Randomized Algorithms for Scientific Computing (RASC)

The Department of Energy, Advanced Scientific Computing Research (DOE/ASCR) program held a four-day virtual workshop on "Randomized Algorithms for Scientific Computing (RASC)" on December 2-3 in 2020 and January 6-7 in 2021. The subsequent report articulates how randomized algorithms research is motivated by application needs and drivers such as: Massive data from experiments, observations, and simulations; Forward problems; Inverse problems; Applications with discrete structure; Experimental designs; Software and libraries for scientific computing; Emerging hardware; and Scientific machine learning. Relevant examples of randomized algorithms include stochastic gradient descent for training scientific machine learning models, compressed sensing, and differential privacy algorithms.

Meeting date
Meeting location
Virtual
Keywords
Scientific computing, Randomized, Algorithms, Robust, Scalable