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- W2567231120 abstract "Well-suited strategy for GPU computing of ESO method driven by isosurfaces is proposed.Comparison of GPU instance of PCG using Jacobi and geometric multigrid preconditioning is presented.Different granularities are used to balance the workload of CUDA threads.Significant speedups with respect to sparse-matrix CPU implementation are achieved.High resolution truss-like designs of real-world topology optimization problems are presented. Evolutionary topology optimization of three-dimensional continuum structures is a computationally demanding task in terms of memory consumption and processing time. This work aims to alleviate these constraints proposing a well-suited strategy for Graphics Processing Unit (GPU) computing. Such a proposal adopts a fine-grained GPU instance of matrix-free iterative solver for structural analysis and an efficient GPU implementation for isosurface extraction and volume fraction calculation. The performance of the solving stage is evaluated using two preconditioning techniques, including the comparison with the sparse-matrix CPU implementation. The proposal is evaluated using topology optimization problems for real-world applications." @default.
- W2567231120 created "2017-01-06" @default.
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- W2567231120 date "2017-04-01" @default.
- W2567231120 modified "2023-10-17" @default.
- W2567231120 title "GPU acceleration for evolutionary topology optimization of continuum structures using isosurfaces" @default.
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- W2567231120 doi "https://doi.org/10.1016/j.compstruc.2016.10.018" @default.
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