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Sparse Matrix-Vector Multiplication: A Data Mapping-Based Architecture

Sparse Matrix-Vector Multiplication: A Data Mapping-Based Ar...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Ahmad Mansour Jürgen Götze Wei-Chun Hsu Shanq-Jang Ruan Information Processing Lab TU Dortmund Dortmund Germany Microsystems Lab Low Power Systems Design Group National Taiwan University of Science and Technology Taipei Taiwan

the performance of the sparse matrix-vector multiplication (SMVM) on a parallel system is strongly affected by the distribution of data among its components. Two costs arise as a result of the used data mapping method: arithmetic and communication. the communication cost often dominates the arithmetic cost, and the gap between these costs tends to increase. therefore, finding a mapping method that reduces the communication cost is of high importance. On the other hand, the load distribution among the processing units must not be sacrificed. In this paper, a data mapping method is proposed for SMVM on Network-on-Chip which achieves balanced working load and reduces the communication cost. Afterwards, an FPGA-based architecture is introduced which is designed to fit with the proposed data mapping method.

关键词： Sparse matrices Computer architecture Finite element analysis Program processors Routing distributed databases Electronic mail

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Generating classified parallel unit tests

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8th international conference on Tests and Proofs, TAP 2014, Held as Part of the Software technologies: applications and Foundations, STAF 2014

作者： Jannesari, Ali Koprowski, Nico Schimmel, Jochen Wolf, Felix German Research School for Simulation Sciences Aachen Germany RWTH Aachen University Aachen Germany Germany

ISBN: (纸本)9783319090986

Automatic generation of parallel unit tests is an efficient and systematic way of identifying data races inside a program. In order to be effective parallel unit tests have to be analysed by race detectors. However, each race detector is suitable for different kinds of race conditions. this leaves the question which race detectors to execute on which unit tests. this paper presents an approach to generate classified parallel unit tests: A class indicates the suitability for race detectors considering low-level race conditions, high-level atomicity violations or race conditions on correlated variables. We introduce a hybrid approach for detecting endangered high-level atomic regions inside the program under test. According to these findings the approach classifies generated unit tests as low-level, atomic high-level or correlated high-level. Our evaluation results confirmed the effectiveness of this approach. We were able to correctly classify 83% of all generated unit tests. © 2014 Springer international Publishing Switzerland.

关键词： Software testing

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A Novel Density Based Clustering Algorithm and its parallelization

A Novel Density Based Clustering Algorithm and its Paralleli...

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Xiaokang Li Binbin Yu Yinghua Zhou Guangzhong Sun School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

K-Means, a simple but effective clustering algorithm, is widely used in data mining, machine learning and computer vision community. K-Means algorithm consists of initialization of cluster centers and iteration. the initial cluster centers have a great impact on cluster result and algorithm efficiency. More appropriate initial centers of k-Means can get closer to the optimum solution, and even much quicker convergence. In this paper, we propose a novel clustering algorithm, Kmms, which is the abbreviation of k-Means and Mean Shift. It is a density based algorithm. Experiments show our algorithm not only costs less initialization time compared with other density based algorithms, but also achieves better clustering quality and higher efficiency. And compared with the popular k-Means++ algorithm, our method gets comparable accuracy, mostly even better. Furthermore, we parallelize Kmms algorithm based on OPenMP from both initialization and iteration step and prove the convergence of the algorithm.

关键词： distributed computing

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8th international conference on Terotechnology

8th International Conference on Terotechnology

引用

8th international conference on Terotechnology

ISBN: (纸本)9783037859803

the proceedings contain 26 papers. the special focus in this conference is on Terotechnology. the topics include: the material properties of different zones of joints welded using a laser;tribological properties of diamond-like carbon coatings;quanitative analysis of the polymer/metal powder magentic composites compacts structure;the average friction coefficient of laser textured surfaces of silicon carbide identified by RSM methodology;evaluation of the state for the material of the live steam superheater pipe coils of V degree;fatigue strength of ductile iron in ultra-high cycle regime;influence of laser surface texturing on scuffing resistance of sliding pairs;contour error of the 3-DoF hydraulic translational parallel manipulator;the impact of the power plant unit start-up scheme on the pollution load;impact of the parameters of laser-vibration treatment on the roughness of aluminium melts;research of the elastic properties of bellows made in SLS technology;the centrifugal pump with the impeller supported in sealing clearances;enhancing safety and security of networked FPGA-based embedded systems;laser texturing, spark erosion and sanding of the surfaces and their practical applications in heat exchange devices;the influence of electrospark and laser treatment upon corrosive resistance of carbon steel;laser cold ablation as a cutting edge method of forming silicon wafers used in solar cells;laser technologies in Microsystems;modelling of the mechanical state of a diamond particle in the metallic matrix;application the 3d image analysis techniques for assessment the quality of material surface layer before and after laser treatment;modeling of errors counting system for PCB soldered in the wave soldering technology;the optimization of the technological process with the fuzzy regression;factorial approach to assessment of GPU computational efficiency in surrogate models and on the possibility of the estimation of the depth of a keyhole formed during laser weldings

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TOUGH2-PETSc: A parallel Solver for TOUGH2

TOUGH2-PETSc: A Parallel Solver for TOUGH2

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Daniel Hathorn Yushu Wu Zizhong Chen Colorado School of Mines Golden CO USA University of California Riverside CA USA

TOUGH2 is a general-purpose numerical simulation program for multi-dimensional, multiphase, multicomponent fluid flows, heat transfer and contaminant transport in porous and fractured media. It has been used worldwide for geothermal reservoir engineering, nuclear waste isolation, environmental assessment and remediation, and modeling flow and transport in variably saturated media. TOUGH2 is very computationally intense, and the accuracy and scope of the simulation is limited by the amount of processing power available on a single computer. this makes it an ideal canadate for parallel computing, as more CPU power and memory is available. Furthermore, TOUGH2's main computational unit is a linear equation solver. In parallel computing, a lot of effort has been spent to develop highly efficient parallel linear equation solvers. In this paper, we present TOUGH2-PETSc, a parallel implementation of TOUGH2 that uses PETSc to solve the linear systems in TOUGH2. PETSc is a library of high-performance linear and non-linear equation solvers that has been throughly tested at scale. Based on TOUGH2 and PETSc, TOUGH2-PETSc gives TOUGH2 users the potential to perform larger scale and higher resolution simulations. Experimental results demonstrate that the parallel TOUGH2-PETSc shows improved performance over the sequential version.

关键词： Mathematical model Water heating Earth Observing System Algorithms Sparse matrices Convergence Reservoirs

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Implementation of P systems by using big data technologies

Implementation of P systems by using big data technologies

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14th international conference on Membrane computing, CMC 2013

作者： Ciobanu, Alex Ipate, Florentin Department of Computer Science Faculty of Mathematics and Computer Science University of Pitesti Str. Targu din Vale 1 110040 Pitesti Romania Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Str. Academiei nr.14 sector 1 Bucharest Romania

ISBN: (纸本)9783642542381

Due to their inherent parallel and non-deterministic nature, P system implementations require vast computing and storage resources. this significantly limits their applications, even more so when the calculation of all possible evolutions of the P system is required. this article exposes the scalability possibilities available with the Big Data ecosystem for P systems implementations, using Map Reduce parallelism to build the P system computation tree. the Hadoop based implementation is then used for generating test suites for cell like P systems, in particular for context-dependent rule coverage testing. Our preliminary evaluations on a benchmark of automatically generated P systems confirm that the proposed approach scales well. © 2014 Springer-Verlag Berlin Heidelberg.

关键词： Big data

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Advanced architectures distributed systems for the implementation of neural networks

Advanced architectures distributed systems for the implement...

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international conference on Emerging eLearning technologies and applications (ICETA)

作者： M. Čopjak M. Tomášek J. Hurtuk Dept. of Computers and Informatics FEI TU of Košice Slovak Republic Dept. of Computers and Informatics FEI TU of Koš¡ice Slovak Republic

Many industries nowadays use management and decision making based on artificial neural networks. However, the major drawback of neural networks lies in their time and computational complexity. the problem with computational complexity could be eliminated using sharing of the computing needs on multiple computing nodes. this article focuses on the architectural design of a distributed system, which aims to solve large neural networks. the article describes the technology GPGPU and the next part of the article deals with an overview of methods for speeding up the calculation and distribution of artificial neural network. the main section describes the design of a model architecture description of the algorithm that allows correct data distribution on computational nodes.

关键词： Graphics processing units Computer architecture parallel processing Neurons Hardware Biological neural networks

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Design of Photovoltaic Microinverter for Off-Grid and Grid-parallel applications

Design of Photovoltaic Microinverter for Off-Grid and Grid-P...

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CIPS 2014;8th international conference on Integrated Power Electronics Systems

作者： Christian Felgemacher Philipp Jaeger Ali Kobeissi Jonas Pfeiffer Dennis Wieg Wolfram Kruschel Benjamin Dombert Samuel Vasconcelos Araujo Peter Zacharias University of Kassel Centre of Competence for Distributed Electric Power Technology (KDEE)

ISBN: (纸本)9783800735785

the design and construction of a 500VA microinverter for photovoltaic applications is presented. the developed microinverter is capable of operating as a standalone AC voltage source for small loads or, alternatively, as a grid-parallel system. Possible applications are therefore small off-grid installations as well as installations where space constraints do not allow enough modules to be combined to use string inverters. the design of the microinverter is based on a two stage concept. Two alternative topologies for the DC-DC converter stage have been considered. A prototype using a current-fed push-pull converter and a full-bridge output stage has been built and was shown to be operational. the prototype has achieved a maximum overall efficiency of 93.9 %, which includes all sensing, control and driving losses. SiC MOSFETs have been utilized to illustrate the capability of wide-band-gap devices.

关键词： Installations output stage PHOTOVOLTAIC Cosmic strings EQUIPMENT Small space constraint VOLTS ALTERNATING CURRENT DC to DC converters

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Hierarchical speech recognition system using MFCC feature extraction and dynamic spiking RSOM

Hierarchical speech recognition system using MFCC feature ex...

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ACIS international conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed computing (SNPD)

作者： Behi Tarek Arous Najet Ellouze Noureddine Laboratory of Signal Universitc Tunis EI Manar Tunisia Laboratory of Signal Image and Information Technologies National Engineering school of tunis Enit Université Tunis El Manar Tunisia

In this paper, we propose new variants of unsupervised and competitive learning algorithms designed to deal with temporal sequences. these algorithms combine features from Spiking Neural Networks (SNNs) and the advantages of the hierarchical self organizing map (HSOM). the first variant named Hierarchical Dynamic recurrent spiking self-organizing map (HD-RSSOM) is characterized by the integration of a temporal controller component to regulate the firing activity of the spiking neurons. the second variant is a hierarchical model which represents a multi-layer extension of HD-RSSOM model. the case study of the proposed HSOM variants is phonemes and words recognition in continuous speech. the applied HSOM variants serve as tools for developing intelligent systems and pursuing artificial intelligence applications.

关键词： Training Speech recognition Neurons Speech Vectors Neural networks Mel frequency cepstral coefficient

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Qos Agent Based Framework and Algorithm for Task Scheduling in Grid

Qos Agent Based Framework and Algorithm for Task Scheduling ...

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IEEE international conference on Intelligent Systems and Control

作者： T. T. Dhivyaprabha Department of Information and Computer Technologies Sri Krishna Arts and Science College

ISBN: (纸本)9781479938384

Grid computing promotes resource sharing, dynamic computational resource allocation, distributed data access from disjoint application domains and allowing various service providers to meet different demands efficiently. With an increase of user demands to the resources, planning the guaranteed Quality of Service (QoS) is a challenging task. the objective of this paper is to propose an agent based grid framework and QoS Time Based Scheduling (QTBS) algorithm for effective task scheduling in the grid computing paradigm. this algorithm is simulated in the GridSim toolkit and the results shows that the proposed work gives better results in makespan, resource utilization rate and load balancing level than algorithms such as QoS guided Weighted Mean Time Min (QWMTM), QoS guided MinMin, Max-Min and Min-Min heuristic algorithms.

关键词： Grid computing Intelligent agent Quality of Service (QoS) Resource Broker Heuristic algorithms

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