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38th International Conference on High Performance Computing, ISC High Performance 2023

作者： Dabah, Adel Ltaief, Hatem Rezki, Zouheir Alouini, Slim Keyes, David Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal Jeddah23955 Saudi Arabia University of California Santa Cruz 1156 High Street Santa CruzCA95064 United States

ISBN: (纸本)9783031320408

Massive Multiple-Input Multiple-Output (M-MIMO) uses hundreds of antennas in mobile communications base stations to increase the amount of transmitted data and the number of connected devices in 5G and beyond. However, M-MIMO systems increase the complexity of recovering the transmitted data (detection phase). To address this challenge, we leverage low-precision arithmetic in recent NVIDIA GPUs to improve the latency/scalability/accuracy of M-MIMO detection. We propose a GPU tree-based detection algorithm that aggregates multiple tree levels and formulates the computation as a matrix multiplication operation followed by a square-norm calculation and sorting (reduction) phase. This process is repeated until reaching the last level of the detection tree. The obtained results show near-optimal data detection with a 10 × speedup compared to a two-socket 28-core IceLake CPU implementation. We further deploy low-precision arithmetic operations. We show that moving from single-precision 32-bit floating-point arithmetic (FP32) to half-precision 16-bit representation (FP16) does not affect the accuracy performance while translating into an additional 1.7 × speedup. In addition, exploiting 8-bit integer representation results in an acceptable error rate degradation that can be compensated by increasing the number of aggregated levels. In addition, we propose a multi-GPU version that computes the matrix-multiplication operation of subsequent iterations in parallel. This latter operation represents more than 80% of the elapsed time for dense constellations. Results with four A100 GPUs show an additional 2.3 × relative speedup compared to our single GPU version. The achieved accuracy/scalability balance may accelerate the deployment of this technology and promote low-precision GPU computations within the wireless communication community. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphics processing unit

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Parallel Approximations for High-Dimensional Multivariate Normal Probability Computation in Confidence Region Detection Applications

arXiv

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arXiv 2024年

作者： Zhang, Xiran Abdulah, Sameh Cao, Jian Ltaief, Hatem Sun, Ying Genton, Marc G. Keyes, David E. Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Statistics Program King Abdullah University of Science and Technology Saudi Arabia Extreme Computing Research Center King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematics The University of Houston HoustonTX United States

Addressing the statistical challenge of computing the multivariate normal (MVN) probability in high dimensions holds significant potential for enhancing various applications. For example, the critical task of detecting confidence regions where a process probability surpasses a specific threshold is essential in diverse applications, such as pinpointing tumor locations in magnetic resonance imaging (MRI) scan images, determining hydraulic parameters in groundwater flow issues, and forecasting regional wind power to optimize wind turbine placement, among numerous others. One common way to compute high-dimensional MVN probabilities is the Separation-of- Variables (SOV) algorithm. This algorithm is known for its high computational complexity of O(n3) and space complexity of O(n2), mainly due to a Cholesky factorization operation for an n × n covariance matrix, where n represents the dimensionality of the MVN problem. This work proposes a high-performance computing framework that allows scaling the SOV algorithm and, subsequently, the confidence region detection algorithm. The framework leverages parallel linear algebra algorithms with a task-based programming model to achieve performance scalability in computing process probabilities, especially on largescale systems. In addition, we enhance our implementation by incorporating Tile Low-Rank (TLR) approximation techniques to reduce algorithmic complexity without compromising the necessary accuracy. To evaluate the performance and accuracy of our framework, we conduct assessments using simulated data and a wind speed dataset. Our proposed implementation effectively handles high-dimensional multivariate normal (MVN) probability computations on shared and distributed-memory systems using finite precision arithmetics and TLR approximation computation. Performance results show a significant speedup of up to 20X in solving the MVN problem using TLR approximation compared to the reference dense solution without sacrificing the

关键词： Statistics

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UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Communications Based on DRL 100

UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Commu...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Hu, Jiawei Ju, Ying Wang, Haoyu Liu, Lei Pei, Qingqi Shee, Y.G. Zhu, Xiaojie Wu, Celimuge University of California Department of Electrical Engineering and Computer Science IrvineCA92697 United States Xidian University Guangzhou Institute of Technology Guangzhou510555 China Xi'an University of Posts Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China Universiti Tunku Abdul Rahman Department of Electrical and Electronic Engineering Kajang43000 Malaysia King Abdullah University of Science and Technology Department of Computer Electrical and Mathematical Sciences and Engineering Thuwal239556900 Saudi Arabia The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182-8585 Japan

ISBN: (纸本)9798331517786

Ensuring reliable communication can be incredibly challenging in emergencies due to the breakdown of conventional infrastructure. However, a promising solution is on the horizon: the integration of reconfigurable intelligent surfaces (RIS) onto unmanned aerial vehicles (UAV), known as UAV-RIS. This innovative approach holds the potential to offer agile and adaptable communication services during crises, overcoming the limitations of traditional systems. This paper establishes an innovative UAV-RIS system with an active RIS to enhance the uplink communication between ground devices (GDs) and the air base station (ABS). We present an advanced communication strategy utilizing deep reinforcement learning (DRL) for UAV-RIS-supported uplink communication in dynamic emergencies. This scheme is designed to optimize the energy efficiency of the UAV-RIS communication system while adhering to quality of service (QoS) constraints for all GDs. It achieves this by jointly optimizing the trajectory of the UAV-RIS and the phase of the active RIS, ensuring efficient and reliable communication in challenging environments. To optimize the performance of the system, we propose a hierarchical Proximal Policy Optimization (H-PPO) algorithm and the upper and lower layers of H-PPO optimize the trajectory and phase control, respectively. Simulation results demonstrate that our scheme can effectively learn the communication strategy to enhance the performance of dynamic emergency communication networks. © 2024 IEEE.

关键词： active reconfigurable intelligent surface deep reinforcement learning quality of service UAV trajectory

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An Improved Unbiased Particle Filter

arXiv

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arXiv 2023年

作者： Jasra, Ajay Maama, Mohamed Ombao, Hernando Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. We assume that, for numerical reasons, one has to time-discretize the diffusion process which typically leads to filtering that is subject to discretization bias. The approach in [16] establishes that when only having access to the time discretized diffusion it is possible to remove the discretization bias with an estimator of finite variance. We improve on the method in [16] by introducing a modified estimator based on the recent work of [17]. We show that this new estimator is unbiased and has finite variance. Moreover, we conjecture and verify in numerical simulations that substantial gains are obtained. That is, for a given mean square error (MSE) and a particular class of multi-dimensional diffusion, the cost to achieve the said MSE falls. Copyright © 2023, The Authors. All rights reserved.

关键词： Mean square error

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Tuning Rate of Strategy Revision in Population Games

Tuning Rate of Strategy Revision in Population Games

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American Control Conference (ACC)

作者： Shinkyu Park Electrical and Computer Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

We investigate a multi-agent decision problem in population games where each agent in a population makes a decision on strategy selection and revision to engage in repeated games with others. The strategy revision is subject to time delays which represent the time it takes for an agent revising its strategy needs to spend before it can adopt a new strategy and return back to the game. We discuss the effect of the time delays on long-term behavior of the agents’ strategy revision. In particular, when the time delays are large, the strategy revision would exhibit oscillation and the agents spend substantial time in "transitioning" between different strategies, which prevents the agents from attaining the Nash equilibrium of the game. As a main contribution of the paper, we propose an algorithm that tunes the rate of the agents’ strategy revision and show such tuning approach ensures convergence to the Nash equilibrium. We validate our analytical results using simulations.

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Conversion of twisted light to twisted excitons using carbon nanotubes

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npj Computational Materials 2022年第1期8卷 392-402页

作者： Xiaoning Zang Nirpendra Singh Mark T.Lusk Udo Schwingenschlögl Applied Physics Program Physical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal23955-6900Saudi Arabia Department of Physics Khalifa University of Science and TechnologyAbu Dhabi127788United Arab Emirates Department of Physics Colorado School of MinesGoldenCO80401USA

Carbon nanotubes are explored as a means of coherently converting the orbital angular momentum of light to an excitonic form that is more amenable to quantum information *** analytical analysis,based on dynamical conductivity,is used to show that orbital angular momentum is conserved,modulo N,for a carbon nanotube illuminated by radially polarized,twisted *** result is numerically demonstrated using real-time time-dependent density functional theory which captures the absorption of twisted light and the subsequent transfer of twisted *** results suggest that carbon nanotubes are promising candidates for constructing optoelectronic circuits in which quantum information is more readily processed while manifested in excitonic form.

关键词： twisted carbon light

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Recent advances in coherent perfect absorber-lasers and their future applications

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Journal of Central South university 2022年第10期29卷 3203-3216页

作者： YANG Min-ye YE Zhi-lu ZHU Liang FARHAT Mohamed CHEN Pai-Yen Department of Electrical and Computer Engineering University of Illinois at ChicagoChicagoIL 60607United States Computer Electricaland Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia

In recent years, peculiar physical phenomena enabled by non-Hermitian systems, especially the parity-time(PT)-symmetric systems, have drawn tremendous research interests. Particularly, special spectral degeneracies known as exceptional points(EPs) and coherent perfect absorber-laser(CPAL) points where zero and infinite large eigenvalues coexist are the most popular topics to be studied. To date, the discussions of EPs that serve as transition boundaries between broken PT-symmetry phase and exact PT-symmetry phase have been intensively presented. However, the theoretical analysis and experimental validations of CPAL points are inadequate. Different from EPs, CPAL points, as a special solution of broken PT-symmetry phase, may exhibit even further counterintuitive physical features, which may have significant implications to study non-Hermitian physics. Here, we review some recent advances of CPAL phenomena in different sub-disciplines of physics, including optics, electronics and electromagnetics, and ***, we also provide an envision of future directions and applications of CPAL systems.

关键词： parity-time symmetry coherent-perfect absorber-laser spectral singularities non-Hermitian physics

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A Robust Data Hiding Reversible Technique for Improving the Security in e-Health Care System

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computer Modeling in engineering & sciences 2023年第1期134卷 201-219页

作者： Saima Kanwal Feng Tao Ahmad Almogren Ateeq Ur Rehman Rizwan Taj Ayman Radwan School of Computer and Communication Lanzhou University of TechnologyLanzhou730050China Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11633Saudi Arabia Department of Electrical Engineering Government College UniversityLahore54000Pakistan Instituto de Telecomunicaoes and Universidade de Aveiro Aveiro3810-193Portugal

The authenticity and integrity of healthcare is the primary *** reversible watermarking schemes have been developed to improve the primary objective but increasing the quantity of embedding data leads to covering image distortion and visual quality resulting in data security detection.A trade-off between robustness,imperceptibility,and embedded capacity is difficult to achieve with current algorithms due to limitations in their *** this purpose insight,an improved reversibility watermarking methodology is proposed to maximize data embedding capacity and imperceptibility while maintaining data security as a primary concern.A key is generated by a random path with minimum bit flipping is selected in the 4 × 4 block to gain access to the data embedding *** random path's complex structure ensures data *** of various sizes(8 KB,16 KB,32 KB)are used to analyze image imperceptibility and evaluate quality *** proposed reversible watermarking methodology performance is tested under standard structures PSNR,SSIM,and *** results revealed that the MRI watermarked images are imperceptible,like the cover image when LSB is 3 bits *** proposed reversible watermarking methodology outperforms other related techniques in terms of average PSNR(49.29).Experiment results show that the suggested reversible watermarking method improves data embedding capacity and imperceptibility compared to existing state-of-the-art approaches.

关键词： Medical images security data hiding LSB matching hiding capacity imperceptibility

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On biased compression for distributed learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 12974-13023页

作者： Aleksandr Beznosikov Samuel Horváth Peter Richtárik Mher Safaryan Computer Electrical and Math. Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal KSA and Skolkovo Institute of Science and Technology Moscow Russia and School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Moscow Russia Computer Electrical and Math. Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal KSA

In the last few years, various communication compression techniques have emerged as an indispensable tool helping to alleviate the communication bottleneck in distributed learning. However, despite the fact biased compressors often show superior performance in practice when compared to the much more studied and understood unbiased compressors, very little is known about them. In this work we study three classes of biased compression operators, two of which are new, and their performance when applied to (stochastic) gradient descent and distributed (stochastic) gradient descent. We show for the first time that biased compressors can lead to linear convergence rates both in the single node and distributed settings. We prove that distributed compressed SGD method, employed with error feedback mechanism, enjoys the ergodic rate $O\left( \delta L \exp[-\frac{\mu K}{\delta L}] + \frac{(C + \delta D)}{K\mu}\right)$, where δ ≥1 is a compression parameter which grows when more compression is applied, L and µ are the smoothness and strong convexity constants, C captures stochastic gradient noise (C = 0 if full gradients are computed on each node) and D captures the variance of the gradients at the optimum (D = 0 for over-parameterized models). Further, via a theoretical study of several synthetic and empirical distributions of communicated gradients, we shed light on why and by how much biased compressors outperform their unbiased variants. Finally, we propose several new biased compressors with promising theoretical guarantees and practical performance.

关键词： compression operators biased compressors distributed learning linear convergence error feedback

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Modeling and Simulation of Grid-Connected PV System Faults Using MATLAB/Simulink

Modeling and Simulation of Grid-Connected PV System Faults U...

引用

Learning and technology Conference (L&T)

作者： Mayar Alkhawaja Sandy Miguel Moutaz Abu Shabab Muhy Eddin Za’Ter Majd Ghazi Batarseh Electrical Engineering Department Princess Sumaya University for Technology Amman Jordan Now With the Electrical and Computer Engineering King Abdullah University of Science and Technology Saudia Arabia Now With the College of Engineering and Computer Science University of Central Florida Orlando USA Electrical and Computer Engineering University of Colorado Boulder Boulder USA

ISBN: (数字)9798331532215

ISBN: (纸本)9798331532222

Grid-connected photovoltaic (PV) systems are crucial to modern renewable energy strategies, but various types of faults can significantly impact their performance. Understanding the behavior of these faults is essential for improving system reliability and reducing maintenance costs. This paper investigates the impact of common faults, including open-circuit, short-circuit, partial shading, and grid faults, by simulating them using MATLAB/Simulink. The focus is on modeling faults that lead to power output reduction. The simulation results demonstrate how different fault types affect critical system parameters, such as grid voltage and active power output. The study highlights the value of simulation as a flexible approach for exploring fault scenarios, providing insights into fault detection and mitigation strategies that can help optimize PV system performance and support the development of robust fault data collection, detection, and classification techniques.

关键词： Renewable energy sources Costs Fault detection Prevention and mitigation System performance Simulation Voltage Real-time systems Maintenance MATLAB

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