Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a conference talk on Deinsum, a framework for distributed multilinear algebra computations using Einstein notation. Delve into the challenges of optimizing data movement in massively-parallel systems and learn how Deinsum addresses these issues. Discover the framework's approach to deriving data movement-optimal tiling and generating distributed schedules, enhancing local computation performance. Examine the application of Deinsum to important tensor kernel classes, including Matricized Tensor Times Khatri-Rao Products and Tensor Times Matrix chains. Gain insights into the framework's workflow, binary operations, communication minimization techniques, and optimal tile size determination. Analyze experimental results showcasing Deinsum's performance on the Piz Daint supercomputer, demonstrating significant speedups over existing solutions.