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检索条件"任意字段=Proceedings of the 5th IEEE Symposium on Parallel and Distributed Processing"

共 3536 条记录，以下是431-440 订阅

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Adaptive N To P Portfolio for Solving Constraint Programming Problems on Top of the parallel Bobpp Framework 28

Adaptive <i>N</i> To <i>P</i> Portfolio for Solving Constrai...

引用

28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Menouer, Tarek Le Cun, Bertrand Univ Versailles St Quentin En Yvelines PRISM Lab Versailles France

ISBN: (纸本)9781479941162

this paper presents a parallelization of Constraint Programming (CP) solver, based on the portfolio principle, in order to quickly solve constraint satisfaction and optimisation problems. the portfolio principle is widely used in the parallelization of boolean SATisfiability (SAT) and CP solvers. It is based on the running of N search strategies for the same problem using N computing cores. Each core uses its own strategy in order to perform a search that is different form the other ones. the first strategy that responds to the needs of the user stops all other strategies. In the usual portfolio principle, the number of search strategies is limited compared to the current number of the computing cores used by parallel machines. the idea of this article is to run N search strategies for the same CP problem and schedule these strategies using P computing cores (P > N). the novelty is that the scheduling of these N strategies is dynamically performed between the different computing cores. the goal is to adapt the scheduling of the search strategies so as to favour the strategy that finds a solution quickly. the performances obtained with this adaptive portfolio solver are illustrated by solving the CP problems modeled using FlatZinc format and solved using the OR-Tools solver on top of the parallel Bobpp framework.

关键词： parallelism Dynamic load balancing Combinatorial Optimization scheduling

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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...

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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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proceedings of the International parallel and distributed processing symposium, IPDPS

Proceedings of the International Parallel and Distributed Pr...

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28th ieee International parallel and distributed processing symposium Workshops, IPDPSW 2014

ISBN: (纸本)9780769552088

the proceedings contain 195 papers. the topics discussed include: autotuning tensor transposition;deterministic synchronization of multi-threaded programs with operational transformation;using physical stigmergy in decentralized optimization under multiple non-separable constraints: formal methods and an intelligent lighting example;hybrid metaheuristic for annual hydropower generation optimization;machine-learning-based identification of defect patterns in semiconductor wafer maps: an overview and proposal;data quality, consistency, and interpretation management for wind farms by using neural networks;graph-based cellular automata approach to maximum lifetime coverage problem in wireless sensor networks;and GPU accelerated nature inspired methods for modeling large scale bi-directional pedestrian movement.

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Efficient Computation of the Phylogenetic Likelihood Function on the Intel MIC Architecture 28

Efficient Computation of the Phylogenetic Likelihood Functio...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Kozlov, Alexey M. Goll, Christian Stamatakis, Alexandros Heidelberg Inst Theoret Studies Sci Comp Grp Exelixis Lab Heidelberg Germany Karlsruhe Inst Technol Inst Theoret Informat D-76128 Karlsruhe Germany

ISBN: (纸本)9781479941162

Phylogenetic inference is the process of reconstructing the evolutionary history of species based on their traits, nowadays mostly using molecular sequence data. Current state-of-the-art inference methods, like Bayesian and Maximum Likelihood (ML) inference, rely on the Phylogenetic Likelihood Function (PLF) as their computational core. Due to the large number of floating-point operations involved, the PLF evaluation is the major bottleneck for large-scale phylogenetic analyses comprising thousands of genes or even whole genomes. Here, we describe an optimized implementation of the PLF kernel for the novel Intel Many Integrated Core (MIC) architecture. Using a MIC-based accelerator (Xeon Phi 5110P), we were able to achieve speedups ranging from 1.9x to 2.8x for different PLF kernels, compared to a highly optimized AVX implementation running on dual-socket Xeon E5-2680 system. By integrating the optimized PLF into the phylogenetic inference program RAxML-Light, we reduced the overall execution times by up to factor of two. To assess the scalability on multiple Xeon Phi cards, we also developed a hybrid MPI-OpenMP version of the ExaML code. When ExaML is executed on two coprocessors on the same node, we obtain speedups of up to a factor of 3.7 (vs. a CPU baseline) and 1.8 (vs. a single MIC). As expected, speedups increase with growing dataset size and become stable for alignments that require processing 1-2 million sites per MIC card.

关键词： bioinformatics phylogenetics maximum likelihood Intel MIC parallel processing MPI

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Maintaining Dependable Communication Service for Mobile Stations in Wireless Mesh Networks by Tracking Capacity Demands 28

Maintaining Dependable Communication Service for Mobile Stat...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Lindhorst, Timo Weseloh, Burkhard Nett, Edgar Univ Magdeburg Inst Distributed Syst Univ Pl 2 D-39106 Magdeburg Germany

ISBN: (纸本)9781479941162

Wireless Mesh Networks (WMNs) form communication networks that combine high flexibility due to self-organization within a completely wireless infrastructure and reliability due to the meshed topology. A fundamental aspect to provide dependable communication in such networks is the avoidance of network overload, which might cause significant packet loss and unbounded time delays. For this purpose, admission control mechanisms have been elaborated to determine the available network capacity and the capacity demands for new communication flows. However, even if a precise assessment of the capacity is available, the presence of mobile stations in the network cause a variation of the network capacity. When a station moves, its capacity demands may increase due to a longer path which may incur the violation of QoS guarantees. We propose a scheme to track the capacity demands of mobile stations and consider these on admission decisions. We show that this approach allows to maintain a dependable communication service even in presence of mobile stations and thus improve the applicability of WMNs for dependable mobile applications.

关键词： Dependable communication Mobility Wireless mesh networks

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Twill: A Hybrid Microcontroller-FPGA Framework for parallelizing Single-threaded C Programs 28

Twill: A Hybrid Microcontroller-FPGA Framework for Paralleli...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Gallatin, Doug Keen, Aaron Lupo, Chris Oliver, John Calif Polytech State Univ San Luis Obispo Comp Engn Program San Luis Obispo CA 93407 USA

ISBN: (纸本)9781479941162

Increasingly System-On-A-Chip platforms which incorporate both microprocessors and re-programmable logic are being utilized across several fields ranging from the auto-motive industry to network infrastructure. Unfortunately, the development tools accompanying these products leave much to be desired, requiring knowledge of both traditional embedded systems languages like C and hardware description languages like Verilog. We propose to bridge this gap with Twill, a truly automatic hybrid compiler that can take advantage of the parallelism inherent in these platforms. Twill can extract long-running threads from single threaded C code and distribute these threads across the hardware and software domains to more fully utilize the asymmetric characteristics between processors and the embedded reconfigurable logic fabric. We show that Twill provides a significant performance increase on the CHStone benchmarks with an average 1.63 times increase over the pure hardware approach and an increase of 22.2 times on average over the pure software approach while in general decreasing the area required by the reconfigurable logic compared to the pure hardware approach.

关键词： Embedded Systems Microcontroller-FPGA Hybrid Systems parallel Architecture

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A Hybrid parallel Tridiagonal Solver on Multi-core Architectures 28

A Hybrid Parallel Tridiagonal Solver on Multi-core Architect...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Tang, Guangping Li, Kenli Li, Keqin Chen, Hang Du, Jiayi Hunan Univ Coll Informat Sci & Engn Changsha 410082 Hunan Peoples R China State Univ New York New Paltz Dept Comp Sci New Paltz NY 12561 USA

ISBN: (纸本)9781479941162

An optimized parallel algorithm is proposed to solve the problem occurred in the process of complicated backward substitution of cyclic reduction during solving tridiagonal linear systems. Adopting a hybrid parallel model, this algorithm combines the cyclic reduction method and the partition method. this hybrid algorithm has simple backward substitution on parallel computers comparing with the cyclic reduction method. In this paper, the operation count and execution time are obtained to evaluate and make comparison for these methods. On the basis of results of these measured parameters, the hybrid algorithm using the hybrid approach with a multi-threading implementation achieves better efficiency than the other parallel methods, i.e., the cyclic reduction and the partition methods. Among them, the cyclic reduction method is previously found to be the fastest algorithm in many ways for solutions. In particular, the approach involved in this paper has the least scalar operation count and the shortest execution time on multi-core computer when the size of an equation is large enough. the hybrid parallel algorithm improves the performance of the cyclic reduction and partition methods by 30% and 20% respectively.

关键词： parallel tridiagonal hybrid algorithm multi-threading

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proceedings - 2014 ieee International symposium on parallel and distributed processing with Applications, ISPA 2014

Proceedings - 2014 IEEE International Symposium on Parallel ...

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12th ieee International symposium on parallel and distributed processing with Applications, ISPA 2014

ISBN: (纸本)9781479942930

the proceedings contain 33 papers. the topics discussed include: analyzing the energy efficiency of the memory subsystem in multicore processors;a proactive customer-aware resource allocation approach for data centers;parallel subgraph counting for multicore architectures;petapar: a scalable petascale framework for meshfree/particle simulation;a high performance compression method for climate data;a utility-maximizing tasks assignment method for rendering cluster system;efficient routing algorithms combining history and social predictors in mobile social networks;a high-throughput and low-latency parallelization of window-based stream joins on multicores;OpenCL application auto-tuning and run-time resource management for multi-core platforms;FPGA-based design using the FASTER toolchain: the case of STM spear development board;and EURETILE design flow: dynamic and fault tolerant mapping of multiple applications onto many-tile systems.

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YAFIM: A parallel Frequent Itemset Mining Algorithm with Spark 28

YAFIM: A Parallel Frequent Itemset Mining Algorithm with Spa...

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28th ieee International parallel & distributed processing symposium Workshops (IPDPSW)

作者： Qiu, Hongjian Gu, Rong Yuan, Chunfeng Huang, Yihua Nanjing Univ Dept Comp Sci & Technol Natl Key Lab Novel Software Technol Nanjing 210023 Jiangsu Peoples R China

ISBN: (纸本)9781479941162

the frequent itemset mining (FIM) is one of the most important techniques to extract knowledge from data in many real-world applications. the Apriori algorithm is the widely-used algorithm for mining frequent itemsets from a transactional dataset. However, the FIM process is both data-intensive and computing-intensive. On one side, large scale data sets are usually adopted in data mining nowadays;on the other side, in order to generate valid information, the algorithm needs to scan the datasets iteratively for many times. these make the FIM algorithm very time-consuming over big data. the parallel and distributed computing is effective and mostly-used strategy for speeding up large scale dataset algorithms. However, the existing parallel Apriori algorithms implemented with the MapReduce model are not efficient enough for iterative computation. In this paper, we proposed YAFIM (Yet Another Frequent Itemset Mining), a parallel Apriori algorithm based on the Spark RDD framework-a specially-designed in-memory parallel computing model to support iterative algorithms and interactive data mining. Experimental results show that, compared with the algorithms implemented with MapReduce, YAFIM achieved 18 x speedup in average for various benchmarks. Especially, we apply YAFIM in a real-world medical application to explore the relationships in medicine. It outperforms the MapReduce method around 25 times.

关键词： Frequent Itemset Mining Apriori Algorithm parallel Computing Spark Medical Application

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Overcoming the Scalability Challenges of Epidemic Simulations on Blue Waters

Overcoming the Scalability Challenges of Epidemic Simulation...

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ieee 28th International parallel & distributed processing symposium (IPDPS)

作者： Yeom, Jae-Seung Bhatele, Abhinav Bisset, Keith Bohm, Eric Gupta, Abhishek Kale, Laxmikant V. Marathe, Madhav Nikolopoulos, Dimitrios S. Schulz, Martin Wesolowski, Lukasz Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Virginia Tech Virginia Bioinformat Inst Blacksburg VA 24061 USA Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA 94551 USA Univ Illinois Dept Comp Sci Urbana IL 61801 USA Queens Univ Belfast Sch EEECS Belfast Antrim BT9 5BN North Ireland

ISBN: (纸本)9780769552071

Modeling dynamical systems represents an important application class covering a wide range of disciplines including but not limited to biology, chemistry, finance, national security, and health care. Such applications typically involve large-scale, irregular graph processing, which makes them difficult to scale due to the evolutionary nature of their workload, irregular communication and load imbalance. EpiSimdemics is such an application simulating epidemic diffusion in extremely large and realistic social contact networks. It implements a graph-based system that captures dynamics among co-evolving entities. this paper presents an implementation of EpiSimdemics in Charm++ that enables future research by social, biological and computational scientists at unprecedented data and system scales. We present new methods for application-specific processing of graph data and demonstrate the effectiveness of these methods on a Cray XE6, specifically NCSA's Blue Waters system.

关键词： contagion simulations scalability performance graph processing social contact networks

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