ASCENT: Collaborative Research: Programmable Photonic Computation Accelerators (PPCA)

随着第四次工业革命的临近，大规模计算变得比以往任何时候都更加苛刻和流行。然而，传统电子微处理器的性能几乎达到了器件速度、片上密度和功耗的极限，将无法继续维持即将到来的数据爆炸。与电子器件相比，光学计算可以非常快并且具有低功耗要求，因为其固有的高速度，大带宽和无限并行性，这对于缓解与需要真实的时间做出人工智能决策的应用相关的数据流量至关重要。现代人工智能的数据驱动训练需要可编程计算的新方法。在该项目中，研究人员将利用最先进的集成光子技术开发创新的可编程光子计算加速器（PPCA），加快计算速度，降低成本和能耗，以维持机器学习的长期性能要求。这项研究与现有的教育活动紧密结合，为本科生和研究生提供了以创新方式参与尖端科学技术的机会。研究人员还提供集成光子设备，机器学习和计算机算法的教育推广活动，以促进K-12学生的兴趣和参与，并扩大代表性不足的群体的参与。技术说明：在电气，通信和网络系统（ECCS）部门的资助下，来自宾夕法尼亚大学和加州大学圣地亚哥分校的研究人员正在开发一种颠覆性的系统级集成纳米光子电路-可编程光子计算加速器（PPCA）-通过量子对称的战略工程进行主动控制，以执行实时可编程数学运算并实现机器学习算法。将探索独特的几何驱动的几何形状，以提供矩阵乘法所需的新型拓扑光子组件，可以通过灵活控制空间变化的光学调制来动态编程。在开发的可编程光子计算加速器平台上，将执行不同的标志性机器学习算法，首次演示光学机器学习，并测试其相应的速度和保真度。研究人员在有源光子电路，集成器件，系统和封装以及计算和机器学习方面具有高度互补的专业知识，这些专业知识将积极协同，从而实现向大规模光子计算加速器的系统级集成的范式转变。如果成功，创新的可编程光子计算加速器可以应用于需要极高速度，能源效率，并行性，显着复杂性和高度可扩展性的领域，在超紧凑的足迹，和完全的可编程性。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

As the Fourth Industrial Revolution is approaching, large-scale computing is becoming more demanding and popular than ever. However, the performance of conventional electronic microprocessors has almost reached their limits for device speed, on-chip density and power consumption and will not be able to continue sustaining the upcoming data explosion. Optical computation can be extremely fast and with low-power requirements compared to electronics, for its intrinsic high speed, large bandwidth, and unlimited parallelism, which are critical to ease the data traffic associated with applications where artificial intelligence decisions need to be made in real time. Novel approaches towards programmable computations are required for data-driven training of modern artificial intelligence. In this project, the investigators will leverage the state-of-the-art integrated photonics technology to develop an innovative programmable photonic computation accelerators (PPCA), accelerating the computation speed and reducing the cost and energy consumption to sustain long term performance requirements for machine learning. This research is closely integrated with the existing educational activities, providing both undergraduate and graduate students with the opportunity to participate in cutting-edge science and technology in an innovative way. The investigators also provide educational outreach activities in integrated photonic devices, machine learning, and computer algorithms to promote the interests and participations of K-12 students and broaden the participations from underrepresented groups. Technical description: With funding from the Electrical, Communications and Cyber Systems (ECCS) Division, the investigators from the University of Pennsylvania and University of California, San Diego are developing a disruptive system-level integrated nanophotonic circuits – Programmable Photonic Computation Accelerators (PPCA) – through active control via strategic engineering of quantum symmetry, to perform real-time programmable mathematical operations and implement machine learning algorithms. Unique symmetry-driven geometries will be explored to deliver novel topological photonic components required for matrix multiplication, which can be dynamically programmed by flexible control of spatial-variant optical modulation. On the developed programmable photonic computation accelerator platform, different iconic machine learning algorithms will be performed to demonstrate optical machine learning for the first time and test its corresponding speed and fidelity. The investigators have highly complementary expertise on active photonic circuits, integrated devices, systems, and packaging, as well as computation and machine learning, which will be actively synergized, enabling a paradigmatic shift towards system-level integration of large-scale photonic computation accelerators. If successful, the innovative programmable photonic computation accelerators could be applied in the domains which demand extreme speed, energy efficiency, parallelism, significant complexity, and high scalability on an ultra-compact footprint, and full programmability.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.