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Exploring one-sided communication and synchronization on a non-cache-coherent many-core architecture

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2017年第15期29卷

作者： Christgau, Steffen Schnor, Bettina Univ Potsdam Inst Comp Sci August Bebel Str 89 D-14482 Potsdam Germany

the ongoing many-core design aims at core counts where cache coherence becomes a serious challenge. therefore, this paper discusses how one-sided communication and the required process synchronization can be realized on a non-cache-coherent many-core CPU. the Intel Single-chip Cloud Computer serves as an exemplary hardware architecture. the presented approach is based on software-managed cache coherence for MPI one-sided communication. the prototype implementation delivers a PUT performance of up to 5 times faster than the default message-based approach and reveals a reduction of the communication costs for the NAS Parallel Benchmarks 3-D fast Fourier Transform by a factor of 5. Further, the paper derives conclusions for future non-cache-coherent architectures.

关键词： MPI one-sided communication programming models and systems for many-cores synchronization software-managed cache coherence

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Motion Blurred Image Restoration Network Based on Insulator Defect Detection

Motion Blurred Image Restoration Network Based on Insulator ...

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China international Electrical and Energy conference (CIEEC)

作者： Le Chang Fafu Qin Xiangchun Luo Peng Li Department of Electrical Engineering of New Energy College China University of Petroleum (East China) Qingdao China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Motion blur generated during aerial photography by UAVs can lead to distortion of the target portion of the captured insulator image, which is not conducive to the subsequent positioning and defect detection of insulators. the motion blur caused by the relative motion between the aerial photography UAV and insulators is usually directional and non-uniform, and is optimized based on the Transformer model in terms of structure and objective function. the self-attention in the Transformer model is improved and combined with convolutional neural network to achieve efficient blurred insulator image restoration without relying on a large amount of training data. Contrast learning is introduced in the objective function part to fully utilize the correlation information between sharp and blurred insulator images. the motion blurred insulator image dataset is constructed for image restoration and defect detection experiments, and the results show that the proposed method outperforms the algorithms such as DeblurGAN-v2 and MIMO-UNet in terms of PSNR and SSIM, and the image quality is greatly improved.

关键词： Training Training data Insulators Linear programming Autonomous aerial vehicles Data models Image restoration

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Autonomous garbage collection: resolving memory leaks in long running network applications

Autonomous garbage collection: resolving memory leaks in lon...

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international conference on Computer Communications and Networks (ICCCN)

作者： B. Willard O. Frieder Electronics and Systems Integration Division Northrop Grumman Corporation Melbourne FL USA Department of Computer Science & Applied Mathematics Illinois Institute of Technology Chicago IL USA

ISBN: (纸本)0818690143

Garbage collection is especially useful for long running server applications in network environments since sustained memory leaks continuously degrade performance and eventually result in application failure. We demonstrate the benefits of a garbage collection technique that effectively mitigates performance degeneration due to memory leaks in applications when source code or object code are not available. Our technique is an extension of the garbage collection method known as conservative garbage collection. We refer to this as autonomous garbage collection. Our prototype demonstrates that this garbage collection technique is indeed feasible. Furthermore, our experimental results show that this technique is more general and easier to use than many of the previous garbage collection proposals targeted at resolving memory leaks in non-cooperative server applications.

关键词： Intelligent networks Random access memory Network servers programming profession Memory management Application software Read-write memory Telecommunication network reliability Degradation Prototypes

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Trajectory Optimization of Aircraft Based on Intelligent Bionic Algorithm

Trajectory Optimization of Aircraft Based on Intelligent Bio...

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IEEE international conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Qianchen Guo Anlan Yin Yichen Wang Harbin Engineering University Harbin China

ISBN: (数字)9798350377033

ISBN: (纸本)9798350377040

With the continuous advancement of AI intelligent algorithms, significant progress has been achieved in unmanned systems research. Among these, the intelligent selection of autonomous flight paths for unmanned aerial vehicles (UAVs) holds substantial research value. the application of bio-inspired intelligent algorithms to solve the optimal flight trajectory for UAVs is critically important. this study first establishes a spline interpolation model for UAV flight trajectories, deriving the mathematical expression of the trajectory based on multiple key points. Subsequently, a wolf pack optimization algorithm is developed to simulate and compute the optimal flight trajectory among infinite possible paths. Finally, comprehensive validation is conducted on the MATLAB simulation platform. Simulations under various initial conditions and scenarios with randomly generated obstacles demonstrate the ability to solve for the optimal flight path accurately. the results rigorously confirm the correctness of the algorithm's application and provide effective guidance for subsequent UAV flight path design.

关键词： Interpolation Biological system modeling Aerospace electronics programming Autonomous aerial vehicles Mathematical models Splines (mathematics) Aircraft MATLAB Trajectory optimization

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Optimal Design of Structural Parameters for Ladder-Type Secondary of Linear Induction Motor Based on Tabu Search Algorithm

Optimal Design of Structural Parameters for Ladder-Type Seco...

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China international Electrical and Energy conference (CIEEC)

作者： Zhuo Zhang Yumei Du Yongxian Liu Ruihua Zhang Liming Shi Zixin Li Key Laboratory of Power Electronics and Electric Drive Institute of Electrical Engineering Chinese Academy of Sciences University of Chinese Academy of Sciences China Beijing China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

In order to improve the performance of the long primary double sided linear induction motor (LP-DSLIM), the equivalent circuit of the ladder-type secondary LP-DSLIM is established under the condition of considering the longitudinal end effects. After determining the optimization variables of the ladder-type secondary of LP-DSLIM, the analytic expressions of thrust, efficiency, power factor and secondary weight and the multi-objective optimization function model are obtained. the thrust, efficiency, power factor and weight of the secondary are optimized under the constraints of the secondary thickness by the tabu search (TS) algorithm. the ladder-type secondary of LP-DSLIM 3D finite element model (FEM) is established, and the analytical optimization is compared with the finite element simulation, which proves the correctness of the optimization results.

关键词： Reactive power Analytical models Solid modeling Induction motors three-dimensional displays Search problems Linear programming

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Local Linear Fitting Method for Lidar Depth Completion Based on RGB Image Guidance

Local Linear Fitting Method for Lidar Depth Completion Based...

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Robotics, Control and Automation Engineering (RCAE), international conference on

作者： Xiaorong Sun Qinghua Zeng Sheng Hong Yineng Li Yan Wang Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

the depth image contains rich spatial information, which is crucial for simultaneous localization and mapping (SLAM) as well as accurate environmental perception. However, the original depth image is often sparse and contains small holes with missing depth values. In this paper, we have implemented point cloud depth image projection and proposed an RGB image guided completion method. Objects of the same class typically have similar color and depth values. Our local linear fitting method utilizes regions with similar colors to construct a completion objective function. Experiments in both indoor and outdoor scenes demonstrate that our method can generate a depth image with the same resolution as the RGB image. Analysis reveals that our method enhances the quality of depth image completion compared to traditional methods that rely solely on point cloud kernel dilation.

关键词： Point cloud compression Simultaneous localization and mapping Laser radar Image color analysis Fitting Linear programming Real-time systems Computational efficiency Kernel Robots

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Multi-stage Local Path Planning Algorithm Based on Obstacles as Anchor Points

Multi-stage Local Path Planning Algorithm Based on Obstacles...

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Advanced Algorithms and Control Engineering (ICAACE), international conference on

作者： Jianyi Zhu Xiaojun Wang Xianyu Qi Bin Lian Yanpeng Dong Beijing Institute of Mechanical Equipment Beijing China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

To address the problem of poor smoothness and solvability in dense obstacle scenarios of traditional local path planning algorithms for unmanned vehicles, a multi-stage local path planning algorithm based on obstacles as anchor points is proposed. First, the planning node digraph based on tree structure is constructed while multi-stage sampling points are set up when the solution space is generated, thus providing reference line fits by cubic spiral that can change in real time according to the position of obstacles. then, to generate smooth and safe local path for unmanned vehicle, quadratic planning algorithm based on multi-stage reference line as guidance to get local path. Simulation results show that the multi-stage local path planning algorithm with obstacles as anchor points can reduce the smoothness cost of planning path by 29%, the solution success rate is not less than 90% which suggests our method has stronger solvability compared with traditional path planning algorithms.

关键词： Spirals Costs Control engineering Simulation programming Path planning Real-time systems

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Optimization of reactive power support in Power Distribution Network - An economical based study

Optimization of reactive power support in Power Distribution...

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international conference on Electrical Energy Systems (ICEES)

作者： C. Kumar Reddy G. Srinivasan B.S. Lokasree Sree Vidyanikethan Engineering College A. Rangampet TIRUPATHI A.P IEEE CHENNAI CMR Institute of Technology Bangalore KARNATAKA

ISBN: (数字)9781728176123

ISBN: (纸本)9781728176130

It is well known that reactive power compensation at optimal nodes, helps in reduction of I 2 R loss and enhancement in bus voltage in Power Distribution Network (PDN) thereby, improvement in efficacy. this work considers financial benefit as objective function to find the optimal nodes for capacitor location and sizing in PDNs. Salp-Swarm Algorithm (SSA) has been engaged to achieve the maximum financial benefit with least capacitor cost by reducing the power loss under three different load levels (75%, 100% and 125%). SSA has been employed to two small radial PDNs and the outcomes are tabulated with the existing results under two categories (Power loss and cost). Considering 10-Bus and 15-Bus PDN, It has been observed that a maximum financial benefit have been observed under light, medium and heavy load levels. It is apparent that SSA yields better I 2 R loss reduction and financial benefit for PDNs despite its simplicity.

关键词： Reactive power Capacitors Linear programming Acceleration Resource management Optimization Convergence

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Quadruped Robot Motion Control Method Based on Adaptive Weight Coefficients MPC

Quadruped Robot Motion Control Method Based on Adaptive Weig...

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Advanced Algorithms and Control Engineering (ICAACE), international conference on

作者： Zhipeng Nan Lin Xu Chengleng Han Guorui Zhao Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

In real-world environments, quadruped robots often need to traverse unstructured terrains and may encounter various unexpected impacts. To enhance the motion balance performance of quadruped robots when facing unknown disturbances in such environments, we propose a fuzzy adaptive weight controller based on Model Predictive Control (MPC). By conducting an in-depth analysis of the impact of weight coefficients in the MPC's objective function on control effectiveness, we have designed an adaptive fuzzy algorithm. this algorithm dynamically adjusts the weight coefficients according to the current errors in the robot's roll and pitch angles, as well as their rates of change. Subsequently, the MPC controller calculates the optimal control torques using these adjusted weight coefficients. To validate the effectiveness of this strategy, we conducted simulations of lateral impacts and walking on unstructured terrains in Gazebo. the simulation results demonstrate that, under various test conditions, the proposed adaptive weight MPC controller significantly improves the robot's motion stability, showcasing its strong capability to handle unknown disturbances.

关键词： Robot motion Adaptation models Heuristic algorithms Prediction algorithms Aerodynamics Linear programming Stability analysis

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SPECTRA Phones: Systematic Personalized Evaluation for Comprehensive Technological Recommendations and Advancements in Phones

SPECTRA Phones: Systematic Personalized Evaluation for Compr...

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international conference on Informatics and Computational Sciences (ICICoS)

作者： Robert G. De Luna Paolo C. Batingan Benedict B. Berbon Mark Joseph Kish Kerby M. Pecayo Renz Justine L. Villegas Polytechnic University of the Philippines Sto. Tomas City Batangas Philippines

ISBN: (数字)9798350375886

ISBN: (纸本)9798350375893

Deciding and purchasing phones becomes crucial in tech-illiterate individuals. Buying phones circulates in a usual manner like acquiring it as soon as it is introduced by the sales officers. Having no further knowledge upon buying might lead to a regretful decision. this study presents application of machine learning techniques such as Cosine Similarity, K-nearest Neighbor, Ball Tree, and Compressed Sparse Row (CSR) Matrix Algorithm in recommending smart phones to consumers based on their personal preferences and requirements. the system undergoes the process of Python programming and GUI implementation to achieve the said inclinations and to have a clear and real-time vision of the purchasing process. the selection process of algorithm revolves only on the abovementioned categories. the models were evaluated using precision, recall, and F1-score evaluation metrics. According to the results presented, Cosine Similarity appears to be the most appropriate recommendation model garnering a score of 71.43 %, 100%, and 83.33% for average of precision, recall, and f1-score respectively.

关键词： Measurement Systematics Machine learning algorithms Machine learning programming Nearest neighbor methods Real-time systems

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