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15th IFIP/ieee International symposium on Integrated Network and Service Management, IM 2017

作者： Zhang, Bowu Hwang, Jinho Marist College PoughkeepsieNY United States IBM T.J. Watson Research Center Yorktown HeightsNY United States

ISBN: (纸本)9783901882890

Recent advance in geo-distributed systems has made distributed data processing possible, where tasks are decomposed into subtasks, deployed into multiple data centers and run in parallel. Compared to conventional approaches that process every task in a single datacenter resulting in high latency and large data aggregation, the geo-distributed cloud systems provide a highly available and more economic platform. However, distributed application (task) execution introduces extra cost and latency as data need to be exchanged between data centers. In addition, task dependency and diverse task constraints make it even more challenging to choose an appropriate task assignment strategy. In this paper, we discuss a task assignment problem in geographically distributed cloud systems. In light of growing demand from big data processing and storage, we consider data intensive tasks where a task often requires significant computing resources and its input data typically located in multiple data centers. By taking the distributed input, task dependency, heterogeneous pricing scheme, and resource constraints into account, we aim to optimize the performance when deploying tasks in geo-graphically distributed data centers. A heuristic algorithm is presented to provide an approximate solution to the proposed NP-hard problem. We perform an extensive simulation study to evaluate the performance of our solution under various settings. the simulation results demonstrate that our approach can outperform the state-of-the-art strategies, and achieve significant reduction in cost and latency. © 2017 IFIP.

关键词： distributed cloud

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Compression and Aggregation for Optimizing Information Transmission in distributed CNN 5

Compression and Aggregation for Optimizing Information Trans...

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5th International symposium on Computing and Networking (CANDAR)

作者： Mitani, Takamasa Fukuoka, Hisakazu Hiraga, Yuria Nakada, Takashi Nakashima, Yasuhiko Nara Inst Sci & Technol Grad Sch Informat Sci 8916-5 Takayama Cho Ikoma Nara 6300192 Japan

ISBN: (纸本)9781538620878

Modern deep learning has significantly improved the performance and has been used in a variety of applications. Due to the heavy processing cost, major platforms for deep learning have been migrated from commodity computers to the cloud where have huge amount of resources. However, the above situation leads to the slowdown of response time due to severe congestion of the network traffic. To alleviate the overconcentration of data traffic and power consumption, many researchers have paid attention to edge computing. We tackle with the parallel processing model using Deep Convolutional Neural Network (DCNN) employed on multiple devices, and the size reduction of network traffic among the devices. We propose a technique that compresses the intermediate data and aggregates common computation in AlexNet for video recognition. Our experiments demonstrate that Zip loss-less compression reduces the amount of data by up to 1/24, and HEVC lossy compression reduces the amount of data by 1/208 with only 3.5% degradation of the recognition accuracy. Moreover, aggregation of common calculation reduces the amount of computation for 30 DCNNs by 90%.

关键词： Convolution Neural Network Edge Computing Model parallel Video Compression Aggregation

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Automatic characterization of hpc job parallel filesystem I/O patterns 18

Automatic characterization of hpc job parallel filesystem I/...

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2018 Practice and Experience in Advanced Research Computing Conference: Seamless Creativity, PEARC 2018

作者： White, Joseph P. Innus, Martins Kofke, Alexander D. Jones, Matthew D. DeLeon, Robert L. Furlani, thomas R. Center for Computational Research Buffalo NY United States University at Buffalo BuffaloNY United States

ISBN: (纸本)9781450364461

As part of the NSF funded XMS project, we are actively researching automatic detection of poorly performing HPC jobs. To aid the analysis we have generated a taxonomy of the temporal I/O patterns for HPC jobs. In this paper we describe the design of temporal pattern characterization algorithms for HPC job I/O. We have implemented these algorithms in the Open XDMoD job analysis framework. these I/O classifications include periodic patterns and a variety of characteristic non-periodic patterns. We present an analysis of the I/O patterns observed on the /scratch filesystem on an academic HPC cluster. this type of analysis can be extended to other HPC usage data such as memory, CPU and interconnect usage. Ultimately this analysis will be used to improve HPC throughput and efficiency by, for example, automatically identifying anomalous HPC jobs. © 2018 Association for Computing Machinery.

关键词： File organization

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distributed publisher-subscriber architectures performance for robotics virtual reality applications: A case study on MQTT 14

Distributed publisher-subscriber architectures performance f...

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14th Latin American Robotics symposium and 5th Brazilian symposium on Robotics, LARS-SBR 2017

作者： Resende Mattioli, Leandro Souza, Daniel S. Cunha, Marcio J. Cardoso, Alexandre Faculty of Electrical Engineering Federal University of Uberlândia Brazil

ISBN: (纸本)9781538609569

Virtual Reality has been traditionally explored in many robotics systems, with applications such as off-line programming, trajectory planning, teleoperation, education, design, natural user interfaces and rehabilitation. Implementing these features in an all-in-one monolithic solution can be complex and slow. Also, new trends in automation, notably the Internet of things, represent promissing technological improvements to the robotics field. this paper presents an alternative for developing such distributed and evolutive applications by defining a minimalistic set of commands for physical and virtual robots and integrating them with a publisher-subscriber network, commonly used with Internet of things. this allows several configurations, depending on the available modules and on which elements subscribe to each topic. thus, we discuss the performance of a small network comprising 3 agents: one input application acting as a real-time publisher and two subscribers associated with a physical and a virtual robot. All machine clocks are synchronized with the ieee 1588-2008 protocol and the application packages are stored with timestamps on log files for evaluating metrics such as the package transmission rate and the latency. Results indicate that the overall performance on a local area network for this kind of application is beyond the physical robot's maximum update rate. Further tests might consider other time syncing mechanisms, wireless networks and different configurations with more network nodes. © 2017 ieee.

关键词： Virtual reality

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Efficient Breadth-First Search on Massively parallel and distributed-Memory Machines

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DATA SCIENCE AND ENGINEERING 2017年第1期2卷 22-35页

作者： Ueno, Koji Suzumura, Toyotaro Maruyama, Naoya Fujisawa, Katsuki Matsuoka, Satoshi Tokyo Inst Technol Tokyo Japan IBM TJ Watson Res Ctr Yorktown Hts NY USA RIKEN Kobe Hyogo Japan Kyushu Univ Fukuoka Japan Tokyo Inst Technol AIST Tokyo Japan

there are many large-scale graphs in real world such as Web graphs and social graphs. the interest in large-scale graph analysis is growing in recent years. Breadth-First Search (BFS) is one of the most fundamental graph algorithms used as a component of many graph algorithms. Our new method for distributed parallel BFS can compute BFS for one trillion vertices graph within half a second, using large supercomputers such as the K-Computer. By the use of our proposed algorithm, the K-Computer was ranked 1st in Graph500 using all the 82,944 nodes available on June and November 2015 and June 2016 38,621.4 GTEPS. Based on the hybrid BFS algorithm by Beamer (proceedings of the 2013 ieee 27th International symposium on parallel and distributed processing Workshops and PhD Forum, IPDPSW '13, ieee Computer Society, Washington, 2013), we devise sets of optimizations for scaling to extreme number of nodes, including a new efficient graph data structure and several optimization techniques such as vertex reordering and load balancing. Our performance evaluation on K-Computer shows that our new BFS is 3.19 times faster on 30,720 nodes than the base version using the previously known best techniques.

关键词： distributed-memory Breadth-First Search Graph500

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Towards Fog-Based Slice-Defined WLAN Infrastructures to Cope with Future 5G Use Cases 16

Towards Fog-Based Slice-Defined WLAN Infrastructures to Cope...

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ieee 16th International symposium on Network Computing and Applications (NCA)

作者： Carmo, Maxweel S. Jardim, Sandino Neto, Augusto V. Aguiar, Rui Corujo, Daniel Univ Fed Rio Grande Norte UFRN Natal RN Brazil UFMT Barra Do Garcas MT Brazil Inst Telecomunicacoes Aveiro Portugal

ISBN: (纸本)9781538614655

the advent of future 5th Generation (5G) use cases, such as ultra-dense networking and ultra-low latency propelled by Smart Cities and IoT projects will demand revolutionary network infrastructures. the need for low latency, high bandwidth, scalability, ubiquitous access and support for IoT resource-constrained devices are some of the prominent issues that networks have to face to support future 5G use cases, which arise since current wireless and mobile infrastructures are not able to fulfill. In particular, the pervasiveness and high-density of Wireless Local Area Networks (WLAN) at urban centers, together with their growing capacity and evolving standards, can be leveraged to support such demand. We argue that the integration of key 5G cornerstone technologies, such as Network Function Virtualization (NFV) and softwarization, fill some of the abovementioned gaps in regards to proper WLAN management and service orchestration. In this paper, we present a solution for slicing WLAN infrastructures, aiming to provide differentiated services on top of the same substrate through customized, isolated and independent digital building blocks. through this proposal, we aim at efficiently handling ultra-dense networking 5G use cases to achieve benefits at unprecedented levels. Towards this goal, we present proof of concept realised over a real testbed and assess its feasibility.

关键词： Wireless LAN Containers Bandwidth Ports (Computers) 5G mobile communication Proposals

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Simulation and Analysis of a Small Biconical Antenna Radiation Simulator 5

Simulation and Analysis of a Small Biconical Antenna Radiati...

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the 5th International symposium on Electromagnetic Compatibility

作者： Du Lihang Gao Cheng Chen Hailin Zhang Qi National Key Laboratory on Electromagnetic Environmental Effects and Electro-optical Engineering PLA University of Science and Technology

ISBN: (纸本)9781509051861;9781509051854

this paper aims to build a small biconical antenna simulator with 1/10 ns（the rise-time is 1 ns and the half-width is10 ns） to meet the needs of a scale model *** of all,on the basis of understanding the fundamental theory of laconical antenna,it presents a detailed analysis of the propagation characteristics of the horizontal electric field parallel to the antenna radiated from the laconical antenna,meanwhile,the influences of half-angle,radius,arm length and height on the electric field are ***,the antenna dimensions are determined as θ=32°,R=1 m,L=7 m,H=6 m,and the test area of the simulator is calculated according to *** results suggest that the test area is symmetrically distributed with respect to both the X and Y axes.

关键词： hybrid simulator biconical antenna electric field field distribution testarea

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Design and optimisation of an efficient HDF5 I/O Kernel for massive parallel fluid flow simulations

Design and optimisation of an efficient HDF5 I/O Kernel for ...

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15th International symposium on parallel and distributed Computing (ISPDC)

作者： Ertl, Christoph Frisch, Jerome Mundani, Ralf-Peter Tech Univ Munich Computat Engn Munich Germany Rhein Westfal TH Aachen Inst Energy Efficiency & Sustainable Bldg E3D Aachen Germany

More and more massive parallel codes running on several hundreds of thousands of cores are entering the computational science and engineering domain, allowing high-fidelity computations on up to trillions of unknowns for very detailed analyses of the underlying problems. Such runs typically produce gigabytes of data, hindering both efficient storage and (interactive) data exploration. Advanced approaches based on inherently distributed data formats such as hierarchical data format version 5 become necessary here to avoid long latencies when storing the data and to support fast (random) access when retrieving the data for visual processing. this paper shows considerations and implementation aspects of an I/O kernel based on hierarchical data format version 5 that supports fast checkpointing, restarting, and selective visualisation using a single shared output file for an existing computational fluid dynamics framework. this functionality is achieved by including the framework's hierarchical data structure in the file, which also opens the door for additional steering functionality. Finally, the performance of the kernel's write routines are presented. Bandwidths close to the theoretical peak on modern supercomputing clusters were achieved by avoiding file-locking and using collective buffering.

关键词： computational fluid dynamics computational steering HDF5 high-performance computing I/O

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19th workshop on advances in parallel and distributed computational models (APDCM 2017)

Proceedings - 2017 IEEE 31st International Parallel and Dist...

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proceedings - 2017 ieee 31st International parallel and distributed processing symposium Workshops, IPDPSW 2017 2017年 832-832页

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7th ieee Workshop parallel/distributed Computing and Optimization (PDCO 2017)

Proceedings - 2017 IEEE 31st International Parallel and Dist...

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proceedings - 2017 ieee 31st International parallel and distributed processing symposium Workshops, IPDPSW 2017 2017年 441-441页

作者： Danoy, Gregoire El Baz, Didier University of Luxembourg Luxembourg Team CDA LAAS-CNRS France

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