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检索条件"任意字段=10th International Conference on Algorithms and Architectures for Parallel Processing"

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A parallel CONVOLUTIONAL NEURAL NETWORK ARCHITECTURE FOR STEREO VISION ESTIMATION 24

A PARALLEL CONVOLUTIONAL NEURAL NETWORK ARCHITECTURE FOR STE...

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24th IEEE international conference on Image processing (ICIP)

作者： Chou, Yao Lee, Dah-Jye Zhang, Dong Hill, Karina Brigham Young Univ Dept Elect & Comp Engn Provo UT 84602 USA Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781509021758

Extracting depth information from the stereo image pair is a commonly used method in 3-D computer vision. For robotics and unmanned vehicle applications that require real-time performance, speed is often more important than accuracy. In recent years, Convolutional Neural Networks (CNNs) have shown great success in many computer vision applications including classification, segmentation, object detection, edge detection, and stereo vision estimation. Existing network architectures for stereo vision estimation predict very little information during the forward pass and are only able to calculate the disparity for one pixel at a time. In this paper, we propose a parallel architecture to speed up disparity map computation by simultaneously processing all pixels on one horizontal line. We train and test our network on five Middlebury datasets. Our parallel architecture achieves at least a 10x speedup compared to existing networks. Its accuracy is also very competitive.

关键词： Stereo Vision CNN Deep Learning parallel Architecture

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Pipelining Computation and Optimization Strategies for Scaling GROMACS on the Sunway Many-Core Processor 17th

Pipelining Computation and Optimization Strategies for Scali...

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17th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Yu, Yang An, Hong Chen, Junshi Liang, Weihao Xu, Qingqing Chen, Yong Univ Sci & Technol China Hefei Anhui Peoples R China Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA

ISBN: (纸本)9783319654829;9783319654812

the increasing gap between plentiful computing elements and limited memory bandwidth makes it increasingly difficult and sometimes even infeasible for HPC community to port more applications onto many-core processor architectures. the Sunway many-core processor SW26010 used to build the Sunway TaihuLight System contains a total of 260 heterogeneous cores. All these cores can be divided into 4 core groups (CGs). Each CG includes a Management processing Element (MPE) core and 64 Computing processing Elements (CPEs) cores. In this paper, we refactor an important molecular dynamics (MD) application GROMACS on the Sunway Taihulight system. By rewriting the compute-intensive kernel of GROMACS, we exploit a suitable parallelism for CPE cluster and implement pipelining computation between MPE and CPE cluster. Optimization strategies including the efficient use of scratchpad, the software-emulated cache and a hybrid parallel algorithm are adopted to solve the challenging memory bandwidth limitation. When comparing the refactored version using MPE and 64 CPEs with the original ported version using only MPE, we achieve a 16x speedup for the compute-intensive kernel. For simulating a molecule with 3 million atoms, we currently have managed to scale to 798,720 cores. Moreover, we analyze the adaptability of our mapping and optimization strategies for solving the memory bandwidth limitation when refactoring a real-world application on the Sunway heterogeneous many-core processor system.

关键词： Sunway TaihuLight system GROMACS parallel model Performance optimization Bandwidth competition Adaptability

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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10th international conference on Security of Information and Networks, SIN 2017

ISBN: (纸本)9781450353038

the proceedings contain 49 papers. the topics discussed include: models and approaches for the safety and the security of distributed systems;redesign CloudRAID for flexible and secure enterprise file sharing over public cloud storage;a universal user revocation scheme with key-escrow resistant for Ciphertext-policy attribute-based access control systems;an enhanced parallel version of RSA public key crypto based algorithm using OpenMP;a model of a secure electronic voting system based on blind intermediaries using Russian cryptographic algorithms;privacy preserving two-server Diffie-Hellman key exchange protocol;attribute-based approach of defining the secure behavior of automata objects;network security architectures for VANET;tamperproof complex event processing in IoT devices using side channel information;integer overflow vulnerabilities detection in software binary code;a novel malware analysis for malware detection and classification using machine learning algorithms;collaborative representation of Grassmann manifold projection metric for robust multi-spectral face recognition;extended multi-spectral imaging for gender classification based on image set;parameters of the two-stage synchronization algorithm for the quantum key distribution system;abnormal leakage of energy in battery-based IoT-devices;a framework for data security in the cloud using collaborative intrusion detection scheme;and integration of role based access control with homomorphic cryptosystem for secure and controlled access of data in cloud.

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Portable and vendor-independent low-level programming and performance benchmarking for graphics cards and processors

Portable and vendor-independent low-level programming and pe...

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IEEE 19th international conference on High Performance Computing and Communications (HPCC)

作者： Rohr, David Lindenstruth, Volker CERN Geneva Switzerland Frankfurt Inst Adv Studies Frankfurt Germany

ISBN: (纸本)9781538659304

GPUs have the potential to speed up programs significantly and are one opportunity to increase the scientific reach of compute-intense scientific applications. Several new programming models based on C and other languages have evolved to leverage the potential of such parallel architectures. Still, the development of individual source code versions using different languages and APIs deteriorates the maintainability of the code. It can also lead to slightly different outputs complicating the verification of the results. For comparing the compute performance, the different nature of the processors, different pricing, and different speed grades of hardware must be taken into account. In this paper, we summarize our experience from adapting a set of applications to GPUs. We present several cases how we implement generic code for multiple architectures and how we overcome the challenges that occurred. the presented applications encompass an algorithm to reconstruct the trajectories of particles for the ALICE High Level Trigger at the Large Hadron Collider at CERN;the Linpack benchmark used for ranking the performance of supercomputers and in particular its matrix multiplication substep;Reed-Solomon based failure erasure coding for redundant data storage;Lattice Quantum Chromo Dynamics computations;and an application for evaluating electron microscopy images.

关键词： Graphics processing units C++ languages Libraries Computer architecture Optimization Benchmark testing Benchmark testing Computer Architecture PROCESSOR Libraries Graphics processing Unit Level Trigger BENCHMARKS supercomputer Programming

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Proceedings - 2017 IEEE international conference on High Performance Computing and Communications Workshops, HPCCWS 2017 and Multicore and Multithreaded architectures and algorithms, M2A2 2017

Proceedings - 2017 IEEE International Conference on High Per...

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2017 IEEE international conference on High Performance Computing and Communications Workshops, HPCCWS 2017 and 8th Multicore and Multithreaded architectures and algorithms, M2A2 2017

ISBN: (纸本)9781538659304

the proceedings contain 12 papers. the topics discussed include: portable and vendor-independent low-level programming and performance benchmarking for graphics cards and processors;a hybrid parallel genetic algorithm with dynamic migration strategy based on Sunway many-core processor;a framework for WAN optimization and data center selection using NaaS;parallel grouping particle swarm optimization with stream processing paradigm;finding hierarchical network model in insulin production process;efficient generation of parallel spin-images using dynamic loop scheduling;a survey and recommendations for distributed, parallel, single pass, incremental Bayesian classification based on MapReduce for big data;AWEDF: an architecture-aware execution and debugging workflow for a highly reliable chip;performance evaluation of Intel broadwell nodes based supercomputer using computational fluid dynamics and climate applications;an efficient elasticity mechanism for server-based pervasive healthcare applications in cloud environment;and thai sentence generation machine employing fixed patterns.

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BIOSIGNALS 2017 - 10th international conference on Bio-Inspired Systems and Signal processing, Proceedings;Part of 10th international Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017

BIOSIGNALS 2017 - 10th International Conference on Bio-Inspi...

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10th international conference on Bio-Inspired Systems and Signal processing, BIOSIGNALS 2017 - Part of 10th international Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017

ISBN: (纸本)9789897582127

the proceedings contain 40 papers. the topics discussed include: swarm intelligence among humans - the case of alcoholics;decomposition of the cardiac and respiratory components from impedance pneumography signals;time-frequency based coherence and phase locking value analysis of human locomotion data using generalized Morse wavelets;cuff-less calibration-free blood pressure estimation under ambulatory environment using pulse wave velocity and photoplethysmogram signals;impact of airflow rate on amplitude and regional distribution of normal lung sounds;a minimally invasive method for beat-by-beat estimation of cardiac pressure-volume loops;characterization of uterine response to misoprostol based on electrohysterogram;flow parameters derived from impedance pneumography after nonlinear calibration based on neural networks;electrohysterogram signals from patients with threatened preterm labor: concentric ring electrode vs disk electrode recordings;automated t wave end detection methods - comparison of four different methods for t wave end detection;linking non-extensive entropy with Lempel-Ziv complexity to obtain the entropic q-index from EEG signals;combining two different DNN architectures for classifying speaker's age and gender;characterisation of resting brain network topologies across the human lifespan with magnetoencephalogram recordings: a phase slope index and granger causality comparison study;and proposal of new tracer concentration model in lung pct study - comparison with commonly used gamma-variate model.

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parallel Multi-objective Optimization for High-Order Epistasis Detection 17th

Parallel Multi-objective Optimization for High-Order Epistas...

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17th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Gallego-Sanchez, Daniel Granado-Criado, Jose M. Santander-Jimenez, Sergio Rubio-Largo, Alvaro Vega-Rodriguez, Miguel A. Univ Extremadura Caceres Spain Univ Lisbon Lisbon Portugal Univ NOVA Lisboa Lisbon Portugal

ISBN: (纸本)9783319654829;9783319654812

Many studies have shown that there is a direct relationship between Single Nucleotide Polymorphisms (SNPs) and the appearance of complex diseases, such as Alzheimer's or Parkinson's. However, recent advances in the Study of the Complete Genome Association indicate that the relationship between SNPs and these diseases goes beyond a simple one-to-one relationship, that is, the appearance of multiple SNPs (epistasis) influences the appearance of these diseases. In this sense, this work proposes the application of the NSGA-II multi-objective algorithm for the detection of epistasis of multiple loci in a database with 31,341 SNPs. Moreover, a parallel study has been performed to reduce the execution time of this problem. Our implementation not only achieves a reasonable good parallel performance and scalability, but also its biological significance overcomes other approaches published in the literature.

关键词： parallelism NSGA-II Epistasis SNP

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Multi-level Grid Based Clustering and GPU parallel Implementations 14

Multi-level Grid Based Clustering and GPU Parallel Implement...

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14th international Symposium on Pervasive Systems, algorithms and Networks (I-SPAN) / 11th international conference on Frontier of Computer Science and Technology (FCST) / 3rd international Symposium of Creative Computing (ISCC)

作者： Qian, Quan Zhao, Shuai Xiao, Chao-Jie Hung, Che-Lun Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Shanghai Univ Mat Genome Inst Shanghai 200444 Peoples R China Providence Univ Dept Comp Sci & Commun Engn Taichung Taiwan

ISBN: (纸本)9781538608401

Clustering algorithm for stream data, as one of stream data mining technologies, has extensive applications on network traffic analysis, telecommunication, planetary remote sensing, web site analysis, etc. Clustering algorithm for stream data has a high demand for real-time processing, but current clustering algorithms for stream data, such as Clustream, Dstream, are all based on sequential algorithms, which are unable to meet the realtime requirement. In this paper, we propose a multi-grid based clustering algorithm for stream data. the algorithm partitions the grid space appropriately on the basis of conventional grid-based DBSCAN clustering algorithm, which can effectively limit the searching scope of grid neighbours to accelerate processing performance. Meanwhile, we utilize CUDA to conduct parallel computing in order to further speed up processing. through the experiments tested on the KDDCUP-99 open testing dataset, it shows that the processing speed of the algorithm proposed by the paper is 10 times faster than that of the conventional grid-based algorithm and moreover the CUDA based algorithm can achieve an speedup of 3 compared with the algorithm executed on CPU.

关键词： Multi-grid clustering algorithm for stream data GPU parallelization

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Speed-Up Computational Finance Simulations with OpenCL on Intel Xeon Phi 22nd

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22nd international European conference on parallel and Distributed Computing (Euro-Par)

作者： Papadimitriou, Michail Cramwinckel, Joris Varbanescu, Ana Lucia Delft Univ Technol Delft Netherlands Ortec Finance Rotterdam Netherlands Univ Amsterdam Amsterdam Netherlands

ISBN: (纸本)9783319589435;9783319589428

Computational finance is a domain where performance is in high demand. In this work, we investigate the suitability of Intel Xeon Phi for computational finance simulations. Specifically, we use a scenario based ALM (Asset Liability Management) model and propose a novel OpenCL implementation for Xeon Phi. To further improve the performance of the application, we apply several optimization techniques (data layout and data locality improvement, loop unrolling) and study their effects. Our results show that the optimized OpenCL code deployed on the Phi can run up to 135x faster than the original scalar code running on an Intel i7 GPP. Furthermore, we also show that choosing the optimal work-item/work-group distribution has a compelling effect on massively parallel and heavily-branching code. Overall, these results are significant for the computational finance specialists, as they enable a major increase in model accuracy, because 10x more simulations can be performed in less than a 10th of the original time.

关键词： OpenCL Computing Accelerated architectures Intel Xeon Phi MIC GPGPU parallel computing Asset Liability Management

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Massively parallel Sequence Alignment with BLAST through Work Distribution Implemented Using PCJ Library 17th

Massively Parallel Sequence Alignment with BLAST Through Wor...

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17th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Nowicki, Marek Bzhalava, Davit Bala, Piotr Nicolaus Copernicus Univ Fac Math & Comp Sci Chopina 12-18 PL-87100 Torun Poland Karolinska Inst Dept Lab Med F46 S-14186 Stockholm Sweden Univ Warsaw Interdisciplinary Ctr Math & Computat Modelling Pawinskiego 5a PL-02106 Warsaw Poland

ISBN: (纸本)9783319654829;9783319654812

this article presents massively parallel execution of the BLAST algorithm on supercomputers and HPC clusters using thousands of processors. Our work is based on the optimal splitting up the set of queries running with the non-modified NCBI-BLAST package for sequence alignment. the work distribution and search management have been implemented in Java using a PCJ (parallel Computing in Java) library. the PCJ-BLAST package is responsible for reading sequence for comparison, splitting it up and start multiple NCBI-BLAST executables. We also investigated a problem of parallel I/O and thanks to PCJ library we deliver high throughput execution of BLAST. the presented results show that using Java and PCJ library we achieved very good performance and efficiency. In result, we have significantly reduced time required for sequence analysis. We have also proved that PCJ library can be used as an efficient tool for fast development of the scalable applications.

关键词： Sequence alignment NGS Next Generation Sequencing parallel programming Java BLAST NCBI-BLAST PCJ

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