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Design and Implementation of distributed Video AI Super-Resolution Reconstruction System 26

Design and Implementation of Distributed Video AI Super-Reso...

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26th ACIS international Winter conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing, SNPD-Winter 2023

作者： Shang, Jingtao Guo, Yangliu Zhou, Taolong Li, Wei China North Vehicle Research Institute Beijing China Communication University of China School of Computer and Cyber Sciences Beijing China China Industrial Control Systems Cyber EmergencyResponse China

ISBN: (纸本)9798350345865

This article proposes a distributed video AI super-resolution reconstruction solution based on MapReduce to address the issue of slow video super-resolution reconstruction in a single-machine environment. The solution utilizes scene detection algorithms and precise video segmentation algorithms to divide long videos into multiple video segments based on scenes. These segments are then assigned to different processing nodes for parallel processing, and finally merged to reduce the time required for video AI super-resolution reconstruction. Experimental results demonstrate that this solution effectively improves the speed of video AI super-resolution reconstruction. In addition, this article addresses the issues of low efficiency and low storage space utilization in the distributed storage system HDFS (Hadoop distributed File System) when storing small files, specifically video segments. It proposes an optimized storage solution based on HDFS and Redis. This solution merges small files and constructs a small file merging and storage model on Redis, effectively alleviating the memory pressure on the NameNode in HDFS when storing a massive number of small files. Experimental results demonstrate that this solution sacrifices a certain degree of read/write performance but mitigates the rapid growth of NameNode memory. This solution holds significant theoretical and practical significance. © 2023 IEEE.

关键词： Image segmentation

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Slim-MY: A Lightweight Network for Power Line Defect Detection with FPGA Acceleration 29

Slim-MY: A Lightweight Network for Power Line Defect Detecti...

引用

29th IEEE international conference on parallel and distributed systems, ICPADS 2023

作者： Zhang, Xiaoyang Chen, Wenjie Zhou, Zihao Duan, Zhuowen East China Normal University MoE Engineering Research Center for Software/Hardware Co-Design Technology and Application Shanghai China

ISBN: (纸本)9798350330717

The power line is a crucial component of the power system. However, long-term exposure to the natural environment can lead to various defects, such as burrs, corrosion, and corona. These defects seriously threaten the safe operation of the power system. Traditional manual inspections and image processing methods are time-consuming, labor-intensive, and have lower accuracy. In light of these, we propose a lightweight network called Slim-MY. It utilizes lightweight feature extraction and fusion modules, significantly reducing computational and parameter overhead while ensuring defect detection accuracy. Furthermore, to accelerate the post-processing process, we propose the FP-NMS algorithm. It parallelizes the sorting and overlapping box removal parts of the NMS algorithm, making it more suitable for deployment on devices that support parallel computing, such as FPGA. By testing on our dataset of power line defects, the Slim-MY network achieves a detection accuracy and computation of 92.7% and 1.1 GFLOPs respectively, which outperforms most other networks. By accelerating on the KV260 FPGA, the Slim-MY network achieves an inference speed of 94 fps, and the FP-NMS algorithm's execution speed is 14.8 times that of the GTX 1080Ti. It indicates the feasibility and efficiency of the method we propose in power line defect detection tasks. © 2023 IEEE.

关键词： Deep Learning Defect Detection FPGA parallel Computing

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Efficient Dynamic Multi-key FHE Scheme from LWE for Untrusted Cloud Environments 29

Efficient Dynamic Multi-key FHE Scheme from LWE for Untruste...

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29th IEEE international conference on parallel and distributed systems, ICPADS 2023

作者： Zeng, Shuchang Hsu, Chingfang Cui, Jianqun Xie, Wei Hou, Qihang Computer School Central China Normal University Wuhan430079 China Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning Central China Normal University Wuhan430079 China School of Computer Central China Normal University Wuhan430079 China

ISBN: (纸本)9798350330717

Fully Homomorphic Encryption (FHE) provides a good solution to directly operate on the ciphertext, and the decryption result is equivalent to the corresponding operation on the plaintext. As a technique suitable for distributed environments, multi-key Fully Homomorphic Encryption (MKFHE) scheme is the most common variant of the FHE scheme since it allows encrypted data to be computed under different keys. Unfortunately, the existing dynamic MKFHE schemes based on learning with errors (LWE) still suffer from the inefficiency of long public keys, which typically grow cube in size along the lattice dimension. Moreover, there current constructions fail to provide reliable and fast algorithms to simultaneously expand ciphertexts with multiple additional keys. In order to solve the above problems, a new faster dynamic MKFHE scheme with shorter public key in asymmetric key setting from LWE is proposed in this paper, in which the size of the public key is further reduced from ∼ O( n3(K + L)2 ) to ∼O( n2(K + L)2 ). In addition, our scheme cleverly adopts the dual-user cooperation method in distributed system to realize the ciphertext expansion locally, thereby reducing the computing overhead of the cloud server. More interestingly, we design a flexible parallel ciphertext expansion algorithm for the first time based on the basic algorithm. This algorithm realizes the ciphertext expansion when multiple keys are added at the same time, thus significantly improving the computational efficiency of ciphertext expansion in the dynamic MKFHE scheme. Finally, the CPA-secure of our scheme based on standard LWE assumptions is proven. © 2023 IEEE.

关键词： Ciphertext expansion distributed GSW Lattice-based cryptography Learning with errors Multi-key fully homomorphic encryption Post-quantum

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Fast Grid Emissions Sensitivities using parallel Decentralized Implicit Differentiation

Fast Grid Emissions Sensitivities using Parallel Decentraliz...

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2024 international conference on Communications Control and Computing Technologies for Smart Grids

作者： Degleris, Anthony Valenzuela, Lucas Fuentes Rajagopal, Ram Pavone, Marco El Gamal, Abbas Stanford Univ Dept Elect Engn Stanford CA 94305 USA Stanford Univ Dept Civil & Environm Engn Stanford CA USA Stanford Univ Dept Aeronaut & Astronaut Stanford CA USA

ISBN: (纸本)9798350318562;9798350318555

Marginal emissions rates-the sensitivity of carbon emissions to electricity demand-are important for evaluating the impact of emissions mitigation measures. Like locational marginal prices, locational marginal emissions rates (LMEs) can vary geographically, even between nearby locations, and may be coupled across time periods because of, for example, storage and ramping constraints. This temporal coupling makes computing LMEs computationally expensive for large electricity networks with high storage and renewable penetrations. Recent work demonstrates that decentralized algorithms can mitigate this problem by decoupling timesteps during differentiation. Unfortunately, we show these potential speedups are negated by the sparse structure inherent in power systems problems. We address these limitations by introducing a parallel, reversemode decentralized differentiation scheme that never explicitly instantiates the solution map Jacobian. We show both theoretically and empirically that parallelization is necessary to achieve non-trivial speedups when computing grid emissions sensitivities. Numerical results on a 500 node system indicate that our method can achieve greater than 10x speedups over centralized and serial decentralized approaches.

关键词： Sensitivity analysis distributed optimization implicit differentiation locational marginal emissions

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Research on improving sagging control strategy based on distributed inverter

Research on improving sagging control strategy based on dist...

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2024 international conference on Electronics, Electrical and Information Engineering, ICEEIE 2024

作者： Li, Mengda Zhu, Hanghang Sun, Yueyue Pei, Guangyao Ning, Han School of Electrical Engineering Shanghai Dianji University Shanghai201306 China

ISBN: (数字)9781510686809

ISBN: (纸本)9781510686793

In microgrids, sag control strategies are commonly employed by inverters across various levels. This study introduces an innovative solution to address challenges in sag control, specifically targeting issues related to uneven reactive power distribution and present transmission line impedance causes the AC bus voltage to drop. The proposed approach involves the implementation of an adaptive virtual impedance method and a feedback bus voltage recovery strategy, both grounded in the principle of multibody consistency. Firstly, the paper analyzes the causes of uneven reactive power distribution and busbar voltage deviation caused by traditional inverter sag control with multi-inverters parallel model. Secondly, the improvement strategy of sag control is proposed, and the virtual impedance and bus voltage feedback method of control based on distributed consistency principle is introduced to achieve the purpose of reactive power equalizing and restoring bus voltage. Finally, two inverter models were built in the MATLAB/Simulink, validation of the proposed strategy and demonstrate the effectiveness of the proposed strategy. Simulation results show that the proposed strategy can effectively improve the performance of the system of rational reactive power distribution and stable bus voltage of multiple inverters and can provide reference for the parallel use of multiple inverters. © 2024 SPIE.

关键词： Control systems Resistance Telecommunications Adaptive control Solar energy Wind energy Digital filtering Power grids Tunable filters Virtual reality

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Analysis of a parallel and distributed BPSO Algorithm for EEG Classification: Impact on Energy, Time and Accuracy 11th

Analysis of a Parallel and Distributed BPSO Algorithm for EE...

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11th international Work-conference on Bioinformatics and Biomedical Engineering (IWBBIO)

作者： Escobar, Juan Jose Lopez-Rodriguez, Jesus Garcia-Gil, Diego Morcillo-Jimenez, Roberto Prieto, Beatriz Ortiz, Andres Kimovski, Dragi Univ Granada CITIC Dept Software Engn Granada Spain Univ Granada Andalusian Res Inst Data Sci & Computat Intellige Granada Spain Univ Granada CITIC Dept Comp Engn Automat & Robot Granada Spain Univ Granada CITIC Dept Comp Sci & Artificial Intelligence Granada Spain Univ Malaga Dept Commun Engn Malaga Spain Univ Klagenfurt Inst Informat Technol Klagenfurt Austria

ISBN: (纸本)9783031646287;9783031646294

Today, the amount of data generated each year is growing exponentially, directly affecting the time required for its analysis. This problem worsens with high-dimensional datasets, such as those used in electroencephalography, so a good feature selection method and techniques that improve algorithms' efficiency are increasingly relevant. Consequently, computing time and energy consumption are reduced, which could be used to explore more solutions to the problem. However, it is also necessary to adapt the applications to take advantage of the hardware offered by high-performance computing systems. Therefore, in this work, a parallel and distributed binary particle swarm optimization algorithm has been implemented, used as a feature selection method, and applied to two real electroencephalography datasets: the University of Essex dataset and the well-known BCI Competition IV 2a dataset. The proposed method has been analyzed in a multi-node computing cluster, not only in terms of classification accuracy, but also from the energy-time point of view to study its impact depending on different experimental conditions and datasets used.

关键词： parallel and distributed computing Energy impact EEG classification KNN Particle swarm optimization Feature selection

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parallel Truss Maintenance of Dynamic Graphs 29

Parallel Truss Maintenance of Dynamic Graphs

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29th IEEE international conference on parallel and distributed systems, ICPADS 2023

作者： Li, Longzhi Jiang, Yuncheng South China Normal University School of Computer Science Guangzhou China South China Normal University School of Artificial Intelligence Foshan China

ISBN: (纸本)9798350330717

Cohesive subgraphs have been a hot research topic in graph data mining, where k-truss is a well-established metric for describing the density of graphs. The k-truss of a graph is the largest subgraph, in which each edge is contained in at least k - 2 triangles. For large-scale dynamic graphs with a few edge changes, truss decomposition takes a high cost to recalculate the truss number of edges, where the truss number indicates the densest k-truss that one edge can be located. Instead, truss maintenance algorithms can directly update the truss number of affected edges and thus decrease the cost. However, previous maintenance algorithms usually suffer from high traversal costs and poor parallelism. We further investigate the truss maintenance problem and propose the superior triangle edge set, which increases/decreases the truss numbers of affected edges by at most 1. Meanwhile, the superior triangle edge set can improve the parallelism of the proposed algorithms. Extensive experiments on real-world graphs of different scales show that our algorithms exhibit good performance and parallelism, and their efficiency outperforms state-of-the-art algorithms by at most one order of magnitude. © 2023 IEEE.

关键词： k-truss parallel algorithm truss maintenance

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JASS: A Tunable Checkpointing System for NVM-based systems 30

JASS: A Tunable Checkpointing System for NVM-based Systems

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30th international conference on High Performance Computing, Data, and Analytics (HiPC)

作者： Singh, Akshin Sarangi, Smruti R. IIT Delhi Comp Sci & Engn New Delhi India

ISBN: (纸本)9798350383225

Checkpointing (or snapshotting) a system's state has always been a problem of great interest and has found a lot of use in ensuring system reliability, record-replay debugging, job migration and running high-throughput transaction systems. In the last few years ultra-fast hardware-assisted NVM-based checkpointing schemes have come up that can collect incremental full-system checkpoints in milliseconds. Unfortunately, such systems have large overheads in terms of their write amplification (increased number of writes). This, in turn, seriously reduces the reliability and lifetime of NVM devices. We propose the first tunable scheme in this space, JASS, where given a checkpoint latency (CL), we near-optimally minimize the write amplification (WA). This allows us to run parallel programs in a disciplined fashion. To realize this goal, we propose many novel hardware along the way such as a rigorous method of flushing pre-checkpoint messages in the NoC, a novel DRAM scrubber and locality predictor, and a control-theoretic algorithm to guarantee a CL while minimizing the WA. We reduce WA by 35-96% as compared to the nearest state-of-the-art competing method and improve performance of PARSEC benchmarks by 19.4%.

关键词： NVMs Checkpointing distributed cache flushing

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Energy-Efficient Scheduling of Moldable Streaming Computations for the Edge-Cloud Continuum 9

Energy-Efficient Scheduling of Moldable Streaming Computatio...

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9th IEEE international conference on Fog and Mobile Edge Computing (FMEC)

作者： Khosravi, Sajad Kessler, Christoph Litzinger, Sebastian Keller, Joerg Linkoping Univ Linkoping Sweden Fernuniv Hagen Germany

ISBN: (纸本)9798350366495;9798350366488

We consider the problem of cost-effectively mapping a swarm of soft real-time stream processing applications with moldable-parallel tasks to multicore resources in the device-edge-cloud continuum, consisting of mobile devices, edge resources and cloud resources. We leverage flexibility from different parallelization degrees and frequency levels (DVFS) for the tasks, keeping application throughput constraints and communication bandwidth limitations while minimizing overall cost (including device/edge resource energy and cloud resource renting). We present two offline algorithmic solutions with a global view of the environment: an integer linear program (ILP) extending the crown scheduling approach for multi-layer distributed systems and a greedy heuristic algorithm. Our experimental evaluation for several real-world and synthetic scenarios shows that the time required for solving the scheduling problem to cost-optimality by the ILP is feasible for nontrivial scenarios. The heuristic achieves about 12% worse cost efficiency on average, yet operates much faster (by 1-2 orders of magnitude), allowing to scale up the problem size more than the ILP approach.

关键词： distributed stream processing Mapping Scheduling Moldable tasks Edge-Cloud continuum Energy efficiency DVFS

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parallel quantum circuit extraction from MBQC-patterns

Parallel quantum circuit extraction from MBQC-patterns

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Quanz, Marcel Staudacher, Korbinian Fuerlinger, Karl Ludwig Maximilians Univ Munchen Munich Germany Ludwig Maximilians Univ Munchen MNM Team Munich Germany

ISBN: (纸本)9798350364613;9798350364606

In the model of measurement-based quantum computing (MBQC), computations are performed via sequential measurements on a highly entangled graph state. MBQC is a natural model for photonic quantum computing and has been shown to be useful for tasks like optimization and verification of general quantum computations. Therefore, it is often necessary to translate between MBQC and the predominantly used quantum circuit model in a fast and reliable way. While there are algorithms with linear complexity to extract quantum circuits from measurement patterns using additional ancilla qubits, efficient ancilla-free extraction has shown to be more costly. We develop strategies to parallelize an existing extraction algorithm based on ZX-calculus by exploiting the graph structure of measurement patterns and evaluate the performance on patterns obtained from a benchmark set of quantum circuits. Our results suggest that possible parallelization speedups are closely related to the graph structure of a pattern.

关键词： MBQC ZX-calculus gflow

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