119 research outputs found

    Acyclic Transformation Technique for the Reachability Analysis of Petri Nets

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    Industrial Engineering and Managemen

    High-Speed Message Routing Mechanisms for Massively Parallel Computers

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    現在超並列処理システム(MPP)は、伝統的なベクトルプロセッサやSIMDマシンの 牙城であった多くの分野に進出している。これらのシステムは、入手が容易な高性能 CPUの急激な進歩をうまく利用し、これらを数百~数千個接続して均質なマルチプ ロセッサのシステムとして構成したものである。しかし、これらのシステムの性能は、 現実の問題を解くときは必ずしも良くなく、常に公称の最高性能にははるかに及ばな いのが現状である。これらのシステムではプロセッサ間の通信はすべて相互結合網に よって行われるので、実現可能な最高性能を決める決定的な要素は相互結合網と、そ れに使われる通信機構である。 本論文ではMPPの相互結合網に使われる、効率的な通信機構を実現する2つの方法 を提案する。第1は「特急ルータ」の提案であり、これを相互結合網に用いた場合の 適合性を検註する。特急ルータは多重の単方向レジスタ挿入パスを利用して、時間 空間混合分割型ネットワークを実現するためのものである。異なる基数や次元数につ いて、特急ルータのスイッチ回路とバッファ回路の性能を予測するための正確なモデ ルを開発した。この結果、特急ルータは効率的な通信を行うためのすべての条件を満 足していることが確かめられた。さらに重要な点は、特急ルータはネットワークに故 障のある場合や、通信が錯綜する場合にも、低遅延時間、高スループットを損なわな い経路制御が行えることである。シミュレーションによって評価した特急ルータのの 性能は、これまでに発表された固定経路選択方式のルータより優れており、また他の 適応経路制御方式のルータに比べても、同程度あるいはそれを越えていることが確か められた。 第2は経路長制限方式のマルチキャスト通信の提案である。マルチキャスト通信は 多くの並列処理問題において速度向上に寄与する通信方式である。そこでワームホー ル通信方式において問題となるマルチキャスト通信におけるデッドロックの問題につ いて研究した。そしてこの問題を解決する方法として経路長制限方式のマルチキャス ト通信を提案し、この方式による通信性能をシミュレーションによって評価し、ユニ キャスト方式やマルチパス方式によるマルチキャスト通信の性能と比較した。その結 果、提案する経路長制限方式のマルチキャスト通信は、パリヤ同期のためのクラスタ へのマルチキャスト通信や、最近傍ノードへのマルチキャストや全ノードへの放送の 場合に、特に優れた解決法となることを明らかにした

    Recent advances in petri nets and concurrency

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    CEUR Workshop Proceeding

    Towards predictive runtime modelling of Kubernetes microservices

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    Kubernetes is one of the major container management platforms utilised by Cloud Service Providers offering to host applications and services. As cloud based services become more prevalent, platform providers are faced with an increasingly complex problem of trying to meet contracted performance levels. Providers must strike a balance between management of resource allocations and contractual obligations to ensure that their service is profitable, while offering competitive pricing rates for contracts. This research explores performance modelling of microservice application tenants within the Kubernetes container management platform. We present a self-adaptive architecture to achieve modelling at runtime. We establish the potential for automated classification of cloud systems, and utilise a hybridised modelling approach to verify system properties and evaluate performance. We achieve this through the modelling of components as Extended Finite State Machines in WATERS, from which we automate the generating of performance models using the PEPA syntax

    Programming and parallelising applications for distributed infrastructures

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    The last decade has witnessed unprecedented changes in parallel and distributed infrastructures. Due to the diminished gains in processor performance from increasing clock frequency, manufacturers have moved from uniprocessor architectures to multicores; as a result, clusters of computers have incorporated such new CPU designs. Furthermore, the ever-growing need of scienti c applications for computing and storage capabilities has motivated the appearance of grids: geographically-distributed, multi-domain infrastructures based on sharing of resources to accomplish large and complex tasks. More recently, clouds have emerged by combining virtualisation technologies, service-orientation and business models to deliver IT resources on demand over the Internet. The size and complexity of these new infrastructures poses a challenge for programmers to exploit them. On the one hand, some of the di culties are inherent to concurrent and distributed programming themselves, e.g. dealing with thread creation and synchronisation, messaging, data partitioning and transfer, etc. On the other hand, other issues are related to the singularities of each scenario, like the heterogeneity of Grid middleware and resources or the risk of vendor lock-in when writing an application for a particular Cloud provider. In the face of such a challenge, programming productivity - understood as a tradeo between programmability and performance - has become crucial for software developers. There is a strong need for high-productivity programming models and languages, which should provide simple means for writing parallel and distributed applications that can run on current infrastructures without sacri cing performance. In that sense, this thesis contributes with Java StarSs, a programming model and runtime system for developing and parallelising Java applications on distributed infrastructures. The model has two key features: first, the user programs in a fully-sequential standard-Java fashion - no parallel construct, API call or pragma must be included in the application code; second, it is completely infrastructure-unaware, i.e. programs do not contain any details about deployment or resource management, so that the same application can run in di erent infrastructures with no changes. The only requirement for the user is to select the application tasks, which are the model's unit of parallelism. Tasks can be either regular Java methods or web service operations, and they can handle any data type supported by the Java language, namely les, objects, arrays and primitives. For the sake of simplicity of the model, Java StarSs shifts the burden of parallelisation from the programmer to the runtime system. The runtime is responsible from modifying the original application to make it create asynchronous tasks and synchronise data accesses from the main program. Moreover, the implicit inter-task concurrency is automatically found as the application executes, thanks to a data dependency detection mechanism that integrates all the Java data types. This thesis provides a fairly comprehensive evaluation of Java StarSs on three di erent distributed scenarios: Grid, Cluster and Cloud. For each of them, a runtime system was designed and implemented to exploit their particular characteristics as well as to address their issues, while keeping the infrastructure unawareness of the programming model. The evaluation compares Java StarSs against state-of-the-art solutions, both in terms of programmability and performance, and demonstrates how the model can bring remarkable productivity to programmers of parallel distributed applications

    Proceedings of the 22nd Conference on Formal Methods in Computer-Aided Design – FMCAD 2022

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    The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing
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