The relentless quest for processing speeds in the range of Teraflops and beyond has accelerated the need for scalable, parallel, High-Performance Computing (HPC) systems. For these systems to be scalable and attain the desirable performance, the interconnection network connecting the processors, must itself be scalable in both size and bandwidth. However, at higher bit rates and longer communication distances, fundamental electrical signaling limitations reduce the inter-processor communication bandwidth while increasing the power dissipation, thereby affecting not only the performance of HPC systems, but also their scalability. In this dissertation, we propose an optical interconnect based architecture for HPC systems called RAPID (Reconfigurable All Photonic Interconnect for Distributed and parallel systems) that maximizes the bandwidth density, optimizes power consumption and enhances scalability using static wavelength allocation. We also present two cost-effective design alternatives of the architecture, a modified version called M-RAPID and an extended version called E-RAPID that minimizes the cost of the interconnect based on the number of transmitters required. In addition, we propose a detailed implementation and integration methodology of RAPID using current complimentary-metal-oxide-semiconductor (CMOS) technology. In order to develop a flexible interconnection architecture, we provide dynamic system reconfiguration that further reduces the communication bottlenecks and achieves better resource utilization. Reconfigurability is realized by monitoring traffic intensities, and implementing dynamic bandwidth re-allocation (DBR) techniques that adapt to changes in communication patterns. A DBR technique - Lock-Step (LS) that balances the load on each communication channel based on past utilization is also presented. While computer-aided design (CAD) toolshave significantly assisted electronic system simulation, the field of system level opto-electronics modeling has lagged behind due to lack of simulation methodologies and tools. We present the design space of developing OPTISIM, a system level modeling and simulation methodology of optical interconnects for HPC systems. Using OPTISIM, we performed detailed simulation of RAPID architectures and compared it to several electrical HPC interconnects using synthetic traffic patterns. Simulation results indicate that the reconfigured architecture shows 35% increased throughput and 20% reduced network latency as compared to HPC electrical networks.

This book provides a broad overview of current research in optical interconnect technologies and architectures. Introductory chapters on high-performance computing and the associated issues in conventional interconnect architectures, and on the fundamental building blocks for integrated optical interconnect, provide the foundations for the bulk of the book which brings together leading experts in the field of optical interconnect architectures for data communication. Particular emphasis is given to the ways in which the photonic components are assembled into architectures to address the needs of data-intensive on-chip communication, and to the performance evaluation of such architectures for specific applications.

This cutting-edge book on off-chip technologies puts the hottest breakthroughs in high-density compliant electrical interconnects, nanophotonics, and microfluidics at your fingertips, integrating the full range of mathematics, physics, and technology issues together in a single comprehensive source. You get full details on state-of-the-art I/O interconnects and packaging, including mechanically compliant I/O approaches, fabrication, and assembly, followed by the latest advances and applications in power delivery design, analysis, and modeling. The book explores interconnect structures, materials, and packages for achieving high-bandwidth off-chip electrical communication, including optical interconnects and chip-to-chip signaling approaches, and brings you up to speed on CMOS integrated optical devices, 3D integration, wafer stacking technology, and through-wafer interconnects.

Optical media are now widely used in the telecommunication networks, and the evolution of optical and optoelectronic technologies tends to show that their wide range of techniques could be successfully introduced in shorter-distance interconnection systems. This book bridges the existing gap between research in optical interconnects and research in high-performance computing and communication systems, of which parallel processing is just an example. It also provides a more comprehensive understanding of the advantages and limitations of optics as applied to high-speed communications. Audience: The book will be a vital resource for researchers and graduate students of optical interconnects, computer architectures and high-performance computing and communication systems who wish to understand the trends in the newest technologies, models and communication issues in the field.

This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.

Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.

This book constitutes the proceedings of the 22nd International Conference on Parallel and Distributed Computing, Applications, and Technologies, PDCAT 2021, which took place in Guangzhou, China, during December 17-19, 2021. The 24 full papers and 34 short papers included in this volume were carefully reviewed and selected from 97 submissions. The papers are categorized into the following topical sub-headings: networking and architectures, software systems and technologies, algorithms and applications, and security and privacy.

The development of technologies to modify natural human physical and cognitive performance is one of increasing interest and concern, especially among military services that may be called on to defeat foreign powers with enhanced warfighter capabilities. Human performance modification (HPM) is a general term that can encompass actions ranging from the use of "natural" materials, such as caffeine or khat as a stimulant, to the application of nanotechnology as a drug delivery mechanism or in an invasive brain implant. Although the literature on HPM typically addresses methods that enhance performance, another possible focus is methods that degrade performance or negatively affect a military force's ability to fight. Advances in medicine, biology, electronics, and computation have enabled an increasingly sophisticated ability to modify the human body, and such innovations will undoubtedly be adopted by military forces, with potential consequences for both sides of the battle lines. Although some innovations may be developed for purely military applications, they are increasingly unlikely to remain exclusively in that sphere because of the globalization and internationalization of the commercial research base. Based on its review of the literature, the presentations it received and on its own expertise, the Committee on Assessing Foreign Technology Development in Human Performance Modification chose to focus on three general areas of HPM: human cognitive modification as a computational problem, human performance modification as a biological problem, and human performance modification as a function of the brain-computer interface. Human Performance Modification: Review of Worldwide Research with a View to the Future summarizes these findings.