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检索条件"任意字段=International Symposium on Computing in Object Oriented Parallel Environment"

共 1034 条记录，以下是11-20 订阅

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An Enhanced Finite Element Thermal Solver with Large-scale parallel computing Capability

An Enhanced Finite Element Thermal Solver with Large-scale P...

引用

international Applied Computational Electromagnetics Society symposium (ACES)

作者： Xiaotian Li Yifan Liu Gaofeng Wang Zhejiang Provincial Key Lab of Large-Scale Integrated Circuits Design School of Electronics and Information Hangzhou Dianzi University Hangzhou China

MOOSE, an object-oriented parallel computing framework, has been universally utilized in developing numerical solver. In this work, a finite element method solver with large-scale parallel computing capability is developed based on the MOOSE framework for high-efficient and scalable thermal simulations. The performance of the developed numerical solver is evaluated through comparing the simulation results of a simplified AMD microprocessor with those obtained by the commercial software COMSOL. High consistence is achieved between the two groups of data, and the simulation time is greatly reduced through utilizing the inhouse simulator.

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Low latency PBFT parallel consensus for IoT blockchain platform

Low latency PBFT parallel consensus for IoT blockchain platf...

引用

international symposium on object-oriented Real-Time Distributed computing

作者： Rabeb Ben Othmen Wassim Abbessi Sofiane Ouni Wafa Badreddine Gilles Dequen CRISTAL Lab RAMSIS Team (ENSI) University of Manouba Manouba Tunisia Laboratoire Modelisation Information Systemes (MIS) Université de Picardie Jules Verne Amiens France

ISBN: (数字)9798350371284

ISBN: (纸本)9798350371291

With the success of blockchains for providing a high security platform for distributed systems, new challenges are presented in relation with the deployment of this technology for IoT applications with time constraints. In this paper, we present a new lightweight blockchain platform that is scalable to hold a large number of transactions and with acceptable latency times. We have designed a new rapid consensus algorithm that improves PBFT to apply it in a random cluster with a small number of Miners. This will enable multiple consensus on different clusters to be executed in parallel to reduce the complexity of PBFT, have acceptable latency and increase the scalability. The evaluations carried out on our proposal by comparing it with other pipeline PBFT improvement approaches, show that our approach has better latency that is still accessible even with a high load of transactions.

关键词： Scalability Pipelines Real-time systems Blockchains Proposals Internet of Things Security

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The HiTar-23 Dataset Construction and Validation For Securing Industrial Internet of Things environment

The HiTar-23 Dataset Construction and Validation For Securin...

引用

international symposium on object-oriented Real-Time Distributed computing

作者： Tarak Dhaouadi Hichem Mrabet Abderrazek Jemai EPT SERCOM Laboratory Tunisia Polytechnic School Carthage University Tunis Tunisia FST SERCOM Laboratory Tunisia Polytechnic School Carthage University Tunis Tunisia INSAT SERCOM Laboratory Tunisia Polytechnic School Carthage University Tunis Tunisia

ISBN: (数字)9798350371284

ISBN: (纸本)9798350371291

The increasing vulnerability of Industrial Internet of Things (IIoT) systems to cyber-attacks necessitates the development of dedicated datasets for robust intelligent security measures. This paper introduces the HiTar-23 dataset, designed to expedite the detection of cyber-attacks in industrial environments. The latter outlines the detailed steps involved in creating the HiTar-23 dataset, emphasizing meticulous methodologies for construction and validation threw the application of supervised machine learning (ML) techniques, specifically leveraging the WEKA 3.9.6 tool, to assess detection capabilities within a simulated industrial framework facilitated by the Arezzo environment. The holistic approach underscores careful dataset construction and sophisticated evaluation methods, providing insights to strengthen IIoT system security.

关键词： Machine learning Real-time systems Internet Security Cyberattack Industrial Internet of Things

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Dynamic Resource Management for Cloud-native Bulk Synchronous parallel Applications

Dynamic Resource Management for Cloud-native Bulk Synchronou...

引用

international symposium on object-oriented Real-Time Distributed computing

作者： Evan Wang Yogesh Barve Aniruddha Gokhale Hongyang Sun Dept of CS Vanderbilt University Nashville TN USA Dept of EECS University of Kansas Lawrence KS USA

Many traditional high-performance computing applications including those that follow the Bulk Synchronous parallel (BSP) communication paradigm are increasingly being deployed in cloud-native virtualized and multi-tenant container clusters. However, such a shared, virtualized platform limits the degree of control that BSP applications can have in effectively allocating resources. This can adversely impact their performance, particularly when stragglers manifest in individual BSP supersteps. Existing BSP resource management solutions assume the same execution time for individual tasks at every superstep, which is not always the case. To address these limitations, we present a dynamic resource management middleware for cloud-native BSP applications comprising a heuristics algorithm that determines effective resource configurations across multiple supersteps while considering dynamic workloads per superstep, and trading off performance improvements with reconfiguration costs. Moreover, we design dynamic programming and reinforcement learning approaches that can be used as pluggable strategies to determine whether and when to enforce a reconfiguration. Empirical evaluations of our solution show between 10% and 25% improvement in performance over a baseline static approach even in the presence of reconfiguration penalty.

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Hierarchical Heterogeneous Cluster Systems for Scalable Distributed Deep Learning

Hierarchical Heterogeneous Cluster Systems for Scalable Dist...

引用

international symposium on object-oriented Real-Time Distributed computing

作者： Yibo Wang Tongsheng Geng Ericson Silva Jean-Luc Gaudiot Electrical Engineering and Computer Science University of California Irvine Irvine USA Electrical Engineering and Computer Science Pontifical Catholic University of Minas Gerais Minas Gerais Brazil

ISBN: (数字)9798350371284

ISBN: (纸本)9798350371291

Distributed deep learning framework tools should aim at high efficiency of training and inference of distributed exascale deep learning algorithms. There are three major challenges in this endeavor: scalability, adaptivity and efficiency. Any future framework will need to be adaptively utilized for a variety of heterogeneous hardware and network environments and will thus be required to be capable of scaling from single compute node up to large clusters. Further, it should be efficiently integrated into popular frameworks such as TensorFlow, PyTorch, etc. This paper proposes a dynamically hybrid (hierarchy) distribution structure for distributed deep learning, taking advantage of flexible synchronization on both centralized and decentralized architectures, implementing multi-level fine-grain parallelism on distributed platforms. It is scalable as the number of compute nodes increases, and can also adapt to various compute abilities, memory structures and communication costs.

关键词： Deep learning Training Costs Scalability parallel processing Real-time systems Inference algorithms

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Container System and Communication Reactivity in a Real-Time Embedded environment

Container System and Communication Reactivity in a Real-Time...

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international symposium on object-oriented Real-Time Distributed computing

作者： Wilhelm Rosinski Lukas Stahlbock Falk Langer Department of Engineering University of Applied Sciences Mittweida Germany IAV GmbH Ingenieurgesellschaft Auto und Verkehr Berlin Germany

In the field of embedded systems, containers are often understood as an additional burden and would also affect their reactivity. With respect to this assumption, we provide measurement results that strongly support the use of containers for real-time applications. This work examines the use of docker containers in systems, that must work under hard deadlines, in terms of their reactivity related to timer events and external signals. For this purpose, measurements for time-critical handling of interrupts and events are performed directly on an embedded platform, which made it necessary to develop a corresponding novel measuring method. Finally, we were able to determine that the same requirements for the reactivity of an embedded system could be met in a docker container if they could also be ensured for applications native on the host system.

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ArkFS: A Distributed File System on object Storage for Archiving Data in HPC environment

ArkFS: A Distributed File System on Object Storage for Archi...

引用

international symposium on parallel and Distributed Processing (IPDPS)

作者： Kyu-Jin Cho Injae Kang Jin-Soo Kim Seoul National University Seoul South Korea

As the burst buffer is being widely deployed in the HPC (High-Performance computing) systems, the distributed file system layer is taking the role of campaign storage where scalability and cost-effectiveness are of paramount importance. However, the centralized metadata management in the distributed file system layer poses a scalability challenge. The object storage system has emerged as an alternative thanks to its simplified interface and scale-out architecture. Despite this, the HPC communities are used to working with the POSIX interface to organize their files into a global directory hierarchy and control access through access control *** this paper, we present ArkFS, a near-POSIX compliant and scalable distributed file system implemented on top of the object storage system. ArkFS achieves high scalability without any centralized metadata servers. Instead, ArkFS lets each client manage a portion of the file system metadata on a per-directory basis. ArkFS supports any distributed object storage system such as Ceph RADOS or S3-compatible system with an appropriate API translation module. Our experimental results indicate that ArkFS shows significant performance improvement under metadata-intensive workloads while showing near-linear scalability. We also demonstrate that ArkFS is suitable for handling the bursty I/O traffic coming from the burst buffer layer to archive cold data.

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Digital Twin Enabled Q-Learning for Flying Base Station Placement: Impact of Varying environment and Model Errors

Digital Twin Enabled Q-Learning for Flying Base Station Plac...

引用

international symposium on object-oriented Real-Time Distributed computing

作者： Terry N. Guo Center for Manufacturing Research Tennessee Technological University Cookeville TN

This paper considers a use case of flying base station placement enabled by digital twin (DT), and demonstrates how DT can help reduce the impact of a non-stationary environment on reinforcement learning (RL). RL is able to learn the optimal policy via interacting with a specific environment. However, it has been observed that RL is very sensitive to environment change, mainly because the environment variation disturbs RL training/learning. A possible approach is to execute the RL process in the DT using snapshots of the environment (parameters), and update the parameters at a proper frequency. The DT-RL bundled approach takes advantage of computing resources in the DT, speeds up the process and saves battery energy of the flying base station, and more importantly, mitigates the nonstationary impact on RL. Specifically, the use case is about quickly connecting mobile users with an aerial bass station. The base station is autonomously and optimally placed according to a predefined criterion to connect scattered slow-movement users. Q-learning, a common type of RL, is employed as a solution to the optimization of base station placement. Tailored for this application, a two-stage base station placement algorithm is proposed and evaluated. For the configuration considered in this paper, numerical results suggest that 1) the Q-learning algorithm run solely in the physical space does not work due to intolerable time consuming and optimization divergence, and 2) the proposed scheme can catch up with random slow movement of mobile users, and tolerate certain measurement and model errors. With necessary modification and extension, the proposed framework could be applied to other DT-assisted cyber-physical systems.

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Characterizing Massively parallel Polymorphism

Characterizing Massively Parallel Polymorphism

引用

IEEE international symposium on Performance Analysis of Systems and Software (ISPASS)

作者： Zhang, Mengchi Alawneh, Ahmad Rogers, Timothy G. Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9781728186436

GPU computing has matured to include advanced C++ programming features. As a result, complex applications can potentially benefit from the continued performance improvements made to contemporary GPUs with each new generation. Tighter integration between the CPU and GPU, including a shared virtual memory space, increases the usability of productive programming paradigms traditionally reserved for CPUs, like object-oriented programming. Programmers are no longer forced to restructure both their code and data for GPU acceleration. However, the implementation and performance implications of advanced C++ on massively multithreaded accelerators have not been well studied. In this paper, we study the effects of runtime polymorphism on GPUs. We first detail the implementation of virtual function calls in contemporary GPUs using microbenchmarking. We then propose Parapoly, the first open-source polymorphic GPU benchmark suite. Using Parapoly, we further characterize the overhead caused by executing dynamic dispatch on GPUs using massively scaled CPU workloads. Our characterization demonstrates that the optimization space for runtime polymorphism on GPUs is fundamentally different than for CPUs. Where indirect branch prediction and ILP extraction strategies have dominated the work on CPU polymorphism, GPUs are fundamentally limited by excessive memory system contention caused by virtual function lookup and register spilling. Using the results of our study, we enumerate several pitfalls when writing polymorphic code for GPUs and suggest several new areas of system and architecture research that can help alleviate overhead.

关键词： GPU object oriented Programming Polymorphism

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TransforMR: Pose-Aware object Substitution for Composing Alternate Mixed Realities 20

TransforMR: Pose-Aware Object Substitution for Composing Alt...

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20th IEEE international symposium on Mixed and Augmented Reality (ISMAR)

作者： Kari, Mohamed Grosse-Puppendahl, Tobias Coelho, Luis Falconeri Fender, Andreas Rene Bethge, David Schutte, Reinhard Holz, Christian Porsche AG Stuttgart Germany Univ Duisburg Essen Duisburg Germany Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland

ISBN: (纸本)9781665401586

Despite the advances in machine perception, semantic scene understanding is still a limiting factor in mixed reality scene composition. In this paper, we present TransforMR, a video see-through mixed reality system for mobile devices that performs 3D-pose-aware object substitution to create meaningful mixed reality scenes. In real-time and for previously unseen and unprepared real-world environments, TransforMR composes mixed reality scenes so that virtual objects assume behavioral and environment-contextual properties of replaced real-world objects. This yields meaningful, coherent, and human-interpretable scenes, not yet demonstrated by today's augmentation techniques. TransforMR creates these experiences through our novel pose-aware object substitution method building on different 3D object pose estimators, instance segmentation, video inpainting, and pose-aware object rendering. TransforMR is designed for use in the real-world, supporting the substitution of humans and vehicles in everyday scenes, and runs on mobile devices using just their monocular RGB camera feed as input. We evaluated TransforMR with eight participants in an uncontrolled city environment employing different transformation themes. Applications of TransforMR include real-time character animation analogous to motion capturing in professional film making, however without the need for preparation of either the scene or the actor, as well as narrative-driven experiences that allow users to explore fictional parallel universes in mixed reality. We make all of our source code and assets available(1).

关键词： Human-centered computing Mixed / augmented reality

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