Abstract: Uintah Hybrid Task-Based Parallelism Algorithm

Uintah is a software framework that provides an environment for solving large-scale science and engineering problems involving the solution of partial differential equations. Uintah uses a combination of fluid-flow solvers and particle-based methods for solids, together with adaptive meshing and synchronous task-based approach with automated load balancing. When applying Uintah to fluid-structure interaction problems, the combination of adaptive meshing and the movement of structures through space present a formidable challenge in terms of achieving scalability on large-scale parallel computers. Adopting a model that uses MPI to communicate between nodes and a shared memory model on-node is one approach to achieve scalability on large-scale systems.This scalability challenge is addressed here for Uintah, by the development of new hybrid runtime and scheduling algorithms combined with novel lock-free data structures, making it possible for Uintah to achieve excellent scalability for a challenging fluid-structure problem with mesh refinement on as many as 256K cores.