RAISE: MemComputing: From Software to Hardware

MemComputing是一种非传统的、基于物理的计算范式，它利用了任何物理系统普遍存在的时间非局部性，即它们过去动态的记忆。虽然它与传统的计算模型，甚至量子计算有着根本的不同，但它可以在现代计算机上的软件中进行仿真。这是因为它依赖于非量子动力学系统来计算。数字版MemComputing机器（DMMs）的软件仿真已经显示出与传统算法相比在解决一些困难的计算问题方面的巨大优势。然而，在许多学术和工业应用中，这些机器的硬件实现不仅是优选的，而且甚至是必要的。这个RAISE项目的主要目标正是在硬件中实现MemComputing，并在一组具有代表性的计算密集型问题上测试其效率。本项目将为最终实现数字万用表作为传统计算机系统的协处理器奠定基础，以增强和大大扩展其功能。最先进的现场可编程门阵列（FPGA）将用于实现这些计算机。为了帮助他们的硬件设计，MemComputing地图的理论将被开发来分析DMM的动态，了解他们的工作方式，并提出改进建议。从小型原型开始，中型和大型DMM将在FPGA中实现。各种组合优化问题解决方案中的时间、空间和能量可扩展性将被用作改进其设计并推动硬件所施加的界限（例如FPGA中逻辑单元的数量）的指标。该项目涉及到计算的核心，具有深远的影响。事实上，它的跨学科性将有助于未来工作人员的专业发展，他们能够成功地跨越传统的学科界限，因为它在工业和学术界都变得越来越重要。最后，MemComputing是一种变革性技术，可以在当今快速发展的科学和工业领域为其用户提供明显的竞争优势。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

MemComputing is an unconventional, physics-based computing paradigm that exploits the ubiquitous time non-locality of any physical system, namely memory of their past dynamics. Although it is fundamentally different from the traditional computing model, and even quantum computing, it can be emulated in software on modern computers. This is because it relies on non-quantum dynamical systems to compute. The software emulation of the digital version of MemComputing machines (DMMs) has already shown great advantages compared to traditional algorithms in the solution of some hard computational problems. However, there are many academic and industrial applications for which a hardware implementation of these machines is not only preferable, but even necessary. The main goal of this RAISE project is precisely to implement MemComputing in hardware, and test its efficiency on a representative set of computationally-intensive problems. This project will then set the foundations towards the ultimate goal of realizing such DMMs as co-processors in our traditional computing systems to both enhance and greatly extend their functions.State-of-the-art field-programmable gate arrays (FPGAs) will be used to implement these computing machines. To assist their hardware design, a theory of MemComputing maps will be developed to analyze the dynamics of DMMs, understand their modus operandi, and suggest improvements. Starting from small-size prototypes, medium- and large-size DMMs will be implemented in FPGAs. Time, space, and energy scalability in the solution of various combinatorial optimization problems will be used as metrics to improve on their design and push the bounds imposed by the hardware (such as the amount of logic cells in FPGAs). The project goes to the very core of what it means to compute, with far-reaching implications. In fact, its interdisciplinarity will help the professional development of a future work force skilled in successfully navigating across traditional disciplinary boundaries, as it is becoming ever more relevant in both industry and academia. Finally, MemComputing is that type of transformative technology that may provide a clear competitive edge to its users in the rapidly evolving scientific and industrial landscape of today.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.