We propose an optical computational device which uses light rays for solving the subset-sum problem. The device has a graph-like representation and the light is traversing it by following the routes given by the connections between nodes. The nodes are connected by arcs in a special way which lets us to generate all possible subsets of the given set. To each arc we assign either a number from the given set or a predefined constant. When the light is passing through an arc it is delayed by the amount of time indicated by the number placed in that arc. At the destination node we will check if there is a ray whose total delay is equal to the target value of the subset sum problem (plus some constants). The proposed optical solution solves a NP-complete problem in time proportional with the target sum, but requires an exponential amount of energy.
Another idea is to use light instead of electrical power. It is hoped that optical computing could advance computer architecture and can improve the speed of data input and output by several orders of magnitude @cite_12 .
@cite_12
2139842859 2013785177 1672611793 2027561983
Optical-computing technology offers new challenges to algorithm designers since it can perform an n-point discrete Fourier transform (DFT) computation in only unit time. Note that the DFT is a nontrivial computation in the parallel random-access machine model, a model of computing commonly used by parallel-algorithm designers. We develop two new models, the DFT–VLSIO (very-large-scale integrated optics) and the DFT–circuit, to capture this characteristic of optical computing. We also provide two paradigms for developing parallel algorithms in these models. Efficient parallel algorithms for many problems, including polynomial and matrix computations, sorting, and string matching, are presented. The sorting and string-matching algorithms are particularly noteworthy. Almost all these algorithms are within a polylog factor of the optical-computing (VLSIO) lower bounds derived by Barakat Reif [Appl. Opt.26, 1015 (1987) and by Tyagi Reif [Proceedings of the Second IEEE Symposium on Parallel and Distributed Processing (Institute of Electrical and Electronics Engineers, New York, 1990) p. 14]. This paper proposes CoNoC (Contention-free optical NoC) as a new architecture for on-chip routing of optical packets. CoNoC is built upon all-optical switches (AOSs) which passively route optical data streams based on their wavelengths. The key idea of the proposed architecture is the utilization of per-receiver wavelength in the data network to prevent optical contention at the intermediate nodes. Routing optical packets according to their wavelength eliminates the need for resource reservation at the intermediate nodes and the corresponding latency, power, and area overheads. Since passive architecture of the AOS confines the optical contention to the end-points, we propose an electrical arbitration architecture for resolving optical contention at the destination nodes. By performing a series of simulations, we study the efficiency of the proposed architecture, its power and energy consumption, and the data transmission latency. Moreover, we compare the proposed architecture with electrical NoCs and alternative ONoC architectures under various synthetic traffic patterns. Averaged across different traffic patterns, the proposed architecture reduces per-packet power consumption by 19 , 28 , 29 , and 91 and achieves per-packet energy reduction of 28 , 40 , 20 , and 99 over Columbia, Phastlane, @l-router, and electrical torus, respectively. Optical Computers provides the first in-depth review of the possibilities and limitations of optical data processing. We present a novel and simple theoretical model of computation that captures what we believe are the most important characteristics of an optical Fourier transform processor. We use this abstract model to reason about the computational properties of the physical systems it describes. We define a grammar for our model's instruction language, and use it to write algorithms for well-known filtering and correlation techniques. We also suggest suitable computational complexity measures that could be used to analyze any coherent optical information processing technique, described with the language, for efficiency. Our choice of instruction language allows us to argue that algorithms describable with this model should have optical implementations that do not require a digital electronic computer to act as a master unit. Through simulation of a well known model of computation from computer theory we investigate the general-purpose capabilities of analog optical processors.