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

Proceedings - 12th IEEE/ACM International Symposium on Clust...

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

ISBN: (纸本)9780769546919

The proceedings contain 137 papers. The topics discussed include: design and implementation of portable and efficient non-blocking collective communication;productive parallel linear algebra programming with unstructured topology adaption;user transparent data and task parallel multimedia computing with pyxis-DT;fine-grained access control in the chirp distributed file system;a map-reduce based framework for heterogeneous processing element cluster environments;workflow scheduling to minimize data movement using multi-constraint graph partitioning;decentralized orchestration of data-centric workflows using the object modeling system;evaluating dynamics and bottlenecks of memory collaboration in cluster systems;GPU performance enhancement via communication cost reduction: case studies of radix sort and WSN relay node placement problem;and client classification policies for SLA enforcement in shared cloud datacenters.

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parallel Remote Sensing Image Processing: Taking Image Classification as an Example

Parallel Remote Sensing Image Processing: Taking Image Class...

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6th international symposium on Intelligence Computation and Applications (ISICA 2012)

作者： Wang, Xiaoyue Li, Zhenhua Gao, Song China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China Auburn Univ Comp Sci & Software Engn Auburn AL 36849 USA

ISBN: (纸本)9783642342882

This paper introduces an architecture of parallel remote sensing image processing software, with advantages including high scalability, platform-independence, language-independence, and so on. It helps achieve high-performance computing in this field. MPI is used as the fundamental distributed message passing protocol. An object-oriented wrapper, *** library, is used in the software to manipulate MPI. Open Source libraries such as GDAL and Open-CV are studied in this paper to help develop detailed image processing programs and implement classification algorithms. A number of experiments are conducted to test the parallel classification programs. The results indicate that in most cases the performance is significantly improved, especially for multi-spectral remote sensing image classification, in which a highest speed-up of 3.92 is reached.

关键词： Remote Sensing Image Processing parallel computing

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The SPAS-UAH cluster for the JEM-EUSO computing model

The SPAS-UAH cluster for the JEM-EUSO computing model

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： De Los Ríos, J.A. Morales Sáez-Cano, G. Prieto, H. Del Peral, L. Carretero, J.H. Shinozaki, K. Rodríguez-Frías, M.D. Group UAH Madrid Spain RIKEN 2-1 Hirosawa Wako Saitama 351-0198 Japan

ISBN: (纸本)9780769547015

The JEM-EUSO space observatory will be launched and attached to the Japanese module of the international Space Station (ISS) in 2016. Its aims is to observe UV photon tracks produced by Ultra High Energy Cosmic Rays (UHECR) and Extremely High Energy Cosmic Rays (EHECR) developing in the atmosphere and producing Extensive Air Showers (EAS). JEM- EUSO will use our atmosphere as a huge calorimeter, to detect the electromagnetic and hadronic components of the EAS. For High Energy Physic (HEP) experiments the huge amount of data and complex analysis algorithms require the use of advanced GRID computational resources. Therefore a complete infrastructure is needed for the simulation and data analysis, in the frame of the GRID architecture, and computing infrastructure, intended for the JEM-EUSO space mission software. Moreover solutions to account for a complete installed cluster system, with the software and data repositories, as well as a many other details are pointed out. © 2012 IEEE.

关键词： Cosmology

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Extending Amdahl's Law for heterogeneous computing

Extending Amdahl's Law for heterogeneous computing

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： Marowka, Ami Department of Computer Science College of Exact Sciences Bar-Ilan University Ramat Gan 52900 Israel

ISBN: (纸本)9780769547015

Energy will be a major limiting factor in future multi-core architectures, so optimizing performance per watt should be a key driver for next generation massive-core architectures. Recent studies show that heterogeneous chips integrating different core architectures, such as CPU and GPU, on a single die is the most promising solution. We investigated how energy efficiency and scalability are affected by the power constraints imposed on contemporary hybrid CPU-GPU processors. Analytical models were developed to extend Amdahl's Law by accounting for energy limitations before examining the three processing modes available to heterogeneous processors, i.e., symmetric, asymmetric, and simultaneous asymmetric. The analysis shows clearly that greater parallelism is the most important factor affecting power consumption. © 2012 IEEE.

关键词： Energy efficiency

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Global data re-allocation via communication aggregation in chapel

Global data re-allocation via communication aggregation in c...

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24th international symposium on Computer Architecture and High Performance computing, SBAC-PAD 2012

作者： Sanz, Alberto Asenjo, Rafael López, Juan Larrosa, Rafael Navarro, Angeles Litvinov, Vassily Choi, Sung-Eun Chamberlain, Bradford L. Department of Computer Architecture University of Málaga Spain Cray Inc. Seattle WA United States

ISBN: (纸本)9781467347907

Chapel is a parallel programming language designed to improve the productivity and ease of use of conventional and parallel computers. This language currently delivers sub optimal performance when executing codes that perform global data re-allocation operations on distributed memory architectures. This is mainly due to data communication that is done without aggregation (one message for each remote array element). In this work, we analyze Chapel's standard Block and Cyclic distribution modules and optimize the communication routines for array assignments by performing aggregation. Thanks to the expressive power of Chapel, the compiler and runtime have enough information to do communication aggregation without user intervention. The runtime relies on the low-level GAS Net networking layer, whose versions of one-sided bulk put/get routines that support strides are particularly useful for us. Experimental results conducted on Hector (a Cray XE6) and Jaguar (Cray XK6)reveal that the implemented techniques can lead to significant reductions in communication time. © 2012 IEEE.

关键词： parallel programming

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Avoiding serialization effects in data / dependency aware task parallel algorithms for spatial decomposition

Avoiding serialization effects in data / dependency aware ta...

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： Niethammer, Christoph Glass, Colin W. Gracia, Jose High Performance Computing Center Stuttgart University of Stuttgart Germany

ISBN: (纸本)9780769547015

Spatial decomposition is a popular basis for parallelising code. Cast in the frame of task parallelism, calculations on a spatial domain can be treated as a task. If neighbouring domains interact and share results, access to the specific data needs to be synchronized to avoid race conditions. This is the case for a variety of applications, like most molecular dynamics and many computational fluid dynamics codes. Here we present an unexpected problem which can occur in dependency-driven task parallelization models like StarSs: the tasks accessing a specific spatial domain are treated as interdependent, as dependencies are detected automatically via memory addresses. Thus, the order in which tasks are generated will have a severe impact on the dependency tree. In the worst case, a complete serialization is reached and no two tasks can be calculated in parallel. We present the problem in detail based on an example from molecular dynamics, and introduce a theoretical framework to calculate the degree of serialization. Furthermore, we present strategies to avoid this unnecessary problem. We recommend treating these strategies as best practice when using dependency-driven task parallel programming models like StarSs on such scenarios. © 2012 IEEE.

关键词： Molecular dynamics

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parallel sparse polynomial multiplication on modern hardware architectures 12

Parallel sparse polynomial multiplication on modern hardware...

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37th international symposium on Symbolic and Algebraic Computation, ISSAC 2012

作者： Biscani, Francesco European Space Agency Advanced Concepts Team 2200 AG Noordwijk Netherlands

ISBN: (纸本)9781450312691

We present a high performance algorithm for the parallel multiplication of sparse multivariate polynomials on modern computer architectures. The algorithm is built on three main concepts: a cache-friendly hash table implementation for the storage of polynomial terms in distributed form, a statistical method for the estimation of the size of the multiplication result, and the use of Kronecker substitution as a homomorphic hash function. The algorithm achieves high performance by promoting data access patterns that favour temporal and spatial locality of reference. We present benchmarks comparing our algorithm to routines of other computer algebra systems, both in sequential and parallel mode. Copyright 2012 ACM.

关键词： Hash functions

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Adaptive computation offloading from mobile devices into the cloud

Adaptive computation offloading from mobile devices into the...

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： Kovachev, Dejan Yu, Tian Klamma, Ralf Information Systems and Database Technologies RWTH Aachen University Ahornstr. 55 52056 Aachen Germany

ISBN: (纸本)9780769547015

The inherently limited processing power and battery lifetime of mobile phones hinder the possible execution of computationally intensive applications like content-based video analysis or 3D modeling. Offloading of computationally intensive application parts from the mobile platform into a remote cloud infrastructure or nearby idle computers addresses this problem. This paper presents our Mobile Augmentation Cloud Services (MACS) middleware which enables adaptive extension of Android application execution from a mobile client into the cloud. Applications are developed by using the standard Android development pattern. The middleware does the heavy lifting of adaptive application partitioning, resource monitoring and computation offloading. These elastic mobile applications can run as usual mobile application, but they can also reach transparently remote computing resources. Two prototype applications using the MACS middleware demonstrate the benefits of the approach. The evaluation shows that applications, which involve complicated algorithms and large computations, can benefit from offloading with around 95\% energy savings and significant performance gains compared to local execution only. © 2012 IEEE.

关键词： Mobile computing

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Big Data Processing in Cloud computing Environments

Big Data Processing in Cloud Computing Environments

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12th international symposium on Pervasive Systems, Algorithms, and Networks (I-SPAN)

作者： Ji, Changqing Li, Yu Qiu, Wenming Awada, Uchechukwu Li, Keqiu Dalian Maritime Univ Coll Informat Sci & Technol Dalian 116026 Peoples R China Dalian Maritime Univ Coll Phys Sci & Technol Dalian 116026 Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China

ISBN: (纸本)9780769549309

With the rapid growth of emerging applications like social network analysis, semantic Web analysis and bioinformatics network analysis, a variety of data to be processed continues to witness a quick increase. Effective management and analysis of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing technics from system and application aspects. First, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including cloud computing platform, cloud architecture, cloud database and data storage scheme. Following the MapReduce parallel processing framework, we then introduce MapReduce optimization strategies and applications reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments.

关键词： Big Data Cloud computing Data Management distributed computing

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Trace file comparison with a hierarchical sequence alignment algorithm

Trace file comparison with a hierarchical sequence alignment...

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： Weber, Matthias Brendel, Ronny Brunst, Holger Center for Information Services and High Performance Computing Technische Universität Dresden Dresden Germany

ISBN: (纸本)9780769547015

Performance optimization, especially in the field of HPC, is an integral part of today's software development process. One powerful way of optimizing applications is to analyze their event traces. Yet, the comparison of traces of multiple application runs is cumbersome. The impact of optimizations in the source code or the usage of different compiler flags has to be tracked manually. The challenge is to automatically identify exactly those areas that changed in the large amount of trace data. We propose a novel solution that combines sequence alignment algorithms with call graph analysis to compare and highlight traces event-wise. Our approach is able to automatically detect differences by aligning event traces. Fine-grained execution time differences can be extracted and displayed in performance charts. The results of our implementation are presented and discussed. © 2012 IEEE.

关键词： Software design

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