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distributed Algorithms for TDMA Link Scheduling in Sensor Networks

Distributed Algorithms for TDMA Link Scheduling in Sensor Ne...

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

作者： Alsulaiman, Thamer Prasad, Sushil K. Zelikovsky, Alexander Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA

ISBN: (纸本)9780769546766

The paper is devoted to Time Division Multiple Access Link Scheduling Protocols in wireless sensor networks for full duplex (two-way) communication, where each sensor is scheduled on an incident link as a transmitter and as a receiver in two different time slots. We formulate the full duplex link scheduling problem (FDLSP) as distance-2 edge coloring in bi-directed graphs. We proves that there exists Delta-approximation algorithm for FDLSP (Delta being the maximum node degree in the network). Then, we present two distributed algorithms. The first is a synchronous algorithm based on finding maximal independent sets. The second is an asynchronous depth first search (DFS) algorithm. The maximal independent set based algorithm requires only O(Delta log*n) communication rounds (where n is the number of processors in the network) for growth bounded graphs, which is a realistic geometric model of sensor networks. For general graphs, the maximal independent set based algorithm requires O(Delta(4) + Delta(3)log*n) communication rounds, improving upon the previous best algorithm with O(n Delta(2) + n(2)m) communication rounds (where m is the number of links in the network). The asynchronous DFS based algorithm requires only O(n) communication rounds for both general and growth bounded graphs. The simulations show that the proposed algorithms assign on average equal or fewer number of time slots compared to the best known distributed algorithm while being significantly faster.

关键词： distributed algorithms Depth--first search Communication Research Sensor networks colored graph algorithms Rounding off network links

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Modeling and Predicting Performance of High Performance computing Applications on Hardware Accelerators

Modeling and Predicting Performance of High Performance Comp...

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26th IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Meswani, Mitesh R. Carrington, Laura Unat, Didem Snavely, Allan Baden, Scott Poole, Stephen UCSD SDSC La Jolla CA USA

ISBN: (纸本)9780769546766

Computers with hardware accelerators, also referred to as hybrid-core systems, speedup applications by offloading certain compute operations that can run faster on accelerators. Thus, it is not surprising that many of top500 supercomputers use accelerators. However, in addition to procurement cost, significant programming and porting effort is required to realize the potential benefit of such accelerators. Hence, before building such a system it is prudent to answer the question 'what is the projected performance benefit from accelerators for the workloads of interest?'. We address this question by way of a performance-modeling framework that predicts realizable application performance on accelerators rapidly and accurately without going to the considerable effort of porting and tuning. The modeling framework first automatically identifies commonly found compute patterns in scientific applications which we term idioms, which may benefit by accelerator technology. Next the framework models the predicted speedup of those idioms if they were to be ported to and run on hardware accelerators. As a proof of concept we characterize two kinds of accelerators 1) the FPGA accelerators on a Convey HC-1 system and 2) an NVIDIA FERMI GPU accelerator. We model performance of the idioms gather/scatter and stream and our predictions show that where these occur in two full-scale HPC applications, Milc and HYCOM, gather/scatter speeds up by as much as 15X, and stream by as much as 14X, whereas the overall compute time of Milc improves by 3.4% and HYCOM by 20%.

关键词： accelerators GPU FPGA performance prediction performance modeling benchmarking HPC

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A parallel and distributed surrogate model implementation for computational steering

A parallel and distributed surrogate model implementation fo...

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

作者： Butnaru, Daniel Buse, Gerrit Pflüger, Dirk Institut für Informatik Technische Universität München Germany

ISBN: (纸本)9780769548050

Understanding the influence of multiple parameters in a complex simulation setting is a difficult task. In the ideal case, the scientist can freely steer such a simulation and is immediately presented with the results for a certain configuration of the input parameters. Such an exploration process is however not possible if the simulation is computationally too expensive. For these cases we present in this paper a scalable computational steering approach utilizing a fast surrogate model as substitute for the time-consuming simulation. The surrogate model we propose is based on the sparse grid technique, and we identify the main computational tasks associated with its evaluation and its extension. We further show how distributed data management combined with the specific use of accelerators allows us to approximate and deliver simulation results to a high-resolution visualization system in real-time. This significantly enhances the steering workflow and facilitates the interactive exploration of large datasets. © 2012 IEEE.

关键词： Real time systems

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parallel Simulation Models for the Evaluation of Future Large-Scale Datacenter Networks 12

Parallel Simulation Models for the Evaluation of Future Larg...

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16th IEEE/ACM international symposium on distributed Simulation and Real Time Applications

作者： Lugones, Diego Katrinis, Kostas Collier, Martin Theodoropoulos, Georgios Dublin City Univ Rince Inst Dublin 9 Ireland IBM Res Dublin Ireland

ISBN: (纸本)9780769548463

The recent trend for Software as a Service and other types of cloud services is driving demand for data centers of ever increasing scale. This will require the scaling up and scaling out of existing data center architectures and will ultimately need new architectures featuring new topologies for the data center networks that interconnect its constituent nodes. The preferred tool for the detailed evaluation of such designs is simulation, as it gives finer detail than analysis at lower cost than testbed evaluation. Realistic simulation times require that the simulation itself be capable of being scaled out, i.e., it should be amenable to parallelization. We describe a simulation framework, together with a methodology for partitioning the relevant simulation models to allow their parallel implementation, and demonstrate its validity by applying it to the simulation of a hybrid optical/electrical network architecture using a cluster of high-end servers. We report on results capturing the performance of our simulator and discuss how these are associated with the underlying hardware hosting the simulation.

关键词： Cloud computing data center simulating Software as a service ARCHITECTURE Simulation models NETWORK STRUCTURE parallelization Scale formation simulator parallel Lines

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High-Performance Design of HBase with RDMA over InfiniBand

High-Performance Design of HBase with RDMA over InfiniBand

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

作者： Huang, Jian Ouyang, Xiangyong Jose, Jithin Wasi-ur-Rahman, Md Wang, Hao Luo, Miao Subramoni, Hari Murthy, Chet Panda, Dhabaleswar K. Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA IBM Corp T J Watson Res Ctr ktown Heights NY USA

ISBN: (纸本)9780769546759

HBase is an open source distributed Key/Value store based on the idea of BigTable. It is being used in many data-center applications (e. g. Facebook, Twitter, etc.) because of its portability and massive scalability. For this kind of system, low latency and high throughput is expected when supporting services for large scale concurrent accesses. However, the existing HBase implementation is built upon Java Sockets Interface that provides sub-optimal performance due to the overhead to provide cross-platform portability. The byte-stream oriented Java sockets semantics confine the possibility to leverage new generations of network technologies. This makes it hard to provide high performance services for data-intensive applications. The High Performance computing (HPC) domain has exploited high performance and low latency networks such as InfiniBand for many years. These interconnects provide advanced network features, such as Remote Direct Memory Access (RDMA), to achieve high throughput and low latency along with low CPU utilization. RDMA follows memory-block semantics, which can be adopted efficiently to satisfy the object transmission primitives used in HBase. In this paper, we present a novel design of HBase for RDMA capable networks via Java Native Interface (JNI). Our design extends the existing open-source HBase software and makes it RDMA capable. Our performance evaluation reveals that latency of HBase Get operations of 1KB message size can be reduced to 43.7 mu s with the new design on QDR platform (32 Gbps). This is about a factor of 3.5 improvement over 10 Gigabit Ethernet (10 GigE) network with TCP Offload. Throughput evaluations using four HBase region servers and 64 clients indicate that the new design boosts up throughput by 3X times over 1 GigE and 10 GigE networks. To the best of our knowledge, this is first HBase design utilizing high performance RDMA capable interconnects.

关键词： HBase InfiniBand RDMA Cloud computing and Clusters

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Exploiting state-of-the-art x86 architectures in scientific computing

Exploiting state-of-the-art x86 architectures in scientific ...

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

作者： Heinecke, Alexander Auckenthaler, Thomas Trinitis, Carsten Institut für Informatik Technische Universität München D-85748 Garching bei München Germany

ISBN: (纸本)9780769548050

In recent years, general purpose x86 architectures have undergone significant modifications towards high performance computing capabilities. Lately, technologies like wider vector units or Fused Multiply-Add (FMA) instruction, which were mainly known from GPU arcitectures, have been introduced. In this paper, we examine the performance of current x86 architectures, namely Intel Sandy Bridge and AMD Bulldozer, for four different parallel workloads with different properties. These properties comprise optimally cache-blocked algorithms as well as adaptive grid structures resulting in memory latency and bandwidth bound executions. The achieved performance on both architectures is very promising, and, if extrapolated towards upcoming server silicon, can be regarded as on par with current high-end GPU based accelerators. © 2012 IEEE.

关键词： parallel architectures

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Software engineering as a service for HPC

Software engineering as a service for HPC

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

作者： Schmidberger, Miriam Schmidberger, Markus Technische Universität München Institut für Informatik Garching Germany HPC and Cloud Computing Consultant Munich Germany

ISBN: (纸本)9780769548050

The application of Software Engineering (SE) techniques in High Performance computing (HPC) is an often discussed and difficult issue. The 'as a service' model approach rising from latest cloud computing trends provides an promising way to offer appropriate software engineering support for high performance computing. This paper presents and discusses the idea and concept for a Software Engineering as a Service (SEaaS) platform for HPC. It is designed to enhance efficient problem solving and implementation, to deal with limited resources, and to guide interdisciplinary teams. The service supports agile SE techniques, can be adapted for the depending HPC environment, is user optimized based on the preferred programming language and will be implemented as an open-source and app-like framework. The implementation and evaluation of the SEaaS app is work in progress. © 2012 IEEE.

关键词： Application programs

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Optimization Of parallel I/O For Cannon's algorithm Based On Lustre

Optimization Of Parallel I/O For Cannon's algorithm Based On...

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11th international symposium on distributed computing and Applications to Business, Engineering and Science (DCABES)

作者： Li, Yunchun Li, Hongda Beihang Univ Beijing Key Lab Network Technol Dept Comp Sci Beijing Peoples R China

ISBN: (纸本)9780769548180

Matrix multiplication is one of the most important operations in linear algebra, widely used in many fields of science and engineering. Cannon's algorithm is a classical distributed algorithm for matrix multiplication for two-dimensional meshes. Generally, MPI-IO is used for its I/O requirements. However it has been well documented that MPI-IO performs poorly in a Lustre file system environment. As the scale of matrix multiplication increased, this problem trends to be serious, becoming one key factor impacting performance of the program. In order to improve the performance of Collective I/O of Cannon's program, we proposed a new aggregation pattern (Stripe-continuous aggregation pattern), which fully considers the stripping mechanism and lock protocol of Lustre file system. The theoretical analysis and experimental results show that the pattern can make full use of the capacity of Lustre file system compared with the other patterns, and improve the I/O performance of the Cannon's program efficiently.

关键词： Cannon's algorithm parallel I/O Lustre file system MPI-IO Collective I/O

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Preface to the Special Issue on intelligent distributed computing

Preface to the Special Issue on intelligent distributed comp...

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作者： BǍdicǍ, Costin Menezes, Ronaldo Software Engineering Department University of Craiova Bvd. Decebal 107 200440 Craiova Romania Florida Institute of Technology United States

New research results and applications of intelligent distributed computing (IDC), including the synergies between intelligent software agents and bioinspired technologies and parallel and distributed computing, are presented. These papers were selected for the Fourth international symposium on Intelligent distributed computing (IDC 2010) and the collocated Second international Workshop on Multi-Agent Systems Technology and Semantics (MASTS 2010), September 16 18, 2010, Tangier,Morocco. Gabriel Ciobanu and Calin Juravle introduce a systematic approach for deriving the software architecture of a mobile agents' environment. Antonio González-Pardo et. al. introduce a new bio-inspired method to improve agent communication for collaborative problem solving using a network of agents. Daniel Diaz et. al. introduce a parallel extension of constraint-based local search algorithm called adaptive search (AS).

关键词： distributed computer systems

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A Novel Associative Model of Data: Toward a distributed Large-Scale Data Processing Scheme for Future Computer Clouds

A Novel Associative Model of Data: Toward a Distributed Larg...

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11th IEEE international symposium on Network computing and Applications (NCA)

作者： Basirat, Amir H. Khan, Asad I. Monash Univ Clayton Sch IT Melbourne Vic 3004 Australia

ISBN: (纸本)9780769547732

Existing cloud frameworks involve isolating low-level operations within an application for data distribution and partitioning. This limits their applicability for many applications with complex data dependency considerations. This paper aims to explore new methods of partitioning and distributing data in the cloud by fundamentally re-thinking the way in which future data management models will need to be developed on the Internet. Loosely-coupled associative computing techniques, which have so far not been considered, can provide the break-through needed for a distributed data management scheme. Using a novel lightweight associative memory algorithm known as Edge Detecting Hierarchical Graph Neuron (EdgeHGN), data retrieval/processing can be modeled as a pattern recognition problem, conducted across multiple records within a single-cycle, utilizing a parallel approach. The proposed model envisions a distributed data management scheme for large-scale data processing and database updating that is capable of providing scalable real-time recognition and processing with high accuracy while being able to maintain low computational cost in its function.

关键词： distributed Data Processing Neural Network One-shot Learning Associative computing Cloud computing

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