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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

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The Method of Improving the Performance of Network Analysis Application for the Whole Power grid 4

The Method of Improving the Performance of Network Analysis ...

引用

4th international Symposium on Resource Exploration and Environmental Science, REES 2020

作者： He, Ming Lu, Yi Li, Jing Zhang, Guofang Guo, Guo State Grid Sichuan Electric Power Company Chengdu China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

With the rapid development of UHV AC / DC hybrid power grid, it is required that the Network Analysis Application have the ability of unified analysis and high-performance computing. In this paper, the time-consuming analysis of each sub-function of Network Analysis Application is carried out to realize the performance bottleneck analysis of the whole process of network analysis. It is proposed that the performance of network analysis should be improved in three aspects: data input and output, topology analysis and core computing of Network Analysis Application. In the aspect of data input, the grid model data service is constructed to realize the combination of measurement reading and model reading, and the parallel model verification and boundary equivalence are completed;In the aspect of data output, it can be parallelized by table, block and equipment;In the aspect of topology analysis, the shared memory programming model OpenMP is adopted, and based on the fork/join parallel mode, its parallelization is realized;In the aspect of core computing, the existing parallel computing methods are summarized, and through the actual power grid simulation analysis, it puts forward the parallel computing mode applicable to different scale power grids and different applications. Finally, the effectiveness of this method is verified by comparing the optimized performance of state estimation. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Application programming interfaces (API)

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Emotional Dialogue Generation Based on Transformer and Conditional Variational Autoencoder

Emotional Dialogue Generation Based on Transformer and Condi...

引用

IEEE international Symposium on parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Hongquan Lin Zhenrong Deng School of Data Science and Software Engineering Wuzhou University Wuzhou China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China

Human-machine dialogue is one of the most challenging tasks in the field of natural language processing, and it is also the basis for the realization of a human-machine inclusive society in the future. At present, the generative dialogue model based on deep learning is prone to generate general responses with single content and no meaningful information, and the existing research considers emotional factors relatively little. Aiming at the shortcomings of existing methods, an emotional dialogue generation model based on Transformer and conditional variational autoencoder(CVAE) is proposed, which is intended to improve the diversity of response information and embed emotional factors in the generated response. This model uses Transformer to extract the semantic features of the text sequence to improve the utilization of the semantic information of the text sequence. To increase the diversity of the response information, the latent variable of the conditional variational self-encoder is introduced into the decoder. In addition, in order to enhance the empathy ability of the model, an emotion perception encoder is used to encode user emotion information, and a pre-trained emotion classification model based on BERT is proposed to detect the emotion information implicit in the utterance. Experiments have shown that the proposed model has a stronger generation ability, more diverse information to generate responses, and a stronger empathy ability.

关键词： Analytical models Computational modeling Semantics Bit error rate Transformers Feature extraction Ubiquitous computing

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ECS2: A Fast Erasure Coding Library for GPU-Accelerated Storage Systems With parallel & Direct IO 22

ECS2: A Fast Erasure Coding Library for GPU-Accelerated Stor...

引用

IEEE international conference on Cluster computing

作者： Chang, Chan Jung Chou, Jerry Chou, Yu-Ching Chung, I-Hsin Natl Tsing Hua Univ Comp Sci Dept Hsinchu Taiwan H3 Platform Inc Taichung Taiwan IBM TJ Watson Res Ctr New York NY USA

ISBN: (纸本)9781728166773

As data volume keeps increasing at a rapid rate, there is an urgent need for large, reliable, and cost-effective storage systems. Erasure coding has drawn increasing attention because of its ability to ensure data reliability with higher storage efficiency, and it has been widely adopted in many distributed and large-scale storage systems, such as Azure cloud storage and HDFS. However, the storage efficiency of erasure code comes at the price of higher computing complexity. While many studies have shown the coding computations can be significantly accelerated using GPU, the overhead of data transfer between storage devices and GPUs become a new performance bottleneck. In this work, we designed and implemented, ECS2, a fast erasure coding library on GPU-accelerated storage to let users enhance their data protection with transparent IO performance and file system like programming interface. By taking advantage of the latest GPUDirect technology supported on Nvidia GPU, our library is able to bypass CPU and host memory copy from the IO path, so that both the computing and IO overhead from coding can be minimized. Using synthetic IO workload based on real storage system trace, we show that the IO latency can be reduced by 10% similar to 20% with GPUDirect technology, and the overall IO throughput of a storage system can be improved up to 70%.

关键词： Storage system Erasure Code Reliability Performance parallel I/O

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Decentralised Blockchain-based Solutions for Electronic Healthcare Record with Interacting Social Networking Components

Decentralised Blockchain-based Solutions for Electronic Heal...

引用

2021 international conference on Innovation and Intelligence for Informatics, computing, and Technologies, 3ICT 2021

作者： Munoz, Daniel-Jesus Constantinescu, Denisa-Andreea ITIS Software CAOSD Group Universidad de Málaga Andalucía Tech Málaga Spain HPACuma Parallel Programming Models and Compilers Group Universidad de Málaga Computer Architecture Department Málaga Spain

ISBN: (纸本)9781665440325

The healthcare industry is a conjunction of monolithic applications based on neutral and time-stamped diagnostics. Hence, it is particularly interested in decentralised technologies to achieve global and social-driven electronic health records. Blockchain is a decentralised networking system where multiple copies of immutable data records are distributed and validated among different independent nodes. While traditionally used to create currently famous digital cryptocurrencies like Bitcoin, its worldwide fever helped to extend its applications beyond the financial industry. However, given how fast completely new technologies evolve, healthcare stakeholders are struggling to find the correct usage of blockchain ecosystem developments. Our goal is to provide a summary of the state-of-the-art efforts in the development of decentralised blockchain-based solutions for electronic healthcare records, in which social networking and wearable technology data is considered in order to provide patient-driven diagnostics - proven to be critical in the current SARS-CoV-2 pandemic. In this paper, we present a comprehensive guide on blockchain technologies competing in the healthcare market, including emerging blockchain-based initiatives and trends. Additionally, we discuss the main caveats of blockchain applications development in this industry based on practical experience. © 2021 IEEE.

关键词： Blockchain

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Time-Based Consensus 25th

Time-Based Consensus

引用

25th international conference on parallel and distributed computing (Euro-Par)

作者： Heydari, Hasan Silvestre, Guthemberg Larrieu, Nicolas Pirovano, Alain Univ Toulouse ENAC Toulouse France

ISBN: (纸本)9783030483401;9783030483395

Reaching consensus is fundamental in distributed computing. For each execution of a consensus algorithm, there is no difference between the proposed values by different nodes with respect to their proposed times. By presenting a realistic application scenario related to distributed asynchronous mobile robots in dynamic environments, we argue some safety-critical, real-time systems require reaching consensus on the newest proposed values when the old proposed values may not be valid anymore. Afterward, we formulate a new type of consensus problem called time-based consensus, which requires to take into account the times of proposed values. Finally, to tackle such a consensus problem, we determine an essential characteristic which should be considered.

关键词： Consensus algorithm distributed mobile robot Safety-critical application Real-time system Dynamic environment

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EPGraph: An Efficient Graph computing Model in Persistent Memory System

EPGraph: An Efficient Graph Computing Model in Persistent Me...

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Baoke Li Cong Cao Fangfang Yuan Yanbing Liu Baohui Li Binxing Fang Chinese Academy of Sciences Institute of Information Engineering Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Department of System Evaluation Chinese Information Technology Securiry Evaluation Center Beijing China Institue of Electronic and Information Engineering of UESTC in Guangdong Dongguan Guangdong China

With the wide range of requirements to analyse large-scale graphs in many real-world applications (e.g., relationship analysis, fraud detection and product recommendation), graph computing recently receives intensive interests. However, the massive volume and the power-law distribution of graphs are objective obstacles to efficient graph computing. Fortunately, Intel Optane DC Persistent Memory (PMEM) has emerged as a new solution, which is expected to play a crucial role in large-scale graph processing. But compared with main memory, PMEM shows much lower bandwidth and higher access latency. Therefore, it becomes paramount to fully exploit the advantages of PMEM in persistent memory systems. In this paper, we propose EPGraph, a novel efficient graph computing model designed by PMEM. To a considerable extent, it improves the spatial locality and the temporal locality of graph computing at the same time. The main contribution of our work lies in three aspects. Firstly, we design a degree-based data layering strategy to reduce the impact of power-law distribution. The hierarchical strategy makes full use of DRAM and PMEM simultaneously. Secondly, we propose a dynamic migration mechanism during the iterative execution of graph computing. The dynamic mechanism equitably schedules the subgraphs which are used in the next iteration. Thirdly, we evaluate the effectiveness of EPGraph on five public graph data sets. Extensive evaluation results show that EPGraph outperforms state-of-the-art graph computing systems by 22.67%-35.03%.

关键词： Schedules Runtime Computational modeling Scalability Memory management Random access memory Dynamic scheduling

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Issues and Algorithm of distributed Shared Memory

Issues and Algorithm of Distributed Shared Memory

引用

international conference on Innovative computing (ICIC)

作者： Mian Basam Ahmad Sundas Sagheer University of Management and Technology Lahore Pakistan

ISBN: (纸本)9781665400923

Internet of things is a rapidly growing industry, and there are more connected devices than humans. There are unlimited internet of things devices around us. The scope of these devices has increased manifold in recent years in different areas like healthcare, unmanned vehicles, automatic monitoring systems, and smart homes, etc. These connected devices produce lots of data that need to be processed to achieve the goal of automation in daily life. The cloud provides many centralized solutions to process data using powerful resources in real-time, but there could be latency issues due to increased network traffic. So a distributed solution is much needed to meet this growing demand of processing data in parallel. In this paper, we propose a distributed shared memory [18] abstraction for the internet of things that uses a graph-aware partitioning algorithm and uses smart message passing techniques to process data in distributed and parallel fashion [19].

关键词： Manifolds Message passing distributed databases Telecommunication traffic Smart homes Medical services Real-time systems

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Modeling and Simulation of QoS-Aware Power Budgeting in Cloud Data Centers 28

Modeling and Simulation of QoS-Aware Power Budgeting in Clou...

引用

28th Euromicro international conference on parallel, distributed and Network-Based Processing (PDP)

作者： Krzywda, Jakob Meyer, Vinfeius Xavier, Miguel G. Ali-Eldin, Ahmed Ostberg, Per-Olov De Rose, Cesar A. F. Elmroth, Erik Umea Univ Dept Comp Sci Umea Sweden Pontificia Univ Catolica Rio Grande do Sul Polytech Sch Porto Alegre RS Brazil Univ Massachusetts Coll Informat & Comp Sci Amherst MA 01003 USA

ISBN: (纸本)9781728165820

Power budgeting is a conm only employed solution to reduce the negative consequences of high power consumption of large scale data centers. While various power budgeting techniques and algorithms have been proposed at different levels of data center infrastructures to optimize the power allocation to servers and hosted applications, testing them has been challenging with no available simulation platform that enables such testing for different scenarios and configurations. To facilitate evaluation and comparison of such techniques and algorithms, we introduce a simulation model for Quality-of-Service aware power budgeting and its implementation in CloudSim. We validate the proposed simulation model against a deployment on a real lestbed, showcase simulator capabilities, and evaluate its scalability.

关键词： cloud computing power budgeting quality of service simulation

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An Effective Automatic Recognition Approach of Chinese Herbal Medicine by Micro Image Processing

An Effective Automatic Recognition Approach of Chinese Herba...

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IEEE international Symposium on parallel and distributed Processing with Applications and IEEE international conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Guangyao Pang Zhenming Yu Honglin Pan Chengwen Xie Ping Gong Xiaoying Zhu Zizhen Peng Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China Guangxi Colleges and Universities Key Laboratory of Industry Software Technology Wuzhou University Wuzhou China

The identification of traditional Chinese medicine is the key to control the quality of traditional Chinese medicine and ensure the safety and effectiveness of clinical medication. Compared with the physical and chemical identification methods with expensive equipment and complex operation, microscopic image identification of traditional Chinese medicine is an effective method with low cost. However, this method still has a high learning cost and identification errors due to staff fatigue. Therefore, this paper designs an effective automatic recognition approach of Chinese herbal medicine by micro image processing. The core of this method is the introduction of transfer learning and data enhancement methods, which effectively alleviates the problem of insufficient number of microscopic image data samples in the microscopic recognition of traditional Chinese medicine, and realizes the automatic recognition of traditional Chinese medicine. We construct a library of microscopic recognition features of Chinese herbal medicine, and designe evaluation experiments on this basis. The results show that the recognition performance of our method is better than that of SSD method, especially the F1 value is increased by 7.25 %.

关键词： Deep learning Image recognition Costs Microscopy Transfer learning Ubiquitous computing Raw materials

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DyRAC: Cost-aware Resource Assignment and Provider Selection for Dynamic Cloud Workloads 26

DyRAC: Cost-aware Resource Assignment and Provider Selection...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Sfakianakis, Yannis Marazakis, Manolis Bilas, Angelos Fdn Res & Technol FORTH Inst Comp Sci ICS Iraklion Crete Greece Univ Crete Dept Comp Sci Iraklion Crete Greece

ISBN: (纸本)9781728190747

A primary concern for cloud users is how to minimize the total cost of ownership of cloud services. This is not trivial to achieve due to workload dynamics. Users need to select the number, size, type of VMs, and the provider to host their services based on available offerings. To avoid the complexity of re-configuring a cloud service, related work commonly approaches cost minimization as a packing problem that minimizes the resources allocated to services. However, this approach does not consider two problem dimensions that can further reduce cost: (1) provider selection and (2) VM sizing. In this paper, we explore a more direct approach to cost minimization by adjusting the type, number, size of VM instances, and the provider of a cloud service (i.e. a service deployment) at runtime. Our goal is to identify the limits in service cost reduction by online re-deployment of cloud services. For this purpose, we design DyRAC, an adaptive resource assignment mechanism for cloud services that, given the resource demands of a cloud service, estimates the most cost-efficient deployment. Our evaluation implements four different resource assignment policies to provide insight into how our approach works, using VM configurations of actual offerings from main providers (AWS, GCP, Azure). Our experiments show that DyRAC reduces cost by up to 33% compared to typical strategies.

关键词： Resource assignment Cost efficiency Cloud computing Provider selection VM type selection

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