University of Münster（明斯特大学）；Heidelberg University（海德堡大学）；Consiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie (CNR-IFN)（意大利国家研究委员会，光子学与纳米技术研究所）；Leibniz University Hannover（汉诺威莱布尼茨大学）；University of Oxford（牛津大学）；University of Exeter（埃克塞特大学）
Ivonne Bente, Shabnam Taheriniya, Francesco Lenzini, Frank Brückerhoff-Plückelmann, Michael Kues, Harish Bhaskaran, C David Wright, Wolfram Pernice
The rapidly increasing demands for computational throughput, bandwidth, and memory capacity fueled by breakthroughs in machine learning pose substantial challenges for conventional electronic computing platforms. For digital scaling to keep pace with the accelerating growth of artificial intelligence (AI) models beyond the trajectory of Moores law, computational power has to double roughly every three months. Historically, advancing compute performance relied on spatial scaling to increase the transistor count on a given chip area and, more recently, the development of parallel and multi-core architectures. Exponential scaling on trajectories much steeper than what can be achieved by such conventional strategies, and in line with the demands of AI, can be achieved with computing platforms that process data using multiple, orthogonal dimensions available to photons. Here we elucidate pivotal developments in the realization of multidimensional computing platforms based on photonic systems. Moving to such architectures holds enormous promise for low-latency, high-bandwidth information processing at reduced energy consumption.
University of Münster（明斯特大学）；Kirchhoff-Institute for Physics, University of Heidelberg（海德堡大学基尔霍夫物理研究所）；IBM Research Europe（IBM欧洲研究院）；Institute of Computer Engineering, University of Heidelberg（海德堡大学计算机工程研究所）；Department of Engineering, University of Exeter（埃克塞特大学工程系）；Department of Materials, University of Oxford（牛津大学材料系）
并置的数据处理和存储是生物系统中的规范。事实上，冯·诺依曼计算架构在物理上和时间上将处理和存储分开，它的诞生更多地是基于现有技术的实用主义。随着我们创造更好硬件的能力的提高，新的计算范式正在被探索。集成光子电路被认为是仅使用光的片上计算的有吸引力的解决方案，利用了在光域中工作的增加的速度和带宽潜力，并且重要的是，消除了对时间和能量消耗的电光转换的需要。在这里，我们表明，我们可以结合集成光学与同位数据存储和处理的新兴领域，使全光子内存计算。通过采用基于相变材料Ge 2Sb 2 Te 5的非易失性光子元件，我们能够在单个器件上实现直接标量乘法。这种元件具有新颖的单次写入/写入和无漂移工艺，可以通过将其值映射到输入脉冲的能量和器件的透射率来乘以两个标量数，并在元件的晶体状态中进行编码。输出脉冲携带着光与物质相互作用的信息，是计算的结果。我们的全光学方法是新颖的，易于制造和操作，并为完全光子计算机的发展奠定了基础。
