Learning at scale often requires domain-specific automation such as assessment and feedback. An organization locked in to a general learning platform without these specialist automations limits its pedagogical offering. An ecosystem of interoperable, platform-agnostic microservices for domain-specific automation would solve this problem. To develop an effective ecosystem, a standard interface (API) for education microservices is required.

In recent years,Silicon Dangling Bond(SiDB) logic has emerged as a promising beyond-CMOS technology due to its integration density and operating frequency. This advancement is driving the development of comprehensive design automation workflows, including physical simulators and gate design tools. Unlike conventional circuit technology, where logic is implemented through transistors, SiDB logic utilizes quantum dots with variable charge states. By strategically arranging these dots, standard logic functions like OR, AND, NAND, etc. can be implemented, which are usually provided asStandard Cellsin design processes. However, finding such arrangements that implement a given Boolean function is a tremendously complex task that involves considering numerous candidates and verifying them through computationally expensive physical simulation. Hence, the automatic obtainment of SiDB logic layouts is thus far limited to simple 2-input functions only— which already require substantial computation resources. In contrast, conventional physical design algorithms for VLSI have long transitioned from single-gate considerations to multi-input standard cells. To address this challenge, this paper proposesQuickCell: A fast algorithm for automatic standard cell design for SiDB logic that uses dedicated search space pruning techniques. In an extensive experimental evaluation, it is demonstrated that combining these pruning techniques yields 1) a drastic reduction of the search space amounting to up to six orders of magnitude, 2) a corresponding decrease of the runtime by up to a factor of 91, 3) the capability to handle more complex functionality, as, e. g., utilized in standard cells, for the first time, significantly narrowing the gap between SiDB logic and conventional CMOS design paradigms, and 4) a significant speedup compared to physical simulation (up to a factor of 10 000), with near independence from the number of I/O pins when determining the non-operationality of a given layout. This efficiency makes these techniques—and by extensionQuickCell—a powerful enabler for the design of complex standard cells.

In recent years, Silicon Dangling Bond (SiDB) logic has emerged as a promising beyond-CMOS technology. Unlike conventional circuit technology, where logic is realized through transistors, SiDB logic utilizes quantum dots with variable charge states. By strategically arranging these dots, logic functions can be constructed. However, determining such arrangements is a tremendously complex task. Because of that, the automatic obtainment of SiDB logic implementations is inefficient. To address this challenge, we propose an idea to speed up the design process by utilizing dedicated search space pruning strategies. Initial results show that the combined pruning techniques yield 1) a drastic reduction of the search space, and 2) a corresponding reduction in runtime by up to a factor of 33.

Recent advancements in Silicon Dangling Bond (SiDB) fabrication have transitioned from manual to automated processes. However, sub-nanometer substrate defects remain a significant challenge, thus preventing the fabrication of functional logic. Current design automation techniques lack defect-aware strategies. This paper introduces an idea for a surface defect model based on experimentally verified defects, which can be applied to enhance the robustness of established gate libraries. Additionally, a prototypical automatic placement and routing algorithm is presented, utilizing STM data from physical experiments to obtain dot- accurate circuitry resilient to atomic surface defects. Initial evaluations on surfaces with varying defect rates demonstrate their critical impact, suggesting that fabrication processes must achieve defect rates of around 0.1 % to further advance this circuit technology.

Field-coupled Nanocomputing (FCN) defines a class of post-CMOS nanotechnologies that promises compact layouts, low power operation, and high clock rates. Recent breakthroughs in the fabrication of Silicon Dangling Bonds (SiDBs) acting as quantum dots enabled the demonstration of a sub-30 nm2 OR gate and wire segments. This motivated the research community to invest manual labor in the design of additional gates and whole circuits which, however, is currently severely limited by scalability issues. In this work, these limitations are overcome by the introduction of a design automation framework that establishes a flexible topology based on hexagons as well as a corresponding Bestagon gate library for this technology and, additionally, provides automatic methods for physical design. By this, the first design automation solution for the promising SiDB platform is proposed. In an effort to support open research and open data, the resulting framework and all design files will be made available.