The challenges of modern computing and new opportunities for optics

Abstract

In recent years, the explosive development of artificial intelligence implementing by artificial neural networks (ANNs) creates inconceivable demands for computing hardware. However, conventional computing hardware based on electronic transistor and von Neumann architecture cannot satisfy such an inconceivable demand due to the unsustainability of Moore’s Law and the failure of Dennard’s scaling rules. Fortunately, analog optical computing offers an alternative way to release unprecedented computational capability to accelerate varies computing drained tasks. In this article, the challenges of the modern computing technologies and potential solutions are briefly explained in Chapter 1. In Chapter 2, the latest research progresses of analog optical computing are separated into three directions: vector/matrix manipulation, reservoir computing and photonic Ising machine. Each direction has been explicitly summarized and discussed. The last chapter explains the prospects and the new challenges of analog optical computing.

Photonic Multiplexing Techniques for Optical Neuromorphic Computing

“…Spatial-division multiplexing is a fundamental approach to boost the computing parallelism and enhance the overall computing speed, as has been widely used in traditional digital computing systems [14][15][16][17][18][19][20][21][22][23][24][25]. ONNs based on SDM feature architectures where the input nodes X and/or weighted synapses W are mapped onto the spatial division.…”

“…The unique advantages of light, such as its ultrawide bandwidths of up to 10's of THz, the low propagation loss and the inherent nature of its analog architecture, make optical neuromorphic computing hardware promising to address the challenges faced by their electronic counterparts [14][15][16][17][18][19][20][21][22][23][24][25]. Ultimately hybrid opto-electronic computing hardware that leverage the broad bandwidths of optics without sacrificing the flexibility of digital electronics may provide the ideal solution.…”

“…Recently, the advances in ONNs have been reviewed from a number of different perspectives [14][15][16][17][18][19][20][21][22][23][24][25], including introducing: optical field interferences for visual computing applications [18], integrated neuromorphic systems and the underlying hardware for implementing weighted interconnects and neurons [19], the training methods [21], energy consumption [22] and prospects and applications of ONNs [23]. Here, we review the most recent advances of ONNs from the perspective of the fundamental photonic multiplexing techniques that offer physical parallelism for the implementation of ONNs.…”

Controllable multiple beam splitting in Hermitian and non-Hermitian symmetric coupled waveguide systems

“…However, mainly motivated by the development of on-chip high-bandwidth photonics which requires a larger number of output ports. The multiway beam splitters form the basic building blocks in wavelength division multiplexing systems and in fibre to home networks [10], and are critically essential for the implementation of quantum logic gates in future quantum computers [11,12]. There has been a growing trend in the realization of multiple waveguides (1 × N ) [10,[13][14][15][16] or from multiple to multiple channels (N × N ) [17].…”

Multiplexed optical differentiator enabled by single-size nanostructured metasurface

“…Compared with traditional methods based on electrical circuits, optical computing has the advantages of parallel processing, high speed and ultra-low power consumption, which is especially suitable for the field of real-time processing with large data rates [1][2][3][4][5][6][7][8][9][10][11][12] . Recently, optical computation 2 devices including Mach-Zehnder Interferometers (MZI) 13,14 , Bragg grating 15 , Microring resonator (MRR) [16][17][18] and photonic crystal microcavity 19 have been widely studied.…”