检索结果-内蒙古大学图书馆

Efficient parallel TLD on CPU-GPU Platform for real-time Tracking

KSII TRANSACTIONS ON INTERNET AND INFORMATION systems 2020年第1期14卷 201-220页

作者： Chen, Zhaoyun Huang, Dafei Luo, Lei Wen, Mei Zhang, Chunyuan Natl Univ Def Technol Coll Comp Changsha 410073 Peoples R China Natl Key Lab Parallel & Distributed Proc Changsha 410073 Peoples R China Southwest Elect & Telecommun Technol Res Inst Chengdu 610000 Peoples R China

Trackers, especially long-term (LT) trackers, now have a more complex structure and more intensive computation for nowadays' endless pursuit of high accuracy and robustness. However, computing efficiency of LT trackers cannot meet the real-time requirement in various real application scenarios. Considering heterogeneous CPU-GPU platforms have been more popular than ever, it is a challenge to exploit the computing capacity of heterogeneous platform to improve the efficiency of LT trackers for real-time requirement. This paper focuses on TLD, which is the first LT tracking framework, and proposes an efficient parallel implementation based on OpenCL. In this paper, we firstly make an analysis of the TLD tracker and then optimize the computing intensive kernels, including Fern Feature Extraction, Fern Classification, NCC Calculation, Overlaps Calculation, Positive and Negative Samples Extraction. Experimental results demonstrate that our efficient parallel TLD tracker outperforms the original TLD, achieving the 3.92 speedup on CPU and GPU. Moreover, the parallel TLD tracker can run 52.9 frames per second and meet the real-time requirement.

关键词： TLD tracker real-time Heterogeneous Platform OpenCL parallel Optimizations

来源：评论

学校读者我要写书评

暂无评论

Reconfiguration durations optimization for highavailability distributed systems: The case of ict rural and elderly infrastructures for development

Reconfiguration durations optimization for highavailability ...

引用

2019 International Conference on Rural and Elderly Health Informatics, IREHI 2019

作者： Gbetie, Erick G. Soidridine, Moindze M. Edoh, Thierry Oscar Dakar Senegal Dakar Senegal

In this paper, we address the problem of very long execution durations during the management activities in rural infrastructures and elderly community information systems. This problem is a major challenge in the NGNM field in terms of constructing ICT4D large-scale collaborative infrastructures for a rural community in developing countries. It is an optimization problem in the strong sense with resource constraints in the context of real-time reconfiguration systems. It is also related to the operability of distributed highavailability networks systems used in NGN communications networks in order to support development in all life areas such as Education, Health, Economy, Agriculture and even to ensure the survival of living beings in developing countries. The resolution of such problems requires a significant and simultaneous reduction of several performance temporal criteria. The reduction of the execution durations allows optimizing performances of network resources. From a practical point of view, the reduction of network resources consumption automatically decreases the overall energy consumption in the remote networks infrastructures in rural areas technologies such as WSN, RFID, NFC, IoT, LoRa, WiMax, AirMax, Wideband satellites access and VSAT. We propose thus an algorithm capable of determining and decreasing in realtime the execution durations for ICT4D rural infrastructures and rural community information systems. This algorithm allows guaranteeing data access, data integration, information sharing and rapid professionals assistance across multiple heterogeneous centers. This algorithm is based on minimal temporal criteria, lower and upper bounds, dominance rules, a branching scheme, and an exploration strategy. Our experiments show that the results of the proposed algorithm are more efficient than those of the existing reference algorithms. © 2020 CEUR-WS. All rights reserved.

关键词： Rural areas

来源：评论

学校读者我要写书评

暂无评论

CLAIRE-parallelIZED DIFFEOMORPHIC IMAGE REGISTRATION FOR LARGE-SCALE BIOMEDICAL IMAGING APPLICATIONS

arXiv

引用

arXiv 2022年

作者： Himthani, Naveen Brunn, Malte Kim, Jae-Youn Schulte, Miriam Mang, Andreas Biros, George Oden Institute The University of Texas at Austin AustinTX United States Institute for Parallel and Distributed Systems University of Stuttgart DE Stuttgart Germany Department of Mathematics University of Houston HoustonTX United States

We study the performance of CLAIRE-a diffeomorphic multi-node, multi-GPU image registration algorithm and software-in large-scale biomedical imaging applications with billions of voxels. At such resolutions, most existing software packages for diffeomorphic image registration are prohibitively expensive. As a result, practitioners first significantly downsample the original images and then register them using existing tools. Our main contribution is an extensive analysis of the impact of downsampling on registration performance. We study this impact by comparing full resolution registrations obtained with CLAIRE to lower resolution registrations for synthetic and real-world imaging datasets. Our results suggest that registration at full resolution can yield a superior registration quality-but not always. For example, downsampling a synthetic image from 10243 to 2563 decreases the Dice coefficient from 92% to 79%. However, the differences are less pronounced for noisy or low contrast high resolution images. CLAIRE allows us not only to register images of clinically relevant size in a few seconds but also to register images at unprecedented resolution in reasonable time. The highest resolution considered are CLARITY images of size 2816 × 3016 × 1162. To the best of our knowledge, this is the first study on image registration quality at such resolutions. Copyright © 2022, The Authors. All rights reserved.

关键词： Image registration

来源：评论

学校读者我要写书评

暂无评论

FastJoin: A Skewness-Aware distributed Stream Join System 33

FastJoin: A Skewness-Aware Distributed Stream Join System

引用

33rd IEEE International parallel and distributed Processing Symposium (IPDPS)

作者： Zhou, Shunjie Zhang, Fan Chen, Hanhua Jin, Hai Zhou, Bing Bing Huazhong Univ Sci & Technol Natl Engn Res Ctr Big Data Technol & Syst Cluster & Grid Comp Lab Serv Comp Technol & Syst LabSch Comp Sci & Techn Wuhan 430074 Peoples R China Univ Sydney Sch Informat Technol Sydney NSW 2006 Australia

ISBN: (纸本)9781728112466

In the bigdata era, many applications are required to perform quick and accurate join operations on large-scale real-time data streams, such as stock trading and online advertisement analysis. To achieve high throughput and low latency, distributed stream join systems explore efficient stream partitioning strategies to execute the complex stream join procedure in parallel. Existing systems mainly deploy two kinds of partitioning strategies, i.e., random partitioning and hash partitioning. Random partitioning strategy partitions one data stream uniformly while broadcasting all the tuples of the other data stream. This simple strategy may incur lots of unnecessary computations for low selectivity stream join. Hash partitioning strategy maps all the tuples of the two data streams according to their attributes for joining. However, hash partitioning strategy suffers from a serious load imbalance problem caused by the skew distribution of the attributes, which is common in real-world data. The skewed load may seriously affect the system performance. In this paper, we carefully model the load skewness problem in distributed join systems. We explore the key tuples which lead to the heavy load skewness, and propose an efficient key selection algorithm, GreedyFit to find out these key tuples. We design a lightweight tuple migration strategy to solve the load imbalance problem in real-time and implement a new distributed stream join system, &Wain. Experimental results using real-world data show that FastJoin can significantly improve the system performance in terms of throughput and latency compared to the slate-of-the-art stream join systems.

关键词： distributed stream join system data skew dynamic load balancing load migration

来源：评论

学校读者我要写书评

暂无评论

Scheduling Periodical Multi-Stage Jobs With Fuzziness to Elastic Cloud Resources

引用

IEEE TRANSACTIONS ON parallel AND distributed systems 2020年第12期31卷 2819-2833页

作者： Zhu, Jie Li, Xiaoping Ruiz, Ruben Li, Wei Huang, Haiping Zomaya, Albert Y. Nanjing Univ Posts & Telecommun Sch Comp Sci & Technol Nanjing 210023 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Jiangsu Key Lab Big Data Secur Intelligent Proc Nanjing 210023 Jiangsu Peoples R China Southeast Univ Sch Comp Sci & Engn Nanjing 211189 Jiangsu Peoples R China Southeast Univ Minist Educ Key Lab Comp Network & Informat Integrat Nanjing 211189 Jiangsu Peoples R China Univ Politecn Valencia Grp Sistemas Optimizac Aplicada Camino Vera S-N Valencia 46022 Spain Nanjing Univ Posts & Telecommun Sch Comp Sci & Technol Nanjing 210048 Jiangsu Peoples R China Univ Sydney Sch Comp Sci Ctr Distributed & High Performance Comp Camperdown NSW 2006 Australia

We investigate a workflow scheduling problem with stochastic task arrival times and fuzzy task processing times and due dates. The problem is common in many real-time and workflow-based applications, where tasks with fixed stage number and linearly dependency are executed on scalable cloud resources with multiple price options. The challenges lie in proposing effective, stable, and robust algorithms under stochastic and fuzzy tasks. A triangle fuzzy number-based model is formulated. Two metrics are explored: the cost and the degree of satisfaction. An iterated heuristic framework is proposed to periodically schedule tasks, which consists of a task collection and a fuzzy task scheduling phases. Two task collection strategies are presented and two task prioritization strategies are employed. In order to achieve a high satisfaction degree, deadline constraints are defined at both job and task levels. By designing delicate experiments and applying sophisticated statistical techniques, experimental results show that the proposed algorithm is more effective and robust than the two existing methods.

关键词： Job scheduling fuzzy processing times fuzzy deadlines cloud computing

来源：评论

学校读者我要写书评

暂无评论

Efficient Operator Placement for distributed Data Stream Processing Applications

引用

IEEE TRANSACTIONS ON parallel AND distributed systems 2019年第8期30卷 1753-1767页

作者： Nardelli, Matteo Cardellini, Valeria Grassi, Vincenzo Lo Presti, Francesco Univ Roma Tor Vergata I-00133 Rome Italy

In the last few years, a large number of real-time analytics applications rely on the Data Stream Processing (DSP) so to extract, in a timely manner, valuable information from distributed sources. Moreover, to efficiently handle the increasing amount of data, recent trends exploit the emerging presence of edge/Fog computing resources so to decentralize the execution of DSP applications. Since determining the Optimal DSP Placement (for short, ODP) is an NP-hard problem, we need efficient heuristics that can identify a good application placement on the computing infrastructure in a feasible amount of time, even for large problem instances. In this paper, we present several DSP placement heuristics that consider the heterogeneity of computing and network resources;we divide them in two main groups: model-based and model-free. The former employ different strategies for efficiently solving the ODP model. The latter implement, for the problem at hand, some of the well-known meta-heuristics, namely greedy first-fit, local search, and tabu search. By leveraging on ODP, we conduct a thorough experimental evaluation, aimed to assess the heuristics' efficiency and efficacy under different configurations of infrastructure size, application topology, and optimization objectives.

关键词： distributed data stream processing geo-distributed systems heuristics operator placement quality of service

来源：评论

学校读者我要写书评

暂无评论

parallel Structure from Motion for Sparse Point Cloud Generation in Large-Scale Scenes

引用

SENSORS 2021年第11期21卷 3939页

作者： Bao, Yongtang Lin, Pengfei Li, Yao Qi, Yue Wang, Zhihui Du, Wenxiang Fan, Qing Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China Beihang Univ State Key Lab Virtual Real & Technol Beijing 100191 Peoples R China Beihang Univ Virtual Real Res Inst Qingdao Res Inst Qingdao 266100 Peoples R China MiningLamp Technol Beijing 100102 Peoples R China

Scene reconstruction uses images or videos as input to reconstruct a 3D model of a real scene and has important applications in smart cities, surveying and mapping, military, and other fields. Structure from motion (SFM) is a key step in scene reconstruction, which recovers sparse point clouds from image sequences. However, large-scale scenes cannot be reconstructed using a single compute node. Image matching and geometric filtering take up a lot of time in the traditional SFM problem. In this paper, we propose a novel divide-and-conquer framework to solve the distributed SFM problem. First, we use the global navigation satellite system (GNSS) information from images to calculate the GNSS neighborhood. The number of images matched is greatly reduced by matching each image to only valid GNSS neighbors. This way, a robust matching relationship can be obtained. Second, the calculated matching relationship is used as the initial camera graph, which is divided into multiple subgraphs by the clustering algorithm. The local SFM is executed on several computing nodes to register the local cameras. Finally, all of the local camera poses are integrated and optimized to complete the global camera registration. Experiments show that our system can accurately and efficiently solve the structure from motion problem in large-scale scenes.

关键词： structure from motion graph segmentation sparse point cloud large-scale scene camera clustering UAV image

来源：评论

学校读者我要写书评

暂无评论

Response time Bounds for Typed DAG parallel Tasks on Heterogeneous Multi-Cores

引用

IEEE TRANSACTIONS ON parallel AND distributed systems 2019年第11期30卷 2567-2581页

作者： Han, Meiling Guan, Nan Sun, Jinghao He, Qingqiang Deng, Qingxu Liu, Weichen Northeastern Univ Sch Comp Sci & Engn Shenyang 110004 Liaoning Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Hong Kong Polytech Univ Hung Hom Hong Kong Peoples R China Northeastern Univ Shenyang 110819 Liaoning Peoples R China Nanyang Technol Univ Sch Comp Sci & Engn Singapore 639798 Singapore

Heterogenerous multi-cores utilize the strength of different architectures for executing particular types of workload, and usually offer higher performance and energy efficiency. In this paper, we study the worst-case response time (WCRT) analysis of typed scheduling of parallel DAG tasks on heterogeneous multi-cores, where the workload of each vertex in the DAG is only allowed to execute on a particular type of cores. The only known WCRT bound for this problem is grossly pessimistic and suffers the non-self-sustainability problem. In this paper, we propose two new WCRT bounds. The first new bound has the same time complexity as the existing bound, but is more precise and solves its non-self-sustainability problem. The second new bound explores more detailed task graph structure information to greatly improve the precision, but is computationally more expensive. We prove that the problem of computing the second bound is strongly NP-hard if the number of types in the system is a variable, and develop an efficient algorithm which has polynomial time complexity if the number of types is a constant. Experiments with randomly generated workload show that our proposed new methods are more precise than the existing bound while having good scalability.

关键词： Task analysis time factors Multicore processing Scheduling algorithms time complexity real-time systems Heterogenerous multi-cores system embedded real-time scheduling response time analysis DAG parallel task

来源：评论

学校读者我要写书评

暂无评论

A Novel Construction and Inference Methodology of Belief Rule Base

引用

IEEE ACCESS 2020年 8卷 209738-209749页

作者： Hu, Qingshuang Li, Chenghai Lu, Yanli Li, Song Air Force Engn Univ Grad Sch Xian 710051 Peoples R China Air Force Engn Univ Air & Missile Def Coll Xian 710051 Peoples R China

The belief rule base model performs well in continuous systems but not in piecewise systems, and it suffers from a combinatorial explosion when there are a large number of model input referential parameters, resulting in a slow model optimization speed. Aiming at these problems, we do the following things. Firstly, different from the existing methods that improve model performance by improving optimization algorithm, we propose a distributed belief rule base model construction and inference methodology, which reduces the algorithm complexity of model construction and inference and improves the model accuracy by dividing the model into several small and independent subsets of belief rule base. Then we prove that the distributed belief rule base model can reduce the optimization algorithm complexity by using this methodology optimizes all subsets in parallel and independently during model construction, and reduce the inference cost of inactivated rules by adopting a hierarchical inference methodology. Then we prove that the proposed distributed belief rule base model performs well on both continuous and piecewise systems;also, construction efficiency and inference accuracy using the same optimization algorithm are higher than those of the traditional belief rule base model through experiments of nonlinear continuous function fitting and binary piecewise function fitting. Finally, we improve that the proposed distributed belief rule base model has a noticeable performance advantage in complex environments compared to the traditional model through the network situation prediction experiment and point out that the distributed belief rule base model is suitable in applications that require high real-time performance and high accuracy.

关键词： Fitting Training data Predictive models Inference algorithms Data models real-time systems Complexity theory Belief rule base distributed model independent optimization parallel optimization hierarchical inference subset of belief rule base network security situation prediction

来源：评论

学校读者我要写书评

暂无评论

parallel Semi-blind Joint Timing-Offset and Channel Estimation for AF-TWRNs

Parallel Semi-blind Joint Timing-Offset and Channel Estimati...

引用

2020 IEEE International Conference on Communications, Computing, Cybersecurity, and Informatics, CCCI 2020

作者： Alfawaz, Oruba El-Moursy, Ali A. Alnajjar, Khawla A. Abdallah, Saeed University of Sharjah Department of Electrical Engineering Sharjah United Arab Emirates

ISBN: (数字)9781728173153

ISBN: (纸本)9781728120355

The estimation of the channel coefficients and the timing offset plays a critical role in the performance of asynchronous amplify-and-forward two-way relay networks. A highly accurate semi-blind algorithm for the joint estimation of the channel coefficients and the timing offset has recently been developed assuming generic pulse shaping filters. This algorithm is based on the expectation maximization (EM) framework, where the system is modeled using a hidden Markov model (HMM), and the posterior probabilities of the data are calculated using the Baum-Welch forward-backward algorithm. The high computational complexity of the Baum-Welch algorithm is the main challenge for real-time implementation of this algorithm. This challenge is addressed in this work by developing an efficient parallel implementation of the EM, including the Baum-Welch. Deep performance and time analysis are performed to study the opportunities for parallelization and choose the suitable technique. Using multithreading, we are able to achieve a maximum net speedup of 4.8X. © 2020 IEEE.

关键词： Channel estimation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：