Milinda Shayamal Fernando.
School of Computing
University of Utah
E-mail : milinda (at) cs (dot) utah (dot) edu
You can find my CV here
I am a Ph.D. (in scientific computing track) student at School of Computing, University of Utah. I did my undergraduate studies in the field of Computer Science at University of Moratuwa. Currently, I am working as a Graduate Research Assistant, under
Prof. Hari Sundar
My research is primarily focused on developing computational algorithms for the numerical solution of large-scale partial differential equations. New discoveries in Science and Engineering are primarily driven by computer simulations(in lieu of physical experiments). In many cases, such as Gravitational Wave (GW) astronomy physical experiments are impossible. In the modern computational era, while computing resources have grown exponentially, they have also become increasingly complex with ever-increasing heterogeneity and fine-grain parallelism, making their use by domain-scientists has become increasingly difficult. My research is focused on developing algorithms and computational codes that enable effective use of modern supercomputers by domain scientists. The key objectives are ease of use by domain scientists (by using symbolical interfaces and automatic code generation), portability (ability to use across different architectures), performance (efficient use of computing resources) and scalability (ability to solve larger problems on next-generation machines). For my current research, the main driving application has been computational relativity and GW astronomy, but the contributions of my research are fundamental and have also had significant impact on other areas such as Computational Fluid Dynamics (CFD).
- 2015-present : Univeristy of Utah, Ph.D. Scientific Computing.
- 2010-2015 : University of Moratuwa, B.Sc. Computer Science
Summary of some of my research work can be found here
- 2019 ACM-IEEE CS George Michael Memorial HPC Fellowship
- 2019 University of Utah Graduate Research Fellowship
- Travel grant to participate in Computational Challenges in Gravitational Wave Astronomy, 2019, Organized by Institute of Pure and Applied Mathematics (IPAM), UCLA.
- The Argonne Training Program on Extreme-Scale Computing (ATPESC), 2016.
- NSF travel grant award (HPDC’17).
- Best Poster Award in CGO 2015, ACM SRC (undergraduate).
For full publication list please visit my Google Schoolar page, here are some of the selected publications.
- Ishii, M., Fernando, M., Saurabh, K., Khara, B., Ganapathysubramanian, B. and Sundar, H., 2019, November. Solving PDEs in space-time: 4D tree-based adaptivity, mesh-free and matrix-free approaches. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 1-61).
- Fernando, M., Neilsen, D., Hirschmann, E.W. and Sundar, H., 2019, June. A scalable framework for adaptive computational general relativity on heterogeneous clusters. In Proceedings of the ACM International Conference on Supercomputing (pp. 1-12).
- Fernando, M., Neilsen, D., Lim, H., Hirschmann, E. and Sundar, H., 2018. Massively Parallel Simulations of Binary Black Hole Intermediate-Mass-Ratio Inspirals https://doi.org/10.1137/18M1196972https://doi.org/10.1137/18M1196972
- Fernando, M., Duplyakin, D. and Sundar, H., 2017, June. Machine and application aware partitioning for adaptive mesh refinement applications. In Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing (pp. 231-242). ACM.
- Fernando, I.D., Jayasena, S., Fernando, M. and Sundar, H., 2017, August. A Scalable Hierarchical Semi-Separable Library for Heterogeneous Clusters. In 2017 46th International Conference on Parallel Processing (ICPP) (pp. 513-522). IEEE.