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Improving the Performance of Dynamical Simulations Via Multiple Right-Hand Sides

Improving the Performance of Dynamical Simulations Via Multi...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Liu, Xing Chow, Edmond Vaidyanathan, Karthikeyan Smelyanskiy, Mikhail Georgia Inst Technol Coll Comp Sch Computat Sci & Engn Atlanta GA 30332 USA Intel Corp Parallel Comp Lab Santa Clara CA 95054 USA

ISBN: (纸本)9780769546759

This paper presents an algorithmic approach for improving the performance of many types of stochastic dynamical simulations. The approach is to redesign existing algorithms that use sparse matrix-vector products (SPMV) with single vectors to instead use a more efficient kernel, the generalized SPMV (GSPMV), which computes with multiple vectors simultaneously. In this paper, we show how to redesign a dynamical simulation to exploit GSPMV in way that is not initially obvious because only one vector is available at a time. We study the performance of GSPMV as a function of the number of vectors, and demonstrate the use of GSPMV in the Stokesian dynamics method for the simulation of the motion of macromolecules in the cell. Specifically, for our application, we find that with modern multicore Intel microprocessors in clusters of up to 64 nodes, we can typically multiply by 8 to 16 vectors in only twice the time required to multiply by a single vector. After redesigning the Stokesian dynamics algorithm to exploit GSPMV, we measure a 30 percent speedup in performance in single-node, data parallel simulations.

关键词： sparse matrix-vector product (SPMV) iterative methods block Krylov subspace methods SIMD (SSE/AVX) Stokesian dynamics Brownian dynamics biological macromolecular simulation

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distributed S-Net: Cluster and grid computing without the hassle 12

Distributed S-Net: Cluster and grid computing without the ha...

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12th IEEE/ACM international symposium on Cluster, Cloud and Grid computing, CCGrid 2012

作者： Grelck, Clemens Julku, Jukka Penczek, Frank Institute of Informatics University of Amsterdam Amsterdam Netherlands VTT Technical Research Center of Finland Espoo Finland Science and Technology Research Institute University of Hertfordshire Hatfield United Kingdom

ISBN: (纸本)9780769546919

S-Net is a declarative coordination language and component technology primarily aimed at modern multi-core/many-core chip architectures. It builds on the concept of stream processing to structure dynamically evolving networks of communicating asynchronous components, which themselves are implemented using a conventional language suitable for the application domain. We present the design and implementation of distributed S-Net, a conservative extension of S-Net aimed at distributed memory architectures ranging from many-core chip architectures with hierarchical memory organisations to more traditional clusters of workstations, supercomputers and grids. Three case studies illustrate how to use distributed S-Net to implement different models of parallel execution. Runtimes obtained on a workstation cluster demonstrate how distributed S-Net allows programmers with little or no background in parallel programming to make effective use of distributed memory architectures with minimal programming effort. © 2012 IEEE.

关键词： Message passing

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A Compiler Back-End for Reconfigurable, Mixed-ISA Processors with Clustered Register Files

A Compiler Back-End for Reconfigurable, Mixed-ISA Processors...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Stripf, Timo Koenig, Ralf Rieder, Patrick Becker, Juergen Karlsruhe Inst Technol Karlsruhe Germany

ISBN: (纸本)9780769546766

Reconfigurable tile-based architectures can dynamically interconnect several tiles in order to establish processor instances with varying resource, performance, and energy characteristics at run time. These flexible processor instances offer a new degree of freedom for adapting to changing applications' requirements while optimizing resource and energy consumption. Our solution for dynamic interconnection of tiles requires a flexible Run-Time Scalable Issue-Width (RSIW) Instruction Set Architecture (ISA) that changes dependent on the configuration. In order to enable high-level programmability of our architecture in C/C++ a novel compiler back-end is needed. In this paper we address this necessity by presenting a novel LLVM compiler back-end targeting the reconfigurable RSIW ISA and supporting mixed-ISA software development. RSIW is comparable to clustered-VLIW ISAs since it expresses parallel operations within the ISA and explicitly uses clustered register files. Therefore, we extended our architecture description language based RISC LLVM back-end by representations of parallel operations as well as compilation passes for clustering and scheduling of parallel operations as well as mixed-ISA code generation. Based on the novel back-end we compare the performance characteristics of several applications compiled for and simulated on different configurations. Additionally, we demonstrate resource-aware re-configuration by a mixed-ISA application scenario.

关键词： configurability parallel operation compilers Degree of freedom register file Tile back-end PROCESSOR Architecture description languages Runtime performance characteristics energy characteristics

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BLOR: Bandwidth and Latency Sensitive Overlay Routing for Flash Data Dissemination

BLOR: Bandwidth and Latency Sensitive Overlay Routing for Fl...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Li, Xiaoyong Wang, Yijie Fu, Yongquan Li, Xiaoling Sun, Weidong Natl Univ Def Technol Sch Comp Sci Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

ISBN: (纸本)9780769546766

Flash data dissemination transmits time-critical data to distributed receivers in a timely manner, which is widely used in many mission-critical applications. However, existing flash data dissemination approaches fail to guarantee the timely transmission due to the unpredictability of the dissemination process. Overlay routing has been widely used as an efficient routing primitive for providing better end-to-end routing quality, based on detouring inefficient routing paths in the P2P network. To improve the predictability of the flash data dissemination process, we propose a bandwidth and latency sensitive overlay routing scheme BLOR, by optimizing the overlay routing and avoiding poor performance of the data dissemination paths. BLOR tries to select optimal paths in terms of latency, bandwidth capacity and available bandwidth in nature, which has never been studied before. Additionally, a location-aware unstructured overlay topology construction scheme is proposed to improve the routing efficiency and data location, as well as an unbiased top-k dominating model is proposed to balance the multi-factor choosing for path selecting, in the optimization process of BLOR. Experimental results with real-world data sets confirm that BLOR significantly improves flash data dissemination.

关键词： data dissemination overlay topology construction routing path selection

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Scalable and resilient workflow executions on production distributed computing infrastructures

Scalable and resilient workflow executions on production dis...

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2012 11th international symposium on parallel and distributed computing, ISPDC 2012

作者： Balderrama, Javier Rojas Huu, Tram Truong Montagnat, Johan I3S Laboratory MODALIS Team University of Nice-Sophia Antipolis France

ISBN: (纸本)9780769548050

In spite of the growing interest for grids and cloud infrastructures among scientific communities and the availability of such facilities at large-scale, achieving high performance in production environments remains challenging due to at least four factors: the low reliability of very large-scale distributed computing infrastructures, the performance overhead induced by shared facilities, the difficulty to obtain fair balance of all user jobs in such an heterogeneous environment, and the complexity of large-scale distributed applications deployment. All together, these difficulties make infrastructure exploitation complex, and often limited to experts. This paper introduces a pragmatic solution to tackle these four issues based on a service-oriented methodology, the reuse of existing middleware services, and the joint exploitation of local and distributed computing resources. Emphasis is put on the integrated environment ease of use. Results on an actual neuroscience application show the impact of the environment setup in terms of reliability and performance. Recommendations and best practices are derived from this experiment. © 2012 IEEE.

关键词： Grid computing

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PQH: A Multithreaded parallel NN Search Index for Content-based Image Retrieval

PQH: A Multithreaded Parallel NN Search Index for Content-ba...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Chen, Hui-zhong Jing, Ning Chen, Yong-guang Chen, Luo Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China Ordnance Engn Coll Shijiazhuang 050003 Peoples R China

ISBN: (纸本)9780769546766

In this paper, we propose a NN search index method called parallel Quantized Hashing (PQH) for relevant retrieval in Content-Based Image Retrieval (CBIR) systems. Aiming at improving the performance of query, the PQH partitions the original dataset into several subsets and keeps the pointers to quantized vectors of each subset in a hashing like structure. It only needs to filter parts of the query space to get candidates via neighboring masks and accesses the corresponding real vectors for precise calculation. The neighboring masks are sets of mask vectors indicating cells close to the query point using different metrics. The PQH is multithreaded designed so that the construction and the query can be run in parallel upon multi-core processors. Our extensive experiments confirm that the sequential PQH is of high query efficiency and outperforms the existing methods such as VA+-file and LSH. The parallel run PQH achieves even higher performance and returns appropriate NN results. And more important it is simple for practical implement in real applications.

关键词： kNN multithreaded parallelism CBIR

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Towards parallel Spatial Query Processing for Big Spatial Data

Towards Parallel Spatial Query Processing for Big Spatial Da...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Zhong, Yunqin Han, Jizhong Zhang, Tieying Li, Zhenhua Fang, Jinyun Chen, Guihai Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Peking Univ Beijing Peoples R China Shanghai Jiao Tong Univ Shanghai Peoples R China Grad Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9780769546766

In recent years, spatial applications have become more and more important in both scientific research and industry. Spatial query processing is the fundamental functioning component to support spatial applications. However, the state-of-the-art techniques of spatial query processing are facing significant challenges as the data expand and user accesses increase. In this paper we propose and implement a novel scheme (named VegaGiStore) to provide efficient spatial query processing over big spatial data and numerous concurrent user queries. Firstly, a geography-aware approach is proposed to organize spatial data in terms of geographic proximity, and this approach can achieve high aggregate I/O throughput. Secondly, in order to improve data retrieval efficiency, we design a two-tier distributed spatial index for efficient pruning of the search space. Thirdly, we propose an "indexing + MapReduce" data processing architecture to improve the computation capability of spatial query. Performance evaluations of the real-deployed VegaGiStore system confirm its effectiveness.

关键词： spatial data management distributed storage spatial index spatial query spatial applications

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distributed shared memory programming in the cloud 12

Distributed shared memory programming in the cloud

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12th IEEE/ACM international symposium on Cluster, Cloud and Grid computing, CCGrid 2012

作者： Anbar, Ahmad Narayana, Vikram K. El-Ghazawi, Tarek Department of Electrical and Computer Engineering George Washington University United States

ISBN: (纸本)9780769546919

Cloud computing is beginning to play a dominant role in scientific computing. However, there are still several challenges that need to be addressed, before data-intensive scientific applications make the transition to the cloud. Adoption of a distributed shared memory (DSM) programming paradigm will be one approach to ease the transition, through the use of Partitioned Global Address Space (PGAS) languages. This paper explores initial results from the adoption of a PGAS language, Unified parallel C, in programming a representative private cloud based on Eucalyptus. © 2012 IEEE.

关键词： parallel programming

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Optimal Resource Rental Planning for Elastic Applications in Cloud Market

Optimal Resource Rental Planning for Elastic Applications in...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Zhao, Han Pan, Miao Liu, Xinxin Li, Xiaolin Fang, Yuguang Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)9780769546759

This paper studies the optimization problem of minimizing resource rental cost for running elastic applications in cloud while meeting application service requirements. Such a problem arises when excessive generated data incurs significant monetary cost on transfer and inventory in cloud. The goal of planning is to make resource rental decisions in response to varying application progress in the most cost-effective way. To address this problem, we first develop a Deterministic Resource Rental Planning (DRRP) model, using a mixed integer linear program, to generate optimal rental decisions given fixed cost parameters. Next, we systematically analyze the predictability of the time-varying spot instance prices in Amazon EC2 and find that the best achievable prediction is insufficient to provide a close approximation to the actual prices. This fact motivates us to propose a Stochastic Resource Rental Planning (SRRP) model that explicitly considers the price uncertainty in rental decision making. Using empirical spot price data sets and realistic cost parameters, we conduct simulations over a wide range of experimental scenarios. Results show that DRRP achieves as much as 50% cost reduction compared to the no-planning scheme. Moreover, SRRP consistently outperforms its DRRP counterpart in terms of cost saving, which demonstrates that SRRP is highly adaptive to the unpredictable nature of spot price in cloud resource market.

关键词： Cloud computing Amazon EC2 Spot Instance Resource Rental Planning Stochastic Optimization

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Pattern Detection Model for Monitoring distributed Systems

Pattern Detection Model for Monitoring Distributed Systems

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13th international symposium on Symbolic and Numeric Algorithms for Scientific computing (SYNASC)

作者： Dinu, Cristian-Mircea Pop, Florin Cristea, Valentin Univ Politehn Bucuresti Fac Automat Control & Comp Sci Splaiul Independentei 313 Bucharest 060042 Romania

ISBN: (纸本)9780769546308

The ever-increasing size, variety and complexity of distributed systems necessitate the development of highly automated and intelligent solutions for monitoring system parameters. In the context of Large Scale distributed Systems, automatically detecting events and activity patterns will provide self-organization abilities and increase the dependability of these systems. We present in this paper a model for representing a wide variety of patterns in the parallel time series describing the distributed system parameters and states. Based on this model, we outline an application architecture for a system that employs advanced machine learning techniques for detecting and learning patterns in a distributed system with only minimal user input. The application is implemented as an add-on to the highly successful MonALISA monitoring framework for distributed systems. We test and validate the proposed model in real-time using the large amount of monitoring data provided by the MonALISA system. The novelty of this solution consists of the expressiveness of the model and the advanced automated data analysis for pattern learning and recognition in a long-time monitored system.

关键词： Large-Scale distributed Systems Pattern Detection Machine Learning Monitoring Resource Allocation MonALISA

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