Parallel framework for topology optimization using the method of moving asymptotes
Structural and Multidisciplinary Optimization
High resolution topology optimization using graphics processing units (GPUs)
Structural and Multidisciplinary Optimization
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We show how the computational power and programmability of modern graphics processing units (GPUs) can be used to efficiently solve large-scale pixel-based material distribution problems using a gradient-based optimality criterion method. To illustrate the principle, a so-called topology optimization problem that results in a constrained nonlinear programming problem with over 4 million decision variables is solved on a commodity GPU.