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parallel Dispatch:A New Paradigm of electrical Power System Dispatch

IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 311-319页

作者： Jun Jason Zhang Fei-Yue Wang Qiang Wang Dazhi Hao Xiaojing Yang David Wenzhong Gao Xiangyang Zhao Yingchen Zhang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver Denver 80210 CO USA State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science (SKL-MCCS CASIA) Beijing 100190 China Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology Changsha 410073 China State Grid Tianjin Electric Power Company Tianjin 300010 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China National Renewable Energy Laboratory Golden CO 80401 USA IEEE

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm,namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids,extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.

关键词： ACP knowledge automation power dispatch parallel dynamic programming parallel intelligence paralle learning situational awareness

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CAMP: A Technique to Estimate Per-Structure Power at Run-time using a Few Simple Parameters

CAMP: A Technique to Estimate Per-Structure Power at Run-tim...

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15th International Symposium on High-Performance computer Architecture

作者： Powell, Michael D. Biswas, Arijit Emer, Joel S. Mukherjee, Shubhendu S. Sheikh, Basit R. Yardi, Shrirang Intel Massachusetts United States Computer Systems Laboratory Cornell University United States Department of Electrical and Computer Engineering Virginia Tech United States

ISBN: (纸本)9781424429325

Microprocessor power has become a first-order constraint at run-time. Designers must employ aggressive power-management techniques at run-time to keep a processors ballooning power requirements under control. Effective power management benefits from knowledge of run-time microprocessor power consumption in both the core and individual microarchitectural structures, such as caches, queues, and execution units. Increasingly feasible per-structure power-control techniques, such as fine-grain clock gating, power gating, and dynamic voltage/frequency scaling (DVFS), become more effective from run-time estimates of per-structure power However, run-time computation of per-structure power estimates based on utilization requires daunting numbers of input statistics, which makes per-structure monitoring of run-time power a challenging problem. To address the challenges of estimating per-structure power in hardware, we propose a new technique, called Common Activity-based Model for Power (CAMP), to estimate activity factors and power for microarchitectural structures. Despite using a relatively few input parameters-specifically nine-based on general microprocessor utilization statistics (e.g., IPC and load rate), our linear-regression-based model estimates activity and dynamic power for over 100 structures in an out-of-order x86 pipeline and core power with an average error of 8%. Because the computations utilize few inputs, CAMP is simple enough to implement in hardware, providing run-time structure and core power estimates for dynamic power management. Because the input statistics are generic in nature and the model remains accurate across incremental microarchitectural refinements, CAMP provides simple intuitive equations relating global microarchitectural statistics to structure activity and power. These equations provide a simple technique that can equate changes in one structure activity to power variations in other structures across the pipeline.

关键词： Pipelines

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GPU accelerated blockchain over key-value database transactions

IET Blockchain

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IET Blockchain 2022年第1期2卷 1-12页

作者： Iliakis, Konstantinos Koliogeorgi, Konstantina Litke, Antonios Varvarigou, Theodora Soudris, Dimitrios Microprocessors and Digital Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zografou Campous 9 Iroon Polytechniou str Athens Greece Distributed Knowledge and Media Systems group Department of Electrical and Computer Engineering National Technical University of Athens Zografou Campous 9 Iroon Polytechniou str Athens Greece

Blockchain is a distributed ledger based on peer-to-peer networks, originally used for crypto-currency systems. Blockchains are being used as an enabling technology for decentralised applications in the areas of Internet-of-Things, finance, supply-chain and others. Consistency, data privacy, performance, and energy efficiency are of paramount importance in such applications. The full nodes of public, permissionless blockchains undertake the task of verifying the transactions generated by the network. Full nodes perform operations such as confirming balances, transactions, and history, i.e. mostly database search queries. Consequently, their throughput is crucial for the performance of blockchain systems. In this work, the benefits of accelerating the blockchain search and insert queries by leveraging GPU platforms are studied. An extensive comparison between the most dominant utilized database is provided, i.e. LevelDB, and MegaKV, a high-performance GPU-accelerated database. Realistic operations that take place in blockchain systems are emulated and evaluated over representative scenarios, showing three orders of magnitude gains in throughput and energy efficiency without compromising the security aspect. The extensive comparison between LevelDB and MegaKV indicates that GPU acceleration is an effective solution for runtime and energy efficiency enhancement of blockchain systems, and the integration of the two technologies is a promising field of research. © 2022 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Blockchain

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parallel Planning:A New Motion Planning Framework for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 236-246页

作者： Long Chen Xuemin Hu Wei Tian Hong Wang Dongpu Cao Fei-Yue Wang IEEE School of Data and Computer Science Sun Yat-sen University the School of Computer Science and Information Engineering Hubei University Institute of Measurement and Control Systems Karlsruhe Institute of Technology Department of Mechanical and Mechatronics Engineering University of Waterloo the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation Chinese Academy of Sciences the Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human ***, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.

关键词： Autonomous driving artificial traffic scene deep learning emergencies motion planning parallel planning

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Kalman-filtering timing recovery scheme for orthogonal frequency domain multiplexing (OFDM) systems 25

Kalman-filtering timing recovery scheme for orthogonal frequ...

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25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000

作者： Hajirostam, Mohamad Maddah-Ali, M.A. Haft-Baradaran, A. Kilani, M.T. Fakhraie, S.M. Sharif-Khani, M. Shoaei, O. VLSI Circuits and Systems Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)0780362934

This paper describes a new technique for timing synchronization in orthogonal frequency domain multiplexing (OFDM) transceiver systems. The proposed technique is based on non-synchronized sampling rate and no pilot is required to be transmitted. Therefore the transmission capacity is increased. The proposed algorithm employs the angles of the received symbols in the OFDM subchannels and provides a computationally efficient technique for estimation of the timing error. An equivalent state space model is also derived for timing error and then Kalman filtering method is exploited for tracking purposes. The proposed technique is very robust, particularly under low signal to noise ratio conditions and has been verified by means of computer simulations. © 2000 IEEE.

关键词： Timing circuits

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Nonlinear prediction with neural networks applied to 1-D DPCM image coding

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Journal of Visual Communication and Image Representation 1992年第3期3卷 247-247页

作者： Li, Jianjun Manikopoulos, Constantine N. Intelligent Systems Laboratory Department of Electrical and Computer Engineering New Jersey Institute of Technology 323 King Blvd. Newark New Jersey 07102 USA

Neural net architectures, with a hidden layer or functional links, have been utilized to generate prediction for one-dimensional (1-D) differential pulse code modulation (DPCM), applied to still image coding. In this approach, the predictor is designed by supervised training based on a typical sequence of pixel values; i.e., the values of the coefficients of the predictor are determined by training on examples. Nonlinear as well as linear correlations are exploited. computer simulation experiments have been carried out to evaluate the resulting performance. At a transmission rate of 1 bit/pixel, for the images Lena and Baboon, the 1-D neural network DPCM provides a 4.17- and 3.74-dB improvement in peak SNR, respectively, over the standard linear DPCM system.

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Multi-resolution surface modeling from multiple range views

Multi-resolution surface modeling from multiple range views

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1992 IEEE computer Society Conference on computer Vision and Pattern Recognition, CVPR 1992

作者： Soucy, M. Laurendeau, D. Computer Vision and Digital Systems Laboratory Department of Electrical Engineering Laval University QC Canada

ISBN: (纸本)0818628553

A multiresolution surface modeling technique is presented. Several registered range views obtained from different viewpoints are first integrated into a nonredundant surface triangulation. The integration technique is based on the reparameterization of the canonic subsets of the Venn diagram of the set of views. The resulting triangulation is then input to a sequential optimization process that computes different levels of resolution of the surfaces of interest. © 1992 IEEE.

关键词： Triangulation

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Comparison of cryptosystems using a single-scale statistical measure

Comparison of cryptosystems using a single-scale statistical...

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2013 26th IEEE Canadian Conference on electrical and computer engineering, CCECE 2013

作者： Terrazas Gonzalez, Jesus D. Kinsner, Witold Cognitive Systems Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada

ISBN: (纸本)9781479900329

A useful measure is presented for comparison of distinct cryptosystems, including (i) the RSA algorithm, (ii) EIGamal algorithm, (iii) a cryptosystem based on radio background noise (RBN), and (iv) a new cryptosystem based on chaos phenomena. The four cryptosystems are implemented to have the same computational power, and are compared through the marginal probability mass functions (mpmf). This paper shows experimentally that the chaos-based modular dynamical cryptosystem is (i) strong to statistical cryptanalysis by leaving no patterns or hooks in the ciphertexts and (ii) faster than the selected algorithms from public-key cryptography (RSA) and elliptic curve cryptography (EIGamal). © 2013 IEEE.

关键词： Public key cryptography

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Towards agent swarm optimization

Towards agent swarm optimization

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10th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2011

作者： Schor, Dario Kinsner, Witold Cognitive Systems Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada

ISBN: (纸本)9781457716966

This paper examines particles in Particle Swarm Optimization (PSO) in terms of situated agents to improve control of the long term behaviour of particles as required for cognitive machines. In PSO, the particles lack goals and temporal knowledge for personal/global best solutions, thus many of the decisions for advancing the position of the particle diverge away from the solution causing the algorithm to take longer as the particles return to their intended path. This paper proposes novel modifications to the standard PSO algorithm to incorporate self-adjusting temporal knowledge to help guide the particles towards the optimal solution faster. The temporal knowledge is incorporated as a weighted sum of L previous steps taken by the particle, where L is automatically adjusted to maintain a certain multiscale measure that satisfies a balance between exploration and seeking the goal. Additional improvements based on the dynamics of the particle's behaviour are described that would allow for real-time predicting of parameters. © 2011 IEEE.

关键词： Particle swarm optimization (PSO)

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An intelligent digital colour image watermarking approach based on wavelets and general regression neural networks

An intelligent digital colour image watermarking approach ba...

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11th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2012

作者： Dang, Hieu V. Kinsner, Witold Cognitive Systems Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada

ISBN: (纸本)9781467327930

In this paper, we propose a new intelligent, robust and adaptive digital watermarking technique for colour images based on the combination of discrete wavelet transform (DWT), human visual system (HVS) model and general regression neural network (GRNN). First, the RGB image is converted to YCrCb image, and then the luminance component Y is decomposed by DWT. Wavelet coefficients are then analyzed by a HVS model to select suitable coefficients for embedding the watermark. The watermark bits are embedded into the selected coefficients by training a GRNN. At the decoder, the trained GRNN is used to recover the watermark from the watermarked image. The experimental results show that our proposed approach achieves robustness and imperceptibility in watermarking. © 2012 IEEE.

关键词： Discrete wavelet transforms

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