Network-on-Chip

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

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

On-board processing for future satellite communications systems: Satellite-Routed FDMA

A frequency division multiple access (FDMA) 30/20 GHz satellite communications architecture without on-board baseband processing is investigated. Conceptual system designs are suggested for domestic traffic models totaling 4 Gb/s of customer premises service (CPS) traffic and 6 Gb/s of trunking traffic. Emphasis is given to the CPS portion of the system which includes thousands of earth terminals with digital traffic ranging from a single 64 kb/s voice channel to hundreds of channels of voice, data, and video with an aggregate data rate of 33 Mb/s. A unique regional design concept that effectively smooths the non-uniform traffic distribution and greatly simplifies the satellite design is employed. The satellite antenna system forms thirty-two 0.33 deg beam on both the uplinks and the downlinks in one design. In another design matched to a traffic model with more dispersed users, there are twenty-four 0.33 deg beams and twenty-one 0.7 deg beams. Detailed system design techniques show that a single satellite producing approximately 5 kW of dc power is capable of handling at least 75% of the postulated traffic. A detailed cost model of the ground segment and estimated system costs based on current information from manufacturers are presented

Shuttle/TDRSS Ku-band downlink study

Assessing the adequacy of the baseline signal design approach, developing performance specifications for the return link hardware, and performing detailed design and parameter optimization tasks was accomplished by completing five specific study tasks. The results of these tasks show that the basic signal structure design is sound and that the goals can be met. Constraints placed on return link hardware by this structure allow reasonable specifications to be written so that no extreme technical risk areas in equipment design are foreseen. A third channel can be added to the PM mode without seriously degrading the other services. The feasibility of using only a PM mode was shown to exist, however, this will require use of some digital TV transmission techniques. Each task and its results are summarized

Heterogeneity and noise in living systems: statistical physics perspectives

Even the most distracted observer could hardly miss noticing the extensive heterogeneity of traits and behaviors displayed by living systems. So great a variability is commonly ascribed to differences at the level of the genome, which originated from the evolution process to adapt the organisms to the different environments they live in. However, phenotypic heterogeneity is found even in genetically identical organisms, from monoclonal cellular populations to human twins. The multitude of microscopic causes that sum up to give such variability is commonly referred to as biological noise, coming both in the form of environmental fluctuations affecting the development of individual organisms (extrinsic noise) and as the unavoidable results of stochasticity at the level of molecular reaction (intrinsic noise). The latter persisting even when genetically identical organisms are kept under nearly identical conditions. For quite a long time, such fluctuations were considered a nuisance that makes experiments just difficult to interpret, needing to enlarge the number of observations to have reliable outcomes, and from the point of view of cells, a disturbance cells need to deal with. In the last two decades, however, experimental progresses allowed to investigate the system at single-cell scale. The emerging view is that noise under some circumstances can have a beneficial role, like promoting survival to adverse environments or enhancing differentiation. Ultimately, evolution tunes the systems so they can take advantage of natural stochastic fluctuations. We will follow noise and fluctuation from the cellular level to the higher level of organization of the cellular population where heterogeneity in the molecular reactions translate in the variability of phenotypes. Biology is very broad though, and noise affects all biological processes. Time restraint and my limited knowledge of biological systems did not allow for an exhaustive discussion of all the aspects in which noise and the subsequent heterogeneity play a role. Instead, we will focus on the regulation of noise. More in details, the first part of the thesis introduces to the impact of noise on gene expression and the regulation mechanisms cells use to control it. The action of large regulatory networks is to coordinate a huge of number molecular interactions to obtain robust system-level outcomes. This capability can emerge even when individual interactions are weak and/or strongly heterogeneous. This is the case of post-transcriptional regulation driven by microRNAs (miRNAs). microRNAs are small non-coding RNA molecules able to regulate gene expression at the post-transcriptional level by repressing target RNA molecules. It has been found that such regulation may lead the system to bimodal distributions in the expression of the target mRNA, usually fingerprint of the presence of two distinct phenotypes. Moreover, the nature of the interaction between miRNAs and their targets gives rise to a complex network of miRNAs interacting with several mRNA targets. Such targets may then cross-regulate each other in an indirect miRNA-mediated manner. This effect, called `competing endogenous RNA (ceRNA) effect', despite being typically weak, has been found to possess remarkable properties in the presence of extrinsic noise, where fluctuations affect all the components of the system. We will discuss crosstalk and illustrate how crosstalk patterns are enhanced by both transcriptional and kinetic heterogeneities and achieve high intensities even for RNAs that are not co-regulated. Moreover, we will see that crosstalk patterns are significantly non-local, i.e. correlate weakly with miRNA-RNA interaction parameters. Since these features appear to be encoded in the network's topology this suggests that such crosstalk is tunable by natural selection. Moving at the cellular level, we focus on the outcomes of gene expression, i.e. the observable phenotypes. Depending on the degree of regulation the cell manages to exert with respect to noise, the distribution of those phenotypes will display a certain extent of heterogeneity. Such cell-to-cell variability is found to have many implications especially for the growth of the whole population. In the second part of the thesis, we discuss some properties of those heterogeneous distributions. First, we focus on the dependence on the initial conditions for the different phases of growth, i.e. the adaptive phase and exponential growth phase. Since cellular populations grow in an exponential fashion, the size and composition of the inoculum shall matter. We discuss this following a novel extensive experimental investigation recently done on cancer cell lines in a controlled environment. Finally, we focus on the effects that a heterogeneous phenotype has on the growth in hostile environments, i.e. environments fluctuating between states in which the growth is favored and others where growth is inhibited. In such a case, if cells can only replicate (by exploiting available resources) and modify their phenotype within a given landscape (thereby exploring novel configurations), an exploration-exploitation trade-off is established, whose specifics depend on the statistics of the environment. The phenotypic distribution corresponding to maximum population fitness requires a non-zero exploration rate when the magnitude of environmental fluctuations changes randomly over time, while a purely exploitative strategy turns out to be optimal in periodic two-state environments. Most notably, the key parameter overseeing the trade-off is linked to the amount of regulation cells can exert

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications