Team overview page 〉Details for: Robert Strzodka
Research interests:
◦ Parallel algorithms on parallel hardware (GPUs, many-core CPUs, FPGAs)
◦ Numerical methods (AMG, Krylov, preconditioners, FMM, multilevel methods, SVD)
◦ Graph algorithms (partitioning, coloring, decomposition, BFS, MST)
Short summary of current research:
My research focuses on significant improvements of performance and accuracy in scientific computing through a global optimization across the entire spectrum of numerical methods, algorithm design, software implementation and hardware acceleration. The potential is enormous, as typical scientific applications utilize only 0.1% of the peak performance of today's computers.