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检索条件"任意字段=12th Euromicro Conference on Parallel, Distributed and Network-Based Processing"

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Towards On-the-fly Self-Adaptation of Stream parallel Patterns 29

Towards On-the-fly Self-Adaptation of Stream Parallel Patter...

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29th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Vogel, Adriano Mencagli, Gabriele Griebler, Dalvan Danelutto, Marco Fernandes, Luiz Gustavo Pontifical Catholic Univ Rio Grande do Sul PUCRS Sch Technol Porto Alegre RS Brazil Tres de Maio Fac SETREM Lab Adv Res Cloud Comp LARCC Tres De Maio Brazil Univ Pisa UNIPI Comp Sci Dept Pisa Italy

ISBN: (纸本)9781665414555

Stream processing applications compute streams of data and provide insightful results in a timely manner, where parallel computing is necessary for accelerating the application executions. Considering that these applications are becoming increasingly dynamic and lung-running, a potential solution is to apply dynamic runtime changes. However, it is challenging for humans to continuously monitor and manually self-optimize the executions. In this paper, we propose self-adaptiveness of the parallel patterns used, enabling flexible on-the-fly adaptations. the proposed solution is evaluated with an existing programming framework and running experiments with a synthetic and a real-world application. the results show that the proposed solution is able to dynamically self-adapt to the most suitable parallel pattern configuration and achieve performance competitive with the best static cases. the feasibility of the proposed solution encourages future optimizations and other applicabilities.

关键词： parallel Computing parallel Patterns parallelism Abstractions Self adaptive systems Stream processing

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Introducing a Stream processing Framework for Assessing parallel Programming Interfaces 29

Introducing a Stream Processing Framework for Assessing Para...

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29th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Garcia, Adriano Marques Griebler, Dalvan Fernandes, Luiz G. L. Schepke, Claudio Pontifical Catholic Univ Rio Grande do Sul PUCRS Sch Technol Porto Alegre RS Brazil Tres de Maio Maio Fac SETREM Lab Adv Res Cloud Comp LARCC Tres De Maio Brazil Fed Univ Pampa UNIPAMPA Alegrete Brazil

ISBN: (纸本)9781665414555

Stream processing applications are spread across different sectors of industry and people's daily lives. the increasing data we produce, such as audio, video, image, and text are demanding quickly and efficiently computation. It can be done through Stream parallelism, which is still a challenging task and most reserved for experts. We introduce a Stream processing framework for asse s s ing parallel Programming Interfaces (PPIs). Our framework targets multi-core architectures and C++ stream processing applications, providing an API that abstracts the details of the stream operators of these applications. therefore, users can easily identify all the basic operators and implement parallelism through different PPIs. In this paper, we present the proposed framework, implement three applications using its API, and show how it works, by using it to parallelize and evaluate the applications with the PPIs Intel TBB, FastFlow, and SPar. the performance results were consistent with the literature.

关键词： Benchmark Framework parallel Programming Stream processing

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network MEMORY FOOTPRINT COMPRESSION thROUGH JOINTLY LEARNABLE CODEBOOKS AND MAPPINGS 12

NETWORK MEMORY FOOTPRINT COMPRESSION THROUGH JOINTLY LEARNAB...

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12th International conference on Learning Representations, ICLR 2024

作者： Yvinec, Edouard Dapogny, Arnaud Bailly, Kevin Sorbonne Université CNRS ISIR 4 Place Jussieu ParisF-75005 France Datakalab 114 boulevard Malesherbes Paris75017 France

the massive interest in deep neural networks (DNNs) for both computer vision and natural language processing has been sparked by the growth in computational power. However, this led to an increase in the memory footprint, to a point where it can be challenging to simply load a model on commodity devices such as mobile phones. To address this limitation, quantization is a favored solution as it maps high precision tensors to a low precision, memory efficient format. In terms of memory footprint reduction, its most effective variants are based on codebooks. these methods, however, suffer from two limitations. First, they either define a single codebook for each tensor, or use a memory-expensive mapping to multiple codebooks. Second, gradient descent optimization of the mapping favors jumps toward extreme values, hence not defining a proximal search. In this work, we propose to address these two limitations. First, we initially group similarly distributed neurons and leverage the re-ordered structure to either apply different scale factors to the different groups, or map weights that fall in these groups to several codebooks, without any mapping overhead. Second, stemming from this initialization, we propose a joint learning of the codebook and weight mappings that bears similarities with recent gradient-based post-training quantization techniques. third, drawing estimation from straight-through estimation techniques, we introduce a novel gradient update definition to enable a proximal search of the codebooks and their mappings. the proposed jointly learnable codebooks and mappings (JLCM) method allows a very efficient approximation of any DNN: as such, a Llama 7B can be compressed down to 2Go and loaded on 5-year-old smartphones. © 2024 12th International conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Mapping

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Method of Data processing System Synthesis for Heterogeneous distributed Databases based on network-Centric Control 12

Method of Data Processing System Synthesis for Heterogeneous...

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12th IEEE International conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2023

作者： Mukhin, Vadym Kornaga, Yaroslav Zavgorodnii, Valerii Bazaka, Yurii Zavgorodnya, Anna Mukhin, Oleg National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of System Design Kiev Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Information Systems and Technologies Kiev Ukraine Igor Sikorsky Kyiv Polytechnic Institute Department of the Artificial Intellect National Technical University of Ukraine Kiev Ukraine

ISBN: (纸本)9798350358056

the methodology for the synthesis of a distributed computer system that includes the database was developed. there are suggested the new models for the data processing parameters evaluation and along with the analysis and forecasting of the functional parameters. the proposed methods for the number of data processing nodes determining in the systems with dynamic structure based on a network-centric control mechanism allows increase the efficiency of the heterogeneous distributed databases. the implementation of the proposed methodology allows synthesizing a distributed data processing system for processing requests to heterogeneous databases, taking into account the parameters of the nodes and the bandwidth of the channels between the nodes. © 2023 IEEE.

关键词： characteristic heterogeneous distributed database method methodology for the synthesis node parameter

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Machine Learning Migration for Efficient Near-Data processing 29

Machine Learning Migration for Efficient Near-Data Processin...

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29th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Cordeiro, Aline S. dos Santos, Sairo R. Moreira, Francis B. Santos, Paulo C. Carro, Luigi Alves, Marco A. Z. Univ Fed Parana Dept Informat Curitiba Parana Brazil Fed Rural Univ Semiarid Dept Exact Sci & Informat Technol Angicos Brazil Univ Fed Rio Grande do Sul Informat Inst Porto Alegre RS Brazil

ISBN: (纸本)9781665414555

Machine Learning (ML) rises as a highly useful tool to analyze the vast amount of data generated in every field of science nowadays. Simultaneously, data movement inside computer systems gains more focus due to its high impact on time and energy consumption. In this contest. the Near-Data processing (NDP) architectures emerged as a prominent solution to increasing data by drastically reducing the required amount of data movement. For NDP, we see three main approaches, Application-Specific Integrated Circuits (ASICs), full Central processing units (CPUs) and Graphics processing Units (GPUs), or vector units integration. However, previous work considered only ASICs, CPUs and GPUs when executing ML algorithms inside the memory. In this paper, we present an approach to execute ML algorithms near-data, using a general-purpose vector architecture and applying near-data parallelism to kernels from KNN, MLP, and CNN algorithms. To facilitate this process, we also present an NDP intrinsics library to ease the evaluation and debugging tasks. Our results show speedups up to 10x for KNN, 11x for MLP, and 3x for convolution when processing near-data compared to a high-performance x86 baseline.

关键词： Near-Data processing Vector processing Machine Learning

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Epileptogenic Foci Localization with Intracranial EEG Using Effective Connectivity network based on Phase Transfer Entropy 12

Epileptogenic Foci Localization with Intracranial EEG Using ...

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12th International conference on System Modeling and Advancement in Research Trends, SMART 2023

作者： Sun, Moyang Zhou, Sun Xiamen University Department of Automation Xiamen China

ISBN: (纸本)9798350369861

One of the greatest challenges of achieving successful surgical outcomes in patients with epilepsy is the correct localization of the epileptogenic foci. Clinicians rely heavily on electroencephalogram (EEG) recordings, especially intracranial EEG (iEEG), to localize the epileptogenic zone and make surgical decisions. In this paper, we propose a method based on a Phase Transfer Entropy (PTE) metric targeting accurate automatic epileptic foci localization using the iEEG recordings. the phase of an oscillation has been shown to be critical in the coordination of anatomically distributed processing. We suggest using a PTE metric for the quantification of directed phase interactions between channels with high computational efficiency and a single parameter. First, infer causal connectivity using PTE between the multi-channel iEEG time series to establish the effective connectivity network of the brain with sliding windows. then, compute features of that time-varying network, and eventually determine the epileptogenic foci. the proposed approach is evaluated on the HUP iEEG dataset, which contains patient data collected during surgical treatment of drug-resistant epilepsy. the results show the effectiveness as well as computational efficiency of the phase-based method in epileptogenic foci localization. © 2023 IEEE.

关键词： Electroencephalography

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Research and Application of Distribution network Dispatching Operation based on Digital Twinning Technology 12

Research and Application of Distribution Network Dispatching...

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12th International conference of Information and Communication Technology, ICTech 2023

作者： Qiao, Junfeng Ou, Zhujian Peng, Lin Zhu, Fuyun Zhou, Aihua Yang, Pei State Grid Smart Grid Research Institute Co. ltd State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology Jiangsu Nanjing210003 China State Grid Jiangsu Electric Power Co. Ltd Nantong Power Supply Company Jiangsu Nanjing210014 China

ISBN: (纸本)9798350332919

In the electric distribution grid, the access of distributed electric power generation also brings new technical challenges. From the perspective of operation, after the distributed generation is related to the electric distribution grid, due to the uncertainty of wind energy, solar energy and other new energy, there will be higher harmonics in the distribution network that affect the power quality and power supply reliability. On the other hand, it is necessary to consider the economic cost and reasonably distribute the output status of different units in the distribution network to achieve the unity of economic and ecological benefits. While, it has occasion to research the dispatching method of electric distribution grid with distributed generation. this paper uses digital twinning technology to build virtual equipment modeling scheme, which integrates equipment basic data, system single line diagram and grid geographic coordinate data. With rapid processing governance as the core and electric grid topology computing function, it realizes the whole process management of electric distribution grid dispatching and management, and provides production management personnel with distribution network digital simulation platform and auxiliary decision-making function. © 2023 IEEE.

关键词： Decision making

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Camouflaged bot detection using the friend list 29

Camouflaged bot detection using the friend list

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29th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Kolomeets, Maxim Tushkanova, Olga Levshun, Dmitry Chechulin, Andrey Russian Acad Sci SPC RAS St Petersburg Fed Res Ctr Lab Comp Secur Problems 14th Line VO 39 St Petersburg Russia ITMO Univ Kronverksky Pr 49 St Petersburg Russia Univ Paul Sabatier Toulouse III 118 Route Narbonn Toulouse France

ISBN: (纸本)9781665414555

the paper considers the task of hot detection in social networks. Study is focused on the case when the account is closed by the privacy settings, and the but needs to he identified by the friend list. the paper proposes a solution that is based on machine learning and statistical methods. Social network Vkontakte is used as a data source. the paper provides the review of data, that one needs to get from the social network for hot detection in the case when the profile is closed by privacy settings. the paper includes a description of features extraction from Vkontakte social network and extracting complexity evaluation;description of features construction using statistics, Benford's law and Gini index. the paper describes the experiment. To collect data for training, we collect hots and real users datasets. To collect hots we made fake groups and bought bats of different quality for them from 3 different companies. We performed two series of experiments. In the first series, all the features were used to train and evaluate the classifiers. In the second series of experiments, the features were preliminary examined for the presence of strong correlation between them. the results demonstrated the feasibility of rather high-accuracy private account hot detection by means of unsophisticated off-the-shelf algorithms in combination with data scaling. the Random Forest Classifier yields the best results, with an ROC AUC more titan 0.9 and FPR less than 0.3. In paper we also discuss the limitations of the experimental part. and plans for future research.

关键词： social network bot bot detection social relationship information security

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Implementation of IEEE1588 Protocol based on STM32H750 12

Implementation of IEEE1588 Protocol Based on STM32H750

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12th International conference of Information and Communication Technology, ICTech 2023

作者： Xiong, XinFei He, Fang Li, Yan Han, WenZe Jiao, YanFei Shenyang Institute of Computing Technology Chinese Academy of Sciences Shengyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350332919

In the industrial control field, multiple nodes in the network need to collect and process data cooperatively. However, due to the lack of clock synchronization capability of the network, the data lacks time series information, which will lead to the abnormal fusion processing of multiple data by the upper computer, In the system, IEEE1588 protocol (accurate clock synchronization protocol of network measurement and control system) is used to solve the above problems. based on the development board with STM32H750 microcontroller as the core, a distributed clock synchronization system is built. the system has built a LwIP (Light Weight TCP/IP Stack) network protocol stack to realize the transmission of various messages during clock synchronization, the time jitter delay from the transmission layer of the network protocol stack to the framing of the data link layer is eliminated, and the accuracy of clock synchronization is improved. the experimental results show that the system can achieve nanosecond level clock synchronization, and can be used in industrial control sites that require high real-time performance. © 2023 IEEE.

关键词： Synchronization

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A Cross-Platform OpenVX Library for FPGA Accelerators 29

A Cross-Platform OpenVX Library for FPGA Accelerators

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29th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Angelica Davila-Guzman, Maria Gran Tejero, Ruben Villarroya-Gaudo, Maria Suarez Gracia, Dario Kalms, Lester Gohringer, Diana Univ Zaragoza DIIS I3A HiPEAC Network Excellence Zaragoza Spain Tech Univ Dresden HiPEAC Network Excellence Dresden Germany

ISBN: (纸本)9781665414555

In Computer Vision, open programming standards sod, as OpenVX have emerged to bring together portability and acceleration across devices. Unfortunately, achieving both goals on UPGAs remains a challenge because FPGAs still require to adapt the code with proprietary extensions. Exclusively for Xilinx devices, the HiF1ip X open source library partially solves this problem by offering a clean C++ OpenVX API that offers the performance of proprietary extensions without exposing its complexity to programmer. While HiFlipVX enables portability within Xilins devices, portability between FPGA manufacturers remains an open challenge. this work extends the HiFlipVX's capabilities with a twofold goal: i) to support Intel FPGA devices with different memory conhgurations. and ii) to enable execution on FPGAs as discrete accelerators. To accomplish these goals, the proposed implementation combines two HIS programming models: C++, using Inters system of tasks that enables to coalesce nodes and reduce control overhead, and OpenCL, which provides efficient compute kernel nodes. On Intel FPGAs. compared with pure OpenCL implementations, the proposed implementation reduces kernel dispatch resources, saving up to 24% of ALUT resources for each kernel in a graph, and improves performance. Gains are 2.6x on overage for representative applications, such as Canny edge detector, or Census transform, compared with state-of-the-art frameworks.

关键词： FPGA HiFlipVX HLS OpenVX OpenCL

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