Evaluating Energy Efficiency of Gigabit Ethernet and Infiniband Software Stacks in Data Centres

Reducing energy consumption has become a key issue for data centres, not only because of economical benefits but also for environmental and marketing reasons. Many approaches tackle this problem from the point of view of different hardware components, such as CPUs, storage and network interface cards (NIC). To this date, few works focused on the energy consumption of network transfers at the software level comprising their complete stacks with different energy characteristics, and the way the NIC selection impacts the energy consumption of applications. Since data centres often install multiple NICs on each node, investigating and comparing them at the software level has high potential to enhance the energy efficiency of applications on Cloud infrastructures. We present a comparative analysis of the energy consumption of the software stack of two of today's most used NICs in data centres, Ethernet and Infiniband. We carefully design for this purpose a set of benchmark experiments to assess the impact of different traffic patterns and interface settings on energy consumption. Using our benchmark results, we derive an energy consumption model for network transfers and evaluate its accuracy for a virtual machine migration scenario. Finally, we propose guidelines for NIC selection from an energy efficiency perspective for different application classes.(VLID)2215294Accepted versio

Modelling energy consumption of network transfers and virtual machine migration

Reducing energy consumption has become a key issue for data centres, not only because of economical benefits but also for environmental and marketing reasons. Therefore, assessing their energy consumption requires precise models. In the past years, many models targeting different hardware components, such as CPU, storage and network interface cards (NIC) have been proposed. However, most of them neglect energy consumption related to VM migration. Since VM migration is a network-intensive process, to accurately model its energy consumption we also need energy models for network transfers, comprising their complete software stacks with different energy characteristics. In this work, we present a comparative analysis of the energy consumption of the software stack of two of today's most used NICs in data centres, Ethernet and Infiniband. We carefully design for this purpose a set of benchmark experiments to assess the impact of different traffic patterns and interface settings on energy consumption. Using our benchmark results, we derive an energy consumption model for network transfers. Based on this model, we propose an energy consumption model for VM migration providing accurate predictions for paravirtualised VMs running on homogeneous hosts. We present a comprehensive analysis of our model on different machine sets and compare it with other models for energy consumption of VM migration, showing an improvement of up to 24% in accuracy, according to the NRMSE error metric. © 2015 Elsevier B.V

Convergencia de tecnologías ópticas y Ethernet en LAN, MAN y SAN: nuevas arquitecturas, análisis de prestaciones y eficiencia energética

Mención Internacional en el título de doctorThe development of Information Technologies in the last decades, especially the last two, together with the introduction of computing devices to the mainstream consumer market, has had the logical consequence of the generalisation of the Internet access. The explosive development of the smartphone market has brought ubiquity to that generalisation, to the point that social interaction, content sharing and content production happens all the time. Social networks have all but increased that trend, maximising the diffusion of multimedia content: images, audio and video, which require high network capacities to be enjoyed quickly. This need for endless bandwidth and speed in information sharing brings challenges that affect mainly optical Metropolitan Area Networks (MANs) and Wide Area Networks (WANs). Furthermore, the wide spreading of Ethernet technologies has also brought the possibility to achieve economies of scale by either extending the reach of Ethernet Local Area Networks (LANs) to the MAN and WAN environment or even integrating them with Storage Area Networks (SANs). Finally, this generalisation of telecommunication technologies in every day life has as a consequence an important rise in energy consumption as well. Because of this, providing energy efficient strategies in networking is key to ensure the scalability of the whole Internet. In this thesis, the main technologies in all the fields mentioned above are reviewed, its core challenges identified and several contributions beyond the state of the art are suggested to improve today’s MANs andWANs. In the first contribution of this thesism, the integration between Metro Ethernet and Wavelength Division Multiplexion (WDM) optical transparent rings is explored by proposing an adaptation architecture to provide efficient broadcast and multicast. The second contribution explores the fusion between transparent WDM and OCDMA architectures to simplify medium access in a ring. Regarding SANs, the third contribution explores the challenges in SANs through the problems of Fibre Channel over Ethernet due to buffer design issues. In this contribution, analysis, design and validation with FCoE traces and simulation is provided to calculate buffer overflow probabilities in the absence of flow control mechanisms taking into account the bursty nature of SAN traffic. Finally, the fourth and last contribution addresses the problems of energy efficiency in Plastic Optical Fibres (POF), a new kind of optical fibre more suitable for transmission in vehicles and for home networking. This contribution suggests two packet coalescing strategies to further improve the energy effiency mechanisms in POFs.El desarrollo de las Tecnologías de la Información en las últimas décadas, especialmente las últimas dos, junto con la introducción de dispositivos informáticos al mercado de masas, ha tenido como consecuencia lógica la generalización del acceso a Internet. El explosivo desarrollo del mercado de teléfonos inteligentes ha añadido un factor de ubicuidad a tal generalización, al extremo de que la interacción social, la compartición y producción de contenidos sucede a cada instante. Las redes sociales no han hecho sino incrementar tal tendencia, maximizando la difusión de contenido multimedia: imágenes, audio y vídeo, los cuales requieren gran capacidad en las redes para poder obtenerse con rapidez. Esta necesidad de ancho de banda ilimitado y velocidad en la compartición de información trae consigo retos que afectan principalmente a las Redes de Área Metropolitana (Metropolitan Area Networks, MANs) y Redes de Área Extensa (Wide Area Networks, WANs). Además, la gran difusión de las tecnologías Ethernet ha traído la posibilidad de alcanzar economías de escala bien extendiendo el alcance de Ethernet más allá de las Redes de Área Local (Local Area Networks, LANs) al entorno de las MAN y las WAN o incluso integrándolas con Redes de Almacenamiento (Storage Area Networks, SANs). Finalmente, esta generalización de las tecnologías de la comunicación en la vida cotidiana tiene también como consecuencia un importante aumento en el consumo de energía. Por tanto, desarrollar estrategias de transmisión en red eficientes energéticamente es clave para asegurar la escalabilidad de Internet. En esta tesis, las principales tecnologías de todos los campos mencionados arriba serán estudiadas, sus más importantes retos identificados y se sugieren varias contribuciones más allá del actual estado del arte para mejorar las actuales MANs y WANs. En la primera contribución de esta tesis, se explora la integración entre Metro Ethernet y anillos ópticos transparentes por Multiplexión en Longitud de Onda (Wavelength Division Multiplex, WDM) mediante la proposición de una arquitectura de adaptación para permitir la difusión y multidifusión eficiente. La segunda contribución explora la fusión entre las arquitecturas transparentes WDM y arquitecturas por Accesso Dividido Múltiple por Códigos Ópticos (OCDMA) para simplificar el acceso en una red en anillo. En lo referente a las SANs, la tercera contribución explora los retos en SANs a través de los problemas de Fibre Channel sobre Ethernet debido a los problemas en el diseño de búferes. En esta contribución, se provee un análisis, diseño y validación con trazas FCoE para calcular las probabilidades de desbordamiento de buffer en ausencia de mecanismos de control de flujo teniendo en cuenta la naturaleza rafagosa del tráfico de SAN. Finalmente, la cuarta y última contribución aborda los problemas de eficiencia energética en Fibras Ópticas Plásticas (POF), una nueva variedad de fibra óptica más adecuada para la transmisión en vehículos y para entornos de red caseros. Esta contribución sugiere dos estrategias de agrupamiento de paquetes para mejorar los mecanismos de eficiencia energética en POFs.Programa Oficial de Posgrado en Ingeniería TelemáticaPresidente: Luca Valcarenghi.- Secretario: Ignacio Soto Campos.- Vocal: Bas Huiszoo

A shared-disk parallel cluster file system

Dissertação apresentada para obtenção do Grau de Doutor em Informática Pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaToday, clusters are the de facto cost effective platform both for high performance computing (HPC) as well as IT environments. HPC and IT are quite different environments and differences include, among others, their choices on file systems and storage: HPC favours parallel file systems geared towards maximum I/O bandwidth, but which are not fully POSIX-compliant and were devised to run on top of (fault prone) partitioned storage; conversely, IT data centres favour both external disk arrays (to provide highly available storage) and POSIX compliant file systems, (either general purpose or shared-disk cluster file systems, CFSs). These specialised file systems do perform very well in their target environments provided that applications do not require some lateral features, e.g., no file locking on parallel file systems, and no high performance writes over cluster-wide shared files on CFSs. In brief, we can say that none of the above approaches solves the problem of providing high levels of reliability and performance to both worlds. Our pCFS proposal makes a contribution to change this situation: the rationale is to take advantage on the best of both – the reliability of cluster file systems and the high performance of parallel file systems. We don’t claim to provide the absolute best of each, but we aim at full POSIX compliance, a rich feature set, and levels of reliability and performance good enough for broad usage – e.g., traditional as well as HPC applications, support of clustered DBMS engines that may run over regular files, and video streaming. pCFS’ main ideas include: · Cooperative caching, a technique that has been used in file systems for distributed disks but, as far as we know, was never used either in SAN based cluster file systems or in parallel file systems. As a result, pCFS may use all infrastructures (LAN and SAN) to move data. · Fine-grain locking, whereby processes running across distinct nodes may define nonoverlapping byte-range regions in a file (instead of the whole file) and access them in parallel, reading and writing over those regions at the infrastructure’s full speed (provided that no major metadata changes are required). A prototype was built on top of GFS (a Red Hat shared disk CFS): GFS’ kernel code was slightly modified, and two kernel modules and a user-level daemon were added. In the prototype, fine grain locking is fully implemented and a cluster-wide coherent cache is maintained through data (page fragments) movement over the LAN. Our benchmarks for non-overlapping writers over a single file shared among processes running on different nodes show that pCFS’ bandwidth is 2 times greater than NFS’ while being comparable to that of the Parallel Virtual File System (PVFS), both requiring about 10 times more CPU. And pCFS’ bandwidth also surpasses GFS’ (600 times for small record sizes, e.g., 4 KB, decreasing down to 2 times for large record sizes, e.g., 4 MB), at about the same CPU usage.Lusitania, Companhia de Seguros S.A, Programa IBM Shared University Research (SUR

Towards Modern, Accessible and Dynamic HPC Using Container-based Virtual Clusters

In this thesis, a novel Virtual Container Cluster (VCC) framework is presented. Despite the growing popularity of container virtualisation in order to increase the flexi-bility of the software stack, run time environment virtualisation still poses significant portability challenges; by depending on the underlying cluster execution paradigm,a niche class of HPC only containers has emerged. This trend is detrimental to reusability, reproducibility, and encouraging new communities to HPC. Traditional virtualisation techniques have a rich history within HPC, and have been demonstrated to offer much more than software flexibility. A Virtual Machine by nature requires an OS and full stack environment akin to a physical machine, and this allows it to be instantiated regardless of the underlying machine and what services it provides. This capability is essential in order to implement job forwarding and spanning - where the burden of an entire job can be transferred or shared between hetero-geneous cluster systems - with a high level of confidence that the environments will be compatible. In turn, this brings improvements to global resource performance, reducing the job turnaround time and increasing cluster utilization. The VCC is an innovative solution that combines the full stack and container virtualisation approaches. Therefore, it offers both the flexibility of containers with the improved portability, performance and scalability of the full stack approach. In order to maintain the same accessibility and lower barrier of entry as the run time environment approach, the design incorporates an autonomous configuration and contextualisation mechanism, along with a Software Defined Networking technology, to ensure the full stack container does not place an additional burden on the user. The usefulness and performance is validated through benchmarking and two case studies: virtual clusters in the classroom and inter-institutional spanning

Serverless Computing Strategies on Cloud Platforms

[ES] Con el desarrollo de la Computación en la Nube, la entrega de recursos virtualizados a través de Internet ha crecido enormemente en los últimos años. Las Funciones como servicio (FaaS), uno de los modelos de servicio más nuevos dentro de la Computación en la Nube, permite el desarrollo e implementación de aplicaciones basadas en eventos que cubren servicios administrados en Nubes públicas y locales. Los proveedores públicos de Computación en la Nube adoptan el modelo FaaS dentro de su catálogo para proporcionar computación basada en eventos altamente escalable para las aplicaciones. Por un lado, los desarrolladores especializados en esta tecnología se centran en crear marcos de código abierto serverless para evitar el bloqueo con los proveedores de la Nube pública. A pesar del desarrollo logrado por la informática serverless, actualmente hay campos relacionados con el procesamiento de datos y la optimización del rendimiento en la ejecución en los que no se ha explorado todo el potencial. En esta tesis doctoral se definen tres estrategias de computación serverless que permiten evidenciar los beneficios de esta tecnología para el procesamiento de datos. Las estrategias implementadas permiten el análisis de datos con la integración de dispositivos de aceleración para la ejecución eficiente de aplicaciones científicas en plataformas cloud públicas y locales. En primer lugar, se desarrolló la plataforma CloudTrail-Tracker. CloudTrail-Tracker es una plataforma serverless de código abierto basada en eventos para el procesamiento de datos que puede escalar automáticamente hacia arriba y hacia abajo, con la capacidad de escalar a cero para minimizar los costos operativos. Seguidamente, se plantea la integración de GPUs en una plataforma serverless local impulsada por eventos para el procesamiento de datos escalables. La plataforma admite la ejecución de aplicaciones como funciones severless en respuesta a la carga de un archivo en un sistema de almacenamiento de ficheros, lo que permite la ejecución en paralelo de las aplicaciones según los recursos disponibles. Este procesamiento es administrado por un cluster Kubernetes elástico que crece y decrece automáticamente según las necesidades de procesamiento. Ciertos enfoques basados en tecnologías de virtualización de GPU como rCUDA y NVIDIA-Docker se evalúan para acelerar el tiempo de ejecución de las funciones. Finalmente, se implementa otra solución basada en el modelo serverless para ejecutar la fase de inferencia de modelos de aprendizaje automático previamente entrenados, en la plataforma de Amazon Web Services y en una plataforma privada con el framework OSCAR. El sistema crece elásticamente de acuerdo con la demanda y presenta una escalado a cero para minimizar los costes. Por otra parte, el front-end proporciona al usuario una experiencia simplificada en la obtención de la predicción de modelos de aprendizaje automático. Para demostrar las funcionalidades y ventajas de las soluciones propuestas durante esta tesis se recogen varios casos de estudio que abarcan diferentes campos del conocimiento como la analítica de aprendizaje y la Inteligencia Artificial. Esto demuestra que la gama de aplicaciones donde la computación serverless puede aportar grandes beneficios es muy amplia. Los resultados obtenidos avalan el uso del modelo serverless en la simplificación del diseño de arquitecturas para el uso intensivo de datos en aplicaciones complejas.[CA] Amb el desenvolupament de la Computació en el Núvol, el lliurament de recursos virtualitzats a través d'Internet ha crescut granment en els últims anys. Les Funcions com a Servei (FaaS), un dels models de servei més nous dins de la Computació en el Núvol, permet el desenvolupament i implementació d'aplicacions basades en esdeveniments que cobreixen serveis administrats en Núvols públics i locals. Els proveïdors de computació en el Núvol públic adopten el model FaaS dins del seu catàleg per a proporcionar a les aplicacions computació altament escalable basada en esdeveniments. D'una banda, els desenvolupadors especialitzats en aquesta tecnologia se centren en crear marcs de codi obert serverless per a evitar el bloqueig amb els proveïdors del Núvol públic. Malgrat el desenvolupament alcançat per la informàtica serverless, actualment hi ha camps relacionats amb el processament de dades i l'optimització del rendiment d'execució en els quals no s'ha explorat tot el potencial. En aquesta tesi doctoral es defineixen tres estratègies informàtiques serverless que permeten demostrar els beneficis d'aquesta tecnologia per al processament de dades. Les estratègies implementades permeten l'anàlisi de dades amb a integració de dispositius accelerats per a l'execució eficient d'aplicacion scientífiques en plataformes de Núvol públiques i locals. En primer lloc, es va desenvolupar la plataforma CloudTrail-Tracker. CloudTrail-Tracker és una plataforma de codi obert basada en esdeveniments per al processament de dades serverless que pot escalar automáticament cap amunt i cap avall, amb la capacitat d'escalar a zero per a minimitzar els costos operatius. A continuació es planteja la integració de GPUs en una plataforma serverless local impulsada per esdeveniments per al processament de dades escalables. La plataforma admet l'execució d'aplicacions com funcions severless en resposta a la càrrega d'un arxiu en un sistema d'emmagatzemaments de fitxers, la qual cosa permet l'execució en paral·lel de les aplicacions segon sels recursos disponibles. Este processament és administrat per un cluster Kubernetes elàstic que creix i decreix automàticament segons les necessitats de processament. Certs enfocaments basats en tecnologies de virtualització de GPU com rCUDA i NVIDIA-Docker s'avaluen per a accelerar el temps d'execució de les funcions. Finalment s'implementa una altra solució basada en el model serverless per a executar la fase d'inferència de models d'aprenentatge automàtic prèviament entrenats en la plataforma de Amazon Web Services i en una plataforma privada amb el framework OSCAR. El sistema creix elàsticament d'acord amb la demanda i presenta una escalada a zero per a minimitzar els costos. D'altra banda el front-end proporciona a l'usuari una experiència simplificada en l'obtenció de la predicció de models d'aprenentatge automàtic. Per a demostrar les funcionalitats i avantatges de les solucions proposades durant esta tesi s'arrepleguen diversos casos d'estudi que comprenen diferents camps del coneixement com l'analítica d'aprenentatge i la Intel·ligència Artificial. Això demostra que la gamma d'aplicacions on la computació serverless pot aportar grans beneficis és molt àmplia. Els resultats obtinguts avalen l'ús del model serverless en la simplificació del disseny d'arquitectures per a l'ús intensiu de dades en aplicacions complexes.[EN] With the development of Cloud Computing, the delivery of virtualized resources over the Internet has greatly grown in recent years. Functions as a Service (FaaS), one of the newest service models within Cloud Computing, allows the development and implementation of event-based applications that cover managed services in public and on-premises Clouds. Public Cloud Computing providers adopt the FaaS model within their catalog to provide event-driven highly-scalable computing for applications. On the one hand, developers specialized in this technology focus on creating open-source serverless frameworks to avoid the lock-in with public Cloud providers. Despite the development achieved by serverless computing, there are currently fields related to data processing and execution performance optimization where the full potential has not been explored. In this doctoral thesis three serverless computing strategies are defined that allow to demonstrate the benefits of this technology for data processing. The implemented strategies allow the analysis of data with the integration of accelerated devices for the efficient execution of scientific applications on public and on-premises Cloud platforms. Firstly, the CloudTrail-Tracker platform was developed to extract and process learning analytics in the Cloud. CloudTrail-Tracker is an event-driven open-source platform for serverless data processing that can automatically scale up and down, featuring the ability to scale to zero for minimizing the operational costs. Next, the integration of GPUs in an event-driven on-premises serverless platform for scalable data processing is discussed. The platform supports the execution of applications as serverless functions in response to the loading of a file in a file storage system, which allows the parallel execution of applications according to available resources. This processing is managed by an elastic Kubernetes cluster that automatically grows and shrinks according to the processing needs. Certain approaches based on GPU virtualization technologies such as rCUDA and NVIDIA-Docker are evaluated to speed up the execution time of the functions. Finally, another solution based on the serverless model is implemented to run the inference phase of previously trained machine learning models on theAmazon Web Services platform and in a private platform with the OSCAR framework. The system grows elastically according to demand and is scaled to zero to minimize costs. On the other hand, the front-end provides the user with a simplified experience in obtaining the prediction of machine learning models. To demonstrate the functionalities and advantages of the solutions proposed during this thesis, several case studies are collected covering different fields of knowledge such as learning analytics and Artificial Intelligence. This shows the wide range of applications where serverless computing can bring great benefits. The results obtained endorse the use of the serverless model in simplifying the design of architectures for the intensive data processing in complex applications.Naranjo Delgado, DM. (2021). Serverless Computing Strategies on Cloud Platforms [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/160916TESI