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检索条件"任意字段=2016 International Congress on Computation Algorithms in Engineering"

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Parallel Algorithm Design for Audio Feature Extraction

Parallel Algorithm Design for Audio Feature Extraction

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2017 5th international Conference on Machinery,Materials and Computing Technology(ICMMCT 2017)

作者： Xiaocheng Luo Jingfei Jiang Junjie Zhu Yong Dou National Laboratory for Parallel and Distributed Processing National University of Defense Technology

Audio feature extraction is a very important technique in the field of sound processing. It extremely impacts the effectiveness and correctness of sound recognition, sound verification, etc. It is a computation intensive stage in the whole sound recognition process, which is a challenging for acceleration. In this paper, a coarse-grained parallel feature extraction algorithm for high throughput of audio slices is proposed to improve the efficiency of audio feature extraction. Three typical audio feature extraction algorithms, Mel Frequency Cepstrum Coefficients(MFCC), Spectrogram image features(SIF), Octave-Based Spectral Contrast, are chosen to parallelize. Experiments results on different platforms show that the speedup of accelerated audio feature extraction is up to 17.23 on the platform with 16 cores 32 threads.

关键词： Feature Extraction Sound Recognition Parallel Algorithm

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Optimal train scheduling under a flexible skip-stop scheme for urban rail transit based on smartcard data

Optimal train scheduling under a flexible skip-stop scheme f...

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IEEE international Conference on Intelligent Rail Transportation (ICIRT)

作者： Peitong Zhang Xiaobo Liu Mei Chen School of Transportation and Logistics Southwest Jiaotong University Chengdu China College of Engineering University of Kentucky Lexington KY

Skip-stop operation is a low cost approach to improving transit operating speed. This paper proposes a new methodology to design a skip-stop strategy for urban rail lines aiming to minimize total travel time while at the same time serve the maximum number of passengers in off-peak hours. Different from the conventional “A/B” scheme, the proposed new scheme called the Flexible Skip-Stop Scheme (FSSS) can provide more combinations of stop modes to accommodate passenger demand. The train headway is optimized, while the train capacity is taken into consideration. A Genetic Algorithm is developed to efficiently search for the optimal solution. Based on one-way real passenger origin-destination (O-D) pairs and entry and exit time data at the stations obtained from the smartcard system, a case study on a single metro rail line in the City of Shenzhen has been conducted. Kinds of scenarios are designed, the privilege of the station which able to be skipped is limited to specific stations according to their passenger flow. Results show that the high demand station trends to achieve the optimal under the All-stop scheme, while skip a low demand station would bring sizable savings for total passenger travel time. This can effectively limit the feasible solution set and reduce the computation time. In addition, tests show that the model can produce skip-stop schedules that not only decrease the total passenger travel time at a given service level, but it also generates significant transit agency cost savings, while the number of skipped stations of the optimized skip-stop operation scheme remains stable.

关键词： Rails Linear programming Rail transportation Real-time systems Optimization Genetic algorithms Urban areas

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QoS Oriented Embedding for Network Virtualization

QoS Oriented Embedding for Network Virtualization

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IEEE international Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Li Xu Hui Li Jingting Sun Kai Pan Guanghui Zhang School of Electronic & Computer Engineering Peking University Shenzhen China

Network virtualization (NV) is an indispensable approach to handle the ossification of current Internet. Previous research has been conducted concerning the implementation issues like heuristic-based mapping algorithms, yet little has focused on quality of service (QoS) for end users who launch virtual network (VN) requests, and revenue both service providers and infrastructure providers can obtain. Through experiments we find that with the same mapping algorithm, varying mapping order tends to bring about different substrate resources allocation and correspondingly, different acceptance ratio and revenue. However, existing research has not yet paid enough attention to this issue. In this paper, we address the issue by proposing a new and comprehensive revenue model, which is employed as a ranking criterion for VN requests before mapping. Additionally, we define the notion of fairness ratio to quantify the QoS that our model centers. The evaluation results show that our practice outperforms exiting ones with desirable fairness and user satisfaction along with higher revenue and increased acceptance ratio (6.5%).

关键词： Substrates Bandwidth Quality of service Mathematical model Virtualization Cloud computing Algorithm design and analysis

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PCAFP for Solving CNOP in Double-Gyre Variation and its Parallelization on Clusters

PCAFP for Solving CNOP in Double-Gyre Variation and its Para...

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IEEE international Conference on High Performance Computing and Communications

作者： Shijin Yuan Mi Li Bin Mu Jingpeng Wang School of Software Engineering Tongji University Shanghai China

ISBN: (纸本)9781509042982

Double-gyre ocean circulation is a typical phenomenon in the northern mid-latitude ocean basins. Its low-frequency variability significantly influences on both ocean and climate. To enhance its predictability, the finding of optimal initial perturbation which can trigger the double-gyre variation is important. CNOP method is adopted to calculate the optimal initial perturbation and this method has already been widely applied. Previous studies show that intelligent algorithms are effective methods to solve CNOP on ENSO event in ZC model. In this paper, it is the first time that intelligent algorithm is used to solve CNOP in ROMS for double-gyre variation. The dimension of the objective function is much higher than that of the ZC model and the calculation time increases dramatically, therefore effective result may not be able to be acquired in acceptable time. We propose an improved intelligent algorithm in accompany with the principal component analysis to solve CNOP, which is called principal component analysis based flower pollination (PCAFP) algorithm. To speed up furtherly, we complete both the parallelization of the nonlinear process of ROMS and the PCAFP algorithm. Different frameworks like OpenMP, MPI and CUDA on GPU are utilized and their performances are compared. Using a 20 nodes' cluster (12 cores in each node) on TH-1A supercomputer system, the computation time is reduced from 324.4 hours (about 13.5 days) to 3.71 hours, and the 87.44x speedup demonstrates that our parallelization can remarkably reduce the time cost. Hence, the proposed PCAFP with its parallelization on clusters can not only obtain optimal initial perturbation that can trigger the double-gyre variation, but also solve CNOP effectively and efficiently.

关键词： CUDA double-gyre variation ROMS CNOP PCAFP cluster parallelization OpenMP MPI

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CDR Based Temporal-Spatial Analysis of Anomalous Mobile Users

CDR Based Temporal-Spatial Analysis of Anomalous Mobile User...

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IEEE international Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Zhen Wang Sihai Zhang China Telecom Corporation Limited Anhui Branch Information Center Dept. of Electronic Engineering and Information Science University of Science and Technology of China Hefei Anhui China

As the competition in mobile markets becomes fiercer, telecom operators have devoted themselves to serving subscribers better. Among large number of subscribers, there are some anomalous users who should be paid more attention to, such as those issuing a lot of unsolicited calls to normal subscribers or making calls to one single phone number continuously. Our study is based on the data of Call Detail Records(CDR) of 10,000 subscribers provided by a Chinese telecom operator, who are randomly sampled from a high-tech industry district for one month. In this paper, we distinguish the abnormal users from the normal ones using agglomerative hierarchical clustering, and divide the anomalous users into telecom marketers or frauds, mobile hot lines and testers. We find that all the anomalous users are distributed in urban areas. In addition, testers and telecom marketers or frauds have relatively weak mobility, and are located in the centralized areas. On the contrary, users being recognized as mobile hot lines show the characteristics of high mobility and relatively decentralized distribution in geographical aspects.

关键词： Telecommunications Mobile communication Indexes Mobile handsets Clustering algorithms Big data Robots

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Failures Prediction in Non-Maintainable Components for Industrial Maintenance Management Using Machine Learning Techniques

Failures Prediction in Non-Maintainable Components for Indus...

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Artificial Intelligence and Quantum computation-Based Sensor Application (ICAIQSA), international Conference on

作者： Sebastian Diaz Vivas Oscar J. Suarez Center for Optimization and Applied Probability (COPA) Universidad de los Andes Bogota Colombia Mechatronics Engineering Department Universidad de Pamplona Pamplona Colombia

ISBN: (数字)9798331517953

ISBN: (纸本)9798331517960

Predictive maintenance of non-maintainable industrial components poses a significant challenge in maintenance management due to the complexity of predicting imminent failures at early stages, influenced by various factors affecting the operation of industrial assets. This paper proposes a new methodology that develops supervised classification Machine Learning (ML) models to predict failures in non-maintainable components by utilizing Time in Service (TIS) as a key feature in the context of a centrifugal pump, a critical asset in industrial processes. Two algorithms are evaluated: Random Forests (RF) and K-Nearest Neighbors (K-NN), using a dataset of 2,000 historical maintenance records. Data partitioning is done through a combination of k-Fold Cross-Validation and Grid Search, and hyperparameters are optimized by minimizing the loss function. The evaluation metrics (precision, recall, accuracy, and F1-Score) are derived from confusion matrices. Results indicated that while both models exhibited competitive performance, RF models achieved a higher average recall (97.11%) than K-NN models (95.2%), which is critical for effective failure detection. This study confirms the feasibility of using supervised ML models to predict failures in non-maintainable industrial assets, with TIS as a foundational feature. The developed models provide a valuable tool for enhancing operational reliability, optimizing maintenance management, and facilitating data-driven decision-making, all in compliance with ISO 14224:2016 standards.

关键词： Radio frequency computational modeling ISO Standards Decision making Computer architecture Predictive models Data models Maintenance Standards Maintenance management

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Electromagnetic Optimization Based on Gaussian Crow Search Approach

Electromagnetic Optimization Based on Gaussian Crow Search A...

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2018 international Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2018

作者： Dos Santos Coelho, Leandro Klein, Carlos Eduardo Mariani, Viviana Cocco Do Nascimento, Carlos Augusto Richter Askarzadeh, Alireza PUCPR Industrial and Systems Eng. Graduate Program PPGEPS Federal University of Parana UFPR Department of Electrical Engineering DEE/PPGEE Pontifical Catholic University of Parana Curitiba PR Brazil PUCPR Mechanical Engineering Graduate Program PPGEM Curitiba Pontifical Catholic University of Parana PR Brazil Department of Energy Management and Optimization Institute of Science and High Technology and Environmental Sciences Graduate University of Advanced Technology Kerman Iran

ISBN: (纸本)9781538649411

Metaheuristic algorithms have provided efficient tools to designers by which it became possible to determine the optimum solutions of optimization problems encountered in several fields such as engineering, finance and computation. Generally metaheuristics are based on metaphors that are taken from nature or some other processes. Recently, an optimization metaheuristic paradigm based on the social behavior of the crows, called crow search algorithm (CSA), has been proposed. The idea of CSA is motivated from the storing process of the excess food in hiding places then restoring it in the necessary time. The CSA has many favorable characteristics, such as ease of implementation, the need to adjust only a few parameters, a favorable balance between search diversification and intensification, and fast convergence and high sensitivity. However, to enhance the performance of the standard CSA approach, this paper proposes to tune the control parameters using population diversity information and normal (Gaussian) probability distribution function. Loney's solenoid benchmark and circular antenna array design problems are used to evaluate the effectiveness of the conventional CSA and the proposed variant. Simulation results and comparisons with the CSA demonstrated that the performance of the proposed MCSA approach is promising in electromagnetics optimization. © 2018 IEEE.

关键词： Optimization

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expanCodes: Tailored LDPC Codes for Big Data Storage

expanCodes: Tailored LDPC Codes for Big Data Storage

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IEEE international Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Yongmei Wei Fengmin Chen School of Engineering Nanyang Polytechnic Singapore

Big data storage demands larger cluster. The increasing size of the cluster may lead to failures of larger number of nodes. To provide reliable big data storage, replications are not cost-effective and does not provide a robust solution to prevent data loss. Traditional erasure codes applied in the RAID system such as Reed-Solomon (R-S) based solutions have limitations in providing high reliability. This is because higher reliability requires erasure codes with larger size. The computational cost of the R-S codes increase quadratically with the number of failures the R-S codes can tolerate for the same redundancy rate. It has been shown that Low Density Parity Check (LDPC) codes have lower computational cost and repair network traffic compared with R-S based solutions. Unfortunately, there does not exist a construction method for LDPC codes with larger size to control the computational cost and repair traffic. In this paper, a novel method is proposed to construct a family of LDPC codes - expanCodes with expandable sizes. The proposed expanCodes allows the encoding and decoding complexity remain unchanged with the increase of the size of the LDPC codes. As a result, increased reliability can be achieved without additional computation and repair traffic. The proposed expanCodes is integrated with the Hadoop system. Simulations show that more than 29% decrease in terms of encoding and decoding latency compared with R-S based solutions.

关键词： Encoding Complexity theory Analytical models Big data Parity check codes Galois fields Decoding

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Stress-aware routing to mitigate aging effects in SRAM-based FPGAs

Stress-aware routing to mitigate aging effects in SRAM-based...

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international Conference on Field Programmable Logic and Applications

作者： Behnam Khaleghi Behzad Omidi Hussam Amrouch Jörg Henkel Hossein Asadi Department of Computer Engineering Sharif University of Technology Tehran Chair for Embedded Systems Karlsruhe Institute of Technology Germany

Continuous shrinking of transistor size to provide high computation capability along with low power consumption has been accompanied by reliability degradations due to e.g., aging phenomenon. In this regard, with huge number of configuration bits, Field-Programmable Gate Arrays (FPGAs) are more susceptible to aging since aging not only degrades the performance, it may additionally result in corrupting the configuration cells and thus causing permanent circuit malfunctioning. While several works have investigated the aging effects in Look-Up Tables (LUTs), the routing fabric of these devices is seldom studied - even though it contributes to the majority of FPGAs' resources and configuration bits. Furthermore, there is a high prospect that errors in its state to propagate to the device outputs. In this paper, we first investigate aging effects in the routing fabric of FPGAs with respect to performance and reliability degradations. Based on this investigation, we enhance the conventional routing algorithm to mitigate the impact of aging by increasing the recovery time (i.e., the mechanism used to heal aging-induced defects) of transistors used in the routing resources. We examine our proposed method as reduction in stress time and required guardband to protect against aging in the routing fabric, as well as in improving the FPGA's lifetime. Our experiments show that the proposed method reduces the average stress time and aging-induced delay of routing resources by 41% and 18.3%, respectively. This, in turn, leads to improving the device lifetime by 130% compared to baseline routing. The proposed method can be applied by simple amending of conventional routing algorithms. Thus, it incurs negligible delay overhead.

关键词： Aging Routing Field programmable gate arrays Table lookup Stress Delays Transistors

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ZNN -- A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory Machines

ZNN -- A Fast and Scalable Algorithm for Training 3D Convolu...

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international Symposium on Parallel and Distributed Processing (IPDPS)

作者： Aleksandar Zlateski Kisuk Lee H. Sebastian Seung Electrical Engineering and Computer Science Dept. Cambridge MA USA Brain and Cognitive Sciences Dept. Massachwsetts Institute of Technology Cambridge MA USA Computer Science Dept. Princeton University Princeton NJ USA

ISBN: (纸本)9781509021413

Convolutional networks (ConvNets) have become a popular approach to computer vision. It is important to accelerate ConvNet training, which is computationally costly. We propose a novel parallel algorithm based on decomposition into a set of tasks, most of which are convolutions or FFTs. Applying Brent's theorem to the task dependency graph implies that linear speedup with the number of processors is attainable within the PRAM model of parallel computation, for wide network architectures. To attain such performance on real shared-memory machines, our algorithm computes convolutions converging on the same node of the network with temporal locality to reduce cache misses, and sums the convergent convolution outputs via an almost wait-free concurrent method to reduce time spent in critical sections. We implement the algorithm with a publicly available software package called ZNN. Benchmarking with multi-core CPUs shows that ZNN can attain speedup roughly equal to the number of physical cores. We also show that ZNN can attain over 90× speedup on a many-core CPU (Xeon Phi™ Knights Corner). These speedups are achieved for network architectures with widths that are in common use. The task parallelism of the ZNN algorithm is suited to CPUs, while the SIMD parallelism of previous algorithms is compatible with GPUs. Through examples, we show that ZNN can be either faster or slower than certain GPU implementations depending on specifics of the network architecture, kernel sizes, and density and size of the output patch. ZNN may be less costly to develop and maintain, due to the relative ease of general-purpose CPU programming.

关键词： Kernel Image edge detection Convolutional codes Transfer functions Training Three-dimensional displays Jacobian matrices

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