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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

共 11314 条记录，以下是511-520 订阅

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Accelerating Actor-based applications with parallel Patterns 27

Accelerating Actor-based Applications with Parallel Patterns

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27th Euromicro international conference on parallel, distributed and Network-Based processing (PDP)

作者： Rinaldi, Luca Torquati, Massimo Mencagli, Gabriele Danelutto, Marco Menga, Tullio Univ Pisa Dept Comp Sci Pisa Italy ATS Adv Technol Solut SpA Milan Italy

ISBN: (纸本)9781728116440

parallel programmers mandate high-level parallel programming tools allowing to reduce the effort of the efficient parallelization of their applications. parallel programming leveraging parallel patterns has recently received renovated attention thanks to their clear functional and parallel semantics. In this work, we propose a synergy between the well-known Actors-based programming model and the pattern-based parallelization methodology. We present our preliminary results in that direction, discussing and assessing the implementation of the Map parallel pattern by using an Actor-based software accelerator abstraction that seamlessly integrates within the C++ Actor Framework (ICAF). The results obtained on the Intel Xeon Phi KNL platform demonstrate good performance figures achieved with negligible programming efforts.

关键词： Computational modeling Message systems Software C++ languages parallel programming Semantics

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A secure protocol for computing dot-products in clustered and distributed environments

A secure protocol for computing dot-products in clustered an...

引用

31st international conference on parallel processing (ICPP 2002)

作者： Ioannidis, I Grama, A Atallah, M Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)0769516777

Dot-products form the basis of various applications ranging from scientific computations to commercial applications in data mining and transaction processing. Typical scientific computations utilizing sparse iterative solvers use repeated matrix-vector products. These can be viewed as dot-products of sparse vectors. In database applications, dot-products take the form of counting operations. With widespread use of clustered and distributed platforms, these operations are increasingly, being performed across networked hosts. Traditional APIs for messaging are susceptible to sniffing, and the data being transferred between hosts is often enough to compromise the entire computation. For example, in a domain decomposition based sparse solver, the entire solution can often be reconstructed easily from boundary values that are communicated on the net. In yet other applications, dot-products may be performed across two hosts that do not want to disclose their vectors, yet, they need to compute the dot-product. In each of these cases, there is a need for secure and anonymous dot-product protocols. Due to the large computational requirements of underlying applications, it is highly desirable that secure protocols add minimal overhead to the original algorithm. Finally, by its very nature, dot-products leak limited amounts of information - one of the parties can detect an entry of the other party's vector by simply probing it with a vector with a I in a particular location and zeros elsewhere. Given all of these constraints, traditional cryptographic protocols are generally unsuitable due to their significant computational and communication overheads. In this paper, we present an extremely efficient and sufficiently secure protocol for computing the dot-product of two vectors using linear algebraic techniques. Using analytical as well as experimental results, we demonstrate superior performance in terms of computational overhead, numerical stability, and security. We show tha

关键词： Computer applications Data mining distributed computing Leak detection Numerical stability Performance analysis Protocols Sparse matrices Transaction databases Vectors

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Supporting Elasticity in OpenMP applications

Supporting Elasticity in OpenMP Applications

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22nd Euromicro international conference on parallel, distributed, and Network-Based processing (PDP)

作者： Galante, Guilherme Bona, Luis C. E. Univ Fed Parana Dept Informat BR-80060000 Curitiba Parana Brazil

ISBN: (纸本)9781479927289

Elasticity can be seen as the ability of a system to increase or decrease the computing resources allocated in a dynamic and on demand way. To explore this feature, several works addressed the development of frameworks and platforms focusing the construction of elastic parallel and distributed applications for IaaS clouds. However, none of these works addressed the exploration of elasticity in multithreaded applications. In this paper, we propose a mechanism to provide elasticity support for OpenMP applications, making possible the dynamic provisioning of cloud resources taking into account the program structure and runtime requirements. In our proposal, the OpenMP directives were modified to support the dynamic adjustment of resources and a set of routines were included to the user-level library to enable the configuration of the elastic execution. Dynamic memory allocation support was also included in elastic OpenMP library. We also present the architecture and implementation of the proposed mechanism. The experiments validate our approach and show some possibilities to use the elastic OpenMP.

关键词： Cloud computing OpenMP elasticity parallel applications

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A distributed data gathering algorithm for wireless sensor networks with uniform architecture

A distributed data gathering algorithm for wireless sensor n...

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15th Euromicro international conference on parallel, distributed and Network-Based processing

作者： Goyeneche, M. Villadangos, J. Astrain, J. J. Prieto, M. Cordoba, A. Univ Publ Navarra Dept Math & Informat Campus Arrosadia Pamplona 31006 Spain

ISBN: (纸本)9780769527840

Wireless sensor networks (WSNs) are commonly used for continuously monitoring applications. Data gathering and in-network processing are techniques to efficiently gather the information from sensor nodes. Usually, these techniques have been analyzed taking into account a global knowledge of the system in order to select the best path to gather the information or to establish a routing function. In this paper we propose a novel distributed data gathering algorithm for wireless networks and evaluate the effect of having a different number of cluster heads transmitting to the base station. We focus the attention on uniformly distributed nodes in a given area to evaluate the effects on the energy consumption. Our proposal distributes uniformly the energy consumption between the complete set of sensors in the system resulting in a similar longevity for all sensors in the system.

关键词： Data acquisition

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Local and Global Shared Memory for Task Based HPC applications on Heterogeneous Platforms 26

Local and Global Shared Memory for Task Based HPC Applicatio...

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26th Euromicro international conference on parallel, distributed, and Network-Based processing (PDP)

作者： Liu, Chao Leeser, Miriam Northeastern Univ Dept ECE Boston MA 02115 USA

ISBN: (纸本)9781538649756

With the prevalence of multicore and manycore processors, developing parallel applications to benefit from massively parallel resources is important. In this work, we introduce a hybrid shared memory mechanism based on a high-level task design. We implemented task scoped global shared data based on the one-sided communication feature of MPI-3 and enable users to implement and create multi-threaded tasks that can execute either on a single node or on multiple nodes. Task threads of distributed nodes can share data sets through global shared data objects using one-sided remote memory access. We ported and developed a set of benchmark applications and tested on a cluster platform. The high-level task design and hybrid shared memory help users develop and maintain parallel programs easily, and the results show that the global shared data can deliver good RMA performance;the multi-threaded task implementations perform up to 20% faster than ordinary OpenMP programs and have better scaling performance than MPI programs on multiple nodes.

关键词： Task analysis Graphics processing units Electronics packaging parallel processing Programming Instruction sets Runtime

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parallel Huffman Decoding: Presenting a Fast and Scalable Algorithm for Increasingly Multicore Devices 15

Parallel Huffman Decoding: Presenting a Fast and Scalable Al...

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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： Johnston, Beau McCreath, Eric C. Australian Natl Univ Res Sch Comp Sci Canberra ACT Australia

ISBN: (纸本)9781538637906

Huffman encoding provides a simple approach for lossless compression of sequential data. The length of encoded symbols varies and these symbols are tightly packed in the compressed data. Thus, Huffman decoding is not easily parallelisable. This is unfortunate since it is desirable to have a parallel algorithm which scales with the increased core count of modern systems. This paper presents a parallel approach for decoding Huffman codes which work by decoding from every location in the bit sequence then concurrently combining the results into the uncompressed sequence. Although requiring more operations than serial approaches the presented approach is able to produce results marginally faster, on sufficiently large data sets, then that of a simple serial implementation. This is achieved by using the large number of threads available on modern GPUs. A variety of implementations, primarily OpenCL, are presented to demonstrate the scaling of this algorithm on CPU and GPU hardware in response to cores available. As devices with more cores become available, the importance of such an algorithm will increase.

关键词： Decoding Program processors Hardware Partitioning algorithms Multicore processing Encoding Image coding

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distributed models of thread-level speculation

Distributed models of thread-level speculation

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2005 international conference on parallel and distributed processing techniques and applications, PDPTA'05

作者： Oancea, Cosmin E. Selby, Jason W.A. Giesbrecht, Mark W. Watt, Stephen M. Department of Computer Science University of Western Ontario London ON N6A 5B7 Canada School of Computer Science University of Waterloo Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781932415605

Thread-level speculation is an aggressive par-allelization technique that can extract parallelism from code which is not provably free of data dependencies. This paper introduces a novel application of thread-level speculation to a distributed heterogeneous environment We propose and evaluate two speculative models which attempt to reduce some of the remote method invocation overhead associated with distributed objects. Our evaluation of the application of thread-level speculation to client-server applications resulted in substantial performance increases, on the order of 3 times for our initial model, and 21 times for the second.

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GraphMP: An Efficient Semi-External-Memory Big Graph processing System on a Single Machine 23

GraphMP: An Efficient Semi-External-Memory Big Graph Process...

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23rd IEEE international conference on parallel and distributed Systems (ICPADS)

作者： Sun, Peng Wen, Yonggang Ta Nguyen Binh Duong Xiao, Xiaokui Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

ISBN: (纸本)9781538621295

Recent studies showed that single-machine graph processing systems can be as highly competitive as cluster-based approaches on large-scale problems. While several out-of-core graph processing systems and computation models have been proposed, the high disk I/O overhead could significantly reduce performance in many practical cases. In this paper, we propose GraphMP to tackle big graph analytics on a single machine. GraphMP achieves low disk I/O overhead with three techniques. First, we design a vertex-centric sliding window (VSW) computation model to avoid reading and writing vertices on disk. Second, we propose a selective scheduling method to skip loading and processing unnecessary edge shards on disk. Third, we use a compressed edge cache mechanism to fully utilize the available memory of a machine to reduce the amount of disk accesses for edges. Extensive evaluations have shown that GraphMP could outperform state-of-the-art systems such as GraphChi, X-Stream and GridGraph by 31.6x, 54.5x and 23.1x respectively, when running popular graph applications on a billion-vertex graph.

关键词： Graph processing Big Data parallel Computing

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A High-performance DSM Leveraging Software Defined Network 44

A High-performance DSM Leveraging Software Defined Network

引用

44th Annual international conference on parallel processing Workshops (ICPPW)

作者： Gao Qiang Tong Weiqin Kausar, Samina Shanghai Univ Sch Comp Engn & Sci Shanghai Peoples R China

ISBN: (纸本)9781467375894

distributed shared memory(DSM) is an implementation of the shared memory model in distributed systems. Software-defined networking (SDN), can be effectively exploited to improve the performance of DSM. In this research, we propose an SDN-based distributed shared memory architecture. This architecture improves distributed applications by tuning network transmission and offloading functionality to the underlying network. We present a dynamic SDN multicast mechanism to reduce the number of consistency-related messages without interfering the unrelated processes in the same multicast group. In addition to these, we design a state-aware transmission mechanism that reduces the contention delays by using multicast communication. Furthermore, a novel write-update mechanism based on SDN orderly multicast is presented. The experiments on the prototype system show that the distributed applications using SDN-based DSM yield remarkable performance improvements. Moreover, this type of prototype system is feasible to implement on existing hardware.

关键词： DSM big data in-memory processing SDN state-aware ordered reliable multicast

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FuzzyGPU: a fuzzy arithmetic library for GPU

FuzzyGPU: a fuzzy arithmetic library for GPU

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22nd Euromicro international conference on parallel, distributed, and Network-Based processing (PDP)

作者： Defour, David Marin, Manuel Univ Perpignan DALI F-66860 Perpignan France Univ Montpellier 2 LIRMM UMR 5506 F-34095 Montpellier France CNRS LIRMM UMR 5506 F-34095 Montpellier France

ISBN: (纸本)9781479927289

Data are traditionally represented using native format such as integer or floating-point numbers in various flavor. However, some applications rely on more complex representation format. This is the case when uncertainty needs to be apprehended. Fuzzy arithmetic is one of the major tools to address this problem, but the execution time of basic operations such as addition or multiplication makes its usage prohibitive. In this article, thanks to a new representation format and modern GPU characteristics we show that it is possible to greatly reduce the execution time of those operations. These techniques have been implemented in fuzzyGPU, a freely distributed library of common operations over fuzzy number.

关键词： floating point arithmetic fuzzy set theory graphics processing units number theory addition operation execution time reduction floating-point numbers fuzzy arithmetic library fuzzy number fuzzyGPU integer numbers multiplication operation representation format uncertainty management usage prohibitive Encoding Graphics processing units Kernel Libraries Memory management Uncertainty

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