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检索条件"任意字段=International Conference on Advances in Parallel and Distributed Computing"

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Performance Evaluation for a PETSc parallel-in-Time Solver Based on the MGRIT Algorithm 24th

Performance Evaluation for a PETSc Parallel-in-Time Solver B...

引用

international European conference on parallel and distributed computing (Euro-Par)

作者： Mele, Valeria Romano, Diego Constantinescu, Emil M. Carracciuolo, Luisa D'Amore, Luisa Univ Naples Federico II Naples Italy CNR Italian Natl Res Council Rome Italy Argonne Natl Lab Math & Comp Sci Div Chicago IL USA

ISBN: (纸本)9783030105495;9783030105488

We herein describe the performance evaluation of a modular implementation of the MGRIT (MultiGrid-In-Time) algorithm within the context of the PETSc (the Portable, Extensible Toolkit for Scientific computing) library. Our aim is to give the PETSc users the opportunity of testing the MGRIT parallel-in-time approach as an alternative to the Time Stepping integrator (TS), when solving their problems arising from the discretization of linear evolutionary models. To this end, we analyzed the performance parameters of the algorithm in order to underline the relationship between the configuration factors and problem characteristics, intentionally overlooking any accuracy issue and spacial parallelism.

关键词： parallelism-in-time Performance evaluation Multigrid reduction MGRIT Linear systems PETSc

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HIGHLY parallel MULTI-PHYSICS SIMULATION OF MUSCULAR ACTIVATION AND EMG 8

HIGHLY PARALLEL MULTI-PHYSICS SIMULATION OF MUSCULAR ACTIVAT...

引用

8th international conference on Computational Methods for Coupled Problems in Science and Engineering (COUPLED)

作者： Maier, B. Emamy, N. Kraemer, A. Mehl, M. Univ Stuttgart Inst Parallel & Distributed Syst Univ Str 38 D-70569 Stuttgart Germany Univ Stuttgart Inst Appl Anal & Numer Simulat Allmandring 5b D-70569 Stuttgart Germany

ISBN: (纸本)9788494919459

Simulation of skeletal muscle activation can help to interpret electromyographic measurements and infer the behavior of the muscle fibers. Existing models consider simplified geometries or a low number of muscle fibers to reduce the computation time. We demonstrate how to simulate a finely-resolved model of biceps brachii with a typical number of 270.000 fibers. We have used domain decomposition to run simulations on 27.000 cores of the supercomputer HazelHen at HLRS in Stuttgart, Germany. We present details on opendihu, our software framework. Its configurability, efficient data structures and modular software architecture target usability, performance and extensibility for future models. We present good parallel weak scaling of the simulations.

关键词： Musculo-skeletal High Performance computing Multi-scale

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A Fire Flame Simulation Scheme with Massively parallel Processing 4th

A Fire Flame Simulation Scheme with Massively Parallel Proce...

引用

4th international conference on Big Data Applications and Services ( (BigDAS)

作者： Im, Byeonguk Baek, Nakhoon Kyungpook Natl Univ Sch Comp Sci & Engn Daegu 41566 South Korea Kyungpook Natl Univ Software Technol Res Ctr Daegu 41566 South Korea Dassomey Com Inc Daegu 41566 South Korea

ISBN: (纸本)9789811306952;9789811306945

Simulating natural phenomena is one of the most important areas in computer graphics area. As one of the natural phenomena simulations, we focused on the simulation of fire flames. Previous fire flame simulations mainly focused on the simulation sequences. At this time, those methods are not suitable for modern computer graphics and massively parallel processing architectures. In this work, we present a prototype implementation of the fire flame simulation system, based on the Compute Unified Device Architecture (CUDA) and Open Graphics Library (OpenGL). Our system shows highly efficient execution of those simulations, to show the real-time fire flame simulations.

关键词： Fire flame Simulation Massively parallel

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On distributed information composition in big data systems 15

On distributed information composition in big data systems

引用

15th IEEE international conference on eScience, eScience 2019

作者： Alquwaiee, Haifa He, Songlin Wu, Chase Tang, Qiang Shen, Xuewen Department of Computer Science New Jersey Institute of Technology NewarkNJ07102 United States School of Electronics and Information Communication University of Zhejiang Hangzhou Zhejiang310018 China

ISBN: (纸本)9781728124513

Modern big data computing systems exemplified by Hadoop employ parallel processing based on distributed storage. The results produced by parallel tasks such as computing modules in scientific workflows or reducers in the MapReduce framework are typically stored in a distributed file system across multiple data nodes. However, most existing systems do not provide a mechanism to compose such distributed information, as required by many big data applications. We construct analytical cost models and formulate a distributed Information Composition problem in Big Data Systems, referred to as DIC-BDS, to aggregate multiple datasets stored as data blocks in Hadoop distributed File System (HDFS) using a composition operator of specific complexity to produce one final output. We rigorously prove that DIC-BDS is NP-complete, and propose two heuristic algorithms: Fixed-window distributed Composition Scheme (FDCS) and Dynamic-window distributed Composition Scheme with Delay (DDCS-D). We conduct extensive experiments in Google clouds with various composition operators of commonly considered degrees of complexity including O(n), O(n log n), and O(n2). Experimental results illustrate the performance superiority of the proposed solutions over existing methods. Specifically, FDCS outperforms all other algorithms in comparison with a composition operator of complexity O(n) or O(n log n), while DDCS-D achieves the minimum total composition time with a composition operator of complexity O(n2). These algorithms provide an additional level of data processing for efficient information aggregation in existing workflow and big data systems. © 2019 IEEE.

关键词： Heuristic algorithms

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Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format

Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs ...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Shaohuai Shi Qiang Wang Xiaowen Chu The Hong Kong University of Science and Technology Hong Kong Baptist University

ISBN: (数字)9781728190747

ISBN: (纸本)9781728183824

Multiplication of a sparse matrix to a dense matrix (SpDM) is widely used in many areas like scientific computing and machine learning. However, existing work under-looks the performance optimization of SpDM on modern manycore architectures like GPUs. The storage data structures help sparse matrices store in a memory-saving format, but they bring difficulties in optimizing the performance of SpDM on modern GPUs due to irregular data access of the sparse structure, which results in lower resource utilization and poorer performance. In this paper, we refer to the roofline performance model of GPUs to design an efficient SpDM algorithm called GCOOSpDM, in which we exploit coalescent global memory access, fast shared memory reuse, and more operations per byte of global memory traffic. Experiments are evaluated on three Nvidia GPUs (i.e., GTX 980, GTX Titan X Pascal, and Tesla P100) using a large number of matrices including a public dataset and randomly generated matrices. Experimental results show that GCOOSpDM achieves 1.5-8x speedup over Nvidia's library cuSPARSE in many matrices.

关键词： Scientific computing Memory management Machine learning Libraries Sparse matrices Resource management Optimization

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Deep Learning for Satellite Image Classification 4th

Deep Learning for Satellite Image Classification

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4th international conference on Advanced Intelligent Systems and Informatics (AISI)

作者： Shafaey, Mayar A. Salem, Mohammed A. -M. Ebied, H. M. Al-Berry, M. N. Tolba, M. F. Ain Shams Univ Fac Comp & Informat Sci Cairo Egypt German Univ Fac Media Engn & Technol Cairo Egypt

ISBN: (纸本)9783319990101;9783319990095

Nowadays, large amounts of high resolution remote-sensing images are acquired daily. However, the satellite image classification is requested for many applications such as modern city planning, agriculture and environmental monitoring. Many researchers introduce and discuss this domain but still, the sufficient and optimum degree has not been reached yet. Hence, this article focuses on evaluating the available and public remote-sensing datasets and common different techniques used for satellite image classification. The existing remote-sensing classification methods are categorized into four main categories according to the features they use: manually feature-based methods, unsupervised feature learning methods, supervised feature learning methods, and objectbased methods. In recent years, there has been an extensive popularity of supervised deep learning methods in various remote-sensing applications, such as geospatial object detection and land use scene classification. Thus, the experiments, in this article, carried out on one of the popular deep learning models, Convolution Neural Networks (CNNs), precisely AlexNet architecture on a standard sounded dataset, UC-Merceed Land Use. Finally, a comparison with other different techniques is introduced.

关键词： Remote-sensing Satellite image Deep learning Convolution Neural Networks (CNNs) UC-Merceed Land Use parallel computing

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Text Extraction from videos using MapReduce

Text Extraction from videos using MapReduce

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international conference on Intelligent computing and Control Systems (ICCS)

作者： Roshan, Chanchal Kumar Kaushal, Rajeet Alam, Sha Rai, Shashank Gholap, Yuvraj Army Inst Technol Dept Informat Technol Pune Maharashtra India

ISBN: (纸本)9781538681138

Due to recent outbursts in the number of point and shoot devices. The data generated in the form of raw video has also increased exponentially. On YouTube alone, 300 hours of video alone is added every minute. This brings up the need of coming up with a long term solutions to tackle such behemoth tasks. The solution should be flexible, robust with ability to scale up and down dynamically as and when required. Needless to say, such system have a high cost and it is also of utmost importance to consider the cost factor and feasibility. Hadoop is one such framework which met all our requirements. It provides facility to distribute a big and complex task to low as well as high end computers to achieve a common goal. Hadoop is a highly scalable storage platform, because it can store and distribute very large data sets across hundreds of inexpensive servers that operate in parallel. Another advantage of using a Hadoop cluster is that it is fault tolerance as copies of the data are made and can be used in case of failure of a node. etc

关键词： Text extraction Hadoop distributed computing Image Processing

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Delay Optimization for Mobile Cloud computing Application Offloading in Smart Cities 12th

Delay Optimization for Mobile Cloud Computing Application Of...

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12th international conference on Innovative Mobile and Internet Services in Ubiquitous computing (IMIS)

作者： Guo, Shan Wang, Ying Meng, Sachula Ma, Nan Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

ISBN: (纸本)9783319935546;9783319935539

In smart cites, more and more smart mobile devices (SMDs) have many computation-intensive applications to be processed. Mobile cloud computing (MCC) as an effective technology can help SMDs reduce their energy consumption and processing delay by offloading the tasks on the distributed cloudlet. However, due to long transmission delay resulting from the unstable wireless environment, the SMD may be out of the serving area before the cloudlet transmits responses to the user. Thus, delay is a crucial problem for the MCC offloading. In this paper, we consider a multi-SMDs MCC system, where each SMD having an application to be offloaded asks for computation offloading to a cloudlet. In order to minimize the total delay of the SMDs in the system, we jointly take the offloading cloudlet selection, wireless access selection, and computation resource allocation into consideration. We formulate the total delay minimization problem as a mixed integer nonlinear programming (MINLP) problem which is NP-hard. We propose an improved genetic algorithm to obtain a local optimal result. Simulation results demonstrated that our proposal could effectively reduce the system delay.

关键词： Mobile cloud computing

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Efficient Load Balancing and Integration Protocols for Mobile Cloud computing in Disaster Situations 12th

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12th international conference on Complex, Intelligent, and Software Intensive Systems (CISIS)

作者： Shibata, Yoshitaka Otomo, Masaki Sato, Goshi Uchida, Noriki Iwate Prefectural Univ Takizawa Iwate 0200611 Japan NICT Resilient ICT Res Ctr Aoba Ku 2-1-3 Katahira Sendai Miyagi Japan Fukuoka Inst Technol Higashi Ku 3-30-1 Wajiro Higashi Fukuoka Japan

ISBN: (纸本)9783319936598;9783319936581

At the occurrence of large-scale disasters, many regions were isolated from critical information exchanges due to the damages on communication and information infrastructures. In those serious disasters, quick and flexible disaster recovery network and computing system is required to deliver the disaster related information after disaster. In this paper, mobile cloud computing for information exchange among isolated shelters is introduced. The vehicle with mobile cloud server traverses the isolated shelters and exchanges information and returns to the disaster headquarter which is connected to cloud computing through Internet. DTN function is introduced to store, carry and exchange messages as a message ferry among the shelters even in the challenged network environment where wired and wireless communication links are completely damaged. The prototype system of mobile vehicle computing is constructed to evaluate the effects of proposed system.

关键词： Disaster information Resilient network Mobile cloud distributed system

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Design and Implementation of High Performance Cryptographic Service Framework Based on TrustZone

Design and Implementation of High Performance Cryptographic ...

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Information Science, parallel and distributed Systems (ISPDS), international conference on

作者： Lu Yuan Chenlin Huang Lulu Wang Yan Ding Yun Li Hua Cheng Academy of Computer Science National University of Defense Technology Changsha China 31618 Troops Fuzhou China Key Laboratory of Mathematical Engineering and advanced computing Wuxi China

ISBN: (数字)9781728196688

ISBN: (纸本)9781728196695

Due to its favorable isolation and security features, TrustZone technology has been widely used in mobile payment, cloud computing, Internet of Things, etc. However, the cryptographic algorithm provided by the trusted execution environment such as Open-TEE and OP-TEE is inadequate, which brings inconvenience to the development of trusted applications. In addition, the system mainly uses the software algorithms to provide cryptographic services and does not make full use of hardware cryptographic resources, which results in the low efficiency of cryptographic service. To Figure out these two issues, aiming at features of domestic Phytium processors, this paper establishes a unified cryptographic service framework in the TrustZone platform to build a more rich and complete cryptographic algorithm library. Meanwhile, it makes full use of the hardware cryptographic resources of the processor platform to improve the performance of cryptographic service. Test result shows that the proposed framework can bring significant convenience to the development of trusted applications. Meanwhile, compared with the original cryptographic service performance, the cryptographic service provided by the new framework can achieve significant performance improvement.

关键词： Cryptography Routing Performance evaluation Information science

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