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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Jincheng Yu Feng Gao Jianfei Cao Chao Yu Zhaoliang Zhang Zhengfeng Huang Yu Wang Huazhong Yang Electronic Engineering Department Tsinghua University Beijing China School of Microelectronics Hefei University of Technology Hefei China

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

Decentralized visual simultaneous localization and mapping (DSLAM) can share locations and environmental information between robots, which is an essential task for many multi-robot applications. The visual odometry (VO) is a basic component to estimate the 6-DoF absolute pose for robot applications. Decentralized place recognition (DPR) is a fundamental element to produce candidate place matches for sharing information among different robots. The goal of this paper is to build a CNN-based real-time DSLAM system on embedded FPGA platforms. Because of the high precision requirement of VO, the existing quantization methods can not be directly applied. We improve the fixed-point fine-tune method for the CNN-based monocular VO, which enables VO can be deployed on the fixed-point FPGA accelerator. We also explore the influence of the DPR frequency on the DSLAM results, and find out a proper DPR frequency to balance the accuracy and speed. A cross-component pipeline scheduling method is proposed to improve DPR frequency and further improve the final accuracy of DSLAM under the same hardware resource constraints.

关键词： Robots Field programmable gate arrays Cameras image reconstruction Quantization (signal) Hardware Feature extraction

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Cloud-based difference algorithm using big GPR data for roadbed damage detection

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2020年第23期32卷 e5545-e5545页

作者： Xu, Xianlei Gao, Wenru Zhang, Di Li, Taotao Qiao, Xu State Key Lab Water Resources Protect & Utilizat Beijing Peoples R China China Univ Min & Technol Beijing State Key Lab Coal Resources & Safe Min Beijing 100083 Peoples R China China Univ Min & Technol Beijing Sch Mech Elect & Informat Engn Beijing Peoples R China

Ground-penetrating radar (GPR) technology is being widely used for urban roadbed damage detection. In this paper, we present the development of a cloud-based difference detection method using big GPR data for roadbed damage detection. Unlike many processing methods relying on standalone servers, the proposed method can achieve high accuracy and processing efficiency by distributing the computation over a server cluster. The method includes a difference detection algorithm for GPR image enhancement and damage extraction, the Hadoop distributed File System, and MapReduce distributed parallel computing framework for big GPR data parallel processing and interpretation. Moreover, to automatize roadbed damage classification, a criterion with seven grades is established based on the wave group shape, amplitude, phase, and attenuation characteristics. We validate the proposed method through a detection experiment that was conducted on the Fourth Ring Road in Beijing, China. The detection revealed 187 damage from the efficient processing of big GPR data, thus suggesting the ability of the proposed method to provide timely support for road safety in cities.

关键词： cloud computing difference detection GPR parallel computation roadbed damage detection

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Rank differences of signals by weighing-selection processing method for implementation of multifunctional image processing processor 4

Rank differences of signals by weighing-selection processing...

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Conference on Emerging Imaging and Sensing Technologies for Security and Defence iv part of SPIE Security + Defence Symposium

作者： Krasilenko, Vladimir G. Lazarev, Alexander A. Nikitovich, Diana V. Vinnitsa Social Econ Inst 86-131 Kelestskaya Str UA-21021 Vinnitsa Ukraine Vinnitsa Natl Tech Univ Vinnytsia Ukraine

ISBN: (数字)9781510630307

ISBN: (纸本)9781510630307;9781510630291

In this paper, we proposed a new iterative process of sorting an array of signals, which differs from the known structures of sorting signals by uniformity, versatility, which allows direct and inverse sorting of an array of analog or digital signals. The basic elements of the proposed sorting structures are simple relational nodes. Such elements can be implemented on a different element basis, including, on devices for selecting a maximum or minimum of two analog or digital signals, which are implemented on CMOS current mirrors and carry out the limited difference function of continuous logic. We offered implementation of homogeneous sorting structure on such elements, consisting of two layers and a multichannel sampling and holding device. Nine signals corresponding to a selection window of a matrix sensor are fed to this structure, we sort them in five iterative steps, and at the output we receive the signals sorted by the rank, which, using the code controlled programmable multiplexer, generates an output signal, corresponding to the selected rank. We evaluated the technical parameters of such a relational preprocessor. The base cells consist of no more than 20 CMOS 1.5 mu m transistors, the total power consumption of the sorting node on 10 continuously logical base cells (CL BC) is 2mW, the supply voltage is 1.8 divided by 3.3V, the range of an input photocurrent is 0.1o24 mu A, the conversion cycle is 10 mu s. The paper considers results of design and modeling of CL BC based on current mirrors (CM) for creating picture type image processors (IP) with matrix parallel inputs-outputs. Such sorting nodes based on them have a number of advantages: high speed and reliability, simplicity, small power consumption, high integration level. The inclusion of an iterative node for sorting signals into a modified nonlinear IP structure makes it possible to significantly simplify its design and increase the functional capabilities of such processor. The simulation results co

关键词： analog relational preprocessor image nonlinear processing simulation continuous logic current mirror sorting networks methods of selection and rank preprocessing rank filtering

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An improved MCB localization algorithm based on received signal strength indicator 20

An improved MCB localization algorithm based on received sig...

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20th International Conference on parallel and distributed Computing, Applications and Technologies, PDCAT 2019

作者： Qiao, Yan Chunyue, Zhou Baitong, Zhong Hui, Tian School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Laboratory of Communication Engineering Beijing Jiaotong University Beijing China Institute of Image Communication and Network Engineering Uniview Hangzhou Zhejiang Province China School of Information and Communication Technology Griffith University Australia

ISBN: (纸本)9781728126166

An improved Monte Carlo Localization Boxed (MCB) localization Algorithm based on received signal strength indicator (RSSI) for mobile wireless sensor networks node localization is proposed. Aiming at the characteristics of instantaneity, mobility and complexity of mobile node location, this algorithm combines RSSI ranging model with MCL algorithm which has high positioning accuracy, good performance and wide application. It establishes anchor node sampling box by using the actual distance of signal propagation obtained, and effectively reduces the sampling range. The simulation results show that this algorithm improves the sampling efficiency, shortens the sampling time, and increases the positioning accuracy compared to the MCL algorithm. It is a low-cost, low-power and low-complexity localization algorithm without additional hardware and communication overhead. © 2019 IEEE.

关键词： Monte Carlo methods

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Challenges of Ship Focusing with Long Coherence processing Interval 39

Challenges of Ship Focusing with Long Coherence Processing I...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Liu, WenKang Xing, MengDao Sun, Guang-Cai Xidian Univ Xian 710071 Peoples R China

ISBN: (纸本)9781538691540

Ship oscillatory motions with long coherence processing interval (CPI) are complex and hard to accurately estimate. The traditional ship imaging methods usually avoid long-CPI focusing by dealing with a short observation time interval, which may make it hard to obtain a high-resolution and high-SNR image. In this paper, the mechanisms and challenges of long CPI imaging of oscillatory targets are investigated. The properties of wavenumber domain support (WDS) and point spreading function (PSF) of oscillatory targets are analyzed. It's found that the WDS spreads as a three-dimensional (3D) thin and curved sweep surface, with time-variant energy density, non-parallel boundaries and a complex structure. The PSF of an oscillatory target has a 3D resolution, but also multiple side-lobes with high level. We inspect the relationships between the properties of the WDS and the non-ideal PSF. Moreover, it's found that scatters distributed on a 3D oscillatory target cannot be focused uniformly on a predefined imaging plane (IP). The projection relationship of the target focusing positions on the slant-range plane (SRP) and the IP are also derived. The simulation results can well validate the proposed method.

关键词： ship image 3D oscillatory motion long coherence processing interval (long-CPI) imaging

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parallel image encryption with bitplane decomposition and genetic algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第19期77卷 25799-25819页

作者： Mozaffari, Saeed Semnan Univ Fac Elect & Comp Engn Semnan Iran

image encryption is an efficient technique to protect image content from unauthorized parties. In this paper a parallel image encryption method based on bitplane decomposition is proposed. The original grayscale image is converted to a set of binary images by local binary pattern (LBP) technique and bitplane decomposition (BPD) methods. Then, permutation and substitution steps are performed by genetic algorithm (GA) using crossover and mutation operations. Finally, these scrambled bitplanes are combined together to obtain encrypted image. Instead of random population selection in GA, a deterministic method with security keys is utilized to improve security level. The proposed encryption method has parallel processing capability for multiple bitplanes encryption. This distributed GA with multiple populations increases encryption speed and makes it suitable for real-time applications. Simulations and security analysis are done to demonstrate efficiency of our algorithm.

关键词： parallel image encryption Bitplain decomposition Local binary pattern Metaheuristic algorithms parallel genetic algorithm GPU programming

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Fast Nonlocal Diffusion by Stacking Local Filters for image Denoising 5th

Fast Nonlocal Diffusion by Stacking Local Filters for Image ...

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5th International Conference of Pioneer Computer Scientists, Engineers and Educators, ICPCSEE 2019

作者： Qiao, Peng Sun, Weichu Dou, Yong Li, Rongchun Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology ChangshaHunan410073 China University of South China HengyangHunan421000 China

ISBN: (纸本)9789811501203

Many image denoising methods achieve state-of-the-art performance with little consideration of computation efficiency. With the popularity of high-definition imaging devices, these denoising methods do not scale well to the high-definition images. Therefore, a fast image denoising method is proposed to meet the demand of processing high-definition images. Based on the analysis of the distribution of the distance distrs between the similar patches and their reference patches from a semantic aspect, the large distrs s was found to occur while their contribution to the overall distribution was small. Therefore, the nonlocal filters was replaced in trainable non-local reaction diffusion (TNLRD) with local filters. For image with 4096 X 4096 resolution, the proposed method runs about 6 times faster than TNLRD via a single-thread CPU implementation. And the GPU implementation of the proposed method is about 10 times faster than the CPU implementation. Furthermore, the proposed model achieves competing denoising performance compared with TNLRD in terms of PSNR and SSIM. © Springer Nature Singapore Pte Ltd. 2019.

关键词： image denoising

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Virtual-Real Fusion processing Based on parallel Distribution 14th

Virtual-Real Fusion Processing Based on Parallel Distributio...

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14th Conference on image and Graphics Technologies and Applications, IGTA 2019

作者： Zhai, Hongyu Zhang, Tongtong Xu, Richeng School of Computer Science and Technology Changchun University of Science and Technology ChangchunJilin130022 China

ISBN: (纸本)9789811399169

For the demand of domestic digital film industry to improve the quality and efficiency of special effects film and television works, This paper studies the transmission quality of virtual and real fusion and the fusion efficiency, and proposes a better video transmission method combined with virtual and real fusion technology, which made the digital video industry more complete. Firstly, the Hadoop platform is built as the basis of distributed transmission, and then the parallel distributed transmission method and the virtual and real fusion technology proposed in this paper are combined to complete the experiment. In this paper, the efficiency of this method is compared with other existing advanced transmission methods. The experimental results show that the efficiency and transmission quality are improved compared with other methods. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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Error Resilient GPU Accelerated image processing for Space Applications

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IEEE TRANSACTIONS ON parallel AND distributed SYSTEMS 2018年第9期29卷 1990-2003页

作者： Davidson, R. L. Bridges, C. P. Univ Surrey Surrey Space Ctr Guildford GU2 7XH Surrey England

Significant advances in spaceborne imaging payloads have resulted in new big data problems in the Earth Observation (EO) field. These challenges are compounded onboard satellites due to a lack of equivalent advancement in onboard data processing and downlink technologies. We have previously proposed a new GPU accelerated onboard data processing architecture and developed parallelised image processing software to demonstrate the achievable data processing throughput and compression performance. However, the environmental characteristics are distinctly different to those on Earth, such as available power and the probability of adverse single event radiation effects. In this paper, we analyse new performance results for a low power embedded GPU platform, investigate the error resilience of our GPU image processing application and offer two new error resilient versions of the application. We utilise software based error injection testing to evaluate data corruption and functional interrupts. These results inform the new error resilient methods that also leverages GPU characteristics to minimise time and memory overheads. The key results show that our targeted redundancy techniques reduce the data corruption from a probability of up to 46 percent to now less than 2 percent for all test cases, with a typical execution time overhead of 130 percent.

关键词： GPU parallel processing error resilience EO image processing image compression onboard satellites

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New Performance Modeling methods for parallel Data processing Applications

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ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION 2019年第3期29卷 15-15页

作者： Bhimani, Janki Mi, Ningfang Leeser, Miriam Yang, Zhengyu Northeastern Univ 360 Huntington Ave Boston MA 02115 USA

Predicting the performance of an application running on parallel computing platforms is increasingly becoming important because of its influence on development time and resource management. However, predicting the performance with respect to parallel processes is complex for iterative and multi-stage applications. This research proposes a performance approximation approach FiM to predict the calculation time with FiM-Cal and communication time with FiM-Com of an application running on a distributed framework. FiM-Cal consists of two key components that are coupled with each other: (1) a Stochastic. Markov Model to capture non-deterministic runtime that often depends on parallel resources, e.g., number of processes, and (2) a machine-learning model that extrapolates the parameters for calibrating our Markov model when we have changes in application parameters such as dataset. Along with the parallel calculation time, parallel computing platforms consume some data transfer time to communicate among different nodes. FiM-Com consists of a simulation queuing model to quickly estimate communication time. Our new modeling approach considers different design choices along multiple dimensions, namely (i) process-level parallelism, (ii) distribution of cores on multi-processor platform, (iii) application related parameters, and (iv) characteristics of datasets. The major contribution of our prediction approach is that FiM can provide an accurate prediction of parallel processing time for the datasets that have a much larger size than that of the training datasets. We evaluate our approach with NAS parallel Benchmarks and real iterative data processing applications. We compare the predicted results (e.g., end-to-end execution time) with actual experimental measurements on a real distributed platform. We also compare our work with an existing prediction technique based on machine learning. We rank the number of processes according to the actual and predicted results from FLM an

关键词： Performance modeling queuing theory Markov model distributed systems execution time parallel calculation communication network prediction

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