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An insightful program performance tuning chain for GPU computing

An insightful program performance tuning chain for GPU compu...

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12th international conference on algorithms and architectures for parallel processing, ICA3PP 2012

作者： Jia, Haipeng Zhang, Yunquan Long, Guoping Yan, Shengen Lab. of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences China College of Information Science and Engineering Ocean University of China China State Key Laboratory of Computing Science Chinese Academy of Sciences China Graduate University of Chinese Academy of Sciences China

ISBN: (纸本)9783642330773

It is challenging to optimize GPU kernels because this progress requires deep technical knowledge of the underlying hardware. Modern GPU architectures are becoming more and more diversified, which further exacerbates the already difficult problem of performance optimization. this paper presents an insightful performance tuning chain for GPUs. the goal is to help non-expert programmers with limited knowledge of GPU architectures implement high performance GPU kernels directly. We achieve it by providing performance information to identify GPU program performance bottlenecks and decide which optimization methods should be adopted, so as to facilitate the best match between algorithm features and underlying hardware characteristics. To demonstrate the usage of tuning chain, we optimize three representative GPU kernels with different compute intensity: Matrix Transpose, Laplace Transform and Integral on both NVIDIA and AMD GPUs. Experimental results demonstrate that under the guidance of our tuning chain, performance of those kernels achieves 7.8~42.4 times speedup compared to their naïve implementations on both NVIDIA and AMD GPU platforms. © 2012 Springer-Verlag.

关键词： Chains

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A task allocation algorithm for logic optimization parallel scheduling

A task allocation algorithm for logic optimization parallel ...

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international conference on Natural Computation (ICNC)

作者： Li Chen Jianlin Qiu Xiang Gu Yang Pan Yanyun Chen Nantong University Nantong CN College of Computer Science and Technology Nantong University China

Based on the analysis of logic optimization and task parallel allocation algorithm, combining with logic optimization features, we propose a new parallel processing algorithm for logic optimization scheduling and allocation. Considering the correlation between minimizers of each logic function, assign the logic associated with high correlation firstly, then with the size of the matrix. through the studies of furnished example, the algorithm can be well in completing the logic scheduling.

关键词： Optimization Logic functions Algorithm design and analysis parallel processing Educational institutions Heuristic algorithms Computers

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Bulgarian X-language parallel Corpus 8

Bulgarian X-language Parallel Corpus

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8th international conference on Language Resources and Evaluation (LREC)

作者： Koeva, Svetla Stoyanova, Ivelina Dekova, Rositsa Rizov, Borislav Genov, Angel Bulgarian Acad Sci Inst Bulgarian Dept Computat Linguist BU-1113 Sofia Bulgaria

ISBN: (纸本)9782951740877

the paper presents the methodology and the outcome of the compilation and the processing of the Bulgarian X-language parallel Corpus (Bul-X-Cor) which was integrated as part of the Bulgarian National Corpus (BulNC). We focus on building representative parallel corpora which include a diversity of domains and genres, reflect the relations between Bulgarian and other languages and are consistent in terms of compilation methodology, text representation, metadata description and annotation conventions. the approaches implemented in the construction of Bul-X-Cor include using readily available text collections on the web, manual compilation (by means of Internet browsing) and preferably automatic compilation (by means of web crawling - general and focused). Certain levels of annotation applied to Bul-X-Cor are taken as obligatory (sentence segmentation and sentence alignment), while others depend on the availability of tools for a particular language (morpho-syntactic tagging, lemmatisation, syntactic parsing, named entity recognition, word sense disambiguation, etc.) or for a particular task (word and clause alignment). To achieve uniformity of the annotation we have either annotated raw data from scratch or transformed the already existing annotation to follow the conventions accepted for BulNC. Finally, actual uses of the corpora are presented and conclusions are drawn with respect to future work.

关键词： parallel corpora corpora construction annotation

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ATLIS: Identifying Locational Information in Text Automatically 8

ATLIS: Identifying Locational Information in Text Automatica...

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8th international conference on Language Resources and Evaluation (LREC)

作者： Vogel, John Verhagen, Marc Pustejovsky, James Brandeis Univ Dept Comp Sci Waltham MA USA

ISBN: (纸本)9782951740877

ATLIS (short for "ATLIS Tags Locations in Strings") is a tool being developed using a maximum-entropy machine learning model for automatically identifying information relating to spatial and locational information in natural language text. It is being developed in parallel with the ISO-Space standard for annotation of spatial information (Pustejovsky, Moszkowicz & Verhagen 2011). the goal of ATLIS is to be able to take in a document as raw text and mark it up with ISO-Space annotation data, so that another program could use the information in a standardized format to reason about the semantics of the spatial information in the document. the tool (as well as ISO-Space itself) is still in the early stages of development. At present it implements a subset of the proposed ISO-Space annotation standard: it identifies expressions that refer to specific places, as well as identifying prepositional constructions that indicate a spatial relationship between two objects. In this paper, the structure of the ATLIS tool is presented, along with preliminary evaluations of its performance.

关键词： ISO-Space location tagging spatial processing

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Accelerating the dynamic programming for the optimal polygon triangulation on the GPU

Accelerating the dynamic programming for the optimal polygon...

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12th international conference on algorithms and architectures for parallel processing, ICA3PP 2012

作者： Nishida, Kazufumi Nakano, Koji Ito, Yasuaki Department of Information Engineering Hiroshima University Kagamiyama 1-4-1 Higashi Hiroshima 739-8527 Japan

ISBN: (纸本)9783642330773

Modern GPUs (Graphics processing Units) can be used for general purpose parallel computation. Users can develop parallel programs running on GPUs using programming architecture called CUDA (Compute Unified Device Architecture). the optimal polygon triangulation problem for a convex polygon is an optimization problem to find a triangulation with minimum total weight. It is known that this problem can be solved using the dynamic programming technique in O(n 3) time using a work space of size O(n 2). the main contribution of this paper is to present an efficient parallel implementation of this O(n 3)-time algorithm on the GPU. In our implementation, we have used two new ideas to accelerate the dynamic programming. the first idea (granularity adjustment) is to partition the dynamic programming algorithm into many sequential kernel calls of CUDA, and to select the best size and number of blocks and threads for each kernel call. the second idea (sliding and mirroring arrangements) is to arrange the temporary data for coalesced access of the global memory in the GPU to minimize the memory access overhead. Our implementation using these two ideas solves the optimal polygon triangulation problem for a convex 16384-gon in 69.1 seconds on the NVIDIA GeForce GTX 580, while a conventional CPU implementation runs in 17105.5 seconds. thus, our GPU implementation attains a speedup factor of 247.5. © 2012 Springer-Verlag.

关键词： Graphics processing unit

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Residual belief propagation for topic modeling

Residual belief propagation for topic modeling

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8th international conference on Advanced Data Mining and Applications, ADMA 2012

作者： Zeng, Jia Cao, Xiao-Qin Liu, Zhi-Qiang School of Computer Science and Technology Soochow University Suzhou 215006 China Shanghai Key Laboratory of Intelligent Information Processing China School of Creative Media City University of Hong Kong Tat Chee Ave 83 Hong Kong Hong Kong

ISBN: (纸本)9783642355264

Fast convergence speed is a desired property for training topic models such as latent Dirichlet allocation (LDA), especially in online and parallel topic modeling algorithms for big data sets. In this paper, we develop a novel and easy-to-implement residual belief propagation (RBP) algorithm to accelerate the convergence speed for training LDA. the proposed RBP uses an informed scheduling scheme for asynchronous message passing, which passes fast convergent messages with a higher priority to influence those slow convergent messages at each learning iteration. Extensive empirical studies confirm that RBP significantly reduces the training time until convergence while achieves a much lower predictive perplexity than several state-of-the-art training algorithms for LDA, including variational Bayes (VB), collapsed Gibbs sampling (GS), loopy belief propagation (BP), and residual VB (RVB). © Springer-Verlag 2012.

关键词： Belief propagation

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parallel texts extraction from multimodal comparable corpora

Parallel texts extraction from multimodal comparable corpora

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8th international conference on Natural Language processing, JapTAL 2012

作者： Afli, Haithem Barrault, Loïc Schwenk, Holger Universit du Maine Avenue Olivier Messiaen F-72085 Le Mans France

ISBN: (纸本)9783642339820

Statistical machine translation (SMT) systems depend on the availability of domain-specific bilingual parallel text. However parallel corpora are a limited resource and they are often not available for some domains or language pairs. We analyze the feasibility of extracting parallel sentences from multimodal comparable corpora. this work extends the use of comparable corpora by using audio sources instead of texts on the source side. the audio is transcribed by an automatic speech recognition system and translated with a baseline SMT system. We then use information retrieval in a large text corpus in the target language to extract parallel sentences. We have performed a series of experiments on data of the IWSLT'11 speech translation task that shows the feasibility of our approach. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Computer aided language translation

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parallel Software Architecture for Experimental Workflows in Computational Biology on Clouds

Parallel Software Architecture for Experimental Workflows in...

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9th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Hodgkinson, Luqman Rosa, Javier Brewer, Eric A. Univ Calif Berkeley Div Comp Sci Berkeley CA 94720 USA

ISBN: (纸本)9783642314995;9783642315008

Cloud computing opens new possibilities for computational biologists. Given the pay-as-you-go model and the commodity hardware base, new tools for extensive parallelism are needed to make experimentation in the cloud an attractive option. In this paper, we present Easy Prot, a parallel message-passing architecture designed for developing experimental workflows in computational biology while harnessing the power of cloud resources. the system exploits parallelism in two ways: by multithreading modular components on virtual machines while respecting data dependencies and by allowing expansion across multiple virtual machines. Components of the system, called elements, are easily configured for efficient modification and testing of workflows during ever-changing experimentation. though Easy Prot, as an abstract cloud programming model, can be extended beyond computational biology, current development brings cloud computing to experimenters in this important discipline who are facing unprecedented data-processing challenges, with a type system designed for proteomics, interactomics and comparative genomics data, and a suite of elements that perform useful analysis tasks on biological data using cloud resources. Availability: Easy Prot is available as a public abstract machine image (AMI) on Amazon EC2 cloud service, with an open source license, registered with manifest easyprot-ami/***.

关键词： parallel architectures scientific workflows cloud computing

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parallel Computation of Bivariate Polynomial Resultants on Graphics processing Units

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10th Nordic international conference on Applied parallel Computing - State of the Art in Scientific and parallel Computing (PARA)

作者： Stussak, Christian Schenzel, Peter Univ Halle Wittenberg Inst Comp Sci D-06120 Halle Saale Germany

ISBN: (纸本)9783642281440

Polynomial resultants are of fundamental importance in symbolic computations, especially in the field of quantifier elimination. In this paper we show how to compute the resultant res(y) (f, g) of two bivariate polynomials f, g is an element of Z[x, y] on a CUDA-capable graphics processing unit (GPU). We achieve parallelization by mapping the bivariate integer resultant onto a sufficiently large number of univariate resultants over finite fields, which are then lifted back to the original domain. We point out, that the commonly proposed special treatment for so called unlucky homomorphisms is unnecessary and how this simplifies the parallel resultant algorithm. All steps of the algorithm are executed entirely on the GPU. Data transfer is only used for the input polynomials and the resultant. Experimental results show the considerable speedup of our implementation compared to host-based algorithms.

关键词： polynomial resultants modular algorithm parallelization GPU CUDA graphics hardware symbolic computation

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Modeling a Million-Node Dragonfly Network using Massively parallel Discrete-Event Simulation

Modeling a Million-Node Dragonfly Network using Massively Pa...

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25th ACM/IEEE international conference for High Performance Computing, Networking, Storage and Analysis (SC)

作者： Mubarak, Misbah Carothers, Christopher D. Ross, Robert Carns, Philip Rensselaer Polytech Inst Dept Comp Sci 110 8th St Troy NY 12180 USA Argonne Natl Lab Div Math & Comp Sci Argonne IL 60439 USA

ISBN: (纸本)9780769549569;9781467362184

A low-latency and low-diameter interconnection network will be an important component of future exascale architectures. the dragonfly network topology, a two-level directly connected network, is a candidate for exascale architectures because of its low diameter and reduced latency. To date, small-scale simulations with a few thousand nodes have been carried out to examine the dragonfly topology. However, future exascale machines will have millions of cores and up to 1 million nodes. In this paper, we focus on the modeling and simulation of large-scale dragonfly networks using the Rensselaer Optimistic Simulation System (ROSS). We validate the results of our model against the cycle-accurate simulator "booksim". We also compare the performance of booksim and ROSS for the dragonfly network model at modest scales. We demonstrate the performance of ROSS on both the Blue Gene/P and Blue Gene/Q systems on a dragonfly model with up to 50 million nodes, showing a peak event rate of 1.33 billion events/second and a total of 872 billion committed events. the dragonfly network model for million-node configurations strongly scales when going from 1,024 to 65,536 MPI tasks on IBM Blue Gene/P and IBM Blue Gene/Q systems. We also explore a variety of ROSS tuning parameters to get optimal results with the dragonfly network model.

关键词： ROSS dragonfly parallel discrete event simulation routing

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