Sharif Digital Repository

This paper proposes a new optical network-on-chip which is scalable, low-power and high-performance. We design a centralized all-optical router which takes advantage of wavelength based structures. Our design achieves fully contention-free operation by utilizing path-based algorithms. By merging primary photonic switches and utilizing WDM technique, we mitigated the number of basic switching elements and thus reduced the consumed power down to 47.37% in comparison with the most prominent structure introduced for wavelength routing; i.e., the λ-Router. We obtained this superiority while maintaining the performance as high as the previous structures, which yields in energy savings. Moreover,... 

Two main sources for power dissipation in parallel buses are data transitions on each wire and coupling between adjacent wires. So far, many techniques have been proposed for reducing the self and coupling powers. Most of these methods utilize one (or more) control bit(s) to manage the behavior of data transitions on the parallel bus. In this paper, we propose a new coding scheme, referred to as GPH, to reduce power dissipation of these control bits. GPH coding scheme employs partitioned Bus Invert and Odd Even Bus-Invert coding techniques. This method benefits from Particle Swarm Optimization (PSO) algorithm to efficiently partition the bus. In order to reduce self and coupling powers of... 

We propose a new optical reconfigurable Network-on-Chip (NoC), named ReFaT ONoC (Reconfigurable Flat and Tree Optical NoC). ReFaT is a dynamically reconfigurable architecture, which customizes the topology and routing paths based on the application characteristics. ReFaT, as an all-optical NoC, routes optical packets based on their wavelengths. For this purpose, we propose a novel architecture for the optical switch, which eliminates the need for optical resource reservation, and thus avoids the corresponding latency and area overheads. As a key idea for dynamic reconfiguration, each application is mapped to a specific set of wavelengths and utilizes its dedicated routing algorithm. We... 

Coping with the intrinsic limitations of electrical networks-on-chip, optical on-chip interconnect is emerged as a promising paradigm for future high performance multi-core designs. However, optical networks-on-chip (ONoCs) are drastically vulnerable to on-chip thermal fluctuation. Specifically, electrical power consumed by processing cores induces temperature drift, which may cause false paths for optical data communication through the network. Therefore, customizing electrical power distribution throughout the chip plays a critical role for reliable data communication in ONoCs. On the other hand, chip-scale distribution of electrical power is directly affected by mapping various... 

Performance of a data center is a function of three features; bandwidth, latency, and reliability. By adopting optical technology in data center network, bandwidth increment, in addition to reduction of transmission latency and power consumption, is achieved. Unfortunately, fault tolerance of the optical networks has raised less attention so far. So in this paper, we propose a fault-tolerant, scalable, and high-performance optical architecture built upon previously proposed O-TF network, with the goal of redundancy optimization and reducing the minimum number of wavelength channels required for non-blocking functionality of the network. Moreover, reducing network diameter, in O-FTF network... 

Data center performance is affected by three main factors; bandwidth, latency, and reliability of intra-data center interconnection network. Bandwidth and latency are definitely improved by adopting optical technology for intra-data center communication, but fault tolerance of the corresponding optical networks has been raised less. Recently, we introduced two Torus-based, all-optical, and non-blocking networks, i.e. O-TF and O-FTF, addressing reliability of optical networks, and now, in this paper, to address the scalability problem, we propose a novel Optical Clos-based architecture which reduces minimum number of required wavelength channels, as well as, the switch size in each node.... 

Exponential growth of traffic and bandwidth demands in current data center networks requires low-latency high-throughput interconnection networks, considering power consumption. By considering growth of both multicast and unicast applications, power efficient communication becomes one of the main design challenges in today's data center networks. Addressing these demands, optical networks suggest several benefits as well as circumventing most disadvantages of electrical networks. In this paper, we propose an all-optical scalable architecture, named as OMUX, for communicating intra-data centers. This architecture utilizes passive optical devices and enables optical circuit switching without... 

Integrated silicon photonic networks have attracted a lot of attention in the recent decades due to their potentials for low-power and high-bandwidth communications. However, these promising networks, as the future technology, are drastically susceptible to thermal fluctuations, which may paralyze wavelength-based operation of these networks. In this regard, precise addressing of thermally induced faults in optical networks-on-chip (ONoCs), as well as revealing practical methods to tackle this challenge will be a break-even point toward implementation of this technology. In this paper, thermal variation is investigated through analyzing on-chip power distribution, which is addressed by power... 

Two main sources for power dissipation in parallel buses are data transitions on each wire and coupling between adjacent wires. There are many techniques for reducing the transition and coupling powers. These methods utilize extra control bits to manage the behavior of data transitions on parallel bus. In this paper, we propose a new coding scheme which tries to reduce power dissipation of control bits. The proposed method employs partitioned Bus Invert and Odd Even Bus Invert coding techniques. This method benefits from Particle Swarm Optimization (PSO) algorithm to efficiently partition the bus. In order to reduce transition and coupling power of control bits, it finds partitions with... 

Convolutional neural networks (CNNs) are at the heart of several machine learning applications, while they suffer from computational complexity due to their large number of parameters and operations. Recently, all-optical implementation of the CNNs has achieved many attentions, however, the recently proposed optical architectures for CNNs cannot fully utilize the tremendous capabilities of optical processing, due to the required electro-optical conversions in-between successive layers. To implement an all-optical multi-layer CNN, it is essential to optically implement all required operations, namely convolution, summation of channels' output for each convolutional kernel feeding the... 

The classification of biological sequences is an open issue for a variety of data sets, such as viral and metagenomics sequences. Therefore, many studies utilize neural network tools, as the well-known methods in this field, and focus on designing customized network structures. However, a few works focus on more effective factors, such as input encoding method or implementation technology, to address accuracy and efficiency issues in this area. Therefore, in this work, we propose an image-based encoding method, called as WalkIm, whose adoption, even in a simple neural network, provides competitive accuracy and superior efficiency, compared to the existing classification methods (e.g. VGDC,... 

The classification performance of all-optical Convolutional Neural Networks (CNNs) is greatly influenced by components’ misalignment and translation of input images in the practical applications. In this paper, we propose a free-space all-optical CNN (named Trans-ONN) which accurately classifies translated images in the horizontal, vertical, or diagonal directions. Trans-ONN takes advantages of an optical motion pooling layer which provides the translation invariance property by implementing different optical masks in the Fourier plane for classifying translated test images. Moreover, to enhance the translation invariance property, global average pooling (GAP) is utilized in the Trans-ONN... 

Optical Neural Networks (ONNs) can be promising alternatives for conventional electrical neural networks as they offer ultra-fast data processing with low energy consumption. However, lack of suitable nonlinearity is standing in their road of achieving this goal. While this problem can be circumvented in feed-forward neural networks, the performance of the recurrent neural networks (RNNs) depends heavily on their nonlinearity. In this paper, we first propose and numerically demonstrate a novel reconfigurable optical activation function, named ROA, based on adding or subtracting the outputs of two saturable absorbers (SAs). RAO can provide both bounded and unbounded outputs by facilitating an... 

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the... 

In this paper, we introduce a modified optical integrator based on suitably designed metamaterial blocks. The integration is performed on an impinging wave pattern as it propagates through these blocks. So far, various metamaterial-based optical integrators have been implemented with appropriate performance in the case of zero- DC input signals. However, these integrators suffer from low accuracy when fed by signals rich in low-frequency contents. The latter property arises from truncation of low-frequency contents of the input wave in the Fourier domain. To solve this shortcoming, we propose a new metasurface-based structure which reflects low-frequency parts of the input signal in the... 

With the growing number of cores, high-performance systems face power challenges due to dominating communication power. Thus, attaining energy efficient high-bandwidth inter-core communication nominates photonic network-on chip as the most promising interconnection paradigm. Although photonic networks pave the way for extremely higher performance communications, their intrinsic susceptibility to thermal fluctuations intimidates reliability of system. This necessitates the development of methodologies to analyze and model thermal effects on network behavior. In this paper, we model temperature fluctuations of optical chips and analyze photonic networks in a holistic approach. We present a... 

In electronic computers, extensive amount of computations required for searching biological sequences in big databases leads to vast amount of energy consumption for electrical processing and cooling. On the other hand, optical processing is much faster than electrical counterpart, due to its parallel processing capability, at a fraction of energy consumption level and cost. In this regard, this paper proposes a correlation-based optical algorithm using metamaterial, taking advantages of optical parallel processing, to efficiently locate the edits as a means of DNA sequence comparison. Specifically, the proposed algorithm partitions the read DNA sequence into multiple overlapping intervals,... 

This paper presents a novel optical processing approach for exploring genome sequences built upon an optical correlator for global alignment and the extended dual-vector-curve-curve (DV-curve) method for local alignment. To overcome the problem of the traditional DV-curve method for presenting an accurate and simplified output, we propose the hybrid amplitude wavelength polarization optical DV-curve (HAWPOD) method, built upon the DV-curve method, to analyze genome sequences in three steps: DNA coding, alignment, and post-Analysis. For this purpose, a tunable graphene-based color filter is designed for wavelength modulation of optical signals. Moreover, all-optical implementation of the... 

Optical networks-on-chip are introduced as an alternative for electrical interconnects in many-core systems, due to their low delay and power consumptions, as well as their high bandwidths. Despite these advantages, physical characteristics of the photonic components are highly sensitive to thermal variations, which results in optical data misrouting through the optical networks at the presence of temperature fluctuation. In this paper, we propose a thermally-resilient all-optical communication approach which improves reliability, as well as performance of the optical networks. For this purpose, we take advantages of auxiliary waveguides and a novel wavelength assignment approach to avoid... 

This paper introduces the concept of on-chip temporal optical computing, based on dispersive Fourier transform and suitably designed modulation module, to perform mathematical operations of interest, such as differentiation, integration, or convolution in time domain. The desired mathematical operation is performed as signal propagates through a fully reconfigurable on-chip photonic signal processor. Although a few numbers of photonic temporal signal processors have been introduced recently, they are usually bulky or they suffer from limited reconfigurability which is of great importance to implement large-scale general-purpose photonic signal processors. To address these limitations, this...