Moderator: Patrick Diehl (Louisiana State University; Louisiana State University, Center for Computation and Technology)
Panelists: Laxmikant V. Kale (University of Illinois), Irina P. Demeshko (Los Alamos National Laboratory), Bryce Adelstein-Lelbach (Nvidia Corporation), Hartmut Kaiser (Louisiana State University; Louisiana State University, Center for Computation and Technology), Zahra Khatami (Oracle), Keno Fischer (Julia Computing Inc), Alice Koniges (University of Hawaii)
Abstract: The new challenges posed by exascale system architectures have resulted in difficulty achieving a desired scalability using traditional distributed-memory runtimes. Task-based programming models show promise in addressing these challenges, providing application developers with a productive and performant approach to programming on next generation systems. Empirical studies show that task-based models can overcome load-balancing issues that are inherent to traditional distributed-memory runtimes, and that task-based runtimes perform comparably to those systems when balanced.
This panel is designed to explore the advantages of task-based programming models on modern and future HPC systems from an industry, university and national lab perspective. It aims at gathering application experts and proponents of these models to present concrete and practical examples of using task-based runtimes to overcome the challenges posed by exascale system architectures,