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

共 1728 条记录，以下是1711-1720 订阅

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Exploiting randomness in sketching for efficient hardware implementation of machine learning applications

Exploiting randomness in sketching for efficient hardware im...

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IEEE international Conference on Computer-Aided Design

作者： Ye Wang Constantine Caramanis Michael Orshansky Department of Electrical and Computer Engineering University of Texas at Austin Austin TX USA

ISBN: (纸本)9781509034215

Energy-efficient processing of large matrices for big-data applications using hardware acceleration is an intense area of research. Sketching of large matrices into their lower-dimensional representations is an effective strategy. For the first time, this paper develops a highly energy-efficient hardware implementation of a class of sketching methods based on random projections, known as Johnson Lindenstrauss (JL) transform. Crucially, we show how the randomness inherent in the projection matrix can be exploited to create highly efficient fixed-point arithmetic realizations of several machine-learning applications. Specifically, the transform's random matrices have two key properties that allow for significant energy gains in hardware implementations. The first is the smoothing property that allows us to drastically reduce operand bit-width in computation of the JL transform itself. The second is the randomizing property that allows bit-width reduction in subsequent machine-learning applications. Further, we identify a random matrix construction method that exploits the special sparsity structure to result in the most hardware-efficient realization and implement the highly optimized transform on an FPGA. Experimental results on (1) the k-nearest neighbor (KNN) classification and (2) the principal component analysis (PCA) show that with the same bit-width the proposed flow utilizing random projection achieves an up to 7× improvement in both latency and energy. Furthermore, by exploiting the smoothing and randomizing properties we are able to use a 1-bit instead of a 4-bit multiplier within KNN, which results in additional 50% and 6% improvement in area and energy respectively. The proposed I/O streaming strategy along with the hardware-efficient JL algorithm identified by us is able to achieve a 50% runtime reduction, a 17% area reduction in the stage of random projection compared to a standard design.

关键词： Transforms Hardware Smoothing methods Principal component analysis Algorithm design and analysis Sparse matrices Signal processing algorithms

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Motion control of thruster-driven underwater vehicle based on Model Predictive Control

Motion control of thruster-driven underwater vehicle based o...

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IEEE international Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Xing Jin Kaizhou Liu Yingbin Feng Yan Huang Yang Zhao Shengguo Cui Guang Yuan State Key Laboratory of Exploitation and Utilization of Deep-sea Mineral Resources Changsha Research Institute of Mining and Metallurgy Co. Ltd Changsha China State Key Laboratory of Robotics Chinese Academy Sciences Shenyang China School of Information Science & Engineering Northeastern University Shenyang China

ISBN: (纸本)9781509027347

Underwater vehicles have been developed over the last six decades for potential uses in scientific, commercial, environmental, and military purposes, and always utilized to perform difficult tasks in cluttered environments such as deep-sea mining, underwater sampling and oceanic investigations. Since underwater vehicles have nonlinear and highly coupled dynamics, motion control can be difficult when completing complex tasks. This paper describes the implementation of a model predictive controller novel in a class of thruster-driven underwater vehicle. In this paper, a constrained discrete-time model predictive control method is employed for the motion control of thruster-driven underwater vehicles. A nonlinear model in six degree of freedom is established based on the dynamics of human occupied vehicle Jiao-long, and converted into a state space model after practical simplification. To ensure the performance of model predictive controller, a full feedback state observer is established to observe the state. In addition, Hildreth's quadratic programming algorithm is incorporated for solving the optimal control sequence, which greatly reduced the computation of the model predictive control algorithm. In order to show the effectiveness of the motion control method, simulations based on dynamics of human occupied vehicle Jiao-long are conducted. Performance on depth control, heading control and hovering control are evaluated. All the results demonstrate the effectiveness of the method.

关键词： Underwater vehicles Vehicles Motion control Optimal control Mathematical model Vehicle dynamics Heuristic algorithms

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On Dynamic Resource Allocation for Blockchain Assisted Federated Learning over Wireless Channels

On Dynamic Resource Allocation for Blockchain Assisted Feder...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Xiumei Deng Jun Li Long Shi Zhe Wang Jessie Hui Wang Taotao Wang Nanjing University of Science and Technology Nanjing China Institute for Network Sciences and Cyberspace Tsinghua University Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781665417631

The blockchain technology has been extensively studied to enable distributed and tamper-proof data processing in federated learning (FL). Most existing blockchain assisted FL (BFL) frameworks have employed a third-party blockchain network to decentralize the model aggregation process. However, the decentralized model aggregation is vulnerable to pooling and collusion attacks from the third-party blockchain network. Driven by this issue, we propose a novel BFL framework that features the integration of training and mining at the client side. In our framework, the client first transmits its trained model to other clients, performs global aggregation upon receiving others' models, and competes to mine a block for aggregated model verification without the intervention of any third-party blockchain network. Considering the model transmission over time-varying wireless channels, we propose a dynamic training client scheduling to meet stringent latency requirement in FL, where clients with qualified channel conditions are scheduled to train their models in each communication round. Furthermore, we formulate a joint optimization problem of the training client scheduling and dynamic resource allocation (i.e., the transmit and computation power at the client side) under the constraint of long-term time-average (LTA) energy consumption. The objective of this optimization problem is to maximize the LTA training data size and thereby optimize the learning performance of FL. To this end, we obtain the closed-form solution by using the Lyapunov optimization method. Our experimental results show that the optimal solution can outperform baseline schemes in terms of learning accuracy and convergence time.

关键词： Training Social computing Processor scheduling Wireless networks Heuristic algorithms Training data Optimization methods

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Hybrid Backtracking Search Optimization Algorithm and K-Means for Clustering in Wireless Sensor Networks

Hybrid Backtracking Search Optimization Algorithm and K-Mean...

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

作者： N.M. Abdul Latiff N.N. Nik Abdul Malik L. Idoumghar Faculty of Electrical Engineering UTM Johor Bahru Johor Malaysia LMIA Laboratory (EA 3993) University of Haute-Alsace Mulhouse France

Rapid technology evolvement in the area of wireless sensor networks (WSNs) has led to many application-specific protocols that are particularly developed to cover different fields of usage and various network scenarios. Energy efficiency is one of the apparent challenges facing WSNs which has impacted immensely on the network performance. Hence, clustering protocols that eliminate energy inefficiencies in the network is essential. As finding an optimal set of cluster heads is an NP-hard problem, the application of heuristic algorithm is required to produce good clustering. In this paper, we propose a clustering solution for WSNs using a hybrid algorithm based on Backtracking Search Optimization Algorithm (BSA) and K-Means. A fitness function that incorporates aspects such as expected energy consumption in the network and maximum intra-cluster distance is utilized to address the problem of energy efficiency. Performance comparison against well-known clustering protocols such as LEACH and LEACH-C reveals that the hybrid of BSA and K-Means clustering algorithm is able to deliver more data to the base station and extends the network lifetime.

关键词： Clustering algorithms Wireless sensor networks Protocols Base stations Energy efficiency Algorithm design and analysis Optimization

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An efficient polygon marine data update approach based on features matching

An efficient polygon marine data update approach based on fe...

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international Conference on Agro-Geoinformatics

作者： Qingxiang Meng Jing Chen School of Remote Sensing and Information Engineering Wuhan University Wuhan China

The sea area under the jurisdiction of China is approximately 300 million km^2, which is one-fifth of the land area of China. There are a plenty of marine resources in China. So, some ocean development strategies are proposed in the 13th Five-Year Plan and 18th Party congress of China. Now, different sources of ocean mapping determine data's differences in classification, scale, spatial location, geometry, topology and attribute description. Those differences make it hard to update and regulate ocean data. After having an array of comprehensive investigations in geometric characteristics of marine polygon data, a multi-level vector polygon features matching model is proposed in this paper. This model is used to match marine data, which means to find out vector features which represent a same object. So, the efficiency of updating is boosted and the longitudinal consistency of marine data is guaranteed. The model is divided into three steps: First, extract key characteristics of complex polygon vector features; Second, describe dynamic geometric characteristics of those features; Third, match and compare the characteristics through an advanced model based on shape and distance. In the first step of the model-extract key characteristics, the Douglas-Peucker Algorithm is improved in this paper to simplify polygon features, which is aimed at extracting those features' geometric characteristics and reserving key characteristics in those geometric characteristics. Also, the parameters, which is called distance threshold-T, in this simplification algorithm is modified dynamically. After the simplification of polygon features, a geometric model is used in this paper to describe shape characteristics and distance characteristics of a polygon feature. When it comes to evaluate the shape similarity of two polygons through a tangent space model (shape distance model), the complexity of this two polygon features should be similar. On the contrary, if a segment of a polygon is mu

关键词： Shape Feature extraction Semantics Data models Oceans Geometry Heuristic algorithms

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One-Sided Interface for Matrix Operations Using MPI-3 RMA: A Case Study with Elemental

One-Sided Interface for Matrix Operations Using MPI-3 RMA: A...

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international Conference on Parallel Processing (ICPP)

作者： Sayan Ghosh Jeff R. Hammond Antonio J. Peña Pavan Balaji Assefaw H. Gebremedhin Barbara Chapman School of Electrical Engineering and Computer Science Washington State University Pullman WA USA Parallel Computing Lab Intel Corp. Portland OR USA Centro Nacional de Supercomputacion Barcelona ES Mathematics and Computer Science Division Argonne National Laboratory Lemont IL USA Institute for Advanced Computational Science Stony Brook University Stony Brook NY USA

A one-sided programming model separates communication from synchronization, and is the driving principle behind partitioned global address space (PGAS) libraries such as Global Arrays (GA) and SHMEM. PGAS models expose a rich set of functionality that a developer needs in order to implement mathematical algorithms that require frequent multidimensional array accesses. However, use of existing PGAS libraries in application codes often requires significant development effort in order to fully exploit these programming models. On the other hand, a vast majority of scientific codes use MPI either directly or indirectly via third-party scientific computation libraries, and need features to support application-specific communication requirements (e.g., asynchronous update of distributed sparse matrices, commonly arising in machine learning workloads). For such codes it is often impractical to completely shift programming models in favor of special one-sided communication middleware. Instead, an elegant and productive solution is to exploit the one-sided functionality already offered by MPI-3 RMA (Remote Memory Access). We designed a general one-sided interface using the MPI-3 passive RMA model for remote matrix operations in the linear algebra library Elemental, we call the interface we designed RMAInterface. Elemental is an open source library for distributed-memory dense and sparse linear algebra and optimization. We employ RMAInterface to construct a Global Arrays-like API and demonstrate its performance scalability and competitivity with that of the existing GA (with ARMCI-MPI) for a quantum chemistry application.

关键词： Libraries Arrays Two dimensional displays computational modeling Matrices Data models

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Fast sparse 2-D DFT computation using sparse-graph alias codes

Fast sparse 2-D DFT computation using sparse-graph alias cod...

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international Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Frank Ong Sameer Pawar Kannan Ramchandran Dept. of Electrical Engineering and Computer Sciences University of California Berkeley

ISBN: (纸本)9781479999897

We present a novel algorithm, named the 2D-FFAST (Two-dimensional Fast Fourier Aliasing-based Sparse Transform), to compute a sparse 2D-Discrete Fourier Transform (2D-DFT) featuring both low sample and computational complexity. The proposed algorithm is based on diverse concepts from signal processing (sub-sampling and aliasing), coding theory (sparse-graph codes) and number theory (Chinese-remainder-theorem) and generalizes the 1D-FFAST algorithm recently proposed by Pawar and Ramchandran to the 2D setting. Concretely, our proposed 2D-FFAST algorithm computes a k-sparse 2D-DFT, with a uniformly random support, of size N = N x × N y using O(k) noiseless spatial-domain measurements in O(k log k) computational time. Our results are attractive when the sparsity is sub-linear with respect to the signal dimension, that is, when k → ∞ and k/N → 0. For the case when the spatial-domain measurements are corrupted by additive noise, our 2D-FFAST framework extends to a noise-robust version of computing a 2D-DFT using O(k log 3 N) measurements in sub-linear time of O(k log 4 N). Empirically, we show that the 2D-FFAST can compute a k = 3509 sparse 2D-DFT of a 508 × 508-size phantom image using only 4.75k measurements. We also empirically evaluate the 2D-FFAST algorithm on a real-world magnetic resonance brain image using a total of 60.18% of Fourier measurements to provide an almost instant reconstruction with SNR=4.5 dB. This provides empirical evidence that the 2D-FFAST architecture is applicable to a wider class of input signals than analyzed theoretically in the paper.

关键词： Discrete Fourier transforms Signal processing algorithms Algorithm design and analysis computational complexity Computer architecture Delays Decoding

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Transfer Learning for Survival Analysis via Efficient L2,1-Norm Regularized Cox Regression

Transfer Learning for Survival Analysis via Efficient L2,1-N...

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IEEE international Conference on Data Mining (ICDM)

作者： Yan Li Lu Wang Jie Wang Jieping Ye Chandan K. Reddy Dept. of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI Dept. of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI Dept. of Computer Science Wayne State University Detroit MI Dept. of Computer Science Virginia Tech Arlington VA

ISBN: (纸本)9781509054749

In survival analysis, the primary goal is to monitor several entities and model the occurrence of a particular event of interest. In such applications, it is quite often the case that the event of interest may not always be observed during the study period and this gives rise to the problem of censoring which cannot be easily handled in the standard regression approaches. In addition, obtaining sufficient labeled training instances for learning a robust prediction model is a very time consuming process and can be extremely difficult in practice. In this paper, we propose a transfer learning based Cox method, called Transfer-Cox, which uses auxiliary data to augment learning when there are insufficient amount of training examples. The proposed method aims to extract "useful" knowledge from the source domain and transfer it to the target domain, thus potentially improving the prediction performance in such time-to-event data. The proposed method uses the l 2,1 -norm penalty to encourage multiple predictors to share similar sparsity patterns, thus learns a shared representation across source and target domains, potentially improving the model performance on the target task. To speedup the computation, we apply the screening approach and extend the strong rule to sparse survival analysis models in multiple high-dimensional censored datasets. We demonstrate the performance of the proposed transfer learning method using several synthetic and high-dimensional microarray gene expression benchmark datasets and compare with other related competing state-of-the-art methods. Our results show that the proposed screening approach significantly improves the computational efficiency of the proposed algorithm without compromising the prediction performance. We also demonstrate the scalability of the proposed approach and show that the time taken to obtain the results is linear with respect to both the number of instances and features.

关键词： Analytical models Learning systems Data models Hazards Predictive models Prediction algorithms Standards

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Battery-Aware Routing in Wireless Ad Hoc Networks - Part I: Energy Model

Battery-Aware Routing in Wireless Ad Hoc Networks - Part I: ...

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The 19th international Teletraffic congress-ITC19

作者： Yuanyuan Yang and Chi Ma Department of Electrical and Computer engineering State University of New York at Stony Brook, Stony Brook, NY 11790 Department of Computer Science State University of New York at Stony Brook, Stony Brook, NY 11790

A key challenge in wireless ad hoc networks is to achieve maximum lifetime for battery-powered mobile devices with dynamic energy efficient algorithms. Recent study in battery technology reveals that the behavior of battery discharging is more complex than we used to think. Battery powered devices might waste a huge amount of energy if we do not carefully schedule and budget their discharging. In this paper, we introduce a novel energy model for batteries and study the effect of battery behavior on routing in wireless ad hoc networks. Based on this model, we also propose a battery-aware routing protocol. The paper consists of two parts. In Part I of the paper, we propose an on-line computable discrete time analytical model to mathematically model battery discharging behavior. The model has low computational complexity and does not require large look-up tables. It is suitable for on-line battery capacity computation in ad hoc network routing. We use the data collected from actual nickel-cadmium battery to evaluate the performance of our model and the results show that it can accurately capture the behavior of battery discharging. In Part II of the paper [1], a battery-aware routing protocol (BAR) is proposed based on the new battery model. By dynamically choosing the nodes with well recovered batteries as routers, and leaving the "fatigue" nodes for recovery, the BAR protocol can effectively recover the node's battery capacity and achieve higher energy efficiency. Our simulation results show that the BAR protocol can increase network lifetime and total data throughput by up to 28% and 24%, respectively, compared with previous routing protocols. As far as we know, this is the first work considering battery-awareness with an accurate on-line computable battery model in ad hoc network routing. We believe our battery model can be used to explore other energy efficient schemes for wireless networks as well.

关键词： Wireless ad hoc networks, energy efficiency, battery models, battery-awareness, routing protocols.

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A Comparative Study of Two Classical Topology-Transparent Scheduling algorithms for Multi-Hop Packet Radio Networks

A Comparative Study of Two Classical Topology-Transparent Sc...

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international Conference on Wireless Communications, Signal Processing and Networking

作者： Dipti Dash Debarshi Kumar Sanyal Arup Sarkar Dibyajyoti Guha School of Computer Engineering KIIT University Bhubaneswar 751024 India

ISBN: (纸本)9781467393393

The aim of topology-transparent scheduling algorithms for multi-hop wireless networks is to find a schedule for the nodes that does not need re-computation when the network topology changes. It caters to highly dynamic scenarios where topology changes occur faster than the speed at which schedule updates can be orchestrated. These algorithms normally take as input only global network parameters like the maximum number of nodes and the maximum degree of a node in the network, rather than the detailed topology of the network. In this paper, we study two classical topology-transparent scheduling algorithms: the algorithm due to Chlamtac and Farag6 and the optimal algorithm due to Ju and Li. We provide qualitative comparison of the algorithms followed by numerical simulations to study their throughput characteristics which are also compared with those of multi-hop slotted-ALOHA and TDMA.

关键词： Wireless network Media access control Topology Scheduling Mobility TDMA

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