This article presents a significant advancement in the field of three-dimensional (3D) printing. We have developed a fast parallel computation algorithm that predicts the optimal orientation of 3D printing using a general-purpose graphic processor unit (GPU). Initially designed for the central processing unit (CPU) version support structure tomography, our algorithm has been successfully adapted for NVIDIA graphic processors and the CUDA toolkit. Despite encountering several challenges, we have achieved a remarkable improvement in calculation speed. Two CPUs and four GPUs of various prices and performances were used for the speed comparison. The high-end GPU showed a surprising multiprocessing performance; a maximum of 16.2 times for Dragon mesh data and 11.2 times on average than the high-end CPU. The proposed method assumes that the input triangle should have a bigger size than the voxel size and a relatively smaller number of triangles, about tens of thousands. Nevertheless, the algorithm has the potential to significantly enhance the efficiency and quality of 3D printing, addressing some constraints and expanding its practical applications.
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