ALBERT

Description: Accurate predictions of future sea level rise require numerical models that capture the complex thermomechanical feedbacks in rapidly deforming ice. Shear margins, grounding zones and the basal sliding interface are locations of particular interest where the stress-field is complex and fundamentally three-dimensional. These transition zones are prone to thermomechanical localisation, which can be captured numerically only with high temporal and spatial resolution. Thus, better understanding the coupled physical processes that govern these boundaries of localised strain necessitates a non-linear, full Stokes model that affords high resolution and scales well in three dimensions. This paper’s goal is to contribute to the growing toolbox for modelling thermomechanical deformation in ice by levering GPU accelerators’ parallel scalability. We propose a numerical model that relies on pseudo-transient iterations to solve the implicit thermomechanical coupling between ice motion and temperature involving shear-heating and a temperature-dependant ice viscosity. Our method is based on the finite-difference discretisation, and we implement the pseudo-time integration in a matrix-free way. We benchmark the mechanical Stokes solver against the finite-element code Elmer/Ice and report good agreement among the results. We showcase a parallel version of the solver to run on GPU-accelerated distributed memory machines, reaching a parallel efficiency of 93 %. We show that our model is particularly useful for improving our process-based understanding of flow localisation in the complex transition zones bounding rapidly moving ice.

Description: Ice sheets lose the majority of their mass through outlet glaciers or ice streams, corridors of fast ice moving multiple orders of magnitude more rapidly than the surrounding ice. The future stability of these corridors of fast-moving ice depends sensitively on the behaviour of their boundaries, namely shear margins, grounding zones and the basal sliding interface, where the stress field is complex and fundamentally three-dimensional. These boundaries are prone to thermomechanical localisation, which can be captured numerically only with high temporal and spatial resolution. Thus, better understanding the coupled physical processes that govern the response of these boundaries to climate change necessitates a non-linear, full Stokes model that affords high resolution and scales well in three dimensions. This paper's goal is to contribute to the growing toolbox for modelling thermomechanical deformation in ice by leveraging graphical processing unit (GPU) accelerators' parallel scalability. We propose FastICE, a numerical model that relies on pseudo-transient iterations to solve the implicit thermomechanical coupling between ice motion and temperature involving shear heating and a temperature-dependent ice viscosity. FastICE is based on the finite-difference discretisation, and we implement the pseudo-time integration in a matrix-free way. We benchmark the mechanical Stokes solver against the finite-element code Elmer/Ice and report good agreement among the results. We showcase a parallel version of FastICE to run on GPU-accelerated distributed memory machines, reaching a parallel efficiency of 99 %. We show that our model is particularly useful for improving our process-based understanding of flow localisation in the complex transition zones bounding rapidly moving ice.

Description: We present an efficient MATLAB-based implementation of the material point method (MPM) and its most recent variants. MPM has gained popularity over the last decade, especially for problems in solid mechanics in which large deformations are involved, such as cantilever beam problems, granular collapses and even large-scale snow avalanches. Although its numerical accuracy is lower than that of the widely accepted finite element method (FEM), MPM has proven useful for overcoming some of the limitations of FEM, such as excessive mesh distortions. We demonstrate that MATLAB is an efficient high-level language for MPM implementations that solve elasto-dynamic and elasto-plastic problems. We accelerate the MATLAB-based implementation of the MPM method by using the numerical techniques recently developed for FEM optimization in MATLAB. These techniques include vectorization, the use of native MATLAB functions and the maintenance of optimal RAM-to-cache communication, among others. We validate our in-house code with classical MPM benchmarks including (i) the elastic collapse of a column under its own weight; (ii) the elastic cantilever beam problem; and (iii) existing experimental and numerical results, i.e. granular collapses and slumping mechanics respectively. We report an improvement in performance by a factor of 28 for a vectorized code compared with a classical iterative version. The computational performance of the solver is at least 2.8 times greater than those of previously reported MPM implementations in Julia under a similar computational architecture.