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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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ParallNormal: an efficient variant calling pipeline for unmatched sequencing data 26

ParallNormal: an efficient variant calling pipeline for unma...

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26th Euromicro international conference on parallel, Distributed, and Network-Based processing (PDP)

作者： Follia, Laura Tordini, Fabio Pernice, Simone Romano, Greta Piaggeschi, Giulia Beatrice Ferrero, Giulio Univ Turin Comp Sci Dept Turin Italy Ctr Expt Res & Med Studies CeRMS Turin Italy Univ Turin Mol Biotechnol & Hlth Sci Dept Turin Italy Italian Inst Genom Med Turin Italy Univ Turin Clin & Biol Sci Dept Turin Italy

ISBN: (纸本)9781538649756

Nowadays, next generation sequencing is closer to clinical application in the field of oncology. Indeed, it allows the identification of tumor-specific mutations acquired during cancer development, progression and resistance to therapy. In parallel with an evolving sequencing technology, novel computational approaches are needed to cope with the requirement of a rapid processing of sequencing data into a list of clinically-relevant genomic variants. Since sequencing data from both tumors and their matched normal samples are not always available (unmatched data), there is a need of a computational pipeline leading to variants calling in unmatched data. Despite the presence of many accurate and precise variant calling algorithms, an efficient approach is still lacking. Here, we propose a parallel pipeline (ParallNormal) designed to efficiently identify genomic variants from whole-exome sequencing data, in absence of their matched normal. ParallNormal integrates well-known algorithms such as BWA and GATK, a novel tool for duplicate removal (DuplicateRemove), and the FreeBayes variant calling algorithm. A re-engineered implementation of FreeBayes, optimized for execution on modern multi-core architectures is also proposed. ParallNormal was applied on whole-exome sequencing data of pancreatic cancer samples without considering their matched normal. the robustness of ParallNormal was tested using results of the same dataset analyzed using matched normal samples and considering genes involved in pancreatic carcinogenesis. Our pipeline was able to confirm most of the variants identified using matched normal data.

关键词： Genomics Sequential analysis Bioinformatics Pipelines Tools Tumors Bayes methods

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LMCC: Lazy Message and Centralized Cache for Asynchronous Graph Computing 18th

LMCC: Lazy Message and Centralized Cache for Asynchronous Gr...

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18th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Xue, Ruini Dong, Zhibin Su, Wei Li, Xiaofang Univ Elect Sci & Technol China Chengdu Peoples R China

ISBN: (纸本)9783030050542;9783030050535

Graph has been widely used in complex network applications modeling, and the asynchronous graph processing model is superceding the BSP model because of its better convergence speed. However, the asynchronous GAS model proposed by PowerGraph usually results in irregular and unpredictable communication patterns as well as vertex-scale barriers, so it is difficult for programmers to optimize codes. To address these challenges, we propose LMCC, an improved message management approach including lazy pull-message model and vertex-oriented centralized cache, which can reduce communication cost in terms of message quantity, and reduce the number of computation iterations in turn, without compromising the accuracy of application results. Based on the deep investigation of the GAS phases, LMCC is designed to be totally transparent to user applications. Experimental results show that LMCC can deliver speedup for various types of graph computing benchmarks ranging from 129% to 271%.

关键词： Graph processing Communication optimization Message combination Centralized cache

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parallel Communication Mechanisms in Solving Integral Equations for Electromagnetic Scattering Based on the Method of Moments 18th

Parallel Communication Mechanisms in Solving Integral Equati...

引用

18th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Song, Lan Peters, Dennis K. Huang, Weimin Liu, Zhiwei Lei, Lixia Wen, Tangliu Wuhan Univ Sch Comp State Key Lab Software Engn Wuhan 430072 Hubei Peoples R China East China Jiaotong Univ Sch Informat Engn Nanchang 330013 Jiangxi Peoples R China Mem Univ Fac Engn & Appl Sci Elect & Comp Engn St John NF Canada

ISBN: (纸本)9783030050511;9783030050504

In this paper, a parallel solution of impedance filling was studied to improve the efficiency for the method of moments (MOM) in solving the integral equation for electromagnetic scattering. Based on the formalization method, the correctness verification method of the parallel communication protocol was proposed to avoid the abnormal situation such as deadlock caused by unsynchronized MPI message delivery. Finally, a numerical example is given to verify the accuracy of the parallel algorithm in a multi-core cluster environment, and the parallel efficiency and computational capability are also tested. From the experiment data, it can be seen that the results of the parallel-based integral equation match well with the results of the Mie analytical solution. the parallel algorithm proposed in this paper is evaluated in terms of the acceleration ratio and parallel efficiency. the experimental results demonstrate the reliability and effectiveness of the method.

关键词： Formal verification parallel communication Electromagnetic scattering Petri net

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A parallel Branch and Bound Algorithm for the Probabilistic TSP 18th

A Parallel Branch and Bound Algorithm for the Probabilistic ...

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18th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Amar, Mohamed Abdellahi Khaznaji, Walid Bellalouna, Monia Univ Manouba Natl Sch Comp Sci CRISTAL Lab POLE GRIFT Tunis Tunisia Tunisia SESAME Univ Ariana Tunisia

ISBN: (纸本)9783030050511;9783030050504

the paper presents parallelization of exact algorithm of resolution for the Probabilistic Traveling Salesman Problem (PTSP). this algorithm allows us, first, to verify the stability of well-solvable special cases and also to optimally solve useful instances of PTSP. It again allows to perform our version of Karp partitioning algorithm, where real problems are very large-sized. the implementation of the algorithm of Karp consists in subdividing the square plan, into sub-plans. So we transform the resolution of a large size problem to the resolution of many small size sub-problems which can be exactly solved. this application can be gridified and these different sub-problems would be processed in parallel by different nodes since they are totally independent. In each sub-plan the Branch and Bound algorithm is used. In this paper we propose two parallelizations of the Branch and Bound algorithm for the resolution of the PTSP. On the one hand, the parallelization of the branches used in the exploration of the tree, on the other hand the parallelization of the algorithm associated with the notion of partitioning introduced by Karp. We perform an experimental study conducted in a multi-core environment to evaluate the performance of the proposed approach.

关键词： PTSP parallel algorithm Open MP Simulations

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Comparative Study of Distributed Deep Learning Tools on Supercomputers 18th

Comparative Study of Distributed Deep Learning Tools on Supe...

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18th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Du, Xin Kuang, Di Ye, Yan Li, Xinxin Chen, Mengqiang Du, Yunfei Wu, Weigang Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou Peoples R China Guangdong Prov Key Lab Big Data Anal & Proc Guangzhou Peoples R China Minist Educ Key Lab Machine Intelligence & Adv Comp Guangzhou Peoples R China

ISBN: (纸本)9783030050511;9783030050504

With the growth of the scale of data set and neural networks, the training time is increasing rapidly. Distributed parallel training has been proposed to accelerate deep neural network training, and most efforts are made on top of GPU clusters. this paper focuses on the performance of distributed parallel training in CPU clusters of supercomputer systems. Using resources at the supercomputer system of "Tianhe-2", we conduct extensive evaluation of the performance of popular deep learning tools, including Caffe, TensorFlow, and BigDL, and several deep neural network models are tested, including AutoEncoder, LeNet, AlexNet and ResNet. the experiment results show that Caffe performs the best in communication efficiency and scalability. BigDL is the fastest in computing speed benefiting from its optimization for CPU, but it suffers from long communication delay due to the dependency on MapReduce framework. the insights and conclusions from our evaluation provides significant reference for improving resource utility of supercomputer resources in distributed deep learning.

关键词： Distributed deep learning Tianhe-2 Speedup Performance evaluation parallel processing

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the parallel Speedup Improving Based on Wave field forward Communication Latency Hiding Technology 10

The Parallel Speedup Improving Based on Wave field forward C...

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10th international conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Xie, Lei Zhao, Changming Wu, Xi Wu, Tao Huang, Min Xiao, Dan Yao, Mingqing Xia, Chaoyang Chengdu Univ Informat Technol Sch Comp Sci Chengdu 610000 Sichuan Peoples R China

ISBN: (纸本)9781538651148

the Finite Difference Method (FDM) is the most common parallel computing method for high performance numerical simulation . the method is able to solve and obtain physical field parameters efficiently when grid strengthening treatment is dense enough. However, FDM processing in parallel acceleration case is necessary to divide all raw data into several parts, which is corresponding to the number of computing nodes amount. It may cause that the edge raw data of each computing node are essential to communicate with the other edge data of the surrounding six adjacent computing nodes. Once the system communication time step is short enough and the computing node is of high computing performance, the communication latency may turn to the primary reason for inefficient parallel. In this paper, it provides a scheme for communication latency hiding that part edge data of each node is able to running in communication and computing simultaneously. the experimental results show that the proposed method has the ability to improve parallel efficiency and reduce the running time definitely.

关键词： Finite Difference Method parallel computing Communication latency Numerical Simulation

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A parallel Fast Fourier Transform Algorithm for Large-Scale Signal Data Using Apache Spark in Cloud 18th

A Parallel Fast Fourier Transform Algorithm for Large-Scale ...

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18th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Yang, Cheng Bao, Weidong Zhu, Xiaomin Wang, Ji Xiao, Wenhua Natl Univ Def Technol Changsha Peoples R China State Key Lab High Performance Comp Changsha Peoples R China Acad Mil Med Sci Beijing Peoples R China

ISBN: (纸本)9783030050573;9783030050566

In the field of signal process, Fast Fourier Transform (FFT) is a widely used algorithm to transform signal data from time to frequency. Unfortunately, with the exponential growth of data, traditional methods cannot meet the demand of large-scale computation on these big data because of three main challenges of large-scale FFT, i.e., big data size, real-time data processing and high utilization of compute resources. To satisfy these requirements, an optimized FFT algorithm in Cloud is deadly needed. In this paper, we introduce a new method to conduct FFT in Cloud with the following contributions: first, we design a parallel FFT algorithm for large-scaled signal data in Cloud;second, we propose a MapReduce-based mechanism to distribute data to compute nodes using big data processing framework;third, an optimal method of distributing compute resources is implemented to accelerate the algorithm by avoiding redundant data exchange between compute nodes. the algorithm is designed in MapReduce computation framework which contains three steps: data preprocessing, local data transform and parallel data transform to integrate processing results. the parallel FFT is implemented in a 16-node Cloud to process real signal data the experimental results reveal an obvious improvement in the algorithm speed. Our parallel FFT is approximately five times faster than FFT in Matlab in when the data size reaches 10 GB.

关键词： Fast fourier transform Cloud computing Apache spark parallel algorithm

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Task-parallel Analysis of Molecular Dynamics Trajectories 18

Task-parallel Analysis of Molecular Dynamics Trajectories

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47th international conference on parallel processing (ICPP)

作者： Paraskevakos, Ioannis Luckow, Andre Khoshlessan, Mahzad Chantzialexiou, George Cheatham, thomas E. Beckstein, Oliver Fox, Geoffrey C. Jha, Shantenu Rutgers State Univ Piscataway NJ 08854 USA Ludwig Maximilians Univ Munchen Munich Germany Arizona State Univ Tempe AZ USA Univ Utah Salt Lake City UT USA Indiana Univ Bloomington IN USA Brookhaven Natl Lab Upton NY 11973 USA

ISBN: (纸本)9781450365109

Different parallel frameworks for implementing data analysis applications have been proposed by the HPC and Big Data communities. In this paper, we investigate three task-parallel frameworks: Spark, Dask and RADICAL-Pilot with respect to their ability to support data analytics on HPC resources and compare them to MPI. We investigate the data analysis requirements of Molecular Dynamics (MD) simulations which are significant consumers of supercomputing cycles, producing immense amounts of data. A typical large-scale MD simulation of a physical system of O(100k) atoms over fisecs can produce from O(10) GB to O(1000) GBs of data. We propose and evaluate different approaches for parallelization of a representative set of MD trajectory analysis algorithms, in particular the computation of path similarity and leaflet identification. We evaluate Spark, Dask and RADICAL-Pilot with respect to their abstractions and runtime engine capabilities to support these algorithms. We provide a conceptual basis for comparing and understanding different frameworks that enable users to select the optimal system for each application. We also provide a quantitative performance analysis of the different algorithms across the three frameworks.

关键词： Data analytics MD Simulations Analysis MD analysis task-parallel

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Neuro-Spectral Audio Synthesis: Exploiting Characteristics of the Discrete Fourier Transform in the Real-Time Simulation of Musical Instruments Using parallel Neural Networks 28th

Neuro-Spectral Audio Synthesis: Exploiting Characteristics o...

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28th international conference on Artificial Neural Networks (ICANN)

作者： Tarjano, Carlos Pereira, Valdecy Univ Fed Fluminense Niteroi RJ Brazil

ISBN: (纸本)9783030304904;9783030304898

Two main approaches are currently prevalent in the digital emulation of musical instruments: manipulation of pre-recorded samples and techniques of real-time synthesis, generally based on physical models with varying degrees of accuracy. Concerning the first, while the processing power of present-day computers enables their use in real-time, many restrictions arising from this sample-based design persist;the huge on disk space requirements and the stiffness of musical articulations being the most prominent. On the other side of the spectrum, pure synthesis approaches, while offering greater flexibility, fail to capture and reproduce certain nuances central to the verisimilitude of the generated sound, offering a dry, synthetic output, at a high computational cost. We propose a method where ensembles of lightweight neural networks working in parallel are learned, from crafted frequency-domain features of an instrument sound spectra, an arbitrary instrument's voice and articulations realistically and efficiently. We find that our method, while retaining perceptual sound quality on par with sampled approaches, exhibits 1/10 of latency times of industry standard real-time synthesis algorithms, and 1/100 of the disk space requirements of industry standard sample-based digital musical instruments. this method can, therefore, serve as a basis for more efficient implementations in dedicated devices, such as keyboards and electronic drumkits and in general purpose platforms, like desktops and tablets or open-source hardware like Arduino and Raspberry Pi. From a conceptual point of view, this work highlights the advantages of a closer integration of machine learning with other subjects, especially in the endeavor of new product development. Exploiting the synergy between neural networks, digital signal processing techniques and physical modelling, we illustrate the proposed method via the implementation of two virtual instruments: a conventional grand piano and a hibrid strin

关键词： Neural networks Acoustic modeling Digital musical instruments Real-time audio synthesis

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Efficient Belief Propagation List Decoding of Polar Codes

Efficient Belief Propagation List Decoding of Polar Codes

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international conference on ASIC

作者： Yuqing Ren Weihong Xu Zaichen Zhang Xiaohu You Chuan Zhang Lab of Efficient Architectures for Digital-communication and Signal-processing (LEADS) National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

As known to all, polar codes have been chosen as the control channel codes for the enhance mobile broadband (eMBB) scenario in the 3GPP RAN1. Due to its excellent performance, polar codes also have caused widespread concern in the academia and industry. In general, polar codes can be decoded by two methods: successive cancellation (SC) and belief propagation (BP) algorithms. However, compared with the series of SC algorithms, the error-correction performance of BP decoding is not satisfactory, even though it has excellent parallel throughput. Hence, this paper proposes an efficient BP list (EBPL) decoding of polar codes which can enhance the performance to the same scale of successive cancellation list (SCL) without sacrificing decoding throughput. With reasonable complexity, the proposed EBPL decoding can achieve comparable BER and FER compared to SCL in simulation results.

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