Pages that link to "Item:Q2310111"
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The following pages link to A GPU domain decomposition solution for spectral stochastic finite element method (Q2310111):
Displaying 13 items.
- A new era in scientific computing: domain decomposition methods in hybrid CPU-GPU architectures (Q653690) (← links)
- A new perspective on the solution of uncertainty quantification and reliability analysis of large-scale problems (Q1667266) (← links)
- Large-scale stochastic topology optimization using adaptive mesh refinement and coarsening through a two-level parallelization scheme (Q1986447) (← links)
- Spectral stochastic isogeometric analysis of free vibration (Q1987952) (← links)
- A comparison of stochastic and data-driven FEM approaches to problems with insufficient material data (Q1988000) (← links)
- Stochastic nonlocal damage analysis by a machine learning approach (Q2020969) (← links)
- Hybrid uncertainty analysis of functionally graded plates via multiple-imprecise-random-field modelling of uncertain material properties (Q2021161) (← links)
- Scalable domain decomposition solvers for stochastic PDEs in high performance computing (Q2310941) (← links)
- Towards a complete FEM-based simulation toolkit on GPUs: unstructured grid finite element geometric multigrid solvers with strong smoothers based on sparse approximate inverses (Q2446654) (← links)
- A GPU parallel randomized CUR compression method for the method of moments (Q2692476) (← links)
- A Stochastic-Based Optimized Schwarz Method for the Gravimetry Equations on GPU Clusters (Q3133684) (← links)
- Efficient numerical strategies for spectral stochastic finite element models (Q3425324) (← links)
- A FETI‐preconditioned conjugate gradient method for large‐scale stochastic finite element problems (Q3649915) (← links)
