Driving the Network-on-Chip Revolution to Remove the Interconnect Bottleneck in Nanoscale Multi-Processor Systems-on-Chip

The sustained demand for faster, more powerful chips has been met by the availability of chip manufacturing processes allowing for the integration of increasing numbers of computation units onto a single die. The resulting outcome, especially in the embedded domain, has often been called SYSTEM-ON-CHIP (SoC) or MULTI-PROCESSOR SYSTEM-ON-CHIP (MP-SoC). MPSoC design brings to the foreground a large number of challenges, one of the most prominent of which is the design of the chip interconnection. With a number of on-chip blocks presently ranging in the tens, and quickly approaching the hundreds, the novel issue of how to best provide on-chip communication resources is clearly felt. NETWORKS-ON-CHIPS (NoCs) are the most comprehensive and scalable answer to this design concern. By bringing large-scale networking concepts to the on-chip domain, they guarantee a structured answer to present and future communication requirements. The point-to-point connection and packet switching paradigms they involve are also of great help in minimizing wiring overhead and physical routing issues. However, as with any technology of recent inception, NoC design is still an evolving discipline. Several main areas of interest require deep investigation for NoCs to become viable solutions: • The design of the NoC architecture needs to strike the best tradeoff among performance, features and the tight area and power constraints of the onchip domain. • Simulation and verification infrastructure must be put in place to explore, validate and optimize the NoC performance. • NoCs offer a huge design space, thanks to their extreme customizability in terms of topology and architectural parameters. Design tools are needed to prune this space and pick the best solutions. • Even more so given their global, distributed nature, it is essential to evaluate the physical implementation of NoCs to evaluate their suitability for next-generation designs and their area and power costs. This dissertation performs a design space exploration of network-on-chip architectures, in order to point-out the trade-offs associated with the design of each individual network building blocks and with the design of network topology overall. The design space exploration is preceded by a comparative analysis of state-of-the-art interconnect fabrics with themselves and with early networkon- chip prototypes. The ultimate objective is to point out the key advantages that NoC realizations provide with respect to state-of-the-art communication infrastructures and to point out the challenges that lie ahead in order to make this new interconnect technology come true. Among these latter, technologyrelated challenges are emerging that call for dedicated design techniques at all levels of the design hierarchy. In particular, leakage power dissipation, containment of process variations and of their effects. The achievement of the above objectives was enabled by means of a NoC simulation environment for cycleaccurate modelling and simulation and by means of a back-end facility for the study of NoC physical implementation effects. Overall, all the results provided by this work have been validated on actual silicon layout

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

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

Network-on-Chip

Limitations of bus-based interconnections related to scalability, latency, bandwidth, and power consumption for supporting the related huge number of on-chip resources result in a communication bottleneck. These challenges can be efficiently addressed with the implementation of a network-on-chip (NoC) system. This book gives a detailed analysis of various on-chip communication architectures and covers different areas of NoCs such as potentials, architecture, technical challenges, optimization, design explorations, and research directions. In addition, it discusses current and future trends that could make an impactful and meaningful contribution to the research and design of on-chip communications and NoC systems

Design Space Exploration and Resource Management of Multi/Many-Core Systems

The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends

Photonic Interconnection Networks for Exascale Computers

[ES] En los últimos años, distintos proyectos alrededor del mundo se han centrado en el diseño de supercomputadores capaces de alcanzar la meta de la computación a exascala, con el objetivo de soportar la ejecución de aplicaciones de gran importancia para la sociedad en diversos campos como el de la salud, la inteligencia artificial, etc. Teniendo en cuenta la creciente tendencia de la potencia computacional en cada generación de supercomputadores, este objetivo se prevee accesible en los próximos años. Alcanzar esta meta requiere abordar diversos retos en el diseño y desarrollo del sistema. Uno de los principales es conseguir unas comunicaciones rápidas y eficientes entre el inmenso número de nodos de computo y los sitemas de memoria. La tecnología fotónica proporciona ciertas ventajas frente a las redes eléctricas, como un mayor ancho de banda en los enlaces, un mayor paralelismo a nivel de comunicaciones gracias al DWDM o una mejor gestión del cableado gracias a su reducido tamaño. En la tesis se ha desarrollado un estudio de viabilidad y desarrollo de redes de interconexión haciendo uso de la tecnología fotónica para los futuros sistemas a exaescala dentro del proyecto europeo ExaNeSt. En primer lugar, se ha realizado un análisis y caracterización de aplicaciones exaescala. Este análisis se ha utilizado para conocer el comportamiento y requisitos de red que presentan las aplicaciones, y con ello guiarnos en el diseño de la red del sistema. El análisis considera tres parámetros: la distribución de mensajes en base a su tamaño y su tipo, el consumo de ancho de banda requerido a lo largo de la ejecución y la matriz de comunicación espacial entre los nodos. El estudio revela la necesidad de una red eficiente y rápida, debido a que la mayoría de las comunaciones se realizan en burst y con mensajes de un tamaño medio inferior a 50KB. A continuación, la tesis se centra en identificar los principales elementos que diferencian las redes fotónicas de las eléctricas. Identificamos una secuencia de pasos en el diseño de un simulador, ya sea haciéndolo desde cero con tecnología fotónica o adaptando un simulador de redes eléctricas existente para modelar la fotónica. Después se han realizado dos estudios de rendimiento y comparativas entre las actuales redes eléctricas y distintas configuraciones de redes fotónicas utilizando topologías clásicas. En el primer estudio, realizado tanto con tráfico sintético como con trazas de ExaNeSt en un toro, fat tree y dragonfly, se observa como la tecnología fotónica supone una clara mejora respecto a la eléctrica. Además, el estudio muestra que el parámetro que más afecta al rendimiento es el ancho de banda del canal fotónico. El segundo estudio muestra el comportamiento y rendimiento de aplicaciones reales en simulaciones a gran escala en una topología jellyfish. En este estudio se confirman las conclusiones obtenidas en el anterior, revelando además que la tecnología fotónica permite reducir la complejidad de algunas topologías, y por ende, el coste de la red. En los estudios realizados se ha observado una baja utilización de la red debido a que las topologías utilizadas para redes eléctricas no aprovechan las características que proporciona la tecnología fotónica. Por ello, se ha propuesto Segment Switching, una estrategia de conmutación orientada a reducir la longitud de las rutas mediante el uso de buffers intermedios. Los resultados experimentales muestran que cada topología tiene sus propios requerimientos. En el caso del toro, el mayor rendimiento se obtiene con un mayor número de buffers en la red. En el fat tree el parámetro más importante es el tamaño del buffer, obteniendo unas prestaciones similares una configuración con buffers en todos los switches que la que los ubica solo en el nivel superior. En resumen, esta tesis estudia el uso de la tecnología fotónica para las redes de sistemas a exascala y propone aprovechar[CA] Els darrers anys, múltiples projectes de recerca a tot el món s'han centrat en el disseny de superordinadors capaços d'assolir la barrera de computació exascala, amb l'objectiu de donar suport a l'execució d'aplicacions importants per a la nostra societat, com ara salut, intel·ligència artificial, meteorologia, etc. Segons la tendència creixent en la potència de càlcul en cada generació de superordinadors, es preveu assolir aquest objectiu en els propers anys. No obstant això, assolir aquest objectiu requereix abordar diferents reptes importants en el disseny i desenvolupament del sistema. Un dels principals és aconseguir comunicacions ràpides i eficients entre l'enorme nombre de nodes computacionals i els sistemes de memòria. La tecnologia fotònica proporciona diversos avantatges respecte a les xarxes elèctriques actuals, com ara un major ample de banda als enllaços, un major paral·lelisme de la xarxa gràcies a DWDM o una millor gestió del cable a causa de la seva mida molt més xicoteta. En la tesi, s'ha desenvolupat un estudi de viabilitat i desenvolupament de xarxes d'interconnexió mitjançant tecnologia fotònica per a futurs sistemes exascala dins del projecte europeu ExaNeSt. En primer lloc, s'ha dut a terme un estudi de caracterització d'aplicacions exascala dels requisits de xarxa. Els resultats de l'anàlisi ajuden a entendre els requisits de xarxa de les aplicacions exascale i, per tant, ens guien en el disseny de la xarxa del sistema. Aquesta anàlisi considera tres paràmetres principals: la distribució dels missatges en funció de la seva mida i tipus, el consum d'ample de banda requerit durant tota l'execució i els patrons de comunicació espacial entre els nodes. L'estudi revela la necessitat d'una xarxa d'interconnexió ràpida i eficient, ja que la majoria de comunicacions consisteixen en ràfegues de transmissions, cadascuna amb una mida mitjana de missatge de 50 KB. A continuació, la tesi se centra a identificar els principals elements que diferencien les xarxes fotòniques de les elèctriques. Identifiquem una seqüència de passos en el disseny i implementació d'un simulador: tractar la tecnologia fotònica des de zero o per ampliar un simulador de xarxa elèctrica existent per modelar la fotònica. Després, es presenten dos estudis principals de comparació de rendiment entre xarxes elèctriques i diferents configuracions de xarxes fotòniques mitjançant topologies clàssiques. En el primer estudi, realitzat tant amb trànsit sintètic com amb traces d'ExaNeSt en un toro, fat tree i dragonfly, vam trobar que la tecnologia fotònica representa una millora notable respecte a la tecnologia elèctrica. A més, l'estudi mostra que el paràmetre que més afecta el rendiment és l'amplada de banda del canal fotònic. Aquest darrer estudi analitza el rendiment d'aplicacions reals en simulacions a gran escala en una topologia jellyfish. Els resultats d'aquest estudi corroboren les conclusions obtingudes en l'anterior, revelant també que la tecnologia fotònica permet reduir la complexitat d'algunes topologies i, per tant, el cost de la xarxa. En els estudis anteriors ens adonem que la xarxa estava infrautilitzada principalment perquè les topologies estudiades per a xarxes elèctriques no aprofiten les característiques proporcionades per la tecnologia fotònica. Per aquest motiu, proposem Segment Switching, una estratègia de commutació destinada a reduir la longitud de les rutes mitjançant la implementació de memòries intermèdies en nodes intermedis al llarg de la ruta. Els resultats experimentals mostren que cadascuna de les topologies estudiades presenta diferents requisits de memòria intermèdia. Per al toro, com més gran siga el nombre de memòries intermèdies a la xarxa, major serà el rendiment. Per al fat tree, el paràmetre clau és la mida de la memòria intermèdia, aconseguint un rendiment similar tant amb una configuració amb memòria intermèdia en tots els co[EN] In the last recent years, multiple research projects around the world have focused on the design of supercomputers able to reach the exascale computing barrier, with the aim of supporting the execution of important applications for our society, such as health, artificial intelligence, meteorology, etc. According to the growing trend in the computational power in each supercomputer generation, this objective is expected to be reached in the coming years. However, achieving this goal requires addressing distinct major challenges in the design and development of the system. One of the main ones is to achieve fast and efficient communications between the huge number of computational nodes and the memory systems. Photonics technology provides several advantages over current electrical networks, such as higher bandwidth in the links, greater network parallelism thanks to DWDM, or better cable management due to its much smaller size. In this thesis, a feasibility study and development of interconnection networks have been developed using photonics technology for future exascale systems within the European project ExaNeSt. First, a characterization study of exascale applications from the network requirements has been carried out. The results of the analysis help understand the network requirements of exascale applications, and thereby guide us in the design of the system network. This analysis considers three main parameters: the distribution of the messages based on their size and type, the required bandwidth consumption throughout the execution, and the spatial communication patterns between the nodes. The study reveals the need for a fast and efficient interconnection network, since most communications consist of bursts of transmissions, each with an average message size of 50 KB. Next, this dissertation concentrates on identifying the main elements that differentiate photonic networks from electrical ones. We identify a sequence of steps in the design and implementation of a simulator either i) dealing with photonic technology from scratch or ii) to extend an existing electrical network simulator in order to model photonics. After that, two main performance comparison studies between electrical networks and different configurations of photonic networks are presented using classical topologies. In the former study, carried out with both synthetic traffic and traces of ExaNeSt in a torus, fat tree and dragonfly, we found that photonic technology represents a noticeable improvement over electrical technology. Furthermore, the study shows that the parameter that most affects the performance is the bandwidth of the photonic channel. The latter study analyzes performance of real applications in large-scale simulations in a jellyfish topology. The results of this study corroborates the conclusions obtained in the previous, also revealing that photonic technology allows reducing the complexity of some topologies, and therefore, the cost of the network. In the previous studies we realize that the network was underutilized mainly because the studied topologies for electrical networks do not take advantage of the features provided by photonic technology. For this reason, we propose Segment Switching, a switching strategy aimed at reducing the length of the routes by implementing buffers at intermediate nodes along the path. Experimental results show that each of the studied topologies presents different buffering requirements. For the torus, the higher the number of buffers in the network, the higher the performance. For the fat tree, the key parameter is the buffer size, achieving similar performance a configuration with buffers on all switches that locating buffers only at the top level. In summary, this thesis studies the use of photonic technology for networks of exascale systems, and proposes to take advantage of the characteristics of this technology in current electrical network topologies.This thesis has been conceived from the work carried out by Polytechnic University of Valencia in the ExaNeSt European projectDuro Gómez, J. (2021). Photonic Interconnection Networks for Exascale Computers [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/166796TESI

On Energy Efficient Computing Platforms

In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.Siirretty Doriast

Doctor of Philosophy

dissertationDeep Neural Networks (DNNs) are the state-of-art solution in a growing number of tasks including computer vision, speech recognition, and genomics. However, DNNs are computationally expensive as they are carefully trained to extract and abstract features from raw data using multiple layers of neurons with millions of parameters. In this dissertation, we primarily focus on inference, e.g., using a DNN to classify an input image. This is an operation that will be repeatedly performed on billions of devices in the datacenter, in self-driving cars, in drones, etc. We observe that DNNs spend a vast majority of their runtime to runtime performing matrix-by-vector multiplications (MVM). MVMs have two major bottlenecks: fetching the matrix and performing sum-of-product operations. To address these bottlenecks, we use in-situ computing, where the matrix is stored in programmable resistor arrays, called crossbars, and sum-of-product operations are performed using analog computing. In this dissertation, we propose two hardware units, ISAAC and Newton.In ISAAC, we show that in-situ computing designs can outperform DNN digital accelerators, if they leverage pipelining, smart encodings, and can distribute a computation in time and space, within crossbars, and across crossbars. In the ISAAC design, roughly half the chip area/power can be attributed to the analog-to-digital conversion (ADC), i.e., it remains the key design challenge in mixed-signal accelerators for deep networks. In spite of the ADC bottleneck, ISAAC is able to out-perform the computational efficiency of the state-of-the-art design (DaDianNao) by 8x. In Newton, we take advantage of a number of techniques to address ADC inefficiency. These techniques exploit matrix transformations, heterogeneity, and smart mapping of computation to the analog substrate. We show that Newton can increase the efficiency of in-situ computing by an additional 2x. Finally, we show that in-situ computing, unfortunately, cannot be easily adapted to handle training of deep networks, i.e., it is only suitable for inference of already-trained networks. By improving the efficiency of DNN inference with ISAAC and Newton, we move closer to low-cost deep learning that in turn will have societal impact through self-driving cars, assistive systems for the disabled, and precision medicine

Heterogeneity, High Performance Computing, Self-Organization and the Cloud

application; blueprints; self-management; self-organisation; resource management; supply chain; big data; PaaS; Saas; HPCaa