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A Two-stage Deep Learning-Based Approach for Automatic Reading of Analog Meters 11

A Two-Stage Deep Learning-Based Approach for Automatic Readi...

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Joint 11th international Conference on Soft computing and Intelligent Systems and 21st international symposium on Advanced Intelligent Systems (SCIS-ISIS)

作者： Ueda, Shohei Suzuki, Kaito Kanno, Jumpei Zhao, Qiangfu Univ Aizu Aizu Wakamatsu Fukushima Japan

ISBN: (纸本)9781728197326

In many factories in Japan, there are still thousands of analog meters to monitor and control the fabrication environments. Human inspectors must walk around, read the meters, record the values, and input them into the computer for further analysis. This process is prone to human errors. To solve the problem, we may consider to replace all analog meters with digital ones, but this is not practical due to the high replacement cost. In this study, we propose a system to automate the meter reading process. Using this system, an inspector just takes a short video of the meter using a smart phone, sends the video to a server, and the server can read the meter value and record the results automatically. To make the system practically useful, we introduce three techniques. The first one is a two-stage deep learning-based method for detecting the meter and its pointer;the second one is homography transform to normalize the view point for capturing the video;and the third is a multi-frame-based method for improving the reading accuracy. Experimental results with circular meters show that the accuracy of the proposed system is acceptable. This paves a way for us to automate the reading process of other types of analog meters.

关键词： computer vision image object detection error analysis

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performance modelling of peer-to-peer routing

Performance modelling of peer-to-peer routing

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21st international Parallel and Distributed Processing symposium, IPDPS 2007

作者： Rai, Idris A. Brampton, Andrew MacQuire, Andrew Mathy, Laurent Computing Department Lancaster University

ISBN: (纸本)1424409101

We propose several models based on discrete-time Markov chains for the analysis of Distributed Hash Tables (DHTs). Specifically, we examine the Pastry routing protocol, as well as a stealth DHT adaptation of Pastry to compute their exact expressions for average number of lookup hops. We show that our analytical models match with the protocols' simulation results almost perfectly, making them ideal for rapid evaluation. ©2007 IEEE.

关键词： Distributed computer systems

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Data shepherding: A last level cache design for large scale chips 21

Data shepherding: A last level cache design for large scale ...

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21st IEEE international Conference on high performance computing and Communications, 17th IEEE international Conference on Smart City and 5th IEEE international Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Jang, Ganghee Gaudiot, Jean-Luc Electrical and Computer Engineering Clarkson University Potsdam United States Electrical Engineering and Computer Science University of California Irvine Irvine United States

ISBN: (纸本)9781728120584

Newer chips include cache memories as large as 128 MB to sustain the bandwidth for the GPGPU module. As 128 MB was a reasonable main memory size a decade ago, we examine the design impact of a larger granularity in the management of caches. We thus propose a cache memory design called the Data Shepherding Cache for larger last level caches. Even with a granularity as large as a page for the management of the last level cache, our Data Shepherding Cache could achieve reasonable performance from a smaller area footage over the same sized set associative cache. © 2019 IEEE.

关键词： Cache memory

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Toward data discovery in dynamic smart city applications 21

Toward data discovery in dynamic smart city applications

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作者： Moeini, Hessam Zeng, Wenxi Yen, I-Ling Bastani, Farokh Department of Computer Science University of Texas Dallas United States

ISBN: (纸本)9781728120584

A smart city leverages the IoT capabilities to ensure the well-being of the inhabitants and their activities in the city. IoT based data collection and data analytics are the fundamental technologies to achieve the goal. Due to the wide varieties of environment conditions and activities that are to be monitored for the urban environment, a large number of sensors of all sorts are deployed across the city and the number of different data streams collected from these sensors can be tremendous. At the same time, different analysis tasks and dynamic queries may be issued and, correspondingly, the relevant data need to be efficiently discovered, retrieved, and analyzed in order to provide the desired answers. As can be seen, how to manage all the IoT data streams to facilitate data discovery can be highly challenging. In this paper, we discuss a set of scenarios to show the importance of data management and discovery in the smart city environment. Then, we present a semantic model for smart city data specification to facilitate data discovery. Finally, we discuss an edge-centric architecture and the data discovery approach for enabling efficient and effective dynamic smart city data analytics. © 2019 IEEE.

关键词： Internet of things

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A Scientific data traffic scheduling algorithm based on software-defined networking 21

A Scientific data traffic scheduling algorithm based on soft...

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作者： Zhou, Yaqiu Ren, Yongmao Zhou, Xu Yang, Wanghong Qin, Yifang Computer Network Information Center Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Computer Network Information Center Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728120584

Compared to ordinary Internet applications, the transfer of scientific data flows often has higher requirements for network performance. The network security devices and systems often affect the efficiency of scientific data transfer. As a new type of network architecture, Software-defined Networking (SDN) decouples the data plane from the control plane. Its programmability allows users to customize the network transfer path and makes the network more intelligent. The Science DMZ model is a private network for scientific data flow transfer, which can improve performance under the premise of ensuring network security. This paper combines SDN with Science DMZ, designs and implements an SDN-based traffic scheduling algorithm considering the load of link. In addition to distinguishing scientific data flow from common data flow, the algorithm further distinguishes the scientific data flows of different applications and performs different traffic scheduling of scientific data for specific link states. Experiments results proved that the algorithm can effectively improve the transmission performance of scientific data flow. © 2019 IEEE.

关键词： Data transfer

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high-performance mesoscopic traffic simulation with GPU for large scale networks 17

High-performance mesoscopic traffic simulation with GPU for ...

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21st IEEE/ACM international symposium on Distributed Simulation and Real Time Applications, DS-RT 2017

作者： Vu, Vinh An Tan, Gary School of Computing National University Singapore Singapore117417 Singapore

ISBN: (纸本)9781538640289

Mesoscopic Traffic Simulation is an important tool in traffic analysis and traffic management support. The balance between traffic modeling details and performance has made Mesoscopic Traffic Simulation one of the key solutions for traffic controllers and policy makers. Mesoscopic traffic simulators offer acceptable speed in simulating normal traffic. However, when traffic prediction and optimization for large scale networks come into context, the performance of mesoscopic traffic simulators is unsatisfactory in optimizing a massive number of control parameters for a much longer prediction horizon. This issue again emphasizes the need to further speed up mesoscopic traffic simulation. This paper proposes a comprehensive framework to massively speed up mesoscopic traffic simulation using GPU without compromising its correctness and realistic modeling property. It also gives an in-depth analysis into the trade-off between simulation correctness and performance speedup. By combining the power of GPU with optimal design and data structures, mesoscopic traffic simulation is able to speed up to more than 6 times compared to original CPU implementation. © 2017 IEEE.

关键词： Graphics processing unit

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Tradeoffs in Designing Accelerator architectures for Visual computing 41

Tradeoffs in Designing Accelerator Architectures for Visual ...

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41st Annual IEEE/ACM international symposium on Microarchitecture

作者： Mahesri, Aqeel Johnson, Daniel Crago, Neal Patel, Sanjay J. Univ Illinois Dept Elect & Comp Engn Ctr Reliable & High Performance Comp Urbana IL 61801 USA

ISBN: (纸本)9781424428366

Visualization, interaction, and simulation (VIS) constitute a class of applications that is growing in importance. This class includes applications such as graphics rendering, video encoding, simulation, and computer vision. These applications are ideally suited for accelerators because of their parallelizability and demand for high throughput. We compile a benchmark suite, VISBench, to sense as a proxy for this application class. We use VISBench to examine some important high level decisions for all accelerator architecture. We propose a highly parallel base architecture. We examine the need for synchronization and data communication. We also examine GPU-style SIMD execution and find that a MIMD architecture usually performs better. Given these high level choices, we use VISBench to explore the microarchitectural design space. We analyze area versus performance tradeoffs in designing individual cores and the memory hierarchy. We find that a design made of small, sample cores achieves much higher throughput than a general purpose uniprocessor. Further we find that a limited amount of support for ILP within each core aids overall performance. We find that fine-grained multithreading improves performance, but only up to a point. We find that word-level (SSE-style) SIMD provides a poor performance to area ratio. Finally, we find that sufficient memory and cache band-width is essential to performance.

关键词： Accelerator architectures Application software Computational modeling Throughput Visualization computer graphics Rendering (computer graphics) Encoding computer simulation computer vision

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Energy optimization on dynamic multiple functions automotive cyber-physical systems 21

Energy optimization on dynamic multiple functions automotive...

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作者： Liu, Yan Xie, Guoqi Jin, Linlin Li, Renfa Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Changsha Hunan China

ISBN: (纸本)9781728120584

A new generation of automotive electronic systems is a typical cyber-physical systems (CPS) based on an integrated architecture, in which multiple functions can be executed on one electronic control unit (ECU) and one function can be assigned to different ECU. Heterogeneity and dynamics are essential characteristics of automotive CPS (ACPS). Considering heterogeneity and dynamics of ACPS, optimizing functional safety and energy consumption in system design is still a challenge. In this paper, we focus on the collaborative optimization of functional safety and energy consumption with global method in the context of prioritizing functional safety. Considering the requirements of functional safety, we propose a deadline driven processor merging for multiple dynamic functions (DPMMDF) algorithm to maximizes the number of functions that meet deadlines when a function arrives dynamically from the perspective of global optimization. Further, we use a global energy saving for multiple dynamic functions (GESMDF) algorithm, combined with the integrated architecture features, to optimize the energy consumption of ACPS by selecting multiple candidate executable ECUs for a task. Experimental results show that combination of the proposed two algorithms can effectively reduce deadline missed ratio (DMR), and minimize energy consumption compared with existing methods. © 2019 IEEE.

关键词： Global optimization

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Enhancing portability of HPC applications across high-end computing platforms

Enhancing portability of HPC applications across high-end co...

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21st international Parallel and Distributed Processing symposium, IPDPS 2007

作者： Slawińska, Magdalena Slawiński, Jaroslaw Kurzyniec, Dawid Sunderam, Vaidy Dept. of Math and Computer Science Emory University 400 Dowman Drive Atlanta GA 30322 United States

ISBN: (纸本)1424409101

Fast hardware turnover in supercomputing centers, stimulated, by rapid technological progress, results in high heterogeneity among HPC platforms, and necessitates that applications are ported and adapted frequently. The cutting-edge nature of the hardware mandates customized performance tuning, which, coupled with continuously growing application complexity, makes the process inherently and increasingly challenging. In this paper, we analyze build procedures of a representative set of HPC applications, and attempt to identify commonalities that can be exploited to enhance cross-platform portability. We then propose a novel method for reducing non-portabilities while preserving high performance. The approach, based on profiles that capture and isolate non-portable features at various levels, requires only a moderate amount of changes to existing makefiles. It leverages the expertise of system designers and administrators, and reduces burdens placed on application scientists. As a proof of concept, we discuss the application of our methodology to enhancing portability of the Mile application across heterogeneous HPC platforms. ©2007 IEEE.

关键词： Computation theory

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Compression of Time Evolutionary Image Data through Predictive Deep Neural Networks 21

Compression of Time Evolutionary Image Data through Predicti...

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21st IEEE/ACM international symposium on Cluster, Cloud and Internet computing (CCGrid)

作者： Roy, Rupak Sato, Kento Bhattachrya, Subhadeep Fang, Xingang Joti, Yasumasa Hatsui, Takaki Hiraki, Toshiyuki Nishiyama Guo, Jian Yu, Weikuan Florida State Univ Tallahassee FL 32306 USA RIKEN Ctr Computat Sci Wako Saitama Japan RIKEN SPring 8 Ctr Wako Saitama Japan Anhui Univ Finance & Econ Bengbu Peoples R China

ISBN: (纸本)9781728195865

Recent advances in Deep Neural Networks (DNNs) have demonstrated a promising potential in predicting the temporal and spatial proximity of time evolutionary data. In this paper, we have developed an effective (de)compression framework called TEZIP that can support dynamic lossy and lossless compression of time evolutionary image frames with high compression ratio and speed. TEZIP first trains a Recurrent Neural Network called PredNet to predict future image frames based on base frames, and then derives the resulting differences between the predicted frames and the actual frames as more compressible delta frames. Next we equip TEZIP with techniques that can exploit spatial locality for the encoding of delta frames and apply lossless compressors on the resulting frames. Furthermore, we introduce window-based prediction algorithms and dynamically pinpoint the trade-off between the window size and the relative errors of predicted frames. Finally, we have conducted an extensive set of tests to evaluate TEZIP. Our experimental results show that, in terms of compression ratio, TEZIP outperforms existing lossless compressors such as x265 by up to 3.2x and lossy compressors such as SZ by up to 3.3x.

关键词： Deep learning Cloud computing Image coding Recurrent neural networks Heuristic algorithms Tools Prediction algorithms

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