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PCGraph: Accelerating GNN Inference on Large Graphs via Partition Caching

PCGraph: Accelerating GNN Inference on Large Graphs via Part...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Lizhi Zhang Zhiquan Lai Yu Tang Dongsheng Li Feng Liu Xiaochun Luo National Laboratory for Parallel and Distributed Processing (PDL) Computer College National University of Defence Technology Changsha China PLA News Media Center Beijing China

Graph neural networks (GNNs) have been emerging as powerful learning tools for unstructured data and successfully applied to many graph-based application domains. Sampling-based GNN inference is commonly adopted in existing graph learning frameworks to handle large-scale graphs. However, this approach is restricted by the problems of redundant vertex embedding computation in GPU and inefficient loading of vertex features from CPU to GPU. In this paper, we propose PCGraph, a system that supports adaptive GNN inference and feature partition caching. PCGraph significantly reduces the vertex embedding computation time by adaptive GNN inference technology, which selects the optimal inference algorithm and minimizes vertex embedding computation. PCGraph also reduces the redundant data transfer between the CPU and GPU by partition the target vertices and caching their corresponding partitions in turn. We evaluate PCGraph against two state-of-the-art industrial GNN frameworks, i.e., PyG and DGL, on a diverse array of benchmarks. Experimental results show that PCGraph reduces up to 99% vertex embedding computation and 98.5% data loading time, and achieves up to 360× performance speedup over the state-of-the-art baselines.

关键词： Adaptive systems Loading Graphics processing units Benchmark testing Data transfer Inference algorithms Graph neural networks

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A chronological history-based execution time estimation model for embarrassingly parallel applications on grids

A chronological history-based execution time estimation mode...

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3rd International Symposium on parallel and distributed processing and Applications, ISPA 2005

作者： Yang, Chao-Tung Shih, Po-Chi Lin, Cheng-Fang Hsu, Ching-Hsien Li, Kuan-Ching High Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan

ISBN: (纸本)3540297693

In order to identify and schedule jobs that are suitable for determined resources, an execution time estimation model is required. In this paper, it is described a Chronological history-based execution time estimation model to predict current execution time, according to the previous execution results. We built a heterogeneous computational Grid environment using Globus Toolkit, and our research is focused in Grid computing environments and to execute parallel jobs on multiple resources by measuring its accuracy. The experimental results shown that our model can accurately predict the execution time of embarrassingly parallel applications. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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Performance analysis of applying replica selection technology for Data Grid environments

Performance analysis of applying replica selection technolog...

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8th International Conference on parallel Computing Technologies, PaCT 2005

作者： Yang, Chao-Tung Chen, Chun-Hsiang Li, Kuan-Ching Hsu, Ching-Hsien High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan

The Data Grid enables the sharing, selection, and connection of a wide variety of geographically distributed computational and storage resources for solving large-scale data intensive scientific applications. Such technology efficiently manage and transfer terabytes or even petabytes of data for data-intensive, high-performance computing applications in wide-area, distributed computing environments. Replica selection process allows an application to choose a replica from replica catalog, based on its performance and data access features. In this paper, we build a Grid environment based on three existing PC Cluster environments and perform performance analysis of data transfers using GridFTP protocol over these systems. In addition, based on experimental results, it is proposed a cost model to pick the best replica, in real and dynamic network situations. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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Visuel: A novel performance monitoring and analysis toolkit for cluster and grid environments

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6th International Conference on Algorithms and Architectures for parallel processing, ICA3PP

作者： Li, Kuan-Ching Cheng, Hsiang-Yao Yang, Chao-Tung Hsu, Ching-Hsien Wang, Hsiao-Hsi Hsu, Chia-Wen Hung, Sheng-Shiang Chang, Chia-Fu Liu, Chun-Chieh Pan, Yu-Hwa Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan High Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan

ISBN: (纸本)3540292357

The computing power provided by high performance low-cost PC-based Cluster and Grid platforms are attractive, and they are equal or superior to supercomputers and mainframes widely available. In this research paper, we present the design rationale and implementation of Visuel, a toolkit for performance measurement and analysis of MPI parallel programs and real time resources monitoring in cluster and grid computing environments. The proposed toolkit is web-based interface to show performance activities of all computing nodes involved in the execution of a MPI parallel program, such as CPU and memory usage levels of each computing node, and monitors all computing nodes of a computing platform by displaying real time performance data. In addition, this toolkit is able to display comparative performance data charts of multiple executions of MPI parallel application under investigation, which facilitates the "what-if" analysis. The usage of this toolkit shows that it outperforms in easing the process of investigation of parallel applications. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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A Heterogeneous Processor Design for CNN-Based AI Applications on IoT Devices 8

A Heterogeneous Processor Design for CNN-Based AI Applicatio...

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8th International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2019

作者： Liu, Zhiqiang Jiang, Jingfei Lei, Guoqing Chen, Kai Qin, Buyue Zhao, Xiaoqiang Artificial Intelligence Research Center National Innovation Institute of Defense Technology Beijing China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China College of System Engineering National University of Defense Technology Changsha China

This paper proposes a heterogeneous processor design for CNN-based AI applications on IoT devices. The heterogeneous processor contains an embedded RISC-V CPU that works as a general processor and an efficient CNN-accelerator that supports a variety of CNN models with a list of macro instructions. For demonstration, we implement a prototype on an FPGA platform with the RISC-V CPU working under 20 MHz and the CNN accelerator working under 100 MHz. As a case study, we run a CNN-based face detection and recognition application on this prototype. The prototype can process one image in 0.72 seconds and an ASIC implementation working under 400 MHz can process one image in less than 0.15 seconds by estimation, which can satisfy the needs for many IoT scenarios such as access control systems and check-in systems. © 2020 The Authors. Published by Elsevier B.V.

关键词： Internet of things

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A Dynamic Replication Mechanism to Reduce Response-Time of I/O Operations in High Performance Computing Clusters

A Dynamic Replication Mechanism to Reduce Response-Time of I...

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IEEE International Conference on Social Computing (SocialCom)

作者： Ehsan Mousavi Khaneghah Seyedeh Leili Mirtaheri Lucio Grandinetti Amir Saman Memaripour Mohsen Sharifi Center of High Performance Computing for Parallel and Distributed Processing University of Calabria Rende Italy School of Computer Engineering Iran University of Science and Technology Tehran Iran

ISBN: (纸本)9781479915194

Extraordinary large datasets of high performance computing applications require improvement in existing storage and retrieval mechanisms. Moreover, enlargement of the gap between data processing and I/O operations' throughput will bound the system performance to storage and retrieval operations and remarkably reduce the overall performance of high performance computing clusters. File replication is a way to improve the performance of I/O operations and increase network utilization by storing several copies of every file. Furthermore, this will lead to a more reliable and fault-tolerant storage cluster. In order to improve the response time of I/O operations, we have proposed a mechanism that estimates the required number of replicas for each file based on its popularity. Besides that, the remaining space of storage cluster is considered in the evaluation of replication factors and the number of replicas is adapted to the storage state. We have implemented the proposed mechanism using HDFS and evaluated it using MapReduce framework. Evaluation results prove its capability to improve the response time of read operations and increase network utilization. Consequently, this mechanism reduces the overall response time of read operations by considering files' popularity in replication process and adapts the replication factor to the cluster state.

关键词： Time factors High performance computing Bandwidth Reliability Throughput System performance History

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Controllable Template Generation for Document-level Event Extraction

Controllable Template Generation for Document-level Event Ex...

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Neural Networks, Information and Communication Engineering (NNICE), International Conference on

作者： Quntian Fang Feng Liu Zhen Huang Zhenliang Guo Changjian Wang Dongsheng Li Minghao Hu National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China Information Research Center Academy of Military Sciences Beijing China

Document-level event extraction task has achieved significant progress based on template generation methods. However, there is no reasonable regulation and restriction in the existing template-based generation methods, which results in the uncontrollability of the generation results. In some scenarios, model generates entities that do not belong to the input text, or generate template content repeatedly. It is determined by the nature of the extraction task and the generation task. To this end, we propose a controllable template generation event extraction model. According to the characteristics of template generation and event extraction tasks, the model devises copy mechanism, inhibition mechanism and rejection mechanism under the appropriately constructed template. Our model achieves state-of-the-art result on MUC-4 dataset, and finally through experimental analysis, it demonstrates the effectiveness of each mechanism we proposed.

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A mathematical model for empowerment of Beowulf clusters for exascale computing

A mathematical model for empowerment of Beowulf clusters for...

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Seyedeh Leili Mirtaheri Ehsan Mousavi Khaneghah Lucio Grandinetti Mohsen Sharifi Center of High Performance Computing for Parallel and Distributed Processing University of Calabria Rende Italy School of Computer Engineering Iran University of Science and Technology Tehran Iran

High-performance computing (HPC) clusters are currently faced with two major challenges - namely, the dynamic nature of new generation of applications and the heterogeneity of platforms - if they are going to be useful for exascale computing. Processes running these applications may well demand unpredictable requirements and changes to system configuration and capabilities at runtime, thereby requiring fast system response without sacrificing the transparency and integrity of the reconfigured empowered system that is running on a heterogeneous platform. While a challenge in and of itself, platform heterogeneity is both useful and instrumental in the handling of unpredictable requests. The realization of such a dynamically reconfigurable and heterogeneous HPC cluster system for exascale computing requires a model to guide running processes to determine if they need empowerment of the current cluster, and if yes, by how much. To show the feasibility of empowerment of traditional HPC clusters for exascale computing, we have selected Beowulf as a noble candidate cluster and present a mathematical model for the empowerment of Beowulf clusters for exascale computing (EBEC). We have developed the model in line with Beowulf's cluster approach and by using vector space algebra. In contrast to traditional hardware-oriented approaches to improvise the performance of clusters, we use a software approach to the development of the proposed model by emphasizing processes, which act as the creators of the cluster and thus should decide on system (re)configuration, as the principal building blocks of the system. We have also adopted a new approach to heterogeneity by considering heterogeneity at different levels including hardware, system software, application software, and system functionality. In addition to support for heterogeneity and dynamic reconfiguration, the proposed model includes support for scalability that is crucial to exascale computing too.

关键词： Vectors Mathematical model Hardware Runtime Computers Computational modeling

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A Wallet-Size Cluster for H.264 Encoding

A Wallet-Size Cluster for H.264 Encoding

引用

International Conference on Information Technology and Applications, ICITA

作者： Liang-Teh Lee Chia-Ying Tseng Kang-Yuan Liu Kuan-Ching Li Department of Computer Science and Engineering Tatung University Taipei Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung Taiwan

ISBN: (纸本)0769523161

A scalable wallet-size cluster computing system has been proposed to obtain low cost, low power consumption and small sized digital home processing center. In this paper, we apply the wallet-size cluster for H.264 encoding to accelerate the H.264 video processing. We analyze the encoder scheme of the H.264, and perform the H.264 encoding in parallel through the nodes of the cluster. The experimental results show that an efficient real time video processing for H.264 can be achieved

关键词： Encoding Video coding Videoconference Costs Energy consumption Acceleration Bit rate IEC standards ISO standards Streaming media

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Breaking up is hard to do - Dispersion: from design to implementation

Breaking up is hard to do - Dispersion: from design to imple...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： M. Isaacs M. Anderson S. Ashworth J. Blackburn-Lynch B. Bynum J. Pearce C. Pemberton Department of Mathematics and Computer Science Berea College Mobile Robotics and Parallel Processing Laboratory Berea KY USA Center for Distributed Robotics University of Minnesota Minneapolis MN USA

This article assesses the performance of a virtual pheromone-based sectored dispersion algorithm which is implemented on a low-cost miniature mobile robotic platform using sonar sensing. The approach is a distributed one and the robotic platform and sensor array are sufficiently inexpensive that they can be employed in undergraduate research and/or for coursework in a small college environment

关键词： Educational robots Robot sensing systems Mobile robots Sensor arrays Service robots parallel robots Hardware Mobile computing Educational institutions Dispersion

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