Run-time management of many-core SoCs: A communication-centric approach

The single core performance hit the power and complexity limits in the beginning of this century, moving the industry towards the design of multi- and many-core system-on-chips (SoCs). The on-chip communication between the cores plays a criticalrole in the performance of these SoCs, with power dissipation, communication latency, scalability to many cores, and reliability against the transistor failures as the main design challenges. Accordingly, we dedicate this thesis to the communicationcentered management of the many-core SoCs, with the goal to advance the state-ofthe-art in addressing these challenges. To this end, we contribute to on-chip communication of many-core SoCs in three main directions. First, we start with a synthesizable SoC with full system simulation. We demonstrate the importance of the networking overhead in a practical system, and propose our sophisticated network interface (NI) that offloads the work from SW to HW. Our results show around 5x and up to 50x higher network performance, compared to previous works. As the second direction of this thesis, we study the significance of run-time application mapping. We demonstrate that contiguous application mapping not only improves the network latency (by 23%) and power dissipation (by 50%), but also improves the system throughput (by 3%) and quality-of-service (QoS) of soft real-time applications (up to 100x less deadline misses). Also our hierarchical run-time application mapping provides 99.41% successful mapping when up to 8 links are broken. As the final direction of the thesis, we propose a fault-tolerant routing algorithm, the maze-routing. It is the first-in-class algorithm that provides guaranteed delivery, a fully-distributed solution, low area overhead (by 16x), and instantaneous reconfiguration (vs. 40K cycles down time of previous works), all at the same time. Besides the individual goals of each contribution, when applicable, we ensure that our solutions scale to extreme network sizes like 12x12 and 16x16. This thesis concludes that the communication overhead and its optimization play a significant role in the performance of many-core SoC

Adaptive Knobs for Resource Efficient Computing

Performance demands of emerging domains such as artificial intelligence, machine learning and vision, Internet-of-things etc., continue to grow. Meeting such requirements on modern multi/many core systems with higher power densities, fixed power and energy budgets, and thermal constraints exacerbates the run-time management challenge. This leaves an open problem on extracting the required performance within the power and energy limits, while also ensuring thermal safety. Existing architectural solutions including asymmetric and heterogeneous cores and custom acceleration improve performance-per-watt in specific design time and static scenarios. However, satisfying applications’ performance requirements under dynamic and unknown workload scenarios subject to varying system dynamics of power, temperature and energy requires intelligent run-time management. Adaptive strategies are necessary for maximizing resource efficiency, considering i) diverse requirements and characteristics of concurrent applications, ii) dynamic workload variation, iii) core-level heterogeneity and iv) power, thermal and energy constraints. This dissertation proposes such adaptive techniques for efficient run-time resource management to maximize performance within fixed budgets under unknown and dynamic workload scenarios. Resource management strategies proposed in this dissertation comprehensively consider application and workload characteristics and variable effect of power actuation on performance for pro-active and appropriate allocation decisions. Specific contributions include i) run-time mapping approach to improve power budgets for higher throughput, ii) thermal aware performance boosting for efficient utilization of power budget and higher performance, iii) approximation as a run-time knob exploiting accuracy performance trade-offs for maximizing performance under power caps at minimal loss of accuracy and iv) co-ordinated approximation for heterogeneous systems through joint actuation of dynamic approximation and power knobs for performance guarantees with minimal power consumption. The approaches presented in this dissertation focus on adapting existing mapping techniques, performance boosting strategies, software and dynamic approximations to meet the performance requirements, simultaneously considering system constraints. The proposed strategies are compared against relevant state-of-the-art run-time management frameworks to qualitatively evaluate their efficacy

Estudo de Heurísticas para Mapeamento Dinâmico de Tarefas sobre a Plataforma HeMPS

Há uma tendência que sistemas intrachip multiprocessados (MPSoC) sejam compostos por dezenas ou centenas de elementos de processamento, permitindo a execução de muitas tarefas em paralelo. Assim, estratégias de alocação de recursos eficientes precisam ser desenvolvidas. Neste sentido, este trabalho investiga o desempenho das heurísticas de mapeamento de tarefas First Free, Nearest Neighbor, Path Load e Best Neighbor no MPSoC HeMPS. A heurística Best Neighbor apresentou o melhor resultado em relação à ocupação dos canais de comunicação do MPSoC, com redução de aproximadamente 32% quando comparada a heurística First Free. No entanto, essa heurística apresentou tempo de execução até 24,21% superior a heurística First Free devido à complexidade de seu algoritmo

A Survey and Comparative Study of Hard and Soft Real-time Dynamic Resource Allocation Strategies for Multi/Many-core Systems

Multi-/many-core systems are envisioned to satisfy the ever-increasing performance requirements of complex applications in various domains such as embedded and high-performance computing. Such systems need to cater to increasingly dynamic workloads, requiring efficient dynamic resource allocation strategies to satisfy hard or soft real-time constraints. This article provides an extensive survey of hard and soft real-time dynamic resource allocation strategies proposed since the mid-1990s and highlights the emerging trends for multi-/many-core systems. The survey covers a taxonomy of the resource allocation strategies and considers their various optimization objectives, which have been used to provide comprehensive comparison. The strategies employ various principles, such as market and biological concepts, to perform the optimizations. The trend followed by the resource allocation strategies, open research challenges, and likely emerging research directions have also been provided

Scalable Task Schedulers for Many-Core Architectures

This thesis develops schedulers for many-cores with different optimization objectives. The proposed schedulers are designed to be scale up as the number of cores in many-cores increase while continuing to provide guarantees on the quality of the schedule

Developing a Framework and Pedagogies for the Delivery of Remote Accessible Laboratory Systems in Science and Engineering

The teaching and learning methods applied to the in-person classroom are not entirely capable of addressing the requirements for an online laboratory environment. The aim of the study is to create the pedagogies for remote laboratories. Therefore, a test environment was developed and user observations were captured over four years. This research proposed an educational framework for online science and engineering laboratory and summarized the most significant aspects to be included in the laboratory design

An e-learning instructional design framework for mobile devices in Africa

English text, with summaries in English, Afrikaans and ZuluThis study aims to propose an e-learning framework for mobile devices in Africa to help improve enrolment rates and education standards in the FET (Further Education and Training) phase. The study is qualitative in nature and employs document analysis as main research method. An overview of the South African education context with supporting statistical data to motivate why an e-learning alternative is crucial for improving South African and African education is provided. The literature review includes a descriptive analysis of 7 existing e- and m-learning frameworks, with key features highlighted for possible adaptation or incorporation into an e-learning framework for Africa. Behaviourism, Constructivism and Connectivism are discussed as applicable learning theories to pedagogically underpin this proposed e-learning framework. Thereafter, a critical evaluation of current South African education policy documents (White Papers, the Norms and Standards for Educators and the Draft Policy for the Provision and Management of Learning Teaching and Support Materials) is conducted to determine whether these policies support and enable e-learning effectively. Part 2 of Chapter 5 comprises a critical analysis and comparison of education systems and applicable legislation in the USA, Finland and Malawi to establish how education is structured and how e-learning is administered in these countries to make relevant recommendations for South Africa and to inform the design of an e-learning framework for Africa. Research findings are presented as answers to the research questions posed and the proposed e-learning framework with further recommendations are presented to the South African Department of Basic Education, teachers and researchers.Die doel van hierdie studie is om ‘n e-onderrig-en-leer raamwerk vir mobiele toestelle vir Afrika voor te stel, sodat inskrywingsgetalle en onderrig- en leerstandaarde in die Verdere Onderrig en Opleidings (VOO) fase verbeter kan word. Dit is ‘n kwalitatiewe studie en dokumentanalise word as navorsingsmetode toegepas. ‘n Oorsig van die huidige Suid-Afrikaanse onderwysstelsel en konteks met ondersteunende statistiese bevindinge word verduidelik om e-onderrig-en-leer as noodsaaklike alternatief vir Suid-Afrika en Afrika te motiveer. Die literatuuroorsig sluit ‘n beskrywende analise van sewe bestaande e- en m-onderrig-en-leer (mobiele-onderrig-en-leer) raamwerke in. Hoofkenmerke van elke raamwerk word uitgelig vir moontlike aanpassing en inkorporering in ‘n e-onderrig-en-leer raamwerk vir die Afrika-konteks. Leerteorië, nl Behaviourisme, Konstruktivisme en Konnektivisme (Connectivism) word in diepte bespreek as pedagogies fundamenteel om die e-onderrig-en-leer raamwerk te onderbou en te ondersteun. ‘n Kritiese evaluasie van Suid-Afrikaanse onderwysbeleid (d.w.s. Witskrifte, die Norme and Standaarde vir Onderwysers en die konsepdokument oor die Voorsiening en Bestuur van Onderrig-, Leer- en Ondersteuningsmateriaal) is gedoen om vas te stel of die beleid wel e-onderrig-en-leer effektief ondersteun en prakties moontlik maak. ‘n Krities analitiese en vergelykende studie van die VSA (Verenigde State van Amerika), Finland en Malawi se onderwysstelsels- en wetgewing is gedoen in hoofstuk 5 deel 2 om te bepaal hoe dié lande onderwys struktureer en hoe e-onderrig-en–leer geadministreer word, sodat relevante voorstelle vir Suid-Afrika gemaak kan word en om insae te lewer in die ontwerp van ‘n e-onderrig-en-leer raamwerk toepaslik vir die Afrika-kontinent. Navorsingsbevindinge word voorgelê aan die Suid-Afrikaanse Departement van Basiese Onderwys, onderwysers sowel as aan navorsers.Lolu cwaningo luhlose ukuphakamisa uhlaka lwe-e-learning lamadivaysi eselula e-Afrika ukusiza ukuthuthukisa izinga lokubhalisa nezindinganiso zemfundo kwiSigaba se-FET (Further Education and Training). Ucwaningo luyimfanelo enemvelo futhi lusebenzisa ukuhlaziywa kwedokhumenti njengendlela yokucwaninga eyinhloko. Ukuhlolisisa umongo wezemfundo waseNingizimu Afrika ngokusekela imniningwane yezibalo ukugqugquzela ukuthi kungani enye yokufunda email ibalulekile ekuthuthukiseni imfundo yaseNingizimu Afrika ne-Afrika. Ukubuyekezwa kwezincwadi kuhlanganisa ukuhlaziywa okuchazayo kwezinhlaka eziyisikhombisa ezisekhona ze-e- e-m-learning, nezici eziyinhloko eziqokonyiswe ukukhishwa kwe-adaption noma ukufakwa kwisakhiwo se-e-learning se-Afrika. Ukuzikhethela, Ukwakhiwa kwe-Constructivism (Kwe Zokwakha) kanye ne-Connectivism (Kwe Zokuxhumana) kuxoxwa njengezifundo ezifanele zokufunda ukusekela lolu hlelo oluhlongozwayo lwe-e-learning. Ngemuva kwaloko, ukuhlolwa okubalulekile kwemibhalo yamanje yemfundo yaseNingizimu Afrika (Amaphepha Asemhlophe, Imigomo Nemigomo Yabafundisi kanye neNqubomgomo Yohlaka Lokufundiswa Nezifundo Nokusekela) kwenziwa ukuze kutholakale ukuthi lezi zinqubomgomo zisekela futhi zikwazi yini ukufundisa nge-e-ephumelelayo. Ingxenye yesibili yeSahluko sesihlanu iqukethe ukuhlaziywa okubucayi kanye nokuqhathaniswa kwezinhlelo zemfundo kanye nemithetho esebenzayo eMelika, eFinland nase Malawi ukuqinisekisa ukuthi imfundo ihlelwe kanjani nokuthi i-e-learning inikezwa kanjani ukwenza izincomo ezifanele eNingizimu Afrika nokwazisa ukuklama uhlaka lwe-e-learning lwe-Afrika. Imiphumela yokucwaninga inikezwa njengezimpendulo zemibuzo yokucwaninga ephakanyisiwe kanye nohlaka oluhlongozwayo lwe-e-learning kanye nezincomo ezengeziwe ezethulwa eMnyangweni wezemfundo Eyisisekelo, othisha nabacwaningi baseNingizimu Afrika.Curriculum and Instructional StudiesM. Ed. (Curriculum Studies

Contributions to energy-aware demand-response systems using SDN and NFV for fog computing

Ever-increasing energy consumption, the depletion of non-renewable resources, the climate impact associated with energy generation, and finite energy-production capacity are important concerns worldwide that drive the urgent creation of new energy management and consumption schemes. In this regard, by leveraging the massive connectivity provided by emerging communications such as the 5G systems, this thesis proposes a long-term sustainable Demand-Response solution for the adaptive and efficient management of available energy consumption for Internet of Things (IoT) infrastructures, in which energy utilization is optimized based on the available supply. In the proposed approach, energy management focuses on consumer devices (e.g., appliances such as a light bulb or a screen). In this regard, by proposing that each consumer device be part of an IoT infrastructure, it is feasible to control its respective consumption. The proposal includes an architecture that uses Network Functions Virtualization (NFV) and Software Defined Networking technologies as enablers to promote the primary use of energy from renewable sources. Associated with architecture, this thesis presents a novel consumption model conditioned on availability in which consumers are part of the management process. To efficiently use the energy from renewable and non-renewable sources, several management strategies are herein proposed, such as the prioritization of the energy supply, workload scheduling using time-shifting capabilities, and quality degradation to decrease- the power demanded by consumers if needed. The adaptive energy management solution is modeled as an Integer Linear Programming, and its complexity has been identified to be NP-Hard. To verify the improvements in energy utilization, an optimal algorithmic solution based on a brute force search has been implemented and evaluated. Because the hardness of the adaptive energy management problem and the non-polynomial growth of its optimal solution, which is limited to energy management for a small number of energy demands (e.g., 10 energy demands) and small values of management mechanisms, several faster suboptimal algorithmic strategies have been proposed and implemented. In this context, at the first stage, we implemented three heuristic strategies: a greedy strategy (GreedyTs), a genetic-algorithm-based solution (GATs), and a dynamic programming approach (DPTs). Then, we incorporated into both the optimal and heuristic strategies a prepartitioning method in which the total set of analyzed services is divided into subsets of smaller size and complexity that are solved iteratively. As a result of the adaptive energy management in this thesis, we present eight strategies, one timal and seven heuristic, that when deployed in communications infrastructures such as the NFV domain, seek the best possible scheduling of demands, which lead to efficient energy utilization. The performance of the algorithmic strategies has been validated through extensive simulations in several scenarios, demonstrating improvements in energy consumption and the processing of energy demands. Additionally, the simulation results revealed that the heuristic approaches produce high-quality solutions close to the optimal while executing among two and seven orders of magnitude faster and with applicability to scenarios with thousands and hundreds of thousands of energy demands. This thesis also explores possible application scenarios of both the proposed architecture for adaptive energy management and algorithmic strategies. In this regard, we present some examples, including adaptive energy management in-home systems and 5G networks slicing, energy-aware management solutions for unmanned aerial vehicles, also known as drones, and applicability for the efficient allocation of spectrum in flex-grid optical networks. Finally, this thesis presents open research problems and discusses other application scenarios and future work.El constante aumento del consumo de energía, el agotamiento de los recursos no renovables, el impacto climático asociado con la generación de energía y la capacidad finita de producción de energía son preocupaciones importantes en todo el mundo que impulsan la creación urgente de nuevos esquemas de consumo y gestión de energía. Al aprovechar la conectividad masiva que brindan las comunicaciones emergentes como los sistemas 5G, esta tesis propone una solución de Respuesta a la Demanda sostenible a largo plazo para la gestión adaptativa y eficiente del consumo de energía disponible para las infraestructuras de Internet of Things (IoT), en el que se optimiza la utilización de la energía en función del suministro disponible. En el enfoque propuesto, la gestión de la energía se centra en los dispositivos de consumo (por ejemplo, electrodomésticos). En este sentido, al proponer que cada dispositivo de consumo sea parte de una infraestructura IoT, es factible controlar su respectivo consumo. La propuesta incluye una arquitectura que utiliza tecnologías de Network Functions Virtualization (NFV) y Software Defined Networking como habilitadores para promover el uso principal de energía de fuentes renovables. Asociada a la arquitectura, esta tesis presenta un modelo de consumo condicionado a la disponibilidad en el que los consumidores son parte del proceso de gestión. Para utilizar eficientemente la energía de fuentes renovables y no renovables, se proponen varias estrategias de gestión, como la priorización del suministro de energía, la programación de la carga de trabajo utilizando capacidades de cambio de tiempo y la degradación de la calidad para disminuir la potencia demandada. La solución de gestión de energía adaptativa se modela como un problema de programación lineal entera con complejidad NP-Hard. Para verificar las mejoras en la utilización de energía, se ha implementado y evaluado una solución algorítmica óptima basada en una búsqueda de fuerza bruta. Debido a la dureza del problema de gestión de energía adaptativa y el crecimiento no polinomial de su solución óptima, que se limita a la gestión de energía para un pequeño número de demandas de energía (por ejemplo, 10 demandas) y pequeños valores de los mecanismos de gestión, varias estrategias algorítmicas subóptimos más rápidos se han propuesto. En este contexto, en la primera etapa, implementamos tres estrategias heurísticas: una estrategia codiciosa (GreedyTs), una solución basada en algoritmos genéticos (GATs) y un enfoque de programación dinámica (DPTs). Luego, incorporamos tanto en la estrategia óptima como en la- heurística un método de prepartición en el que el conjunto total de servicios analizados se divide en subconjuntos de menor tamaño y complejidad que se resuelven iterativamente. Como resultado de la gestión adaptativa de la energía en esta tesis, presentamos ocho estrategias, una óptima y siete heurísticas, que cuando se despliegan en infraestructuras de comunicaciones como el dominio NFV, buscan la mejor programación posible de las demandas, que conduzcan a un uso eficiente de la energía. El desempeño de las estrategias algorítmicas ha sido validado a través de extensas simulaciones en varios escenarios, demostrando mejoras en el consumo de energía y el procesamiento de las demandas de energía. Los resultados de la simulación revelaron que los enfoques heurísticos producen soluciones de alta calidad cercanas a las óptimas mientras se ejecutan entre dos y siete órdenes de magnitud más rápido y con aplicabilidad a escenarios con miles y cientos de miles de demandas de energía. Esta tesis también explora posibles escenarios de aplicación tanto de la arquitectura propuesta para la gestión adaptativa de la energía como de las estrategias algorítmicas. En este sentido, presentamos algunos ejemplos, que incluyen sistemas de gestión de energía adaptativa en el hogar, en 5G networkPostprint (published version

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse