Growing interest in semiconductor workforce development has generated demand for platforms capable of supporting large numbers of independent hardware designs for research and training without imposing high per-project overhead. Traditional multi-project wafer (MPW) services based solely on physical co-placement have historically met this need, yet their scalability breaks down as project counts rise. Recent efforts towards scalable chip tapeouts mitigate these limitations by integrating many small designs within a shared die and attempt to amortize costly resources such as IO pads and memory macros. However, foundational principles for arranging, linking, and validating such densely integrated design sites have received limited systematic investigation. This work presents a new approach with three key techniques to address this gap. First, we establish a structured formulation of the design space that enables automated, algorithm-driven packing of many projects, replacing manual layout practices. Second, we introduce an architecture that exploits only the narrow-area regions between sites to deliver on off-chip communication and other shared needs. Third, we provide a practical approach for on-chip power domains enabling per-project power characterization at a standard laboratory bench and requiring no expertise in low-power ASIC design. Experimental results show that our approach achieves substantial area reductions of up to 13x over state-of-the-art physical-only aggregation methods, offering a scalable and cost-effective path forward for large-scale tapeout environments.
翻译:半导体人才培养日益受到关注,催生了对于能够支持大量独立硬件设计以用于研究和培训的平台的需求,同时要求不增加高昂的单项目开销。传统仅基于物理共置的多项目晶圆(MPW)服务历来满足这一需求,但随着项目数量增加,其可扩展性面临瓶颈。近期面向可扩展芯片流片的努力通过将多个小型设计集成在共享芯片内,并尝试分摊如IO焊盘和存储宏单元等昂贵资源,以缓解这些限制。然而,对于此类高密度集成设计单元的排列、连接和验证的基础原则,目前缺乏系统性的研究。本文提出一种新方法,包含三项关键技术以填补这一空白。首先,我们建立了设计空间的结构化表述,实现了多个项目的自动化、算法驱动的布局,替代了手动布局实践。其次,我们引入一种架构,仅利用单元间的狭窄区域来实现片外通信及其他共享需求。第三,我们提供了一种实用的片上电源域方法,使得每个项目可在标准实验台上进行电源特性分析,且无需低功耗ASIC设计专业知识。实验结果表明,我们的方法相较于最先进的纯物理聚合方法,实现了高达13倍的面积缩减,为大规模流片环境提供了一条可扩展且经济高效的路径。