2,980 research outputs found

    Coupling Routing Algorithm and Data Encoding for Low Power Networks on Chip

    Get PDF
    The routing algorithm used in a Network-on-Chip (NoC) has a strong impact on both the functional and non functional indices of the overall system. Traditionally, routing algorithms have been designed considering performance and cost as the main objectives. In this study we focus on two important non functional metrics, namely, power dissipation and energy consumption. We propose a selection policy that can be coupled with any multi-path routing function and whose primary goal is reducing power dissipation. As technology shrinks, the power dissipated by the network links represents an ever more significant fraction of the total power budget. Based on this, the proposed selection policy tries to reduce link power dissipation by selecting the output port of the router which minimises the switching activity of the output link. A set of experiments carried out on both synthetic and real traffic scenarios is presented. When the proposed selection policy is used in conjunction with a data encoding technique, on average, 31% of energy reduction and 37% of power saving is observed. An architectural implementation of the selection policy is also presented and its impact on cost (silicon area) and power dissipation of the baseline router is discussed

    Single integrated device for optical CDMA code processing in dual-code environment

    Get PDF
    We report on the design, fabrication and performance of a matching integrated optical CDMA encoder-decoder pair based on holographic Bragg reflector technology. Simultaneous encoding/decoding operation of two multiple wavelength-hopping time-spreading codes was successfully demonstrated and shown to support two error-free OCDMA links at OC-24. A double-pass scheme was employed in the devices to enable the use of longer code length

    Book Review

    Get PDF
    A Scholarly Review of “Error Control for Network-On-Chip Links” (Authors: Bo Fu and Paul Ampadu, 2012)Fu, B.; and Ampadu, P. 2012. Error Control for Network-On-Chip Links.Springer Science+Business Media, LLC, New York, NY, USA.Available: <http://dx.doi.org/10.1007/978-1-4419-9313-7>

    Low Power Processor Architectures and Contemporary Techniques for Power Optimization – A Review

    Get PDF
    The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. © 2009 ACADEMY PUBLISHER

    Reconfigurable Instruction Cell Architecture Reconfiguration and Interconnects

    Get PDF

    Network-on-Chip

    Get PDF
    Addresses the Challenges Associated with System-on-Chip Integration Network-on-Chip: The Next Generation of System-on-Chip Integration examines the current issues restricting chip-on-chip communication efficiency, and explores Network-on-chip (NoC), a promising alternative that equips designers with the capability to produce a scalable, reusable, and high-performance communication backbone by allowing for the integration of a large number of cores on a single system-on-chip (SoC). This book provides a basic overview of topics associated with NoC-based design: communication infrastructure design, communication methodology, evaluation framework, and mapping of applications onto NoC. It details the design and evaluation of different proposed NoC structures, low-power techniques, signal integrity and reliability issues, application mapping, testing, and future trends. Utilizing examples of chips that have been implemented in industry and academia, this text presents the full architectural design of components verified through implementation in industrial CAD tools. It describes NoC research and developments, incorporates theoretical proofs strengthening the analysis procedures, and includes algorithms used in NoC design and synthesis. In addition, it considers other upcoming NoC issues, such as low-power NoC design, signal integrity issues, NoC testing, reconfiguration, synthesis, and 3-D NoC design. This text comprises 12 chapters and covers: The evolution of NoC from SoC—its research and developmental challenges NoC protocols, elaborating flow control, available network topologies, routing mechanisms, fault tolerance, quality-of-service support, and the design of network interfaces The router design strategies followed in NoCs The evaluation mechanism of NoC architectures The application mapping strategies followed in NoCs Low-power design techniques specifically followed in NoCs The signal integrity and reliability issues of NoC The details of NoC testing strategies reported so far The problem of synthesizing application-specific NoCs Reconfigurable NoC design issues Direction of future research and development in the field of NoC Network-on-Chip: The Next Generation of System-on-Chip Integration covers the basic topics, technology, and future trends relevant to NoC-based design, and can be used by engineers, students, and researchers and other industry professionals interested in computer architecture, embedded systems, and parallel/distributed systems

    Securing in-memory processors against Row Hammering Attacks

    Get PDF
    Modern applications on general purpose processors require both rapid and power-efficient computing and memory components. As applications continue to improve, the demand for high speed computation, fast-access memory, and a secure platform increases. Traditional Von Neumann Architectures split the computing and memory units, causing both latency and high power-consumption issues; henceforth, a hybrid memory processing system is proposed, known as in-memory processing. In-memory processing alleviates the delay of computation and minimizes power-consumption; such improvements saw a 14x speedup improvement, 87\% fewer power consumption, and appropriate linear scalability versus performance. Several applications of in-memory processing include data-driven applications such as Artificial Intelligence (AI), Convolutional and Deep Neural Networks (CNNs/DNNs). However, processing-in-memory can also suffer from a security and reliability issue known as the Row Hammer Security Bug; this security exploit flips bits within memory without access, leading to error injection, system crashes, privilege separation, and total hijack of a system; the novel Row Hammer security bug can negatively impact the accuracies of CNNs and DNNs via flipping the bits of stored weight values without direct access. Weights of neural networks are stored in a variety of data patterns, resulting in either a solid (all 1s or all 0s), checkered (alternating 1s and 0s in both rows and columns), row-stripe (alternating 1s and 0s in rows), or column-striped (alternating 1s and 0s in columns) manner; the row-stripe data pattern exhibits the largest likelihood of a Row Hammer attack, resulting in the accuracies of neural networks dropping over 30\%. A row-stripe avoidance coding scheme is proposed to reduce the probability of the Row Hammer Attack occurring within neural networks. The coding scheme encodes the binary portion of a weight in a CNN or DNN to reduce the chance of row-stripe data patterns, overall reducing the likelihood of a Row Hammer attack occurring while improving the overall security of the in-memory processing system
    • 

    corecore