Large-scale Sustainable Search on Unconventional Computing Hardware

Abstract

Since the advent of the Internet, quantifying the relative importance of web pages is at the core of search engine methods. According to one algorithm, PageRank, the worldwide web structure is represented by the Google matrix, whose principal eigenvector components assign a numerical value to web pages for their ranking. Finding such a dominant eigenvector on an ever-growing number of web pages becomes a computationally intensive task incompatible with Moore's Law. We demonstrate that special-purpose optical machines such as networks of optical parametric oscillators, lasers, and gain-dissipative condensates, may aid in accelerating the reliable reconstruction of principal eigenvectors of real-life web graphs. We discuss the feasibility of simulating the PageRank algorithm on large Google matrices using such unconventional hardware. We offer alternative rankings based on the minimisation of spin Hamiltonians. Our estimates show that special-purpose optical machines may provide dramatic improvements in power consumption over classical computing architectures.

arXiv comment17 pages, 5 figures

References in corpus (20)

• Neuromorphic Silicon Photonic Networks
• Bose-Einstein condensation of photons in an optical microcavity
• Network of Time-Multiplexed Optical Parametric Oscillators as a Coherent Ising Machine
• A Coherent Ising Machine Based On Degenerate Optical Parametric Oscillators
• Large-scale photonic Ising machine by spatial light modulation
• Quantum Hopfield neural network
• Google matrix analysis of directed networks
• Nanophotonic spin-glass for realization of a coherent Ising machine
• Adiabatic quantum algorithm for search engine ranking
• Sign-changing photon-mediated atom interactions in multimode cavity QED
• Variable Potentials for Thermalized Light and Coupled Condensates
• Optical control of synchronous phases in a programmable polariton cell
• Summarizing CPU and GPU Design Trends with Product Data
• Enhancing associative memory recall and storage capacity using confocal cavity QED
• Realizing spin-Hamiltonians in nanoscale active photonic lattices
• Controllable Josephson junction for photon Bose-Einstein condensates
• Number Partitioning with Grover's Algorithm in Central Spin Systems
• Polaritonic network as a paradigm for dynamics of coupled oscillators
• Exact Mapping Between a Laser Network Loss Rate and the Classical XY Hamiltonian by Laser Loss Control
• Universal Emergence of PageRank