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parallel track reconstruction in CMS using the cellular automaton approach

Parallel track reconstruction in CMS using the cellular auto...

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20th international conference on Computing in High Energy and Nuclear Physics (CHEP)

作者： Funke, D. Hauth, T. Innocente, V. Quast, G. Sanders, P. Schieferdecker, D. Karlsruhe Inst Technol D-76021 Karlsruhe Germany CERN Geneva Switzerland

the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is a general-purpose particle detector and comprises the largest silicon-based tracking system built to date with 75 million individual readout channels. the precise reconstruction of particle tracks from this tremendous amount of input channels is a compute-intensive task. the foreseen LHC beam parameters for the next data taking period, starting in 2015, will result in an increase in the number of simultaneous proton-proton interactions and hence the number of particle tracks per event. Due to the stagnating clock frequencies of individual CPU cores, new approaches to particle track reconstruction need to be evaluated in order to cope with this computational challenge. Track finding methods that are based on cellular automata (CA) off er a fast and parallelizable alternative to the well-established Kalman filter-based algorithms. We present a new cellular automaton based track reconstruction, which copes with the complex detector geometry of CMS. We detail the specific design choices made to allow for a high-performance computation on GPU and CPU devices using the OpenCL framework. We conclude by evaluating the physics performance, as well as the computational properties of our implementation on various hardware platforms and show that a significant speedup can be attained by using GPU architectures while achieving a reasonable physics performance at the same time.

关键词： Cellular automata

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Adaptive Load Balancing for Massively parallel Multi-Level Monte Carlo Solvers

Adaptive Load Balancing for Massively Parallel Multi-Level M...

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Sukys, Jonas ETH Zurich Switzerland

ISBN: (纸本)9783642552243

the Multi-Level Monte Carlo algorithm was shown to be a robust solver for uncertainty quantification in the solutions of multidimensional systems of stochastic conservation laws. For random fluxes or random initial data with large variances, the time step of the explicit time stepping scheme becomes random due to the random CFL stability restriction. Such sample path dependent complexity of the underlying deterministic solver renders our static load balancing of the MLMC algorithm very inefficient. We introduce an adaptive load balancing procedure based on two key ingredients: (1) pre-computation of the time step size for each draw of random inputs (realization), (2) distribution of the samples using the greedy algorithm to "workers" with heterogeneous speeds of execution. Numerical experiments showing strong scaling are presented.

关键词： Uncertainty quantification Conservation laws Multi-level Monte Carlo FVM Load balancing Greedy algorithms Linear scaling

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parallel K-Medoids clustering algorithm based on Hadoop

Parallel K-Medoids clustering algorithm based on Hadoop

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IEEE international conference on Software Engineering and Service Sciences (ICSESS)

作者： Yaobin Jiang Jiongmin Zhang Department of Computer Science and Technology East China Normal University China

ISBN: (纸本)9781479932801

the K-Medoids clustering algorithm solves the problem of the K-Means algorithm on processing the outlier samples, but it is not be able to process big-data because of the time complexity[1]. MapReduce is a parallel programming model for processing big-data, and has been implemented in Hadoop. In order to break the big-data limits, the parallel K-Medoids algorithm HK-Medoids based on Hadoop was proposed. Every submitted job has many iterative MapReduce procedures: In the map phase, each sample was assigned to one cluster whose center is the most similar with the sample; in the combine phase, an intermediate center for each cluster was calculated; and in the reduce phase, the new center was calculated. the iterator stops when the new center is similar to the old one. the experimental results showed that HK-Medoids algorithm has a good clustering result and linear speedup for big-data.

关键词： Clustering algorithms Algorithm design and analysis Partitioning algorithms Programming Computational modeling Indexes Educational institutions

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Efficient and scalable CGRA-based implementation of Column-wise Givens Rotation

Efficient and scalable CGRA-based implementation of Column-w...

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international conference on Application Specific Systems (ASAP), architectures and Processors

作者： Zoltán Endre Rákossy Farhad Merchant Axel Acosta-Aponte S.K. Nandy Anupam Chattopadhyay Institute for Communication Technologies and Embedded Systems (ICE) RWTH University Aachen Germany CADLab Indian Institute of Science Bangalore India

Givens Rotation is a key computation-intensive block in embedded wireless applications. In order to achieve an efficient mapping which smoothly scales to the underlying architecture, we propose two new Column-based Givens Rotation algorithms, derived from traditional Fast Givens and Square-root and Division Free Givens algorithms. these algorithms allow annihilation of multiple elements in a column of the input matrix simultaneously, without a dependency bottle-neck allowing increased parallelism, resource sharing and scalability. the ease of mapping and scalability has been tested on a layered coarse-grained reconfigurable architecture reaching close to optimal results for highly parallel architectures.

关键词： parallel processing Scalability Arrays Kernel Algorithm design and analysis Complexity theory

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Geo-Data Fusion Integrator for Object-Oriented Spatiotemporal OLAP Cubes 5

Geo-Data Fusion Integrator for Object-Oriented Spatiotempora...

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5th international conference on Computing for Geospatial Research and Application (COM.Geo)

作者： Ngan, Chun-Kit Penn State Univ Engn & Informat Sci Div Great Valley Sch Grad Profess Studies Malvern PA 19355 USA

ISBN: (纸本)9781479943210

We first propose a Geo-Data Fusion Integrator. Specifically, we design a sequential-parallel-modularized (SPM) approach to integrate different datasets into a geo-data object, i.e., a multidimensional unified-OLAP cube, archived in a geo-data warehouse for decision-making analysis. Different datasets of geo-data objects are processed in parallel across multi-stages in sequence, and then integrated into a well-defined OLAP cube. Each SPM component is a self-contained, modularized unit that processes the data. the technical merits of this SPM approach include fast manipulations, error minimization, and easy maintenance. Second, to create a unified geo-data object, we extend the object-oriented spatial-temporal data model as a multidimensional OLAP cube, i.e., a Star-based Geo-Object-Oriented SpatiotEmporal (S-GOOSE) data model, which combines the advantages of both OLTP and OLAP approaches. this S-GOOSE data model is an object-relational-based cube that enables military operators to analyze unified geo-data objects from multiple dimensions, such as time, space, and location, to help them make a better decision on paths.

关键词： data processing data integration data modeling OLAP cube

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Performance Analysis of parallel Sorting algorithms Using MPI

Performance Analysis of Parallel Sorting Algorithms Using MP...

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Frontiers of Information Technology (FIT)

作者： Muhammad Hanif Durad Muhammad Naveed Akhtar Irfan-ul-Haq

Sorting is one of the classic problems of data processing and many practical applications require implementation of parallel sorting algorithms. Only a few algorithms have been implemented using MPI, in this paper a few additional parallel sorting algorithms have been implemented using MPI. A unified performance analysis of all these algorithms has been presented using two different architectures. On basis of experimental results obtained some guidelines has been suggested for the selection of proper algorithms.

关键词： Sorting Algorithm design and analysis Clustering algorithms Market research Hypercubes Performance analysis

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A Spatiotemporal Interpolation Method Using Radial Basis Functions for Geospatiotemporal Big Data 5

A Spatiotemporal Interpolation Method Using Radial Basis Fun...

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5th international conference on Computing for Geospatial Research and Application (COM.Geo)

作者： Losser, Travis Li, Lixin Piltner, Reinhard Georgia So Univ Dept Comp Sci Statesboro GA 30460 USA Georgia So Univ Dept Math Sci Statesboro GA 30460 USA

ISBN: (纸本)9781479943210

this research designs and implements the Radial Basis Function (RBF) spatiotemporal interpolation method to assess the trend of daily PM(2.)5 concentration for the contiguous United States over the year of 2009, at both the census block group level and county level. this research also compares the performance of the RBF spatiotemporal interpolation with the Inverse Distance Weighting (IDW) spatiotemporal interpolation. Traditionally, when handling spatiotemporal interpolation, researchers tend to treat space and time separately and reduce the spatiotemporal interpolation problems to a sequence of snapshots of spatial interpolations. In this paper, PM(2.)5 data interpolation is conducted in the continuous space-time domain by integrating space and time simultaneously under the assumption that spatial and temporal dimensions are equally important when interpolating a continuous changing phenomenon in the space-time domain. the RBF-based spatiotemporal interpolation methods are evaluated by leave-one-out cross validation. More importantly, this study explores computational issues (computer processing speed) faced during implementation of spatiotemporal interpolation for huge data sets. parallel programming techniques and an advanced data structure named k-d tree are adapted in this paper to address the computational challenges.

关键词： Inverse Distance Weighting Radial Basis Functions fine particulate matter PM2.5 geospatiotemporal big data k-d tree leave-one-out cross validation parallel programming spatiotemporal interpolation

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parallelizing sparse recovery algorithms: A stochastic approach

Parallelizing sparse recovery algorithms: A stochastic appro...

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international conference on Digital Signal processing (DSP)

作者： Achal Shah Angshul Majumdar Indian Institute of Technology Guwahati Indraprastha Institute of Information Technology Delhi

this work proposes a novel technique for accelerating sparse recovery algorithms on multi-core shared memory architectures. All prior works attempt to speed-up algorithms by leveraging the speed-ups in matrix-vector products offered by the GPU. A major limitation of these studies is that in most signal processing applications, the operators are not available as explicit matrices but as implicit fast operators. In such a practical scenario, the prior techniques fail to speed up the sparse recovery algorithms. Our work is based on the principles of stochastic gradient descent. the main sequential bottleneck of sparse recovery methods is a gradient descent step. Instead of computing the full gradient, we compute multiple stochastic gradients in parallel cores; the full gradient is estimated by averaging these stochastic gradients. the other step of sparse recovery algorithms is a shrinkage operation which is inherently parallel. Our proposed method has been compared with existing sequential algorithms. We find that our method is as accurate as the sequential version but is significantly faster - the larger the size of the problem, the faster is our method.

关键词： Signal processing algorithms Sparse matrices Acceleration Vectors Graphics processing units Digital signal processing

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A GPU-based Computer-assisted Microscopy System for Assessing the Importance of Different Families of Histological Characteristics in Cancer Diagnosis

A GPU-based Computer-assisted Microscopy System for Assessin...

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5th international conference on Graphic and Image processing (ICGIP)

作者： Glotsos, Dimitris Kostopoulos, Spiros Sidiropoulos, Konstantinos Ravazoula, Panagiota Kalatzis, Ioannis Asvestas, Pantelis Cavouras, Dionisis Technol Educ Inst Athens Dept Biomed Technol Engn Med Image & Signal Proc Lab Athens 12210 Greece Brunel Univ West London Sch Engn & Design Uxbridge UB8 3PH Middx England Hosp Univ Patras Dept Pathol Patras GR-26504 Greece

ISBN: (纸本)9781628410013

In this study a Computer-Aided Microscopy (CAM) system is proposed for investigating the importance of the histological criteria involved in diagnosing of cancers in microscopy in order to suggest the more informative features for discriminating low from high-grade brain tumours. Four families of criteria have been examined, involving the grey-level variations (i.e. texture), the morphology (i.e. roundness), the architecture (i.e. cellularity) and the overall tumour qualities (expert's ordinal scale). the proposed CAM system was constructed using a modified Seeded Region Growing algorithm for image segmentation, and the Probabilistic Neural Network classifier for image classification. the implementation was designed on a commercial Graphics processing Unit card using parallel programming. the system's performance using textural, morphological, architectural and ordinal information was 90.8%, 87.0%, 81.2% and 88.9% respectively. Results indicate that nuclei texture is the most important family of features regarding the degree of malignancy, and, thus, may guide more accurate predictions for discriminating low from high grade gliomas. Considering that nuclei texture is almost impractical to be encoded by visual observation, the need to incorporate computer-aided diagnostic tools as second opinion in daily clinical practice of diagnosing rare brain tumours may be justified.

关键词： Computer-assisted microscopy cancer Seeded Region Growing Graphics processing Unit Probabilistic Neural Network brain tumours breast tumours

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Bidirectional DC-DC Converter Using Modular Marx Power Switches and Series/parallel Inductor for High-Voltage Applications

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5th IFIP WG 5.5/SOCOLNET Doctoral conference on Computing, Electrical and Industrial Systems, DoCEIS 2014

作者： Luís, Ricardo Silva, J.Fernando A. Quadrado, José C. Pinto, Sónia Ferreira de Mesquita e Sousa, Duarte Instituto Superior de Engenharia de Lisboa R. Conselheiro Emídio Navarro 1959-007 Lisboa Portugal Instituto Superior Técnico Instituto Superior Técnico INESC-id DEEC AC Energia Av. Rovisco Pais 1049-001 Lisboa Portugal

ISBN: (纸本)9783642547331

this paper presents the modelling and the numerical simulation results of a bidirectional DC-DC converter using modular Marx power electronic switches to be applicable in high-voltage converters. To achieve ample voltage ratio between high-voltage and low-voltage sides, the proposed DC-DC converter uses also a power electronic circuit, in the low-voltage converter side, that changes the connection between three inductors, as a series or parallel connection, to aid the energy transfer to the inductors. © IFIP international Federation for Information processing 2014.

关键词： DC-DC converters

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