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DIANA: A Device Abstraction Framework for parallel Computations

DIANA: A Device Abstraction Framework for Parallel Computati...

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2nd international Conference on parallel, distributed, Grid and Cloud Computing for Engineering

作者： Panagiotidis, A. Kauker, D. Frey, S. Ertl, T. Univ Stuttgart Visualizat & Interact Syst Grp Stuttgart Germany

ISBN: (纸本)9781905088423

In this paper we present the distributed memory processing In A Node Abstraction layer (DIANA). DIANA provides a common interface to hide the complexity of managing different application programming interfaces (APIs), software development kits (SDKs), and libraries for different many-core devices. Advantages introduced by using DIANA include easier maintainability and higher flexibility and portability. Through the use of exchangeable plugins, DIANA can support new hardware and computations, passing their functionality along to applications without source changes or rebuilding.

关键词： abstraction layer parallel computation GPGPU modular framework finite element method simulation maintainability

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Experiences using cloud computing for a scientific workflow application

Experiences using cloud computing for a scientific workflow ...

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2nd international Workshop on Scientific Cloud Computing, ScienceCloud'11, Co-located with 20th international ACM symposium on High-Performance parallel and distributed Computing, HPDC 2011

作者： Vöckler, Jens-Sönke Juve, Gideon Deelman, Ewa Rynge, Mats Berriman, Bruce Information Sciences Institute University of Southern California United States Infrared Processing and Analysis Center California Institute of Technology United States

ISBN: (纸本)9781450306997

Clouds are rapidly becoming an important platform for scientific applications. In this paper we describe our experiences running a scientific workflow application in the cloud. The application was developed to process astronomy data released by the Kepler project, a NASA mission to search for Earth-like planets orbiting other stars. This workflow was deployed across multiple clouds using the Pegasus Workflow Management System. The clouds used include several sites within the FutureGrid, NERSC's Magellan cloud, and Amazon EC2. We describe how the application was deployed, evaluate its performance executing in different clouds (based on Nimbus, Eucalyptus, and EC2), and discuss the challenges of deploying and executing workflows in a cloud environment. We also demonstrate how Pegasus was able to support sky computing by executing a single workflow across multiple cloud infrastructures simultaneously. © 2011 ACM.

关键词： Orbits

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Rapid parallel genome indexing with MapReduce

Rapid parallel genome indexing with MapReduce

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2nd international Workshop on MapReduce and Its applications, MapReduce'11, Co-located with 20th international ACM symposium on High-Performance parallel and distributed Computing, HPDC 2011

作者： Menon, Rohith K. Bhat, Goutham P. Schatz, Michael C. Department of Computer Science Stony Brook University United States Simons Center for Quantitative Biology Cold Spring Harbor Laboratory United States

ISBN: (纸本)9781450307000

Sequence alignment is one of the most important applications in computational biology, and is used for such diverse tasks as identifying homologous proteins, analyzing gene expression, mapping variations between individuals, or assembling de novo the genome of organism. Except for trivial cases involving just a small number of short sequences, virtually all other sequence alignment tasks rely on a precomputed index of the sequence to accelerate the alignment. Two of the most important index structures are the suffix array, which consists of the lexicographically sorted list of suffixes of a genome, and the closely related Burrows-Wheeler Transform (BWT), which is a permutation of the genome based on the suffix array. Constructing these structures on large sequences, such as the human genome, requires several hours of serial computation and must be performed for each genome, or genome assembly, to be analyzed. Here we present a novel parallel algorithm for constructing the suffix array and the BWT of a sequence leveraging the unique features of the MapReduce parallel programming model. We demonstrate the performance of the algorithm by greatly accelerating suffix array and BWT construction on five significant genomes using as many as 120 cores leased from the Amazon Elastic Compute Cloud (EC2), reducing the end-to-end runtime from hours to mere minutes. The source code is available under an open source GPL License at: http://***/p/genome-indexing/ © 2011 ACM.

关键词： MapReduce

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A parallel Random Forest classifier for R

A parallel Random Forest classifier for R

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2nd international Workshop on Emerging Computational Methods for the Life Sciences, ECMLS'11, Co-located with 20th international ACM symposium on High-Performance parallel and distributed Computing, HPDC 2011

作者： Mitchell, Lawrence Sloan, Terence M. Mewissen, Muriel Ghazal, Peter Forster, Thorsten EPCC School of Physics and Astronomy University of Edinburgh Edinburgh EH9 3JZ United Kingdom Medical School Division of Pathway Medicine University of Edinburgh 49 Little France Crescent Edinburgh EH16 4SB United Kingdom

ISBN: (纸本)9781450307024

The statistical language R is favoured by many biostaticians for processing microarray data. In recent times, the quantity of data that can be obtained in experiments has risen significantly, making previously fast analyses time consuming, or even not possible at all with the existing software infrastructure. High Performance Computing (HPC) systems offer a solution to these problems, but at the expense of increased complexity for the end user. The Simple parallel R Interface (SPRINT) is a library for R that aims to reduce the complexity of using HPC systems by providing biostatisticians with drop-in parallelized replacements of existing R functions. In this paper we describe the implementation of a parallel version of the Random Forest classifier in the SPRINT library. © Copyright 2011 ACM.

关键词： Data handling

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A parallel input-output system for resolving spatial data challenges: An agent-based model case study

A parallel input-output system for resolving spatial data ch...

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ACM SIGSPATIAL 2nd international Workshop on High Performance and distributed Geographic Information Systems, ACM SIGSPATIAL HPDGIS 2011

作者： Shook, Eric Wang, Shaowen Department of Geography University of Illinois at Urbana-Champaign Urbana IL 61801 United States University of Illinois at Urbana-Champaign Urbana IL 61801 United States

ISBN: (纸本)9781450310406

With recent advances in data collection technologies such as remote sensing and global positioning systems, the amount of spatial data being produced has been increasing at a staggering rate. Simultaneously, a shift is being experienced in computing from single-core to multi-core processors. To effectively utilize the computational power afforded by these new generation of processors for serving data-intensive geospatial applications, parallel computing techniques need to be employed. parallel computing, however, raises new challenges associated with handling the input and output of spatial data in parallel. This paper describes a parallel Input/Output System (PIOS) to address challenges associated with handling large amounts of diverse spatial data. The PIOS is based on a hierarchical structure that uses a scalable file partitioning strategy and combines data and metadata to enable efficient handling of terabyte-scale data sets in parallel. A spatially-explicit agent-based model is developed as a case study. Computational experiments were conducted on a supercomputer supported by the National Science Foundation. PIOS achieved ten times speedup in parallel input/output time, and was demonstrated to efficiently scale to over one thousand processing cores and handle multiple terabytes of data. © 2011 ACM.

关键词： Supercomputers

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Asynchronous peer-to-peer distributed computing for financial applications

Asynchronous peer-to-peer distributed computing for financia...

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25th IEEE international parallel and distributed processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Garcia, Thierry Ming, Chau Nguyen, The Tung El-Baz, Didier Spiteri, Pierre Université de Toulouse INP - ENSEEIHT IRIT 2 Rue Camichel F-31071 Toulouse Cedex France Advanced Solutions Accelerator 199 Rue de l'Oppidum F-34170 Castelnau le Lez France CNRS - LAAS 7 avenue du colonel Roche F-31077 Toulouse France Université de Toulouse UPS INSA INP ISAE France

ISBN: (纸本)9780769543857

This paper deals with the numerical solution of financial applications, more specifically the computation of American and European options derivatives modelled by boundary values problems. In such applications we have to solve large-scale algebraic linear systems. We concentrate on synchronous and asynchronous parallel iterative algorithms carried out on peer-to-peer networks. The properties of the operators arising in the discretized problem ensure the convergence of the parallel iterative synchronous and asynchronous algorithms. Computational experiments performed on peer-to-peer networks are presented and analyzed. © 2011 IEEE.

关键词： Peer to peer networks

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Distribution-Transparency in Runtime Verification

Distribution-Transparency in Runtime Verification

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9th IEEE international symposium on parallel and distributed processing with applications Workshops (ISPAW)/ICASE/SGH/GSDP

作者： Malakuti, Somayeh Aksit, Mehmet Bockisch, Christoph Univ Twente Dept Comp Sci NL-7500 AE Enschede Netherlands

ISBN: (纸本)9780769544298

Run-time verification checks whether the active execution traces of an application fulfills its specified behavior and is especially applicable when one needs to consider the actual execution context in the verification. In today's practices, software is more and more distributed over multiple processes, possibly running at different locations. This is supported by middleware that, to some extend, allows implementing applications in a distribution-transparent way. We define four requirements for the effective verification of such software: 1) abstraction of less-critical details of software behavior due to the complexity of software behavior, 2) distribution-transparent specification of software behavior, as software is also implemented in such a way, 3) end-to-end verification of behavior, and 4) automatic generation of verification modules for arbitrary process and distribution structures. The existing runtime verification systems fall in short to fulfill these requirements, therefore their applicability is limited. We develop the E-Chaser runtime verification system to facilitate the verification of distributed software by addressing these requirements. This paper explains the approach and the prototype implementation of E-Chaser based on the Java-RMI technology.

关键词： runtime verification distributed software distribution transparency end-to-end properties

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processing Smart Meter Data Streams in the Cloud

Processing Smart Meter Data Streams in the Cloud

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2nd IEEE PES international Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe)

作者： Lohrmann, Bjoern Kao, Odej Tech Univ Berlin Dept Complex & Distributed IT Syst D-10587 Berlin Germany

ISBN: (纸本)9781457714214

The ongoing integration of renewable energy sources is likely to increase the fluctuations in the ratio of produced and consumed power. Several types of Demand Response (DR) programs have been proposed to deal with the increasing volatility of power production and consumption. Many of these, such as Real Time Pricing (RTP), require intensive monitoring of the consumers' power consumption. This is one of the reasons why smart meters are currently being deployed by many utilities. Smart meters offer a two-way communication channel between the consumer and the utility, thus extending the power grid by a complex, large scale communication infrastructure. With the growing deployment of smart meters, power utilities face the problem of processing and storing the incoming data to support latency-sensitive applications such as Real-Time Pricing. In this paper we present a set of requirements for a utility-side IT infrastructure to process incoming smart meter data streams. We propose the use of Infrastructure-as-a-Service clouds and frameworks for parallel stream processing in clouds to address these requirements. Based on the Nephele cloud computing framework we demonstrate the practicality of this approach based on experiments with one million simulated smart meters and a prototypical Real-Time Pricing application deployed in our own private cloud.

关键词： Smart Metering Real-Time Pricing Cloud Computing Stream processing

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parallel biomedical image processing with GPGPUs in cancer research

Parallel biomedical image processing with GPGPUs in cancer r...

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3rd IEEE international symposium on Logistics and Industrial Informatics, LIndI 2011

作者： Reményi, Attila Szénási, Sándor Bándi, István Vámossy, Zoltán Valcz, Gábor Bogdanov, Pál Sergyán, Szabolcs Kozlovszky, Miklos Óbuda University John von Neumann Faculty of Informatics Budapest Hungary Semmelweiss University 2nd Department of Internal Medicine Budapest Hungary MTA SZTAKI/Laboratory of Parallel and Distributed Computing Budapest Hungary

ISBN: (纸本)9781457718410

The main aim of this work is to show, how GPGPUs can facilitate certain type of image processing methods. The software used in this paper is used to detect special tissue part, the nuclei on (HE - hematoxilin eosin) stained colon tissue sample images. Since pathologists are working with large number of high resolution images - thus require significant storage space -, one feasible way to achieve reasonable processing time is the usage of GPGPUs. The CUDA software development kit was used to develop processing algorithms to NVIDIA type GPUs. Our work focuses on how to achieve better performance with coalesced global memory access when working with three-channel RGB tissue images, and how to use the on-die shared memory efficiently. © 2011 IEEE.

关键词： Image processing

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Comparison of parallel programming models for multicore architectures

Comparison of parallel programming models for multicore arch...

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25th IEEE international parallel and distributed processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Deepak, Shekhar T.C. Varaganti, Kiran Suresh, Rahul Garg, Rahul Ramamoorthy, Ramalingam Frontier Research Group Samsung India Software Operations Pvt. Ltd. Bagmane Tridib 65/2 Bagmane Tech Park Byrasandra Bengaluru - 560093 India

ISBN: (纸本)9780769543857

Multicore computing platforms have emerged as the most common computing platform to overcome challenges stemming from high power densities and thermal hot spots in conventional microprocessors. However, providing multiple cores does not directly translate into increased performance or better energy efficiency for most applications. The burden is placed on developers and tools to find and exploit parallelism and eventually utilize all of the available computing resources. Since multicore applications are more complex than single core applications, the software development tools play a crucial role to help programmers create high performance and correct software. In this paper we compare the most popular programming models OpenMP, GCD and Pthreads by applying these models to parallelize face detection and automatic speech recognition applications. © 2011 IEEE.

关键词： Speech recognition

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