Cloud-efficient modelling and simulation of magnetic nano materials

Scientific simulations are rarely attempted in a cloud due to the substantial performance costs of virtualization. Considerable communication overheads, intolerable latencies, and inefficient hardware emulation are the main reasons why this emerging technology has not been fully exploited. On the other hand, the progress of computing infrastructure nowadays is strongly dependent on perspective storage medium development, where efficient micromagnetic simulations play a vital role in future memory design. This thesis addresses both these topics by merging micromagnetic simulations with the latest OpenStack cloud implementation while providing a time and costeffective alternative to expensive computing centers. However, many challenges have to be addressed before a high-performance cloud platform emerges as a solution for problems in micromagnetic research communities. First, the best solver candidate has to be selected and further improved, particularly in the parallelization and process communication domain. Second, a 3-level cloud communication hierarchy needs to be recognized and each segment adequately addressed. The required steps include breaking the VMisolation for the host’s shared memory activation, cloud network-stack tuning, optimization, and efficient communication hardware integration. The project work concludes with practical measurements and confirmation of successfully implemented simulation into an open-source cloud environment. It is achieved that the renewed Magpar solver runs for the first time in the OpenStack cloud by using ivshmem for shared memory communication. Also, extensive measurements proved the effectiveness of our solutions, yielding from sixty percent to over ten times better results than those achieved in the standard cloud.Aufgrund der erheblichen Leistungskosten der Virtualisierung werden wissenschaftliche Simulationen in einer Cloud selten versucht. Beträchtlicher Kommunikationsaufwand, erhebliche Latenzen und ineffiziente Hardwareemulation sind die Hauptgründe, warum diese aufkommende Technologie nicht vollständig genutzt wurde. Andererseits hängt der Fortschritt der Computertechnologie heutzutage stark von der Entwicklung perspektivischer Speichermedien ab, bei denen effiziente mikromagnetische Simulationen eine wichtige Rolle für die zukünftige Speichertechnologie spielen. Diese Arbeit befasst sich mit diesen beiden Themen, indem mikromagnetische Simulationen mit der neuesten OpenStack Cloud-Implementierung zusammengeführt werden, um eine zeit- und kostengünstige Alternative zu teuren Rechenzentren bereitzustellen. Viele Herausforderungen müssen jedoch angegangen werden, bevor eine leistungsstarke Cloud-Plattform als Lösung für Probleme in mikromagnetischen Forschungsgemeinschaften entsteht. Zunächst muss der beste Kandidat für die Lösung ausgewählt und weiter verbessert werden, insbesondere im Bereich der Parallelisierung und Prozesskommunikation. Zweitens muss eine 3-stufige CloudKommunikationshierarchie erkannt und jedes Segment angemessen adressiert werden. Die erforderlichen Schritte umfassen das Aufheben der VM-Isolation, um den gemeinsam genutzten Speicher zwischen Cloud-Instanzen zu aktivieren, die Optimierung des Cloud-Netzwerkstapels und die effiziente Integration von Kommunikationshardware. Die praktische Arbeit endet mit Messungen und der Bestätigung einer erfolgreich implementierten Simulation in einer Open-Source Cloud-Umgebung. Als Ergebnis haben wir erreicht, dass der neu erstellte Magpar-Solver zum ersten Mal in der OpenStack Cloud ausgeführt wird, indem ivshmem für die Shared-Memory Kommunikation verwendet wird. Umfangreiche Messungen haben auch die Wirksamkeit unserer Lösungen bewiesen und von sechzig Prozent bis zu zehnmal besseren Ergebnissen als in der Standard Cloud geführt

Adaptive Resource Relocation in Virtualized Heterogeneous Clusters

Cluster computing has recently gone through an evolution from single processor systems to multicore/multi-socket systems. This has resulted in lowering the cost/performance ratio of the compute machines. Compute farms that host these machines tend to become heterogeneous over time due to incremental extensions, hardware upgrades and/or nodes being purchased for users with particular needs. This heterogeneity is not surprising given the wide range of processor, memory and network technologies that become available and the relatively small price difference between these various options. Different CPU architectures, memory capacities, communication and I/O interfaces of the participating compute nodes present many challenges to job scheduling and often result in under or over utilization of the compute resources. In general, it is not feasible for the application programmers to specifically optimize their programs for such a set of differing compute n odes, due to the difficulty and time-intensiveness of such a task. The trend of heterogeneous compute farms has coincided with resurgence in the virtualization technology. Virtualization technology is receiving widespread adoption, mainly due to the benefits of server consolidation and isolation, load balancing, security and fault tolerance. Virtualization has also generated considerable interest in the High Performance Computing (HPC) community, due to the resulting high availability, fault tolerance, cluster partitioning and accommodation of conflicting user requirements. However, the HPC community is still wary of the potential overheads associated with‘ virtualization, as it results in slower network communications and disk I/O, which need to be addressed. The live migration feature, available to most virtualization technologies, can be leveraged to improve the throughput of a heterogeneous compute farm (HC) used for HPC applications. For this we mitigated the slow network communication in Xen; an open source virtual machine monitor. We present a detailed analysis of the communication framework of Xen and propose communication configurations that give 50% improvement over the conventional Xen network configuration. From a detailed study of the migration facility in Xen, we propose an improvement in the live migration facility specifically targeting HPC applications. This optimization gives around 50% improvement over the default migration facility of Xen. In this thesis, we also investigate resource scheduling in heterogeneous compute farm with the perspective of dynamic resource re-mapping. Our approach is to profile each job in the compute farm at runtime, and propose a better resource mapping compared to the initial allocation. We then migrate the job(s) to the best-suited homogeneous sub-cluster to improve overall throughput of the HC. For this, we develop a novel heterogeneity and virtualization-aware profiling framework, which is able to predict the CPU and communication characteristics of high performance scientific applications. The prediction accuracy of our performance estimation model is over 80%. The framework implementation is lightweight, with an overhead of 3%. Our experiments show that we are able to improve the throughput of the compute farm by 25% and the time saved by the HC with our framework is over 30%. The framework can be readily extended to HCs supporting a cloud computing environment

Optimizing Virtual Machine I/O Performance in Virtualized Cloud by Differenciated-frequency Scheduling and Functionality Offloading

Many enterprises are increasingly moving their applications to private cloud environments or public cloud platforms. A key technology driving cloud computing is virtualization which can serve multiple VMs in one physical machine hence providing better management flexibility and significant savings in operational costs. However, one important consequence of virtualized hosts in the cloud is the negative impact it has on the I/O performance of the applications running in the VMs

Virtualization services: scalable methods for virtualizing multicore systems

Multi-core technology is bringing parallel processing capabilities from servers to laptops and even handheld devices. At the same time, platform support for system virtualization is making it easier to consolidate server and client resources, when and as needed by applications. This consolidation is achieved by dynamically mapping the virtual machines on which applications run to underlying physical machines and their processing cores. Low cost processor and I/O virtualization methods efficiently scaled to different numbers of processing cores and I/O devices are key enablers of such consolidation. This dissertation develops and evaluates new methods for scaling virtualization functionality to multi-core and future many-core systems. Specifically, it re-architects virtualization functionality to improve scalability and better exploit multi-core system resources. Results from this work include a self-virtualized I/O abstraction, which virtualizes I/O so as to flexibly use different platforms' processing and I/O resources. Flexibility affords improved performance and resource usage and most importantly, better scalability than that offered by current I/O virtualization solutions. Further, by describing system virtualization as a service provided to virtual machines and the underlying computing platform, this service can be enhanced to provide new and innovative functionality. For example, a virtual device may provide obfuscated data to guest operating systems to maintain data privacy; it could mask differences in device APIs or properties to deal with heterogeneous underlying resources; or it could control access to data based on the ``trust' properties of the guest VM. This thesis demonstrates that extended virtualization services are superior to existing operating system or user-level implementations of such functionality, for multiple reasons. First, this solution technique makes more efficient use of key performance-limiting resource in multi-core systems, which are memory and I/O bandwidth. Second, this solution technique better exploits the parallelism inherent in multi-core architectures and exhibits good scalability properties, in part because at the hypervisor level, there is greater control in precisely which and how resources are used to realize extended virtualization services. Improved control over resource usage makes it possible to provide value-added functionalities for both guest VMs and the platform. Specific instances of virtualization services described in this thesis are the network virtualization service that exploits heterogeneous processing cores, a storage virtualization service that provides location transparent access to block devices by extending the functionality provided by network virtualization service, a multimedia virtualization service that allows efficient media device sharing based on semantic information, and an object-based storage service with enhanced access control.Ph.D.Committee Chair: Schwan, Karsten; Committee Member: Ahamad, Mustaq; Committee Member: Fujimoto, Richard; Committee Member: Gavrilovska, Ada; Committee Member: Owen, Henry; Committee Member: Xenidis, Jim

Distributed Shared Memory based Live VM Migration

Cloud computing is the new trend in computing services and IT industry, this computing paradigm has numerous benefits to utilize IT infrastructure resources and reduce services cost. The key feature of cloud computing depends on mobility and scalability of the computing resources, by managing virtual machines. The virtualization decouples the software from the hardware and manages the software and hardware resources in an easy way without interruption of services. Live virtual machine migration is an essential tool for dynamic resource management in current data centers. Live virtual machine is defined as the process of moving a running virtual machine or application between different physical machines without disconnecting the client or application. Many techniques have been developed to achieve this goal based on several metrics (total migration time, downtime, size of data sent and application performance) that are used to measure the performance of live migration. These metrics measure the quality of the VM services that clients care about, because the main goal of clients is keeping the applications performance with minimum service interruption. The pre-copy live VM migration is done in four phases: preparation, iterative migration, stop and copy, and resume and commitment. During the preparation phase, the source and destination physical servers are selected, the resources in destination physical server are reserved, and the critical VM is selected to be migrated. The cloud manager responsibility is to make all of these decisions. VM state migration takes place and memory state is transferred to the target node during iterative migration phase. Meanwhile, the migrated VM continues to execute and dirties its memory. In the stop and copy phase, VM virtual CPU is stopped and then the processor and network states are transferred to the destination host. Service downtime results from stopping VM execution and moving the VM CPU and network states. Finally in the resume and commitment phase, the migrated VM is resumed running in the destination physical host, the remaining memory pages are pulled by destination machine from the source machine. The source machine resources are released and eliminated. In this thesis, pre-copy live VM migration using Distributed Shared Memory (DSM) computing model is proposed. The setup is built using two identical computation nodes to construct all the proposed environment services architecture namely the virtualization infrastructure (Xenserver6.2 hypervisor), the shared storage server (the network file system), and the DSM and High Performance Computing (HPC) cluster. The custom DSM framework is based on a low latency memory update named Grappa. Moreover, HPC cluster is used to parallelize the work load by using CPUs computation nodes. HPC cluster employs OPENMPI and MPI libraries to support parallelization and auto-parallelization. The DSM allows the cluster CPUs to access the same memory space pages resulting in less memory data updates, which reduces the amount of data transferred through the network. The thesis proposed model achieves a good enhancement of the live VM migration metrics. Downtime is reduced by 50 % in the idle workload of Windows VM and 66.6% in case of Ubuntu Linux idle workload. In general, the proposed model not only reduces the downtime and the total amount of data sent, but also does not degrade other metrics like the total migration time and the applications performance

Low power processor architecture and multicore approach for embedded systems

13301甲第4319号博士（工学）金沢大学博士論文本文Full 以下に掲載：1.IEICE Transactions Vol. E98-C(7) pp.544-549 2015. IEICE. 共著者： S. Otani, H. Kondo. /2.Reuse 許可エビデンス送

Towards a cloud enabler : from an optical network resource provisioning system to a generalized architecture for dynamic infrastructure services provisioning

This work was developed during a period where most of the optical management and provisioning system where manual and proprietary. This work contributed to the evolution of the state of the art of optical networks with new architectures and advanced virtual infrastructure services. The evolution of optical networks, and internet globally, have been very promising during the last decade. The impact of mobile technology, grid, cloud computing, HDTV, augmented reality and big data, among many others, have driven the evolution of optical networks towards current service technologies, mostly based on SDN (Software Defined Networking) architectures and NFV(Network Functions Virtualisation). Moreover, the convergence of IP/Optical networks and IT services, and the evolution of the internet and optical infrastructures, have generated novel service orchestrators and open source frameworks. In fact, technology has evolved that fast that none could foresee how important Internet is for our current lives. Said in other words, technology was forced to evolve in a way that network architectures became much more transparent, dynamic and flexible to the end users (applications, user interfaces or simple APIs). This Thesis exposes the work done on defining new architectures for Service Oriented Networks and the contribution to the state of the art. The research work is divided into three topics. It describes the evolution from a Network Resource Provisioning System to an advanced Service Plane, and ends with a new architecture that virtualized the optical infrastructure in order to provide coordinated, on-demand and dynamic services between the application and the network infrastructure layer, becoming an enabler for the new generation of cloud network infrastructures. The work done on defining a Network Resource Provisioning System established the first bases for future work on network infrastructure virtualization. The UCLP (User Light Path Provisioning) technology was the first attempt for Customer Empowered Networks and Articulated Private Networks. It empowered the users and brought virtualization and partitioning functionalities into the optical data plane, with new interfaces for dynamic service provisioning. The work done within the development of a new Service Plane allowed the provisioning of on-demand connectivity services from the application, and in a multi-domain and multi-technology scenario based on a virtual network infrastructure composed of resources from different infrastructure providers. This Service Plane facilitated the deployment of applications consuming large amounts of data under deterministic conditions, so allowing the networks behave as a Grid-class resource. It became the first on-demand provisioning system that at lower levels allowed the creation of one virtual domain composed from resources of different providers. The last research topic presents an architecture that consolidated the work done in virtualisation while enhancing the capabilities to upper layers, so fully integrating the optical network infrastructure into the cloud environment, and so providing an architecture that enabled cloud services by integrating the request of optical network and IT infrastructure services together at the same level. It set up a new trend into the research community and evolved towards the technology we use today based on SDN and NFV. Summing up, the work presented is focused on the provisioning of virtual infrastructures from the architectural point of view of optical networks and IT infrastructures, together with the design and definition of novel service layers. It means, architectures that enabled the creation of virtual infrastructures composed of optical networks and IT resources, isolated and provisioned on-demand and in advance with infrastructure re-planning functionalities, and a new set of interfaces to open up those services to applications or third parties.Aquesta tesi es va desenvolupar durant un període on la majoria de sistemes de gestió de xarxa òptica eren manuals i basats en sistemes propietaris. En aquest sentit, la feina presentada va contribuir a l'evolució de l'estat de l'art de les xarxes òptiques tant a nivell d’arquitectures com de provisió d’infraestructures virtuals. L'evolució de les xarxes òptiques, i d'Internet a nivell mundial, han estat molt prometedores durant l'última dècada. L'impacte de la tecnologia mòbil, la computació al núvol, la televisió d'alta definició, la realitat augmentada i el big data, entre molts altres, han impulsat l'evolució cap a xarxes d’altes prestacions amb nous serveis basats en SDN (Software Defined Networking) i NFV (Funcions de xarxa La virtualització). D'altra banda, la convergència de xarxes òptiques i els serveis IT, junt amb l'evolució d'Internet i de les infraestructures òptiques, han generat nous orquestradors de serveis i frameworks basats en codi obert. La tecnologia ha evolucionat a una velocitat on ningú podria haver predit la importància que Internet està tenint en el nostre dia a dia. Dit en altres paraules, la tecnologia es va veure obligada a evolucionar d'una manera on les arquitectures de xarxa es fessin més transparent, dinàmiques i flexibles vers als usuaris finals (aplicacions, interfícies d'usuari o APIs simples). Aquesta Tesi presenta noves arquitectures de xarxa òptica orientades a serveis. El treball de recerca es divideix en tres temes. Es presenta un sistema de virtualització i aprovisionament de recursos de xarxa i la seva evolució a un pla de servei avançat, per acabar presentant el disseny d’una nova arquitectura capaç de virtualitzar la infraestructura òptica i IT i proporcionar serveis de forma coordinada, i sota demanda, entre l'aplicació i la capa d'infraestructura de xarxa òptica. Tot esdevenint un facilitador per a la nova generació d'infraestructures de xarxa en el núvol. El treball realitzat en la definició del sistema de virtualització de recursos va establir les primeres bases sobre la virtualització de la infraestructura de xarxa òptica en el marc de les “Customer Empowered Networks” i “Articulated Private Networks”. Amb l’objectiu de virtualitzar el pla de dades òptic, i oferir noves interfícies per a la provisió de serveis dinàmics de xarxa. En quant al pla de serveis presentat, aquest va facilitat la provisió de serveis de connectivitat sota demanda per part de l'aplicació, tant en entorns multi-domini, com en entorns amb múltiples tecnologies. Aquest pla de servei, anomenat Harmony, va facilitar el desplegament de noves aplicacions que consumien grans quantitats de dades en condicions deterministes. En aquest sentit, va permetre que les xarxes es comportessin com un recurs Grid, i per tant, va esdevenir el primer sistema d'aprovisionament sota demanda que permetia la creació de dominis virtuals de xarxa composts a partir de recursos de diferents proveïdors. Finalment, es presenta l’evolució d’un pla de servei cap una arquitectura global que consolida el treball realitzat a nivell de convergència d’infraestructures (òptica + IT) i millora les capacitats de les capes superiors. Aquesta arquitectura va facilitar la plena integració de la infraestructura de xarxa òptica a l'entorn del núvol. En aquest sentit, aquest resultats van evolucionar cap a les tendències actuals de SDN i NFV. En resum, el treball presentat es centra en la provisió d'infraestructures virtuals des del punt de vista d’arquitectures de xarxa òptiques i les infraestructures IT, juntament amb el disseny i definició de nous serveis de xarxa avançats, tal i com ho va ser el servei de re-planificació dinàmicaPostprint (published version

Effects of Communication Protocol Stack Offload on Parallel Performance in Clusters

The primary research objective of this dissertation is to demonstrate that the effects of communication protocol stack offload (CPSO) on application execution time can be attributed to the following two complementary sources. First, the application-specific computation may be executed concurrently with the asynchronous communication performed by the communication protocol stack offload engine. Second, the protocol stack processing can be accelerated or decelerated by the offload engine. These two types of performance effects can be quantified with the use of the degree of overlapping Do and degree of acceleration Daccs. The composite communication speedup metrics S_comm(Do, Daccs) can be used in order to quantify the combined effects of the protocol stack offload. This dissertation thesis is validated empirically. The degree of overlapping Do, the degree of acceleration Daccs, and the communication speedup Scomm characteristic of the system configurations under test are derived in the course of experiments performed for the system configurations of interest. It is shown that the proposed metrics adequately describe the effects of the protocol stack offload on the application execution time. Additionally, a set of analytical models of the networking subsystem of a PC-based cluster node is developed. As a result of the modeling, the metrics Do, Daccs, and Scomm are obtained. The models are evaluated as to their complexity and precision by comparing the modeling results with the measured values of Do, Daccs, and Scomm. The primary contributions of this dissertation research are as follows. First, the metric Daccs and Scomm are introduced in order to complement the Do metric in its use for evaluation of the effects of optimizations in the networking subsystem on parallel performance in clusters. The metrics are shown to adequately describe CPSO performance effects. Second, a method for assessing performance effects of CPSO scenarios on application performance is developed and presented. Third, a set of analytical models of cluster node networking subsystems with CPSO capability is developed and characterised as to their complexity and precision of the prediction of the Do and Daccs metrics

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

Remote sensing big data computing: challenges and opportunities

As we have entered an era of high resolution earth observation, the RS data are undergoing an explosive growth. The proliferation of data also give rise to the increasing complexity of RS data, like the diversity and higher dimensionality characteristic of the data. RS data are regarded as RS ‘‘Big Data’’. Fortunately, we are witness the coming technological leapfrogging. In this paper, we give a brief overview on the Big Data and data-intensive problems, including the analysis of RS Big Data, Big Data challenges, current techniques and works for processing RS Big Data