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GPU acceleration for evolutionary topology optimization of continuum structures using isosurfaces

机译:GPU加速用于使用等值面的连续体结构的演化拓扑优化

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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. (C) 2016 Elsevier Ltd. All rights reserved.
机译:就内存消耗和处理时间而言,三维连续体结构的进化拓扑优化是一项计算要求很高的任务。这项工作旨在减轻这些限制,提出了一种适用于图形处理单元(GPU)计算的策略。该提议采用无矩阵迭代求解器的细粒度GPU实例进行结构分析,并采用有效的GPU实现进行等值面提取和体积分数计算。使用两种预处理技术评估求解阶段的性能,包括与稀疏矩阵CPU实现的比较。使用针对实际应用的拓扑优化问题评估该建议。 (C)2016 Elsevier Ltd.保留所有权利。

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