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检索条件"任意字段=5th International Conference on Algorithms and Architectures for Parallel Processing"

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Performance Evaluation of Scientific Applications on Intel Xeon Phi Knights Landing Clusters

Performance Evaluation of Scientific Applications on Intel X...

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international conference on High Performance Computing & Simulation (HPCS)

作者： Ji-Hoon Kang Oh-Kyoung Kwon Hoon Ryu Jinwoo Jeong Kyunghun Lim Intel Parallel Computing Center Korea Institute of Science and Technology Information Republic of Korea Research Center Moasys Corporation Republic of Korea

ISBN: (纸本)9781538678800

Korea Institute of Science and Technology Information (KISTI) is building its 5th supercomputer based on Intel Xeon Phi Knights Landing (KNL) processors, and plans to provide an open service to computational scientists in the near future. We perform solid benchmark tests for several well-known open/commercial application softwares in a 16 node pilot system for a preliminary performance evaluation of KNL systems. Based on their results, we present detailed discussion with a focus on the performance gain that can be obtained with unique features in KNL processors. Performance of application software measured in our KNL pilot system is compared to that obtained in the current supercomputer based on traditional multicore processors, to claim the practical benefits of Intel onboard Many-Integrated- Core architectures for large-scale scientific computing.

关键词： Benchmark testing Program processors Bandwidth Supercomputers Application software Random access memory Computational modeling

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Performance Evaluation of Two Load Balancing algorithms on a Hybrid parallel Architecture 14th

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14th international conference on parallel Computing Technologies (PaCT)

作者： do Nascimento, Tiago M. dos Santos, Rodrigo W. Lobosco, Marcelo Univ Fed Juiz de Fora Grad Program Computat Modeling Juiz De Fora Brazil

ISBN: (纸本)9783319629322;9783319629315

Accelerated processing Units (APUs) are an emerging architecture that integrates, in a single silicon chip, the traditional CPU and the GPU. Due to its heterogeneous architecture, APUs impose new challenges to data parallel applications that want to take advantage of all the processing units available on the hardware to minimize its execution time. Some standards help in the task of writing parallel code for heterogeneous devices, but it is not easy to find the data division between CPU and GPU that will minimize the execution time. In this context, this work further extends and details load balancing algorithms designed to be used in a data parallel problem. Also, a sensitivity analysis of the parameters used in our models was performed. the results have shown that the algorithms are effective in their purpose of improving the performance of an application on an heterogeneous environment.

关键词： Load balancing Hybrid parallel architectures APU HPC

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Task-Based Conjugate Gradient: From Multi-GPU Towards Heterogeneous architectures 22nd

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22nd international European conference on parallel and Distributed Computing (Euro-Par)

作者： Agullo, E. Giraud, L. Guermouche, A. Nakov, S. Roman, J. Inria Bordeaux France Univ Bordeaux Bordeaux France

ISBN: (纸本)9783319589435;9783319589428

Whereas most parallel High Performance Computing (HPC) numerical libaries have been written as highly tuned and mostly monolithic codes, the increased complexity of modern architectures led the computational science and engineering community to consider more modular programming paradigms such as task-based paradigms to design new generation of parallel simulation code;this enables to delegate part of the work to a third party software such as a runtime system. that latter approach has been shown to be very productive and efficient with compute-intensive algorithms, such as dense linear algebra and sparse direct solvers. In this study, we consider a much more irregular, and synchronizing algorithm, namely the Conjugate Gradient (CG) algorithm. We propose a task-based formulation of the algorithm together with a very fine instrumentation of the runtime system. We show that almost optimum speed up may be reached on a multi-GPU platform (relatively to the mono-GPU case) and, as a very preliminary but promising result, that the approach can be effectively used to handle heterogenous architectures composed of a multicore chip and multiple GPUs. We expect that these results will pave the way for investigating the design of new advanced, irregular numerical algorithms on top of runtime systems.

关键词： High Performance Computing (HPC) Multi-GPUs Heterogeneous architectures Task-based model Runtime system Sparse linear systems Conjugate Gradient

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DPiSAX: Massively Distributed Partitioned iSAX 17

DPiSAX: Massively Distributed Partitioned iSAX

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17th IEEE international conference on Data Mining (ICDMW)

作者： Yagoubi, Djamel-Edine Akbarinia, Reza Masseglia, Florent Palpanas, themis Inria Montpellier France LIRMM Montpellier France Paris Descartes Univ Paris France

ISBN: (纸本)9781538638354

Indexing is crucial for many data mining tasks that rely on efficient and effective similarity query processing. Consequently, indexing large volumes of time series, along with high performance similarity query processing, have became topics of high interest. For many applications across diverse domains though, the amount of data to be processed might be intractable for a single machine, making existing centralized indexing solutions inefficient. We propose a parallel indexing solution that gracefully scales to billions of time series, and a parallel query processing strategy that, given a batch of queries, efficiently exploits the index. Our experiments, on both synthetic and real world data, illustrate that our index creation algorithm works on 1 billion time series in less than 2 hours, while the state of the art centralized algorithms need more than 5 days. Also, our distributed querying algorithm is able to efficiently process millions of queries over collections of billions of time series, thanks to an effective load balancing mechanism.

关键词： Time series analysis Query processing Indexing Sparks Partitioning algorithms Data mining

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Efficient Generation of parallel Spin-images Using Dynamic Loop Scheduling

Efficient Generation of Parallel Spin-images Using Dynamic L...

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IEEE 19th international conference on High Performance Computing and Communications (HPCC)

作者： Eleliemy, Ahmed Mohammed, Ali Ciorba, Florina M. Univ Basel Dept Math & Comp Sci Basel Switzerland

ISBN: (纸本)9781538659304

High performance computing (HPC) systems underwent a significant increase in their processing capabilities. Modern HPC systems combine large numbers of homogeneous and heterogeneous computing resources. Scalability is, therefore, an essential aspect of scientific applications to efficiently exploit the massive parallelism of modern HPC systems. this work introduces an efficient version of the parallel spin-image algorithm (PSIA), called EPSIA. the PSIA is a parallel version of the spin-image algorithm (SIA). the (P)SIA is used in various domains, such as 3D object recognition, categorization, and 3D face recognition. EPSIA refers to the extended version of the PSIA that integrates various well-known dynamic loop scheduling (DLS) techniques. the present work: (1) Proposes EPSIA, a novel flexible version of PSIA;(2) Showcases the benefits of applying DLS techniques for optimizing the performance of the PSIA;(3) Assesses the performance of the proposed EPSIA by conducting several scalability experiments. the performance results are promising and show that using well-known DLS techniques, the performance of the EPSIA outperforms the performance of the PSIA by a factor of 1.2 and 2 for homogeneous and heterogeneous computing resources, respectively.

关键词： Spin-image algorithm Static loop scheduling Dynamic loop scheduling Self scheduling Guided self scheduling Factoring Efficient performance

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parallel Grouping Particle Swarm Optimization with Stream processing Paradigm

Parallel Grouping Particle Swarm Optimization with Stream Pr...

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IEEE 19th international conference on High Performance Computing and Communications (HPCC)

作者： Ma, Kun Liu, Shuhui Lin, Yongzheng Yu, Ziqiang Ji, Ke Univ Jinan Shandong Prov Key Lab Network Based Intelligent C Jinan 250022 Peoples R China

ISBN: (纸本)9781538659304

Particle swarm optimization (PSO) is a new swarm intelligence technique inspired by social behavior of bird flocking. However, PSO algorithm easily leads convergence difficulty when processing large-scale data. Besides, MapReduce-based PSO need repeating startup of migration strategy job. In this paper, we use a case of live data migration to present parallel grouping PSO with stream processing paradigm. First, fitness, position and velocity are proposed to present particle processing. Second, stream-based grouping are proposed speed up convergence. the experimental results show the best performance of our method in all.

关键词： load balancing stream processing data migration particle swarm optimization

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7th international Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage architectures, ADMS 2016 and 4th international Workshop on In-Memory Data Management and Analytics, IMDM 2016

7th International Workshop on Accelerating Data Analysis and...

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7th international Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage architectures, ADMS 2016 and 4th international Workshop on In-Memory Data Management and Analytics, IMDM 2016

ISBN: (纸本)9783319561103

the proceedings contain 9 papers. the special focus in this conference is on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage architectures. the topics include: Efficient range queries on modern CPUs;vectorized time series algorithms on modern commodity CPUs;compression-aware in-memory query processing;overtaking CPU DBMSes with a GPU in whole-query analytic processing with parallelism-friendly execution plan optimization;making in-memory databases fast on modern NICs;an analysis on modern hardware;locality-adaptive parallel hash joins using hardware transactional memory;an embedded in-memory DBMS enabling instant snapshot sharing and runtime fragility in main memory.

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the Impact of international Inter-City Investment on Enterprises Performance: Pluralistic Interpretation of Geographical Death 17th

The Impact of International Inter-City Investment on Enterpr...

引用

17th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Zhan, Yanghao Chen, Yan Zhai, Ruirui Beijing Univ Posts & Telecommun Beijing Peoples R China

ISBN: (纸本)9783319654829;9783319654812

this paper aims to test the impact of inter-city investment on enterprises performance. By using a panel dataset of Chinese firms which have invested in 43 countries and regions over the of 2003-2009 and gravity model, we find that institutional distance is favorable to Chinas outward direct investment, which implies that the Chinese multinationals dont seem willing to enter those countries that have similar institutions with their home country, in this sense, Chinese enterprises outward direct investment can be interpreted as being driven by the motivation of institutional escape. Technology distance displays an Inversed-U shape which suggests some technical distance is the premise for ODI and may reflect the fact of simultaneous existence of both the technology utilization ODI and the technology-seeking ODI of China. Geographical distance has no significant impact on Chinas outward direct investment which supports the proposition of death of distance. these findings point to the importance of going beyond firm boundary to consider various distances between home and host countries in making investment decisions, which not only overcome the defects of the existing studies, but also propose new theoretical explanations for the phenomenon that Chinese enterprises are still capable of ODI even when the ownership advantages are missing. According to the results of this paper, Chinese enterprises should choose to invest in the countries with large institutional distance, small economic and medium technical distance from the home country, and, at the same time, they should not bother geographical distance too much.

关键词： ODI Enterprises performance Geographical distance

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Tracking the world state with recurrent entity networks 5

Tracking the world state with recurrent entity networks

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5th international conference on Learning Representations, ICLR 2017

作者： Henaff, Mikael Weston, Jason Szlam, Arthur Bordes, Antoine LeCun, Yann Facebook AI Research Courant Institute New York University United States

We introduce a new model, the Recurrent Entity Network (EntNet). It is equipped with a dynamic long-term memory which allows it to maintain and update a representation of the state of the world as it receives new data. For language understanding tasks, it can reason on-the-fly as it reads text, not just when it is required to answer a question or respond as is the case for a Memory Network (Sukhbaatar et al., 2015). Like a Neural Turing Machine or Differentiable Neural Computer (Graves et al., 2014;2016) it maintains a fixed size memory and can learn to perform location and content-based read and write operations. However, unlike those models it has a simple parallel architecture in which several memory locations can be updated simultaneously. the EntNet sets a new state-of-the-art on the bAbI tasks, and is the first method to solve all the tasks in the 10k training examples setting. We also demonstrate that it can solve a reasoning task which requires a large number of supporting facts, which other methods are not able to solve, and can generalize past its training horizon. It can also be practically used on large scale datasets such as Children's Book Test, where it obtains competitive performance, reading the story in a single pass. © ICLR 2019 - conference Track Proceedings. All rights reserved.

关键词： parallel architectures

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Optimization Scheme Based on parallel Computing Technology 8th

Optimization Scheme Based on Parallel Computing Technology

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8th international Symposium on parallel architectures, algorithms, and Programming (PAAP)

作者： Li, Xiulai Chen, Chaofan Luo, Yali Chen, Mingrui Hainan Univ Haikou Hainan Peoples R China

ISBN: (纸本)9789811064425;9789811064418

parallel computing is a high performance technology to solve problems, in order to improve computing efficiency, we use the processor to concurrent execute several parts divided from one problem. Based on the current issues in parallel computing area, both the data processing repetition rate and the parallel computing time depend on the time of the last thread in the task completing. this paper was written to take an overview of the existing parallel computing techniques and structures, and propose a solution of adding an advanced thread or advanced processor to make up the deficiency in parallel computing area.

关键词： parallel structure parallel computing parallel model parallel technology

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