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Automatic fitting of neuron parameters

Automatic fitting of neuron parameters

引用

IEEE international conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Jiamin Shen Ye Wang Lihong Cao Neuroscience and Intelligent Media Institute Communication University of China Beijing

Artificial neural networks are inspired by biological neural networks formed by many real neurons with spiking activities. It is important to simulate the spiking activities under different conditions. It is well known that the Hodgkin-Huxley (HH) equations can be used for simulation. However, we usually don't know the conductance of ion channels in the equation, which is required for simulation. In this paper, we develop a parallel genetic algorithm to estimate the conductance with a visual software tool. By fitting the experimental data, it is shown that when the number of individuals in the genetic algorithm is above 2000, the 5th generation can yield a near optimal solution and achieve a good fitting result.

关键词： Neurons Fitting Genetic algorithms Ions Mathematical model Graphics processing units

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HIGHLY parallel HEVC MOTION ESTIMATION BASED ON MULTIPLE TEMPORAL PREDICTORS AND NESTED DIAMOND SEARCH 24

HIGHLY PARALLEL HEVC MOTION ESTIMATION BASED ON MULTIPLE TEM...

引用

24th IEEE international conference on Image processing (ICIP)

作者： Hojati, Esmaeil Franche, Jean-Francois Coulombe, Stephane Vazquez, Carlos Ecole Technol Super Montreal PQ Canada

ISBN: (纸本)9781509021758

Rate-constrained motion estimation (RCME) is the most computationally intensive task of H.265/HEVC encoding. Massively parallel architectures, such as graphics processing units (GPUs), used in combination with a multi-core central processing unit (CPU), provide a promising computing platform to achieve fast encoding. However, the dependencies in deriving motion vector predictors (MVPs) prevent the parallelization of prediction units (PUs) processing at a frame level. Moreover, the conditional execution structure of typical fast search algorithms is not suitable for GPUs designed for data-intensive parallel problems. In this paper, we propose a novel highly parallel RCME method based on multiple temporal motion vector (MV) predictors and a new fast nested diamond search (NDS) algorithm well-suited for a GPU. the proposed framework provides fine-grained encoding parallelism. Experimental results show that our approach provides reduced GPU load with better BD-Rate compared to prior full search parallel methods based on a single MV predictor.

关键词： HEVC rate-constrained motion estimation GPU massively parallel architecture

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Application of Batch and Stream Collaborative Computing in Urban Traffic Data processing 17th

Application of Batch and Stream Collaborative Computing in U...

引用

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

作者： Zhang, Tao Zhao, Shuai Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

ISBN: (纸本)9783319654829;9783319654812

Analysis of urban traffic data has obtained a great attention in recent years. In the study of urban traffic data processing, the batch computing based on historical data and the stream computing based on real-time data are isolated, and the two computing frameworks are not synergized. therefore, a method of urban traffic data processing based on batch and stream collaborative computing is proposed. Batch computing has the advantage of high throughput, so it is more suitable for calculating the historical data of urban traffic and the results of stream computing deeply. Stream computing with the advantage of low delay can be used to calculate the traffic data in real time, combined with the results of batch computing, then the conclusion of urban traffic data processing are more comprehensive and accurate.

关键词： Batch computing Stream computing Collaborative computing Urban traffic data processing

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Configuring Concurrent Computation of Phylogenetic Partial Likelihoods: Accelerating Analyses Using the BEAGLE Library 17th

Configuring Concurrent Computation of Phylogenetic Partial L...

引用

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

作者： Ayres, Daniel L. Cummings, Michael P. Univ Maryland Ctr Bioinformat & Computat Biol College Pk MD 20742 USA

ISBN: (纸本)9783319654829;9783319654812

We describe our approach in augmenting the BEAGLE library for high-performance statistical phylogenetic inference to support concurrent computation of independent partial likelihoods arrays. Our solution involves identifying independent likelihood estimates in analyses of partitioned datasets and in proposed tree topologies, and configuring concurrent computation of these likelihoods via CUDA and opencL frameworks. We evaluate the effect of each increase in concurrency on throughput performance for our partial likelihoods kernel for a four-state nucleotide substitution model on a variety of parallel computing hardware, such as NVIDIA and AMD GPU5, and Intel multicore cPus, observing up to 16-fold speedups over our previous implementation. Finally, we evaluate the effect of these gains on an domain application program, MrBayes. For a partitioned nucleotide-model analysis we observe an average speedup for the overall run time of 2.1-fold over our previous parallel implementation, and 10-fold over the native MrBayes with SSE.

关键词： Bayes methods Biology computing Evolution (biology) Phylogeny Maximum likelihood estimation Multicore processing parallel programming High performance computing

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Accelerating Exhaustive Pairwise Metagenomic Comparisons 17th

Accelerating Exhaustive Pairwise Metagenomic Comparisons

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

作者： Perez-Wohlfeil, Esteban Torreno, Oscar Trelles, Oswaldo Univ Malaga Dept Comp Architecture Blvd Louis Pasteur 35 Malaga Spain

ISBN: (纸本)9783319654829;9783319654812

In this manuscript, we present an optimized and parallel version of our previous work IMSAME, an exhaustive gapped aligner for the pairwise and accurate comparison of metagenomes. parallelization strategies are applied to take advantage of modern multiprocessor architectures. In addition, sequential optimizations in CPU time and memory consumption are provided. these algorithmic and computational enhancements enable IMSAME to calculate near optimal alignments which are used to directly assess similarity between metagenomes without requiring reference databases. We show that the overall efficiency of the parallel implementation is superior to 80% while retaining scalability as the number of parallel cores used increases. Moreover, we also show that sequential optimizations yield up to 8x speedup for scenarios with larger data.

关键词： High Performance Computing Pairwise comparison parallel computing Next Generation Sequencing Metagenome comparison

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Educational Multiprocessor Simulator "E14" and Its Usage for Expanding the Formula of Amdahl's Law 25

Educational Multiprocessor Simulator "E14" and Its Usage for...

引用

25th Euromicro international conference on parallel, Distributed and Network-Based processing (PDP)

作者： Eremin, Evgeny A. Perm State Humanitarian Pedag Univ Perm Russia

ISBN: (纸本)9781509060580

this paper describes demonstrative software simulator "E14", helpful in studying on an ordinary PC essentials of parallel calculations. It contains five virtual processors with identical instruction set, one of which controls the other four. Simulator has several mechanisms of data exchange between processors, so it can be used for studying both architectures with shared and distributed memory. parallel architecture of "E14" naturally extends classical single-processor one, hence proposed approach makes students' knowledge more systematic. "E14" may also be employed as a platform for the estimation of parallel algorithms' performance. the example, considered in the paper, clearly demonstrates how data exchange between processors may essentially degrade speedup, predicted by Amdahl's law.

关键词： multiprocessor mullticore computer architecture parallel calculations speedup Amdahl's law education simulator

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Feature Selection and Intrusion Detection in Cloud Environment based on Machine Learning algorithms 15

Feature Selection and Intrusion Detection in Cloud Environme...

引用

15th IEEE international Symposium on parallel and Distributed processing with Applications (ISPA) / 16th IEEE international conference on Ubiquitous Computing and Communications (IUCC)

作者： Javadpour, Amir Abharian, Sanaz Kazemi Wang, Guojun Guangzhou Univ Guangzhou Guangdong Peoples R China Sharif Univ Technol Tehran Iran

ISBN: (纸本)9781538637906

Characteristics and way of behavior of attacks and infiltrators on computer networks are very difficult and need an expert. In addition;the advancement of computer networks, the number of attacks and infiltrations is also increasing. In fact, the knowledge coming from expert will lose its value over time and must be updated and made available to the system and this makes the need for expert person always felt. In machine learning techniques, knowledge is extracted from the data itself which has diminished the role of the expert. Various methods used to detect intrusions, such as statistical models, safe system approach, neural networks, etc., all weaken the fact that it uses all the features of an information packet rotating in the network for intrusion detection. Also, the huge volume of information and the unthinkable state space is also an important issue in the detection of intrusion. therefore, the need for automatic identification of new and suspicious patterns in attempt for intrusion with the use of more efficient methods (Lower cost and higher performance) is needed more than before. the purpose of this paper is to provide a new method based on intrusion detection systems and its various architectures aimed at increasing the accuracy of intrusion detection in cloud computing.

关键词： intrusion detection feature Selection classification Algorithm machine learning neural network cloud computing

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Online Speech Decoding Optimization Strategy with Viterbi Algorithm on GPU

Online Speech Decoding Optimization Strategy with Viterbi Al...

引用

international conference of Advanced Informatics: Concept, theory and Application (ICAICTA)

作者： Alfonsus Raditya Arsadjaja Achmad Imam Kistijantoro School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9781538648056

Automatic Speech Recognition (ASR) has been popular recently. But the current algorithm for speech recognition is slow and needed the way to recognize faster. One way to achieve it is with GPU, which provides parallel computation; but ASR is hard to parallelize directly. this paper describes how to build parallel ASR system, which requires several steps. First, we must convert the data structure to make it compatible with GPU, then we have to make several kernels that equivalent to the serial algorithm in CPU. We will describe several optimization strategies for make ASR run much faster after we got the correct GPU program. those strategies are based on profiling result and analysis of the GPU program execution flow. Best implementation that we had have a speedup around 5.59-6.18 times from the serial CPU implementation.

关键词： Graphics processing units Viterbi algorithm Decoding Hidden Markov models Acoustics Speech recognition Kernel

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PEvoRNN: Extended CUDA-Based Hybrid parallel Evolutionary Robot Controller 5

PEvoRNN: Extended CUDA-Based Hybrid Parallel Evolutionary Ro...

引用

5th international conference on Electrical Engineering - Boumerdes (ICEE-B)

作者： Benalia, Nour El-Houda Djedi, NourEddine Polytech Natl Sch Dept Preparatory Classes Algiers Algeria Biskra Univ Dept Comp Sci LESIA Lab Biskra Algeria

ISBN: (纸本)9781538606865

Development and simulation of artificial biological models require a considerable computational complexity which can be surmounted using Modern Graphic processing Units (GPUs), since these devices adopt parallel multi-core architecture which favors the inherently data-parallel nature. In this paper, we present an extended version of our hybrid model presented in [1], [2], based on a high tuning CUDA parameter (Compute Unified Device Architecture) for the parallel evolutionary strategy (ES) and a recurrent neural network (RNN), called PEvoRNN. this proposal takes the advantages of the GPU memory hierarchy effective use, the best parallelism management by investigating tuning CUDA parameters and the optimal GPU-based coding, to generate optimal trajectories of a humanoid robot using GPU Accelerator at multiple levels. PEvoRNN represents a controller which monitors the movement and the evolution of a 3D humanoid robot simulated on the open dynamic engine simulator (ODE). Moreover, this proposal makes feasible and tractable the integration of multiple complex evolutionary methods for heterogeneous training locomotion process. the effectiveness of the proposed parallel tuned evolutionary training technique was validated for real movements in terms of a promising speedup, since this field requires powerful computational resources.

关键词： Graphics processing units Computational modeling Biological system modeling Tuning Physics Robot sensing systems

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On the Use of Binary Trees for DNA Hydroxymethylation Analysis 17th

On the Use of Binary Trees for DNA Hydroxymethylation Analys...

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

作者： Gonzalez, Cesar Perez, Mariano Orduna, Juan M. Chaves, Javier Garcia, Ana-Barbara Univ Valencia Dept Informat Avda Univ S-N Valencia 46100 Spain CIBERDEM Carlos III Hlth Inst INCLIVA Hlth Res Inst Avda Menendez Pelayo 4 Accesorio Valencia 46010 Spain

ISBN: (纸本)9783319654829;9783319654812

DNA methylation (mC) and hydroxymethylation (hmC) can have a significant effect on normal human development, health and disease status. Hydroxymethylation studies require specific treatment of DNA, as well as software tools for their analysis. In this paper, we propose a parallel software tool for analyzing the DNA hydroxymethylation data obtained by TAB-seq. the software is based on the use of binary trees for searching the different occurrences of methylation and hydroxymethylation in DNA samples. the binary trees allow to efficiently store and access the information about the methylation of each methylated/hydroxymethylated cytosines in the samples. Evaluation results shows that the performance of the application is only limited by the computer input/output bandwidth, even for the case of very long samples.

关键词： High performance computing DNA hydroxymethylation parallel pipeline

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