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arXiv 2021年

作者： Wu, Wansen Chang, Tao Li, Xinmeng Yin, Quanjun Zhu, Jiancheng The College of Systems Engineering National University of Defense Technology Hunan Changsha410073 China National Key Laboratory of Parallel and Distributed Processing College of Computer Science and Technology National University of Defence Technology Changsha410073 China

Vision-Language Navigation (VLN) tasks require an agent to follow human language instructions to navigate in previously unseen environments. This challenging field involving problems in natural language processing, computer vision, robotics, etc., has spawn many excellent works focusing on various VLN tasks. This paper provides a comprehensive survey and an insightful taxonomy of these tasks based on the different characteristics of language instructions in these tasks. Depending on whether the navigation instructions are given for once or multiple times, this paper divides the tasks into two categories, i.e., single-turn and multi-turn tasks. For single-turn tasks, we further subdivide them into goal-oriented and route-oriented based on whether the instructions designate a single goal location or specify a sequence of multiple locations. For multi-turn tasks, we subdivide them into passive and interactive tasks based on whether the agent is allowed to question the instruction or not. These tasks require different capabilities of the agent and entail various model designs. We identify progress made on the tasks and look into the limitations of existing VLN models and task settings. Finally, we discuss several open issues of VLN and point out some opportunities in the future, i.e., incorporating knowledge with VLN models and implementing them in the real physical world. © 2021, CC BY.

关键词： Taxonomies

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Grid-aware Scheduling and Control of Electric Vehicle Charging Stations for Dispatching Active Distribution Networks. Part-II: Intra-day and Experimental Validation

arXiv

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arXiv 2024年

作者： Gupta, Rahul K. Fahmy, Sherif Chevron, Max Figini, Enea Paolone, Mario School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta30308 United States Distributed Electrical Systems Laboratory École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland

In Part-I, we presented an optimal day-ahead scheduling scheme for dispatching active distribution networks accounting for the flexibility provided by electric vehicle charging stations (EVCSs) and other controllable resources such as battery energy storage systems (BESSs). Part-II presents the intra-day control layer for tracking the dispatch plan computed from the day-ahead scheduling stage. The control problem is formulated as model predictive control (MPC) with an objective to track the dispatch plan setpoint every 5 minutes, while actuated every 30 seconds. MPC accounts for the uncertainty of the power injections from stochastic resources (such as demand and generation from photovoltaic - PV plants) by short-term forecasts. MPC also accounts for the grid's operational constraints (i.e., the limits on the nodal voltages and the line power-flows) by a linearized optimal power flow (LOPF) model based on the power-flow sensitivity coefficients, and for the operational constraints of the controllable resources (i.e., BESSs and EVCSs). The proposed framework is experimentally validated on a real-life ADN at the EPFL's distributed electrical systems laboratory and is composed of a medium voltage (MV) bus connected to three low voltage distribution networks. It hosts two controllable EVCSs (172 kWp and 32 kWp), multiple PV plants (aggregated generation of 42 kWp), uncontrollable demand from office buildings (20 kWp), and two controllable BESSs (150kW/300kWh and 25kW/25kWh). © 2024, CC BY-NC-ND.

关键词： Model predictive control

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Comparison of Image Processing Resource Allocation for Multi-Target Tracking of Dismounted Targets

Comparison of Image Processing Resource Allocation for Multi...

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International Conference on Information Fusion

作者： Jon P. Champion Juan R. Vasquez Distributed Information Systems Branch Air Force Research Laboratory Rome NY USA Department of Electrical and Computer Engineering WPAFB Air Force Institute of Technology OH USA

ISBN: (纸本)1424409535

Dismounted targets can be tracked in urban environments with video sensors. Real-time systems are unable to process all of the imagery, demanding some method for prioritization of the processing resources. Furthermore, various segmentation algorithms exist within image processing, each algorithm possesses unique capabilities, and each algorithm has an associated computational cost. Additional complexity arises in the prioritization problem when targets become occluded (i.e., a building) and when the targets are intermixed with other dismounted entities. This added complexity leads to the question "which portions of the scene warrant both low cost and high cost processing?" The approach presented in this paper is to apply multi-target tracking techniques in conjunction with an integer programming optimization routine to determine optimal allocation of the video processing resources. This architecture results in feedback from the tracking routine to the image processing function which in turn enhances the ability of the tracker

关键词： Image processing Resource management Target tracking Costs Real time systems Image segmentation Computational efficiency Layout Linear programming Feedback

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Application of QR decomposition-based least squares technique to improve air traffic control radar

Application of QR decomposition-based least squares techniqu...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： T. Ogunfunmi Nam Ling Signal and Image Processing Laboratory (SIPL) Department of Electrical Engineering Santa Clara University Santa Clara CA USA Computer Systems and Parallel Processing Research Laboratory (CSPPRL) Department of Computer Engineering Santa Clara University Santa Clara CA USA

For real-time radar processing, it is very desirable to have an algorithm that does not assume restricted statistics of the input data and can be implemented for high-speed processing (without a high cost) to meet real-time requirements. We therefore apply the QR decomposition-based least-squares method for linear prediction to the problem of computing the reflection coefficients of a lattice predictor, instead of using the conventional Burg algorithm. We also propose a modified one-dimensional ring architecture for implementing the QR method of least-squares. The particular application considered in this case is that of surveillance radar systems for air traffic control.< >

关键词： Least squares methods Air traffic control Radar applications Signal processing algorithms Radar signal processing Statistics Systolic arrays Radar imaging Signal processing Surveillance

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Grid-aware Scheduling and Control of Electric Vehicle Charging Stations for Dispatching Active Distribution Networks. Part-I: Day-ahead and Numerical Validation

arXiv

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arXiv 2024年

作者： Gupta, Rahul K. Fahmy, Sherif Chevron, Max Vasapollo, Riccardo Figini, Enea Paolone, Mario School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta30308 United States Distributed Electrical Systems Laboratory École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland

This paper proposes a grid-aware scheduling and control framework for Electric Vehicle Charging Stations (EVCSs) for dispatching the operation of an active power distribution network. The framework consists of two stages. In the first stage, we determine an optimal day-ahead power schedule at the grid connection point (GCP), referred to as the dispatch plan. Then, in the second stage, a real-time model predictive control is proposed to track the day-ahead dispatch plan using flexibility from EVCSs. The dispatch plan accounts for the uncertainties of vehicles connected to the EVCS along with other uncontrollable power injections, by day-ahead predicted scenarios. We propose using a Gaussian-Mixture-Model (GMM) for the forecasting of EVCS demand using the historical dataset on arrival, departure times, EV battery capacity, State-of-Charge (SoC) targets, etc. The framework ensures that the grid is operated within its voltage and branches power-flow operational bounds, modeled by a linearized optimal power-flow model, maintaining the tractability of the problem formulation. The scheme is numerically and experimentally validated on a real-life distribution network at the EPFL connected to two EVCSs, two batteries, three photovoltaic plants, and multiple heterogeneous loads. The day-ahead and real-time stages are described in Part-I and Part-II papers respectively. © 2024, CC BY-NC-ND.

关键词： Electric power distribution

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Quantization improvements for LU Decomposition to Solve Linear Equations *

Quantization improvements for LU Decomposition to Solve Line...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Lin Chen Kang He Hao Jiang Roberto Barrio Jie Liu Tiejun Li Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer Science and Technology National University of Defense Technology Changsha China University of Zaragoza Zaragoza Spain

Quantization is an effective method for compressing Deep Neural Networks. Now, it is considered to accelerate the traditional HPC applications. In this article, we present a quantization method (q8gemm) using integer 8-bits(INT8) for matrix multiplication, which is implemented by block techniques to overcome the overflow problem. We choose different scales for one matrix’s each row and those for the other matrix’s each column to keep the numbers in range. With the intel advanced matrix extension cblas_gemm_s8u8s32, our q8gemm can accelerate panel-matrix multiplication in LU factorization. Furthermore, we propose a new mixed-precision solver (q8gesv 1 ) for the linear equations. Using q8gemm in INT8, q8gesv modifies LU factorization in FP32 and then utilizes GMRES iterative refinement in FP64 to bring the solution back to 64 bits accuracy. Numerical tests show that on two Intel CPU platforms with avx2 and avx512, q8gemm achieves a speedup of 1.313-1.621 over cblas_sgemm of MKL. The execution time of cblas_gemm_s8u8s32 makes up 86.78%-90.85% of the q8gemm. By means of q8gemm, our q8gesv can achieve a speedup of 1.176-1.493 over the optimized Higham’s mixed-precision algorithm utilized in the HPL-AI benchmark and a speedup of 1.1-1.459 over the LAPACKE_dsgesv function from MKL LAPACK. Meanwhile, q8gesv runs up to 2.859X faster on Intel(R) Core(TM) i5-10600KF and to 2.224X faster on Intel(R) Xeon(R) Gold 6130 than the LAPACKE_dgesv function from MKL LAPACK.

关键词： Deep learning Gold Quantization (signal) Benchmark testing

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A mathematical model, heuristic, and simulation study for a basic data staging problem in a heterogeneous networking environment

A mathematical model, heuristic, and simulation study for a ...

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Heterogeneous Computing Workshop

作者： Min Tan M.D. Theys H.J. Siegel N.B. Beck M. Jurczyk Cisco Systems Inc. San Jose CA USA Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Computer Engineering and Computer Science University of Missouri Columbia Columbia MO USA

Data staging is an important data management problem for a distributed heterogeneous networking environment, where each data storage location and intermediate node may have specific data available, storage limitations, and communication links. Sites in the network request data items and each item is associated with a specific deadline and priority. It is assumed that not all requests can be satisfied by their deadline. The work concentrates on solving a basic version of the data staging problem in which all parameter values for the communication system and the data request information represent the best known information collected so far and stay fixed throughout the scheduling process. A mathematical model for the basic data staging problem is introduced. Then, a multiple-source shortest-path algorithm based heuristic for finding a suboptimal schedule of the communication steps for data staging is presented. A simulation study is provided, which evaluates the performance of the proposed heuristic. The results show the advantages of the proposed heuristic over two random based scheduling techniques. This research, based on the simplified static model, serves as a necessary step toward solving the more realistic and complicated version of the data staging problem involving dynamic scheduling, fault tolerance, and determining where to stage data.

关键词： Mathematical model computer networks distributed computing Data engineering Military computing Intelligent networks computer network management Environmental management Memory Satellite broadcasting

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Electromagnetic Time Reversal Applied to Fault Location: On the Properties of Back-Injected Signals

Electromagnetic Time Reversal Applied to Fault Location: On ...

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Power systems Computation Conference

作者： Zhaoyang Wang Reza Razzaghi Mario Paolone Farhad Rachidi Electromagnetic Compatibility (EMC) Laboratory Department of Electrical and Computer Systems Engineering Monash University Melbourne Australia Distributed Energy System Laboratory (DESL) Swiss Federal Institute of Technology EPFL Lausanne Switzerland

By using the electromagnetic time reversal (EMTR) theory, the paper studies its properties in order to derive a new fault location method to be used in power networks. It is shown that, in the reversed-time stage, the current signal observed at the true fault location can be clearly distinguished since it appears as a time-delayed copy of the back-injected fault-originated transient signal. Then, based on this similarity property, a fault location method is derived. Finally, the method is numerically validated with reference to a reproducible simulated power network composed of an inhomogeneous multi-conductor transmission-line system.

关键词： Cross-correlation sequence Electromagnetic time reversal Electromagnetic transients Fault location Power system

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Locality Protected Dynamic Cache Allocation Scheme on GPUs

Locality Protected Dynamic Cache Allocation Scheme on GPUs

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Yang Zhang Zuocheng Xing Li Zhou Chunsheng Zhu National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China School of Electronic Science and Engineering National University of Defense Technology Changsha China Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada

ISBN: (纸本)9781509032068

As we are approaching the exascale era in supercomputing, designing a balanced computer system with powerful computing ability and low energy consumption becomes increasingly important. GPU is a widely used accelerator in most recently applied supercomputers. It adopts massive multithreads to hide long latency and has high energy efficiency. In contrast to its strong computing power, GPUs have few on-chip resources with several MB of fast on-chip memory storage per SM (Streaming Multiprocessors). GPU caches exhibit poor efficiency due to the mismatch of the throughput-oriented execution model and its cache hierarchy design. Since the severe deficiency in on-chip memory, the benefit of high computing capacity of GPUs is pulled down by the poor cache performance dramatically, which limits system performance and energy-efficiency. In this paper, we put forward a locality protected scheme to make full use of the data locality based on the fixed capacity. We present a Locality Protected method based on instruction PC (LPP) to promote GPU performance. Firstly, we use a PC-based collector to collect the reuse information of each cache line. After getting the dynamic reuse information of the cache line, we take an intelligent cache allocation unit (ICAU) which coordinates the reuse information with LRU (Least Recently Used) replacement policy to find out the cache line with the least locality for eviction. The results show that LPP provides an up to 17.8% speedup and an average of 5.5% improvement over the baseline method.

关键词： Graphics processing units System-on-chip computer architecture Instruction sets Resource management Optimization Electronic mail

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Jeeva: Enterprise Grid Enabled Web Portal for Protein Secondary Structure Prediction

Jeeva: Enterprise Grid Enabled Web Portal for Protein Second...

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International Conference on Advanced Computing and Communications (ADCOM)

作者： Chao Jin Jayavardhana Gubbi Rajkumar Buyya Marimuthu Palaniswami Grid Computing and Distributed Systems (GRIDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Melbourne VIC Australia Department of Electrical and Electronic Engineering University of Melbourne Melbourne VIC Australia

This paper presents a grid portal for protein secondary structure prediction developed by using services of Aneka, a .NET-based enterprise grid technology. The portal is used by research scientists to discover new prediction structures in a parallel manner. An SVM (support vector machine)-based prediction algorithm is used with 64 sample protein sequences as a case study to demonstrate the potential of enterprise grids.

关键词： Portals Protein engineering Grid computing Prediction algorithms Support vector machines distributed computing Environmental management Chaos computer science History

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