Please note: This seminar will be given online.
Kazem Cheshmi, Department of Computer Science
University of Toronto
Sparse matrix computations are an important class of algorithms frequently used in scientific simulations such as computer graphics and weather modeling as well as in data analytics codes and machine learning computations. The performance of these simulations relies heavily on the high-efficient implementations of sparse computations.