Circuit design and analysis for on-FPGA communication systems

On-chip communication system has emerged as a prominently important subject in Very-Large- Scale-Integration (VLSI) design, as the trend of technology scaling favours logics more than interconnects. Interconnects often dictates the system performance, and, therefore, research for new methodologies and system architectures that deliver high-performance communication services across the chip is mandatory. The interconnect challenge is exacerbated in Field-Programmable Gate Array (FPGA), as a type of ASIC where the hardware can be programmed post-fabrication. Communication across an FPGA will be deteriorating as a result of interconnect scaling. The programmable fabrics, switches and the specific routing architecture also introduce additional latency and bandwidth degradation further hindering intra-chip communication performance. Past research efforts mainly focused on optimizing logic elements and functional units in FPGAs. Communication with programmable interconnect received little attention and is inadequately understood. This thesis is among the first to research on-chip communication systems that are built on top of programmable fabrics and proposes methodologies to maximize the interconnect throughput performance. There are three major contributions in this thesis: (i) an analysis of on-chip interconnect fringing, which degrades the bandwidth of communication channels due to routing congestions in reconfigurable architectures; (ii) a new analogue wave signalling scheme that significantly improves the interconnect throughput by exploiting the fundamental electrical characteristics of the reconfigurable interconnect structures. This new scheme can potentially mitigate the interconnect scaling challenges. (iii) a novel Dynamic Programming (DP)-network to provide adaptive routing in network-on-chip (NoC) systems. The DP-network architecture performs runtime optimization for route planning and dynamic routing which, effectively utilizes the in-silicon bandwidth. This thesis explores a new horizon in reconfigurable system design, in which new methodologies and concepts are proposed to enhance the on-FPGA communication throughput performance that is of vital importance in new technology processes

Embedded dynamic programming networks for networks-on-chip

PhD ThesisRelentless technology downscaling and recent technological advancements in three dimensional integrated circuit (3D-IC) provide a promising prospect to realize heterogeneous system-on-chip (SoC) and homogeneous chip multiprocessor (CMP) based on the networks-onchip (NoCs) paradigm with augmented scalability, modularity and performance. In many cases in such systems, scheduling and managing communication resources are the major design and implementation challenges instead of the computing resources. Past research efforts were mainly focused on complex design-time or simple heuristic run-time approaches to deal with the on-chip network resource management with only local or partial information about the network. This could yield poor communication resource utilizations and amortize the benefits of the emerging technologies and design methods. Thus, the provision for efficient run-time resource management in large-scale on-chip systems becomes critical. This thesis proposes a design methodology for a novel run-time resource management infrastructure that can be realized efficiently using a distributed architecture, which closely couples with the distributed NoC infrastructure. The proposed infrastructure exploits the global information and status of the network to optimize and manage the on-chip communication resources at run-time. There are four major contributions in this thesis. First, it presents a novel deadlock detection method that utilizes run-time transitive closure (TC) computation to discover the existence of deadlock-equivalence sets, which imply loops of requests in NoCs. This detection scheme, TC-network, guarantees the discovery of all true-deadlocks without false alarms in contrast to state-of-the-art approximation and heuristic approaches. Second, it investigates the advantages of implementing future on-chip systems using three dimensional (3D) integration and presents the design, fabrication and testing results of a TC-network implemented in a fully stacked three-layer 3D architecture using a through-silicon via (TSV) complementary metal-oxide semiconductor (CMOS) technology. Testing results demonstrate the effectiveness of such a TC-network for deadlock detection with minimal computational delay in a large-scale network. Third, it introduces an adaptive strategy to effectively diffuse heat throughout the three dimensional network-on-chip (3D-NoC) geometry. This strategy employs a dynamic programming technique to select and optimize the direction of data manoeuvre in NoC. It leads to a tool, which is based on the accurate HotSpot thermal model and SystemC cycle accurate model, to simulate the thermal system and evaluate the proposed approach. Fourth, it presents a new dynamic programming-based run-time thermal management (DPRTM) system, including reactive and proactive schemes, to effectively diffuse heat throughout NoC-based CMPs by routing packets through the coolest paths, when the temperature does not exceed chip’s thermal limit. When the thermal limit is exceeded, throttling is employed to mitigate heat in the chip and DPRTM changes its course to avoid throttled paths and to minimize the impact of throttling on chip performance. This thesis enables a new avenue to explore a novel run-time resource management infrastructure for NoCs, in which new methodologies and concepts are proposed to enhance the on-chip networks for future large-scale 3D integration.Iraqi Ministry of Higher Education and Scientific Research (MOHESR)

Social Insect-Inspired Adaptive Hardware

Modern VLSI transistor densities allow large systems to be implemented within a single chip. As technologies get smaller, fundamental limits of silicon devices are reached resulting in lower design yields and post-deployment failures. Many-core systems provide a platform for leveraging the computing resource on offer by deep sub-micron technologies and also offer high-level capabilities for mitigating the issues with small feature sizes. However, designing for many-core systems that can adapt to in-field failures and operation variability requires an extremely large multi-objective optimisation space. When a many-core reaches the size supported by the densities of modern technologies (thousands of processing cores), finding design solutions in this problem space becomes extremely difficult. Many biological systems show properties that are adaptive and scalable. This thesis proposes a self-optimising and adaptive, yet scalable, design approach for many-core based on the emergent behaviours of social-insect colonies. In these colonies there are many thousands of individuals with low intelligence who contribute, without any centralised control, to complete a wide range of tasks to build and maintain the colony. The experiments presented translate biological models of social-insect intelligence into simple embedded intelligence circuits. These circuits sense low-level system events and use this manage the parameters of the many-core's Network-on-Chip (NoC) during runtime. Centurion, a 128-node many-core, was created to investigate these models at large scale in hardware. The results show that, by monitoring a small number of signals within each NoC router, task allocation emerges from the social-insect intelligence models that can self-configure to support representative applications. It is demonstrated that emergent task allocation supports fault tolerance with no extra hardware overhead. The response-threshold decision making circuitry uses a negligible amount of hardware resources relative to the size of the many-core and is an ideal technology for implementing embedded intelligence for system runtime management of large-complexity single-chip systems

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

Embedded computing systems design: architectural and application perspectives

Questo elaborato affronta varie problematiche legate alla progettazione e all'implementazione dei moderni sistemi embedded di computing, ponendo in rilevo, e talvolta in contrapposizione, le sfide che emergono all'avanzare della tecnologia ed i requisiti che invece emergono a livello applicativo, derivanti dalle necessità degli utenti finali e dai trend di mercato. La discussione sarà articolata tenendo conto di due punti di vista: la progettazione hardware e la loro applicazione a livello di sistema. A livello hardware saranno affrontati nel dettaglio i problemi di interconnettività on-chip. Aspetto che riguarda la parallelizzazione del calcolo, ma anche l'integrazione di funzionalità eterogenee. Sarà quindi discussa un'architettura d'interconnessione denominata Network-on-Chip (NoC). La soluzione proposta è in grado di supportare funzionalità avanzate di networking direttamente in hardware, consentendo tuttavia di raggiungere sempre un compromesso ottimale tra prestazioni in termini di traffico e requisiti di implementazioni a seconda dell'applicazione specifica. Nella discussione di questa tematica, verrà posto l'accento sul problema della configurabilità dei blocchi che compongono una NoC. Quello della configurabilità, è un problema sempre più sentito nella progettazione dei sistemi complessi, nei quali si cerca di sviluppare delle funzionalità, anche molto evolute, ma che siano semplicemente riutilizzabili. A tale scopo sarà introdotta una nuova metodologia, denominata Metacoding che consiste nell'astrarre i problemi di configurabilità attraverso linguaggi di programmazione di alto livello. Sulla base del metacoding verrà anche proposto un flusso di design automatico in grado di semplificare la progettazione e la configurazione di una NoC da parte del designer di rete. Come anticipato, la discussione si sposterà poi a livello di sistema, per affrontare la progettazione di tali sistemi dal punto di vista applicativo, focalizzando l'attenzione in particolare sulle applicazioni di monitoraggio remoto. A tal riguardo saranno studiati nel dettaglio tutti gli aspetti che riguardano la progettazione di un sistema per il monitoraggio di pazienti affetti da scompenso cardiaco cronico. Si partirà dalla definizione dei requisiti, che, come spesso accade a questo livello, derivano principalmente dai bisogni dell'utente finale, nel nostro caso medici e pazienti. Verranno discusse le problematiche di acquisizione, elaborazione e gestione delle misure. Il sistema proposto introduce vari aspetti innovativi tra i quali il concetto di protocollo operativo e l'elevata interoperabilità offerta. In ultima analisi, verranno riportati i risultati relativi alla sperimentazione del sistema implementato. Infine, il tema del monitoraggio remoto sarà concluso con lo studio delle reti di distribuzione elettrica intelligenti: le Smart Grid, cercando di fare uno studio dello stato dell'arte del settore, proponendo un'architettura di Home Area Network (HAN) e suggerendone una possibile implementazione attraverso Commercial Off the Shelf (COTS)

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

Low-Power Embedded Design Solutions and Low-Latency On-Chip Interconnect Architecture for System-On-Chip Design

This dissertation presents three design solutions to support several key system-on-chip (SoC) issues to achieve low-power and high performance. These are: 1) joint source and channel decoding (JSCD) schemes for low-power SoCs used in portable multimedia systems, 2) efficient on-chip interconnect architecture for massive multimedia data streaming on multiprocessor SoCs (MPSoCs), and 3) data processing architecture for low-power SoCs in distributed sensor network (DSS) systems and its implementation. The first part includes a low-power embedded low density parity check code (LDPC) - H.264 joint decoding architecture to lower the baseband energy consumption of a channel decoder using joint source decoding and dynamic voltage and frequency scaling (DVFS). A low-power multiple-input multiple-output (MIMO) and H.264 video joint detector/decoder design that minimizes energy for portable, wireless embedded systems is also designed. In the second part, a link-level quality of service (QoS) scheme using unequal error protection (UEP) for low-power network-on-chip (NoC) and low latency on-chip network designs for MPSoCs is proposed. This part contains WaveSync, a low-latency focused network-on-chip architecture for globally-asynchronous locally-synchronous (GALS) designs and a simultaneous dual-path routing (SDPR) scheme utilizing path diversity present in typical mesh topology network-on-chips. SDPR is akin to having a higher link width but without the significant hardware overhead associated with simple bus width scaling. The last part shows data processing unit designs for embedded SoCs. We propose a data processing and control logic design for a new radiation detection sensor system generating data at or above Peta-bits-per-second level. Implementation results show that the intended clock rate is achieved within the power target of less than 200mW. We also present a digital signal processing (DSP) accelerator supporting configurable MAC, FFT, FIR, and 3-D cross product operations for embedded SoCs. It consumes 12.35mW along with 0.167mm2 area at 333MHz

Wireless Chip-Scale Communications for Neural Network Accelerators

Wireless on-chip communications have been proposed as a complement to conventional Network-on-Chip (NoC) paradigms in manycore processors. In massively parallel architectures, the fast broadcast and reconfigurability capabilities of the wireless plane open the door to new scalable and adaptive architectures with significant impact on a plethora of fields. This thesis aims to explore such impact in the all-pervasive field of AI accelerators, designing and evaluating new accelerators augmented with wireless on-chip communication.The last decade has witnessed an explosive growth in the use of Deep Neural Networks in fields such as computer vision, natural language processing, medicine or economics. Their achievements in accuracy across so many relevant and different applications exhibit the enormous potential of this disruptive technology. However, this unprecedented performance is closely tied with the fact that their new designs contain much deeper and bigger layer sets, forcing them to manage millions - and in some cases even billions - of parameters. This comes at a high computational and communication cost at the processor level, which has prompted the development of new hardware aimed at handling such large computing expense more efficiently, the so called \acrlong{dnn} accelerators. This work explores the potential of enhancing the performance of these accelerators by introducing Wireless Networks-on-Chip in their design, a novel interconnect paradigm proposed by the research community to overcome some of the communication challenges that manycore systems face. Specifically, both on-chip and off-chip wireless interconnect implementations have been studied and evaluated. In the off-chip case, a theoretical improvement of 13X in the runtime has been achieved, but at the expense of some area and power overheads.La última década ha sido testigo de un inmenso crecimiento en el uso de Deep Neural Networks en campos como la visión artificial, procesamiento de lenguaje natural, medicina o economía. Haber conseguido estos resultados sin precedentes en aplicaciones tan relevantes y variadas muestra el enorme potencial de esta tecnología tan disruptiva. Sin embargo, estos logros van muy ligados al hecho de que los nuevos diseños contienen muchas más capas y más profundas, lo que se traduce en millones - y en algunos casos billones - de parámetros. Esto supone un gran coste computacional y de comunicación a nivel de procesador, lo que ha impulsado el desarrollo de nuevo hardware que permita gestionar tal coste de manera más eficiente, los llamados aceleradores de Deep Neural Networks. Este proyecto explora la potencial mejora en rendimiento de estos aceleradores mediante la introducción de Wireless Newtorks-on-Chip en su diseño, un nuevo paradigma de interconexiones propuesto por la comunidad científica para superar algunos de los problemas de comunicación que sistemas manycore deben afrontar. Específicamente, implementaciones tanto on-chip como off-chip se han estudiado y evaluado. Se ha conseguido una mejora teórica de 13X en el runtime, pero con algunos costes añadidos de área y potencia.La darrera dècada ha estat testimoni d'un immens creixement en l'ús de Deep Neural Networks en camps com la visió artificial, processament de llenguatge natural, medicina o economia. Haver aconseguit aquests resultats sense precedents en aplicacions tan rellevants i variades mostra l?enorme potencial d?aquesta tecnologia tan disruptiva. No obstant, aquests èxits van molt lligats al fet de que els nous dissenys contenen moltes més capes i més profundes, cosa que es tradueix en milions - i en alguns casos bilions - de paràmetres. Això suposa un gran cost computacional i de comunicació a nivell de processador, cosa que ha impulsat el desenvolupament de nou hardware que permetin gestionar tal cost de manera més eficient, els anomenats acceleradors de Deep Neural Networks. Aquest projecte explora la potencial millora en rendiment d'aquests acceleradors mitjançant la introducció de Wireless Newtorks-on-Chip al seu disseny, un nou paradigma d'interconnexions proposat per la comunitat científica per a superar alguns dels problemes de comunicació que sistemes manycore han d'afrontar. Específicament, implementacions tant on-chip com off-chip s'han estudiat i evaluat. En el cas off-chip, s'ha aconseguit una millora teòrica de 13X al runtime però amb alguns costos afegits d'àrea i potència