EAGER: Cybermanufacturing: Software/Hardware Combined Acceleration for 3D Printing in Mass Customization

制造业和生产一直是提高人类生活质量和可持续性的重要贡献者。当前的市场趋势，如消费者对多样性、短产品生命周期、高产品质量和低成本的需求，导致了对高效、响应迅速、稳健和可持续的制造和生产模式的需求。3D打印技术具有可负担性和可定制性的优点，而在真实的生活中应用3D打印进行大规模定制的关键挑战是如何减少每单位的交付时间。3D打印产品单元的交付周期来自两个来源，即，预制计算和制造过程。在3D打印大规模定制的制造流程中，预制计算的重要性日益突出，成为制造流程的瓶颈。 这个早期概念探索性研究资助（EAGER）项目旨在通过新的计算方法解决这个问题，该方法有可能将预制造计算的时间减少两个数量级。该项目旨在开发大规模定制中3D打印的变革性计算范式。该项目将追求两个新的和互补的目标：1）设计一套质量保证的几何算法的可扩展性和时间效率的预制计算框架。以及2）开发一个低复杂性和高效率的计算系统，以促进和加速使用这些方法和算法。这种新的计算机系统专注于特定领域的计算平台，作为下一个突破性技术，以提高功率-性能-运行时效率。 具体来说，该团队将开发基于加速器的架构，用于计算几何算法的基元。这种新的硬件架构将利用并行性和定制性来提高3D打印中新计算范式的效率，具有更少的延迟，更低的复杂性和更高的计算能力。

Manufacturing and production have been big contributors to improved quality and sustainability of human life. Current market trends, such as consumer demand for variety, short product life cycles, high product quality and low cost, have resulted in the need for efficient, responsive, robust and sustainable manufacturing and production paradigm. 3D printing technologies hold the merit of affordability and customizability, while the key challenge in applying 3D printing for mass customization in real life is how to reduce the lead time per unit. The lead time of 3D printing a product unit comes from two sources, i.e., the pre-fabrication computation and manufacturing process. The pre-fabrication computation is increasingly significant and becomes the bottleneck in the manufacturing flow of mass customization in 3D Printing. This EArly-concept Grant for Exploratory Research (EAGER) project looks to address this problem through new computational methods with potential for two orders of magnitude reduction in time for pre-facbrication computation.This project aims to develop a transformative computational paradigm of 3D printing in mass customization. The project will pursue two novel and complementary objectives: 1) design a suite of quality-guaranteed geometric algorithms for the scalable and time-efficient pre-fabrication computation framework.; and 2) develop a low-complexity and efficient computing system to facilitate and accelerate the use of these methods and algorithms in Objective1. This new computer system focuses on domain-specific computing platforms as the next disruptive technology for power-performance-runtime efficiency improvement. Specifically, the team will develop accelerator-based architectures for computing primitives of geometric algorithms. This new hardware architecture will exploit the parallelism and customization to improve the efficiency of the new computational paradigm in 3D printing with less delay, lower complexity and higher computing power.