What question did this study set out to answer?

This research aims to develop a randomized preconditioner that enhances the efficiency of solving nonlinear algebraic systems in multiphysics problems using GPUs.

July 1, 2026The International Journal of High Performance Computing Applications

A randomized point-block Schwarz preconditioner for multiphysics problems on fully unstructured meshes on GPUs

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Authors

WMWenpeng MaXinyang Normal University XLXiaofan LeXinyang Normal University XCXiao‐Chuan CaiUniversity of Macau

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Implication

Randomized trial shows improved performance of a preconditioner in nonlinear algebraic systems, indicating efficiency gains on heterogeneous GPU systems.

Key Points

This research aims to develop a randomized preconditioner that enhances the efficiency of solving nonlinear algebraic systems in multiphysics problems using GPUs.
Proposed a randomized iterative method for LU factorization of matrices
Utilized a warp-based thread partitioning strategy for parallel computation
Applied to discretized incompressible Navier-Stokes and hyperelasticity equations
Achieved a 12x speedup on 8 GPUs compared to 8 CPU cores
The randomized method showed 2x–5x gains over determined baseline in one application
Attained up to 45% parallel efficiency on 64 GPUs during cerebral artery blood flow simulation

Cite This Study

Ma et al. (2026) studied this question.

synapsesocial.com/papers/6a44afdc5cd2549c8bc44b2b https://doi.org/10.1177/10943420261462361

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Implication

Randomized trial shows improved performance of a preconditioner in nonlinear algebraic systems, indicating efficiency gains on heterogeneous GPU systems.

A randomized point-block Schwarz preconditioner for multiphysics problems on fully unstructured meshes on GPUs

Discussion

Member takes

Implication

Key Points

Cite This Study

A randomized point-block Schwarz preconditioner for multiphysics problems on fully unstructured meshes on GPUs

Discussion

Member takes

Implication

Key Points

Cite This Study

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