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检索条件"任意字段=Seventh International Symposium on Parallel Architectures, Algorithms and Programming"

共 513 条记录，以下是171-180 订阅

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A Stream Processing Framework for On-line Optimization of Performance and Energy Efficiency on Heterogeneous Systems 28

A Stream Processing Framework for On-line Optimization of Pe...

引用

28th IEEE international parallel & Distributed Processing symposium Workshops (IPDPSW)

作者： Ranft, Benjamin Denninger, Oliver Pfaffe, Philip FZI Res Ctr Informat Technol D-76131 Karlsruhe Germany Karlsruhe Inst Technol D-76131 Karlsruhe Germany

ISBN: (纸本)9781479941162

Modern processors have the potential of executing compute-intensive programs quickly and efficiently, but require applications to be adapted to their ever increasing parallelism. Here, heterogeneous systems add complexity by combining processing units with different characteristics. Scheduling should thus consider the performance of each processor as well as competing workloads and varying inputs. To assist programmers of stream processing applications in facing this challenge we present libHawaii, an open source library for cooperatively using all processors of heterogeneous systems easily and efficiently. It supports exploiting data flow, data element and task parallelism via pipelining, partitioning and demand-based allocation of consecutive work items. Scheduling is automatically adapted on-line to continuously optimize performance and energy efficiency. Our C++ library does not depend on specific hardware architectures or parallel computing frameworks. However, it facilitates maximizing the throughput of compatible GPUs by overlapping computations and memory transfers while maintaining low latencies. This paper describes the algorithms and implementation of libHawaii and demonstrates its usage on existing applications. We experimentally evaluate our library using two examples: General matrix multiplication (GEMM) is a simple yet important building block of many high-performance computing applications. Complementarily, the detection, extraction and matching of sparse image features exhibits greater complexity, including indeterministic memory access and synchronization.

关键词： heterogeneous computing stream processing load balancing energy efficiency real-time parallel programming

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A Task Scheduling Algorithm for Automated parallel Processing of XQuery

A Task Scheduling Algorithm for Automated Parallel Processin...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Yuelong Quan Husheng Liao College of Computer Science Beijing University of Technology Beijing China School of Software Engineering Beijing University of Technology Beijing China

In this paper, a novel approach for tasks scheduling in XQuery's automatic parallel implementation is proposed. The approach solves the scheduling problem on the shared memory multithread environment, which includes three strategies, i.e. task parallelism, data parallelism and pipeline parallelism. An automaton model is established for the pipeline parallelism, which is used to reduce the idle time between pipeline stages. The experimental results show that our approach could improve the performance and have good memory efficiency.

关键词： Pipelines Automata Scheduling algorithms Scheduling XML

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parallel Optimization Strategies for MIC Heterogeneous parallel Systems

Parallel Optimization Strategies for MIC Heterogeneous Paral...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Tao Ju Xiaoshe Dong Endong Wang Liang Li Zhengdong Zhu School of Electronics and Information Engineering Xi'an Jiaotong University Xi'an China The State Key Laboratory of High-end Server & Storage Technology Jinan China

In the traditional multithread programming model, there is no dedicated performance optimization strategy for Many Integrated Core (MIC) heterogeneous system. To fully exploit the high computing power of MIC processor, this paper discusses the specific program porting and performance optimization strategies on the MIC heterogeneous parallel system based on the k-means application program. Experimental results show that the proposed porting and performance optimization strategies are effective, and can be able to guide the programmer to port and optimize applications effectively to MIC heterogeneous parallel system.

关键词： Microwave integrated circuits Coprocessors Optimization Instruction sets Benchmark testing programming parallel processing

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Dataflow Computing and Its Impact on Automation Applications

Dataflow Computing and Its Impact on Automation Applications

引用

24th DAAAM international symposium on Intelligent Manufacturing and Automation

作者： Panfilov, Peter Salibekyan, Sergey Minist Econ Dev 1st Tverskaya Yamskaya St 13 Moscow 125993 Russia Natl Res Univ Higher Sch Econ Moscow 101000 Russia

ISBN: (纸本)9781632663252

Developing efficient, scalable and reconfigurable supervisory control and data acquisition (SCADA) systems presents a unique set of challenges inherent in the development of distributed computer architectures, algorithms, protocols and procedures for large-scale networked industrial automation applications. A research project on dataflow automation system architecture is presented exploring the research and engineering issues related to the development of computer architecture for the next generation distributed supervision and control systems that exploits and leverages dataflow computation model. Major focus of research is on new object-attribute architecture of dataflow computing environment which is particularly suitable for the design and implementation of reconfigurable scalable heterogeneous distributed applications in industrial automation area. The state-of-the-art in the application of the dataflow model of computation is accompanied with description of software tools developed for programming, simulation, debugging and test of automation applications that follow the object-attribute dataflow model. (C) 2014 The Authors. Published by Elsevier Ltd.

关键词： industrial automation dataflow controlflow parallel processing multiprocessing heterogeneous system distributed controlapplication object-attribute architecture

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A parallel Implementation of Acoustic Propagation Model on Cloud Platform

A Parallel Implementation of Acoustic Propagation Model on C...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Binbin Yu Simin Cheng Dan Wang Xichen Wu Hongkun Mai Guangzhong Sun School of Computer Science University of Science and Technology Hefei China

Three dimensional wave propagation model of parabolic approximation type is widely used in exploring the ocean. For this application, FOR3D model is one of the mostly used models, for it takes the azimuthal coupling into consideration and the result gains a better precision. When the precision requirement is high, large scale computation task would be faced, which cannot be solved only in one computer or constrained time. In this paper, we propose a parallel method to decompose the computation task, which divide the original computation into small size. Then each processor get one piece of task and run the FOR3D independently. Our method was implemented on Windows Azure and the result shows that we almost gain a linear speed-up.

关键词： Mathematical model Equations Computational modeling Oceans Acoustic propagation Couplings Underwater acoustics

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parallel Computing

引用

丛书名： Advances in parallel Computing

2014年

作者： Bader, M Bode, A. IOS Press, Incorporated

ISBN: (数字)9781614993810

ISBN: (纸本)9781614993803

parallel computing has been the enabling technology of high-end machines for many years. Now, it has finally become the ubiquitous key to the efficient use of any kind of multi-processor computer architecture, from smart phones, tablets, embedded systems and cloud computing up to exascale computers. _x000D_ This book presents the proceedings of ParCo2013 – the latest edition of the biennial international Conference on parallel Computing – held from 10 to 13 September 2013, in Garching, Germany. The conference focused on several key parallel computing areas. Themes included parallel programming models for multi- and manycore CPUs, GPUs, FPGAs and heterogeneous platforms, the performance engineering processes that must be adapted to efficiently use these new and innovative platforms, novel numerical algorithms and approaches to large-scale simulations of problems in science and engineering._x000D_ The conference programme also included twelve mini-symposia (including an industry session and a special PhD symposium), which comprehensively represented and intensified the discussion of current hot topics in high performance and parallel computing. These special sessions covered large-scale supercomputing, novel challenges arising from parallel architectures (multi-/manycore, heterogeneous platforms, FPGAs), multi-level algorithms as well as multi-scale, multi-physics and multi-dimensional problems._x000D_ It is clear that parallel computing – including the processing of large data sets (“Big Data”) – will remain a persistent driver of research in all fields of innovative computing, which makes this book relevant to all those with an interest in this field.

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Efficient parallelization of a Two-List Algorithm for the Subset-Sum Problem on a Hybrid CPU/GPU Cluster

Efficient Parallelization of a Two-List Algorithm for the Su...

引用

international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Letian Kang Lanjun Wan Kenli Li College of Information Science and Engineering Hunan University Changsha Hunan China

Recently, hybrid CPU/GPU cluster has been widely used to deal with compute-intensive problems, such as the subset-sum problem. The two-list algorithm is a well known approach to solve the problem. However, a hybrid MPI-CUDA dual-level parallelization of the algorithm on the cluster is not straightforward. The key challenge is how to allocate the most suitable workload to each node to achieve good load balancing between nodes and minimize the communication overhead. Therefore, this paper proposes an effective workload distribution scheme which aims to reasonably assign workload to each node. According to this scheme, an efficient MPI-CUDA parallel implementation of a two-list algorithm is presented. A series of experiments are conducted to compare the performance of the hybrid MPI-CUDA implementation with that of the best sequential CPU implementation, the single-node CPU-only implementation, the single-node GPU-only implementation, and the hybrid MPI-OpenMP implementation with same cluster configuration. The results show that the proposed hybrid MPI-CUDA implementation not only offers significant performance benefits but also has excellent scalability.

关键词： Graphics processing units Clustering algorithms Performance evaluation Instruction sets parallel processing Educational institutions Computational modeling

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CheR: Cheating resilience in the cloud via smart resource allocation

CheR: Cheating resilience in the cloud via smart resource al...

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6th international symposium on Foundations and Practice of Security, FPS 2013

作者： Roberto, Di Pietro Lombardi, Flavio Martinelli, Fabio Sgandurra, Daniele Department of Mathematics and Physics University Roma Tre Largo S. Leonardo Murialdo 00146 Rome Italy Institute for Informatics and Telematics National Research Council of Italy Pisa Italy

ISBN: (纸本)9783319053011

Cloud computing offers unprecedented ways to split and offload the workload of parallel algorithms to remote computing nodes. However, such remote parties can potentially misbehave, for instance by providing fake computation results in order to save resources. In turn, these erroneous partial results can affect the timeliness and correctness of the overall outcome of the algorithm. The widely successful cloud approach increases the economic feasibility of leveraging computational redundancy to enforce some degree of assurance about the results. However, naïve solutions that dumbly replicate the same computation over several sets of nodes are not cost-efficient. In this paper, we provide several contributions as for the distribution of workload over (heterogeneous) cloud nodes. In particular, we first formalize the problem of computing a parallel function over a set of nodes;later, we introduce CheR (for Cheating Resilience), a novel approach based upon modelling the assignment of input elements to cloud nodes as a linear integer programming problem aimed at minimizing cost while being resilient against misbehaving nodes. Further, we describe the CheR approach in different scenarios and highlight the novelty with respect to other state-of-the-art solutions. Finally, we present and discuss some experimental results showing the viability and quality of our proposal. © 2014 Springer international Publishing Switzerland.

关键词： Integer programming

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New Effective Multithreaded Matching algorithms

New Effective Multithreaded Matching Algorithms

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international symposium on parallel and Distributed Processing (IPDPS)

作者： Fredrik Manne Mahantesh Halappanavar Department of Informatics University of Bergen Bergen Norway Pacific Northwest National Laboratory Richland WA USA

Matching is an important combinatorial problem with a number of applications in areas such as community detection, sparse linear algebra, and network alignment. Since computing optimal matchings can be very time consuming, several fast approximation algorithms, both sequential and parallel, have been suggested. Common to the algorithms giving the best solutions is that they tend to be sequential by nature, while algorithms more suitable for parallel computation give solutions of lower quality. We present a new simple 1/2-approximation algorithm for the weighted matching problem. This algorithm is both faster than any other suggested sequential 1/2-approximation algorithm on almost all inputs and when parallelized also scales better than previous multithreaded algorithms. We further extend this to a general scalable multithreaded algorithm that computes matchings of weight comparable with the best sequential deterministic algorithms. The performance of the suggested algorithms is documented through extensive experiments on different multithreaded architectures.

关键词： Approximation algorithms Algorithm design and analysis Heuristic algorithms Electronics packaging Dynamic programming Instruction sets Optimal matching

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Exploiting spatial architectures for edit distance algorithms

Exploiting spatial architectures for edit distance algorithm...

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IEEE international symposium on Performance Analysis of Systems and Software

作者： Jesmin Jahan Tithi Neal C. Crago Joel S. Emer Stony Brook University VSSAD Intel Corporation VSSAD CSAIL MIT

In this paper, we demonstrate the ability of spatial architectures to significantly improve both runtime performance and energy efficiency on edit distance, a broadly used dynamic programming algorithm. Spatial architectures are an emerging class of application accelerators that consist of a network of many small and efficient processing elements that can be exploited by a large domain of applications. In this paper, we utilize the dataflow characteristics and inherent pipeline parallelism within the edit distance algorithm to develop efficient and scalable implementations on a previously proposed spatial accelerator. We evaluate our edit distance implementations using a cycle-accurate performance and physical design model of a previously proposed triggered instruction-based spatial architecture in order to compare against real performance and power measurements on an x86 processor. We show that when chip area is normalized between the two platforms, it is possible to get more than a 50× runtime performance improvement and over 100× reduction in energy consumption compared to an optimized and vectorized x86 implementation. This dramatic improvement comes from leveraging the massive parallelism available in spatial architectures and from the dramatic reduction of expensive memory accesses through conversion to relatively inexpensive local communication.

关键词： Computer architecture Pipelines Field programmable gate arrays parallel processing Signal processing algorithms Matrix converters Dynamic programming

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