Cross-Layer Platform for Dynamic, Energy-Efficient Optical Networks

The design of the next-generation Internet infrastructure is driven by the need to sustain the massive growth in bandwidth demands. Novel, energy-efficient, optical networking technologies and architectures are required to effectively meet the stringent performance requirements with low cost and ultrahigh energy efficiencies. In this thesis, a cross-layer communications platform is proposed to enable greater intelligence and functionality on the physical layer. Providing the optical layer with advanced networking capabilities will facilitate the dynamic management and optimization of optical switching based on performance monitoring measurements and higher-layer attributes. The cross-layer platform aims to create a new framework for networks to incorporate packet-scale measurement subsystems and techniques for monitoring the health of the optical channel. This will allow for quality-of-service- and energy-aware routing schemes, as well as an enhanced awareness of the optical data signals. This thesis first presents the design and development of an optical packet switching fabric. Leveraging a networking test-bed environment to validate networking hypotheses, advanced switching functionalities are demonstrated, including the support for quality-of-service based routing and packet multicasting. The investigated cross-layering is based on emerging optical technologies, enabling packet protection techniques and packet-rate switching fabric reconfiguration. Coupled with fast performance monitoring, the platform will achieve significant performance gains within the endeavor of all-optical switching. Allowing for a more intelligent, programmable optical layer aims to support greater flexibility with respect to bandwidth allocation and potentially a significant reduction in the network's energy consumption. The ultimate deliverable of this work is a high-performance, cross-layer enabled optical network node. The experimental demonstration of an initial prototype creates a dynamic network element with distributed control plane management, featuring fast packet-rate optical switching capabilities and embedded physical-layer performance monitoring modules. The cross-layer box enables an intelligent traffic delivery system that can dynamically manipulate optical switching on a packet-granular scale. With the goal of achieving advanced multi-layer routing and control algorithms, the network node requires an intelligent co-optimization across all the layers. The proposed cross-layer design should drive optical technologies and architectures in an innovative way, in order to fulfill the void between the design of basic photonic devices and the networking protocols that use them. The performance of the entire network -- from the optical components, to the routing algorithms and user applications -- should be optimized in concert. This contribution to the area of cross-layer network design creates an adaptable optical pipe that is extremely flexible and intelligent aware of both the physical optical signals and higher-layer requirements. The impact of this work will be seen in the realization of dynamic, energy-efficient optical communication links in future networking infrastructures

Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

A Modular Approach to Adaptive Reactive Streaming Systems

The latest generations of FPGA devices offer large resource counts that provide the headroom to implement large-scale and complex systems. However, there are increasing challenges for the designer, not just because of pure size and complexity, but also in harnessing effectively the flexibility and programmability of the FPGA. A central issue is the need to integrate modules from diverse sources to promote modular design and reuse. Further, the capability to perform dynamic partial reconfiguration (DPR) of FPGA devices means that implemented systems can be made reconfigurable, allowing components to be changed during operation. However, use of DPR typically requires low-level planning of the system implementation, adding to the design challenge. This dissertation presents ReShape: a high-level approach for designing systems by interconnecting modules, which gives a ‘plug and play’ look and feel to the designer, is supported by tools that carry out implementation and verification functions, and is carried through to support system reconfiguration during operation. The emphasis is on the inter-module connections and abstracting the communication patterns that are typical between modules – for example, the streaming of data that is common in many FPGA-based systems, or the reading and writing of data to and from memory modules. ShapeUp is also presented as the static precursor to ReShape. In both, the details of wiring and signaling are hidden from view, via metadata associated with individual modules. ReShape allows system reconfiguration at the module level, by supporting type checking of replacement modules and by managing the overall system implementation, via metadata associated with its FPGA floorplan. The methodology and tools have been implemented in a prototype for a broad domain-specific setting – networking systems – and have been validated on real telecommunications design projects

FASTER: Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration

The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) EU FP7 project, aims to ease the design and implementation of dynamically changing hardware systems. Our motivation stems from the promise reconfigurable systems hold for achieving high performance and extending product functionality and lifetime via the addition of new features that operate at hardware speed. However, designing a changing hardware system is both challenging and time-consuming. FASTER facilitates the use of reconfigurable technology by providing a complete methodology enabling designers to easily specify, analyze, implement and verify applications on platforms with general-purpose processors and acceleration modules implemented in the latest reconfigurable technology. Our tool-chain supports both coarse- and fine-grain FPGA reconfiguration, while during execution a flexible run-time system manages the reconfigurable resources. We target three applications from different domains. We explore the way each application benefits from reconfiguration, and then we asses them and the FASTER tools, in terms of performance, area consumption and accuracy of analysis

Implementation of a Neuromorphic Development Platform with DANNA

Neuromorphic computing is the use of artificial neural networks to solve complex problems. The specialized computing field has been growing in interest during the past few years. Specialized hardware that function as neural networks can be utilized to solve specific problems unsuited for traditional computing architectures such as pattern classification and image recognition. However, these hardware platforms have neural network structures that are static, being limited to only perform a specific application, and cannot be used for other tasks. In this paper, the feasibility of a development platform utilizing a dynamic artificial neural network for researchers is discussed

Modern computing: Vision and challenges

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress