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检索条件"任意字段=4th International Symposium on Parallel and Distributed Processing and Applications"

共 3818 条记录，以下是71-80 订阅

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Integrating Abstractions to Enhance the Execution of distributed applications 30

Integrating Abstractions to Enhance the Execution of Distrib...

引用

30th IEEE international parallel and distributed processing symposium (IPDPS)

作者： Turilli, Matteo Liu, Feng Zhang, Zhao Merzky, Andre Wilde, Michael Weissman, Jon Katz, Daniel S. Jha, Shantenu Rutgers State Univ Elect & Comp Engn RADICAL Lab New Brunswick NJ 08901 USA Univ Minnesota Comp Sci & Engn Dept Minneapolis MN USA Univ Calif Berkeley AMPLab Berkeley CA 94720 USA Univ Chicago Computat Inst Chicago IL 60637 USA Argonne Natl Lab Chicago IL USA

ISBN: (纸本)9781509021406

One of the factors that limits the scale, performance, and sophistication of distributed applications is the difficulty of concurrently executing them on multiple distributed computing resources. In part, this is due to a poor understanding of the general properties and performance of the coupling between applications and dynamic resources. this paper addresses this issue by integrating abstractions representing distributed applications, resources, and execution processes into a pilot-based middleware. the middleware provides a platform that can specify distributed applications, execute them on multiple resource and for different configurations, and is instrumented to support investigative analysis. We analyzed the execution of distributed applications using experiments that measure the benefits of using multiple resources, the late-binding of scheduling decisions, and the use of backfill scheduling.

关键词： abstractions middleware execution strategies distributed systems

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A novel Optimization Technique for Mastering Energy Consumption in Cloud Data center 15

A novel Optimization Technique for Mastering Energy Consumpt...

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15th IEEE international symposium on parallel and distributed processing with applications (ISPA) / 16th IEEE international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Ben Maaouia, Omar Fkaier, Hazem Jemni, Mohamed Cerin, Christophe Univ Tunis LATICE ENSIT Tunis Tunisia Univ Tunis El Manar FST Tunis Tunisia Univ Paris 13 LIPN UMR 7030 CNRS Villetaneuse France

ISBN: (纸本)9781538637906

Cloud computing is one of the most popular technologies nowadays because of its wide utilities and various benefits in several IT companies all over the world. However, in front of the increasing users' requests for computing services, cloud providers are encouraged to deploy large data centers, which consumes very large amount of energy and contribute to high operational costs. Among the effects, carbon dioxide emission rate is growing each day due to the huge amount of power consumption. this energy efficiency is an important issue in cloud computing, mainly due to the required electrical power to run these systems and to cool them. therefore, energy consumption has become a major concern for the widespread deployment of Cloud data centers. the growing importance for parallel applications in the Cloud introduces significant challenges in reducing energy consumption from hosted servers. this paper addresses the problem of placing independent applications on the physical servers (hosts) of a Cloud infrastructure. We proposed a novel heuristic to allocate applications so that total energy consumption is reduced. Our proposal respects various constraints e.g. the machines availability, capability and the duplication of applications. Experiments are illustrated to validate the potential of our approach.

关键词： Resource management for parallel and distributed systems Cloud computing Energy consumption Minimization

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BINARY: A Bandwidth Variation Pattern-Aware Rate Adaptation for HTTP Adaptive Streaming over 4G Cellular Network 15

BINARY: A Bandwidth Variation Pattern-Aware Rate Adaptation ...

引用

15th IEEE international symposium on parallel and distributed processing with applications (ISPA) / 16th IEEE international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Du, Haipeng Zheng, Qinghua Zhang, Weizhan Gao, Xiang Xi An Jiao Tong Univ Dept Comp Sci & Technol SPKLSTN Lab Xian Shaanxi Peoples R China

ISBN: (纸本)9781538637906

Recently, HTTP Adaptive Streaming(HAS) has been an essential solution for mobile video streaming to improve the Quality of Experience(QoE). the rate adaption of HAS dynamically switches between different quality levels of the same media content as the available bandwidth changes. In this paper, we propose BINARY, a novel HAS rate adaptation algorithm for the 4G cellular network with a dual character. BINARY differentiates the patterns of bandwidth variation as constant bandwidth fluctuation and instantaneous bandwidth hopping. In the first case, BINARY performs smoothed bandwidth prediction and conservative rate switching to avoid frequent video quality oscillations. In the other case, BINARY performs positive bandwidth prediction and aggressive rate switching to prevent rebuffering and make full use of available bandwidth. We evaluate the performance of BINARY through extensive experiments on a 4G network testbed. the results demonstrate that BINARY achieves improved QoE in higher average bitrate, reduced bitrate switching frequency, and lower rebuffering ratio.

关键词： HTTP adaptive streaming 4G Cellular Network Rate adaption

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parallel Computing in DNNs Using CPU and MIC 15

Parallel Computing in DNNs Using CPU and MIC

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15th IEEE international symposium on parallel and distributed processing with applications (ISPA) / 16th IEEE international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Fan, Sijiang Zhang, Shiqing He, Ximing Fei, Jiawei Shen, Li Wang, Zhiying Natl Univ Def Technol Sch Comp State Key Lab High Performance Comp Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

Acceleration for the training process of Deep Neural Networks (DNNs) has been the focus of deep learning field. there were many researches of accelerating deep learning on different platforms. Among them, Intel Xeon Phi Co-processor is a many-core platform which provides both strong programmability and high performance. But previous work about Intel Many Integrated Core (MIC) focused on parallel computing only in MIC. In this paper, we speed up the training process of DNNs applied for automatic speech recognition with CPU+MIC architecture. In this architecture, the training process of DNNs is executed both on MIC and CPU. We apply several optimization methods for I/O and calculation and set up experiments to approve these methods. Putting all methods together, results show that our optimized algorithm acquires about 20x speedup compared with the original sequential algorithm on CPU which uses one core.

关键词： DNNs Hybrid Architecture parallel Computing Load Balance

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Real-Time Ship detection from Infrared Images through Multi-feature Fusion 19

Real-Time Ship detection from Infrared Images Through Multi-...

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19th IEEE international symposium on parallel and distributed processing with applications (IEEE ISPA)

作者： Miao, Rui Jiang, Hongxu Tian, Fangzheng Li, Xiaobin Zhang, Yonghua Dong, Dong Beihang Univ Hangzhou Innovat Inst Beijing Key Lab Digital Media Beijing Peoples R China

ISBN: (纸本)9781665435741

Real-time ship detection from remote sensing imagery it is a great challenge due to the complex scene, the changeable characteristics of ship target, and the uncontrollable interference factors. In this letter, an infrared ship detection algorithm based on multi-feature fusion is proposed. Based on the fully analysis of the target features, the proposed algorithm combines the cascade rejection mechanism with multi-features through a cascade linear classifier from simple to complex, and uses fine features to accurately distinguish the target from the complex background. Large number of experimental results show that the proposed method can achieve better results in detection performance and real-time processing.

关键词： Image processing Real-time Multi-feature Fusion

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parallel analysis of TACLeBench kernel benchmark's loop and procedure level speculation 19

Parallel analysis of TACLeBench kernel benchmark's loop and ...

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19th IEEE international symposium on parallel and distributed processing with applications (IEEE ISPA)

作者： Meng, Huiling Wang, Yaobin Li, Ling Musariri, Manasah Wang, Xinyi Southwest Univ Sci & Technol Mianyang Sichuan Peoples R China

ISBN: (纸本)9781665435741

thread level speculation (TLS) technology has gained substantial international recognition due to its unique parallel program execution. It uses the potential parallel execution of programs to improve the utilization of multi-core resources. However, the kernel benchmark of TACLeBench has not effectively been analyzed using TLS parallelization. In response to this problem, we select 7 programs in the TACLeBench kernel benchmark to analyze its loop and procedure level speculation executions to measure their maximum potential parallelism. Furthermore, we discuss its runtime characteristics (thread size, speculative parallelism coverage, dependency feature) and the influence of program source code on speedup. Our experimental results illustrate that: 1) Most applications achieve impressive results. Bsort reaches 20.79x speedup in loop level speculation, and lms has 9.51x speedup in procedure level speculation;2) By using TLS to accelerate the TACLeBench kernel benchmark, most applications effectively utilize computing resources from 4 to 16 cores;3) the kernel benchmark is more suitable for developing parallelism in loop level speculation.

关键词： thread level speculation (TLS) multi-core TACLeBench

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OMB-Py: Python Micro-Benchmarks for Evaluating Performance of MPI Libraries on HPC Systems 36

OMB-Py: Python Micro-Benchmarks for Evaluating Performance o...

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36th IEEE international parallel and distributed processing symposium (IEEE IPDPS)

作者： Alnaasan, Nawras Jain, Arpan Shafi, Aamir Subramoni, Hari Panda, Dhabaleswar K. Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9781665497473

Python has become a dominant programming language for emerging areas like Machine Learning (ML), Deep Learning (DL), and Data Science (DS). An attractive feature of Python is that it provides easy-to-use programming interface while allowing library developers to enhance performance of their applications by harnessing the computing power offered by High Performance Computing (HPC) platforms. Efficient communication is key to scaling applications on parallel systems, which is typically enabled by the Message Passing Interface (MPI) standard and compliant libraries on HPC hardware. mpi4py is a Python-based communication library that provides an MPI-like interface for Python applications allowing application developers to utilize parallel processing elements including GPUs. However, there is currently no benchmark suite to evaluate communication performance of mpi4py-and Python MPI codes in general-on modern HPC systems. In order to bridge this gap, we propose OMB-Py-Python extensions to the open-source OSU Micro-Benchmark (OMB) suite-aimed to evaluate communication performance of MPI-based parallel applications in Python. To the best of our knowledge, OMBPy is the first communication benchmark suite for parallel Python applications. OMB-Py consists of a variety of point-to-point and collective communication benchmark tests that are implemented for a range of popular Python libraries including NumPy, CuPy, Numba, and PyCUDA. Our evaluation reveals that mpi4py introduces a small overhead when compared to native MPI libraries. We plan to publicly release OMB-Py to benefit the Python HPC community.

关键词： MPI Python mpi4py OMB Benchmarks HPC

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A three-Level parallel Algorithm For MrBayes 3.2 15

A Three-Level Parallel Algorithm For MrBayes 3.2

引用

15th IEEE international symposium on parallel and distributed processing with applications (ISPA) / 16th IEEE international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Zhao, Mingjie Ren, Qiang Wang, Yilin Deng, Ruikang Ren, Mingming Wang, Gang Liu, Xiaoguang Nankai Univ Nankai Baidu Joint Lab Tianjin Peoples R China

ISBN: (纸本)9781538637906

MrBayes is a popular bioinformatics software that is widely used in phylogenetic analysis. the core algorithm of Mrbayes is Metropolis Coupled Markov Chain Monte Carlo (MC3). However, when dealing with large data sets, MC3 algorithm is too slow to meet researcher's requirements. Although several parallelizations have been proposed for MrBayes, such as MPI (Message Passing Interface) based MrBayes, GPU (Graphics processing Unit) based MrBayes, there is still no efficient parallel algorithm to fully utilize computing power of modern CPU and computer architecture. this paper (a) presents a new three-level hybrid parallel algorithm, include data-level parallelism (DLP), thread-level parallelism (TLP), and process-level parallelism (PLP), which can be used on most modern multi-core computers;(b) compares the performance of different combinations of parallel strategies on real-world protein data sets. the experimental results show that, this hybrid parallel algorithm does convert more computing powers into higher speedup. Furthermore, the proposed algorithm's speedup is near the speedup on one GPU at the same data sets. this algorithm is fit for practical use in phylogenetic inferences.

关键词： MrBayes SIMD hybrid parallel computing

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NetANNS: A High-Performance distributed Search Framework Based On In-Network Computing 19

NetANNS: A High-Performance Distributed Search Framework Bas...

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19th IEEE international symposium on parallel and distributed processing with applications (IEEE ISPA)

作者： Zhang, Penghao Pan, Heng Li, Zhenyu Xie, Gaogang Cui, Penglai Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Purple Mt Labs Nanjing Peoples R China Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China

ISBN: (纸本)9781665435741

Approximate nearest neighbor search (ANNS) is the most basic and important algorithm in Database, Machine Learning and other applications. With the expansion of cloud computing, the academia focuses on the study of how to optimize distributed frameworks based on approximate nearest neighbor search such as MapReduce, and Memcached. We implement a new distributed ANNS search framework (NetANNS). the main contributions of NetANNS are to accelerate the data preprocessing with programmable switch, and integrate a variety of efficient ANNS algorithms so that it can choose the most suitable algorithm for each datasets. the experiments show that the search efficiency of NetANNS is about 2x than the common distributed ANNS frameworks which are implemented based on the framework of MapReduce.

关键词： approximate nearest neighbor search distributed search in-network computation

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the Coming Age of Pervasive Data processing 18

The Coming Age of Pervasive Data Processing

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18th international symposium on parallel and distributed Computing (ISPDC)

作者： Rellermeyer, Jan S. Khorasani, Sobhan Omranian Graur, Dan Parthasarathy, Apourva Delft Univ Technol Distributed Syst Grp Delft Netherlands

ISBN: (纸本)9781728138015

Emerging Big Data analytics and machine learning applications require a significant amount of computational power. While there exists a plethora of large-scale data processing frameworks which thrive in handling the various complexities of data-intensive workloads, the ever-increasing demand of applications have made us reconsider the traditional ways of scaling (e.g., scale-out) and seek new opportunities for improving the performance. In order to prepare for an era where data collection and processing occur on a wide range of devices, from powerful HPC machines to small embedded devices, it is crucial to investigate and eliminate the potential sources of inefficiency in the current state of the art platforms. In this paper, we address the current and upcoming challenges of pervasive data processing and present directions for designing the next generation of large-scale data processing systems.

关键词： Big Data Machine Learning Systems Performance Efficiency

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