At SCL, We focus on research at the frontiers of High-Performance Computing (HPC) and its convergence with Data Science towards cyber-enabled discovery and design across disciplines. In particular, we develop advanced algorithms, software tools and systems for computational modeling, simulation, and knowledge abstraction. We design scalable parallel solutions for large sparse graphs/matrices driven by big-data applications and simulations. We study performance scaling, resource scheduling, energy efficiency and fault tolerance techniques for exascale computing and beyond.


Our lab is currently recruiting strong Ph.D. candidates in the research of High Performance Computing and its applications to the fields of parallel scientific computing, computational neuroscience, machine learning, energy efficiency, etc.

Please contact Dr. Raghavan if you are interested in pursuing research in the lab.