Genomics Applications," Parallel Computing, vol. 75, July 2018, pp. 130-145, https://www.sciencedirect.com/science/article/pii/S016781911830084X, https://arxiv.org/abs/1705.08210.
W. Joubert, J. Nance, S. Climer, D. Weighill, D. Jacobson, "Parallel Accelerated Custom Correlation Coefficient Calculations for Genomics Applications," Parallel Computing 84 (2019), 15-23, https://www.sciencedirect.com/science/article/pii/S0167819118301431, https://arxiv.org/abs/1705.08213
Wayne Joubert, Deborah Weighill, David Kainer, Sharlee Climer, Amy Justice, Kjiersten Fagnan, Daniel Jacobson, "Attacking the Opioid Epidemic: Determining the Epistatic and Pleiotropic Genetic Architectures for Chronic Pain and Opioid Addiction," SC18 Gordon Bell Award paper, https://dl.acm.org/citation.cfm?id=3291732
"GPU-enabled comparative genomics calculations on leadership-class HPC systems," http://on-demand.gputechconf.com/gtc/2017/presentation/s7156-wayne-joubert-comparative.pdf
"CoMet: An HPC application for comparative genomics calculations," https://www.olcf.ornl.gov/wp-content/uploads/2017/11/2018UM-Day1-Joubert.pdf