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A Multi-Layered Scheme for distributed simulations on the Cloud Environment

IEEE TRANSACTIONS ON CLOUD COMPUTING 2019年第1期7卷 5-18页

作者： Guan, Shichao De Grande, Robson Eduardo Boukerche, Azzedine Univ Ottawa PARADISE Res Lab Sch Informat Technol & Engn Ottawa ON Canada

In order to improve simulation performance and to integrate simulation resources among geographically distributed locations, the concept of distributed simulation is proposed. Several types of distributed simulation standards, such as DIS and HLA, are established to formalize simulations and achieve reusability and interoperability of simulation components. To implement these distributed simulation standards and to manage the underlying system of distributed simulation applications, we employ grid computing and cloud computing technologies. These tackle the details of operation, configuration, and maintenance of simulation platforms in which simulation applications are deployed. However, for modelers who may not be familiar with the management of distributed systems, it is challenging to make a simulation-run-ready environment among different types of computing resources and network environments. In this article, a new multi-layered cloud-based scheme is proposed for enabling modeling and simulation based on different distributed simulation standards. This scheme is designed to ease the management of underlying resources and to achieve rapid elasticity that can provide unlimited computing capability to end users;it considers energy consumption, security, multi-user availability, scalability, and deployment issues. A mechanism for handling diverse network environments is described;by adopting it, idle public resources can be easily configured as additional computing capabilities for the local resource pool. A fast deployment model is built to relieve the migration and installation process of this platform. An energy-saving strategy is utilized to reduce the consumption of computing resources. Security components are implemented to protect sensitive information and block malicious attacks in the cloud. In the experiments, the proposed scheme is compared with its corresponding grid computing platform;the cloud computing platform achieves similar performance, but incorp

关键词： Cloud computing DIS HLA availability energy consumption usability elasticity distributed simulations

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Enhancing Load Balancing Efficiency Based on Migration Delay for Large-Scale distributed simulations 2015

Enhancing Load Balancing Efficiency Based on Migration Delay...

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19th IEEE/ACM International Symposium on distributed Simulation and Real Time Applications (DS-RT)

作者： Alghamdi, Turki G. De Grande, Robson Eduardo Boukerche, Azzedine Univ Ottawa EECS PARADISE Res Lab Ottawa ON K1N 6N5 Canada

ISBN: (纸本)9781467378222

Load management is an essential and important factor for distributed simulations running on shared resources due to load imbalances that can caused considerable performance loss. This feature is essential for High Level Architecture (HLA)-based simulations since the HLA framework does not present the ability to manage resources or help detect load imbalances that could directly cause decrease of performance. A migration-aware dynamic balancing system has been designed for HLA simulations to offer an efficient load-balancing scheme that works in large-scale environments. This system presents some limitations on estimating costs and benefits, so we propose an enhancement to this existing load balancing system, which improves the accuracy of generating federate migrations. The proposed scheme aims to precisely estimate the migration delay and gain by analyzing the load on shared resources, preventing the issuing of migrations costly towards simulation execution time. Upon a performance analysis, the proposed decision-making analysis scheme has shown an improvement on decreasing the number of migrations and consequently decreasing execution time.

关键词： distributed simulations High Level Architecture Load Balancing Performance

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StreaMD: the toolkit for high-throughput molecular dynamics simulations

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JOURNAL OF CHEMINFORMATICS 2024年第1期16卷 123页

作者： Ivanova, Aleksandra Mokshyna, Olena Polishchuk, Pavel Palacky Univ Inst Mol & Translat Med Fac Med & Dent Hnevotinska 5 Olomouc 77900 Czech Republic Czech Acad Sci Inst Organ Chem & Biochem Flemingovo Namesti 542-2 Prague 6 Czech Republic

Molecular dynamics simulations serve as a prevalent approach for investigating the dynamic behaviour of proteins and protein-ligand complexes. Due to its versatility and speed, GROMACS stands out as a commonly utilized software platform for executing molecular dynamics simulations. However, its effective utilization requires substantial expertise in configuring, executing, and interpreting molecular dynamics trajectories. Existing automation tools are constrained in their capability to conduct simulations for large sets of compounds with minimal user intervention, or in their ability to distribute simulations across multiple servers. To address these challenges, we developed a Python-based tool that streamlines all phases of molecular dynamics simulations, encompassing preparation, execution, and analysis. This tool minimizes the required knowledge for users engaging in molecular dynamics simulations and can efficiently operate across multiple servers within a network or a cluster. Notably, the tool not only automates trajectory simulation but also facilitates the computation of free binding energies for protein-ligand complexes and generates interaction fingerprints across the trajectory. Our study demonstrated the applicability of this tool on several benchmark datasets. Additionally, we provided recommendations for end-users to effectively utilize the *** contributionThe developed tool, StreaMD, is applicable to different systems (proteins, ligands and their complexes including co-factors) and requires a little user knowledge to setup and run molecular dynamics simulations. Other features of StreaMD are seamless integration with calculation of MM-GBSA/PBSA binding free energies and protein-ligand interaction fingerprints, and running of simulations within distributed environments. All these will facilitate routine and massive molecular dynamics simulations.

关键词： Molecular dynamics High-throughput molecular dynamics distributed simulations GROMACS

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Modal Analysis of System Partitioning in distributed Real-Time simulations 45

Modal Analysis of System Partitioning in Distributed Real-Ti...

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45th Annual Conference of the IEEE Industrial Electronics Society (IECON)

作者： Bogdanovic, Milica Stevic, Marija Monti, Antonello Rhein Westfal TH Aachen E ON Energy Res Ctr Inst Automat Complex Power Syst Aachen Germany

ISBN: (纸本)9781728148786

Selection of a suitable decoupling point for system partitioning represents one of the challenges in distributed real-time simulation (DRTS) and (distributed) power hardware in the loop (D-PHIL) setups. In case of DRTS, the decoupling point represents the point where system is partitioned between two digital real-time simulators. In D-PHIL setups, the decoupling point is a point where a device under test is connected (coupled) to the rest of the simulated system. This work proposes a methodology based on the analysis of eigenvalues and participation matrix of the monolithic continuous model of the system, which refers to naturally coupled system, to determine the suitable decoupling point for system partitioning with respect to the simulation fidelity. Sampling period and delay between subsystems are considered in the analysis, and decoupling points analysis is influenced by them. The methodology is validated based on time-domain simulations.

关键词： distributed simulations real-time simulations participation factors system partitioning modal analysis eigenvalue analysis

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A Digital Framework for Locally and Geographically distributed Simulation of Power Grids

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ENERGY TECHNOLOGY 2023年第3期11卷 2201186-2201186页

作者： Kyesswa, Michael Weber, Moritz Wiegel, Friedrich Wachter, Jan Waczowicz, Simon Kuehnapfel, Uwe Hagenmeyer, Veit Karlsruhe Inst Technol Inst Automat & Appl Informat D-76131 Karlsruhe Germany

The power system sector is expected to contribute significantly to addressing the global climate change challenge through solutions such as the integration of distributed energy resources with low carbon emissions and demand side management as part of the flexibility solutions. However, the transformations in the power grids necessitate additional solutions to ensure the stable and reliable operation of the grids. Such novel solutions require detailed studies in laboratories before implementation in real grids. Power systems simulations combined with power-hardware-in-the-loop (P-HIL) experiments provide a reliable form of conducting such studies. The current article introduces the Energy Grids simulations and Analysis Laboratory of the Energy Lab 2.0 as a digital framework enabling local and distributed analysis of power grids. The outstanding feature of the laboratory is its ability to connect the simulation of validated networks directly to the real hardware of the Energy Lab 2.0 in form of P-HIL setups and virtually to distant energy research infrastructures, thus enabling geographically distributed experimental studies. Results of the benchmark case studies show that the communication methods available in the simulation laboratory can be used to accurately set up locally and geographically distributed simulations, as well as for reliably interfacing physical hardware components to real-time simulations.

关键词： distributed simulations power grids power-hardware-in-the-loop real-time simulations

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Stability-Based Generalization Analysis of distributed Learning Algorithms for Big Data

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2020年第3期31卷 801-812页

作者： Wu, Xinxing Zhang, Junping Wang, Fei-Yue Shanghai Tech Inst Elect & Informat Dept Commun & Informat Engn Shanghai 201411 Peoples R China Fudan Univ Sch Comp Sci Shanghai Key Lab Intelligent Informat Proc Shanghai 200433 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Macau 999078 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

As one of the efficient approaches to deal with big data, divide-and-conquer distributed algorithms, such as the distributed kernel regression, bootstrap, structured perception training algorithms, and so on, are proposed and broadly used in learning systems. Some learning theories have been built to analyze the feasibility, approximation, and convergence bounds of these distributed learning algorithms. However, less work has been studied on the stability of these distributed learning algorithms. In this paper, we discuss the generalization bounds of distributed learning algorithms from the view of algorithmic stability. First, we introduce a definition of uniform distributed stability for distributed algorithms and study the distributed algorithms' generalization risk bounds. Then, we analyze the stability properties and generalization risk bounds of a kind of regularization-based distributed algorithms. Two generalization distributed risks obtained show that the generalization distributed risk bounds for the difference between their generalization distributed and empirical distributed/leave-one-computer-out risks are closely related to the size of samples n and the amount of working computers m mathcal O(m/n(1/2)). Furthermore, the results in this paper indicate that, for a good generalization regularized distributed kernel algorithm, the regularization parameter lambda should be adjusted with the change of the term m/n(1/2). These theoretic discoveries provide the useful guidance when deploying the distributed algorithms on practical big data platforms. We explore our theoretic analyses through two simulation experiments. Finally, we discuss some problems about the sufficient amount of working computers, nonequivalence, and generalization for distributed learning. We show that the rules for the computation on one single computer may not always hold for distributed learning.

关键词： Big data distributed learning algorithms distributed simulations generalization

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Principles and Techniques for Performance Management and Validation of Cloud Hosted distributed Applications

Principles and Techniques for Performance Management and Val...

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学位级别：博士

Advances in distributed simulations and machine learning techniques have enabled a new class of workloads to migrate to cloud computing platforms to take advantage of their scalability and elastic properties. These applications are characterized by distributed computations that are hosted across heterogeneous cloud resources. It is in this context that multiple challenges manifest in terms of resource and performance management, monitoring and deployment, and accessibility. For example, cloud platforms may exhibit substantial performance variability for applications running in their multi-tenant environments caused due to interference among noisy neighbors, which can result in violations of application service level objectives (SLOs). Second, individual executing components of these distributed applications may exhibit variability in execution times, which can result in stragglers that can degrade the overall performance. Third, given the large resource configuration selections available in the cloud platforms and heterogeneous computations exhibited by tasks within the distributed application, determining the optimal set of resource configurations that can meet SLOs of these distributed application while minimizing operating costs becomes a complex problem. Fourth, application developers often do not possess the expertise needed in deploying and monitoring these large-scale distributed applications. Finally, validating the solutions that address these challenges itself is a hard problem as it requires setting up large-scale experimental setups. To address the plethora of challenges, this dissertation makes the following research contributions: First, it develops a systematic and low-cost methodology for interference-aware performance modeling and benchmarking. Second, it describes model-driven techniques to allow for easy configuration and deployment of monitoring infrastructure needed for benchmarking. Third, it presents a Co-simulation-as-a-Service (

关键词： distributed simulations co-simulations latency performance cloud edge measurement benchmarking model driven interference deployment distributed systems education

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distributed Co-Simulation of Complex Engineered Systems by Combining the High Level Architecture and Functional Mock-up Interface

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SIMULATION MODELLING PRACTICE AND THEORY 2019年 97卷 101967-000页

作者： Falcone, Alberto Garro, Alfredo Univ Calabria Dept Informat Modeling Elect & Syst Engn Via P Bucci 41C I-87036 Arcavacata Di Rende Italy

Modern Complex Engineered Systems (CES) are the result of the ever-growing advances in science and technology that involve new paradigms, architectures and functionalities derived from multiple domains. Due to the nature of CES, which are composed of many heterogeneous components often designed and manufactured by organizations belonging to different engineering domains, is difficult to handle their whole lifecycle through classical Modeling and Simulation (M&S) techniques. To manage this complexity, it is necessary the definition of more suitable techniques capable of addressing, in an integrated way, the issues of reusability, interoperability and distribution of CES simulation models. In this context, great benefits may come from the joint exploitation of distributed Simulation (DS) and Co-Simulation approaches. To concretely explore this opportunity, this article proposes a solution that relies on the integration of the Functional Mock-up Interface (FMI) and the IEEE 1516 - High Level Architecture (HLA) standard. To prove the feasibility and validity of the defined solution, a case study concerning a scenario in the context of the Simulation Exploration Experience (SEE) international project, led by NASA, is also presented.

关键词： Modeling methodologies High level architecture (HLA) Functional mock-up interface (FMI) distributed simulations

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Integrating HLA-Based distributed Simulation for Management Science and BPMN

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IFAC-PapersOnLine 2018年第11期51卷 655-660页

作者： Gorecki, Simon Bouanan, Youssef Zacharewicz, Gregory Ribault, Judicael Perry, Nicolas IMS lab. University of Bordeaux France Arts et métiers ParisTech ENSAM of Bordeaux France

Modeling and Simulation are becoming more and more complex, making their design very challenging. Modeling and Simulation of complex systems requires simultaneous consideration of several points of view and the study of these systems needs skills belonging to different scientific fields. In distributed Simulation domain, IEEE 1516-2010 - High Level Architecture (HLA) is one of the most used standard. However, it does not provide any official graphical language for defining distributed simulation behaviors. Business Process Model and Notation standard could be an interesting solution for defining HLA execution scenario. This paper present application experiment applied to solar power plant. Our proposition consists in restrict the HLA execution process in order to use one federate as Master, controlling the others as Slaves. This allows us to generate a component responsible for the simulation execution process with parsing a Business Process Model and Notation diagram. In this paper, we present an application of this concept. © 2018

关键词： Solar energy Interoperability Models Solar power plants Business process model distributed simulations High level architecture Notation Simulation

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Resource Contention Aware Execution of Multiprocessor Tasks on Heterogeneous Platforms 1

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23rd International Conference on Parallel and distributed Computing (Euro-Par)

作者： Dietze, Robert Hofmann, Michael Runger, Gudula Tech Univ Chemnitz Dept Comp Sci Chemnitz Germany

ISBN: (数字)9783319751788

ISBN: (纸本)9783319751788;9783319751771

In high performance computing (HPC), the tasks of complex applications have to be assigned to the compute nodes of heterogeneous HPC platforms in such a way that the total execution time is minimized. Common approaches, such as task scheduling methods, usually base their decisions on task runtimes that are predicted by cost models. A high accuracy and reliability of these models is crucial for achieving low execution times for all tasks. The individual runtimes of concurrently executed tasks are often affected by contention for hardware resources, such as communication networks, the main memory, or hard disks. However, existing cost models usually ignore the effects of resource contention, thus leading to large deviations between predicted and measured runtimes. In this article, we present a resource contention aware cost model for the execution of multiprocessor tasks on heterogeneous platforms. The integration of the proposed model into two task scheduling methods is described. The cost model is validated in isolation as well as within the utilized scheduling methods. Performance results with different benchmark tasks and with tasks of a complex simulation application are shown to demonstrate the performance improvements achieved by taking the effects of resource contention into account.

关键词： Resource contention Multiprocessor tasks Heterogeneous platforms Scheduling methods distributed simulations

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