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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Cao, Hua Chen, Jiazhong Huzhong Univ Sci & Technol Sch Software Engn Wuhan Peoples R China Huzhong Univ Sci & Technol Sch Comp Sci Wuhan Peoples R China

ISBN: (纸本)9781467345651;9780769549033

An important processing stage in computer vision such as recognizes an object is feature extraction. Among those feature extraction algorithms, Lowe proposed the scale-invariant feature transform (SIFT) algorithm has been considered as one of the robust approaches. But due to the implementation of the convolution search operation, the computing of SIFT algorithm is highly time-consuming. there are such problems as consuming too much power, sacrifice accuracy and lacking scalability for hardware-based acceleration scheme, it is still necessary to find the software-based acceleration approaches, especially for some applications and researches which need high-precision matched. Matlab is a general algorithm development environment with powerful image processing and other supporting toolboxes. With the rapid development of multicore CPU technology, using multicore computer and Matlab is an intuitive and simple way to speed up the computing for SIFT algorithm. In this paper, we try to have a view for using the Matlab parallel toolbox to accelerate the SIFT algorithm by two schemes of task-parallelism and data-parallelism modal. the results show that the parallel versions of former sequential algorithm with simple modifications achieve the speedup up to 6.6 times

关键词： Feature Extraction Scale-invariant Feature Transform(SIFT) Multicore Matlab parallel toolbox component

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Combination of XML-RPC and mobile agent technologies

Combination of XML-RPC and mobile agent technologies

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18th IASTED international conference on parallel and distributed computing and systems

作者： Motomura, Shinichi Kawamura, Takao Sugahara, Kazunori Tottori Univ Grad Sch Engn 4-101Koyama Minami Tottori Japan Tottori Univ Dept Informat & Knowledge Engn Tottori Japan

ISBN: (纸本)9780889866386

In this paper, we present usages of XML-RPC and the effectiveness in a mobile agent framework named Maglog which is implemented in a Java environment. XML-RPC is used for the following two purposes in Maglog. First, it is a transport mechanism that an agent migrates from one computer to another one. Second, it is an interface which is accessible from applications, written in any other language, which support for XML-RPC. In order to realize an agent migration mechanism, custom serialization mechanism is implemented to customize Java's built-in serialization mechanism. In custom serialization mechanism, objects which represent for an agent are encoded as an XML document. Encoded objects are transferred using XMLRPC. For deserialization, a dynamic class loader is implemented. If no custom serialization is used, an object cannot be deserialized on a remote host, because the class description of the object may not be in the host. As an example of an interface which is accessible from applications, we show a user interface program of a distributed e-Leaming system which we have developed.

关键词： distributed software systems and applications XML-RPC XML mobile agent Java

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A parallel H.264 Encoder with CUDA: Mapping and Evaluation

A Parallel H.264 Encoder with CUDA: Mapping and Evaluation

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Wu, Nan Wen, Mei Su, Huayou Ren, Ju Zhang, Chunyuan Natl Univ Def Technol Comp Sch Changsha Hunan Peoples R China

ISBN: (纸本)9781467345651

Efficient mapping of a real-time HD video application to graphics hardware is challenging. Developers face the challenges of choosing the right parallelism model, balancing thread's process granularity between massive computing resources on the GPU, and partitioning tasks between the CPU and GPU. the paper illustrated the mapping approaches by a case of HD H.264 encoderbased on X264 reference code and then evaluating it on state-of-the-art CPU and GPUs in depth. In the paper, we first split most of the computing task into Single-Instruction Multiple-thread (SIMT) kernels, which are then chained intocertaininput/output data stream. then we implementeda completedH.264 encoding on the computer unified device architecture (CUDA) platform. Finally, we present methods for exploiting multi-level parallelism and memory efficiency when mapping H.264 code, which we use to increase the efficiency of the execution on GPUs. Our experimental results show that computation efficiencyof GPU and then real-time encoding performance are achievedwith CUDA.

关键词： GPU Programming Video Processing parallel Algorithm Real Time Encode High-performance Media computing

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A Demo Paper: An Analytic Workflow Framework for Green Campus

A Demo Paper: An Analytic Workflow Framework for Green Campu...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Lee, Chonho Chaisiri, Sivadon Zoebir, Bong Chen, Changbing Lee, Bu-Sung Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore

ISBN: (纸本)9781467345651

this paper proposes a multi-tenant workflow framework that allows users to create data analytic workflows whose tasks are efficiently scheduled and distributed in cloud computing environment. We provide a demo of an event room assignment (ERA) as a test application of the framework. the ERA dynamically and automatically assigns registered events (e.g., meetings, classes, conferences, etc.) to available rooms meeting the user requirements such as the event size, purpose, reservation period, etc. the assignment will lead to the energy efficiency with respect to the power usage (e.g., lighting, ventilation, devices, etc.), and the energy savings can be achieved without affecting people's comfort. We run the ERA with power consumption data (whose size is approximately 50GB) collected from each of over 200 rooms in a building at Dept. of Engineering, Tokyo University. through the demonstration, we will show that the proposed framework accelerates the speed of data analysis by providing user-friendly workflow composition and parallel processing features utilizing cloud computing technologies.

关键词： Big Data Analytics Cloud computing Workflow Composition Cloud computing Energy Resources of Australia Evoked Response Audiometry European Union Agency for Railways Workflow User needs energy saving Energy efficiency Frameworks Power consumption Rooms

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Using approximation with time-parallel simulation

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SIMULATION-TRANSACTIONS OF thE SOCIETY FOR MODELING AND SIMULATION international 2005年第4期81卷 255-266页

作者： Kiesling, T Univ Bundeswehr Munchen Fak Informat D-85577 Neubiberg Germany

Temporal decomposition of simulation models, which is used in time-parallel simulation, is a promising alternative to classical spatial decomposition. It has been successfully applied to a small number of different models, most prominently for the simulation of computer caches and queuing systems. Unfortunately, widespread use is prevented by the state-match problem, which restricts the application of time-parallel simulation. Instead of a correct solution to the state-match problem, this work proposes the use of approximate solutions to facilitate the temporal decomposition of simulation models and to extend the class of models suitable for time-parallel simulation. However, this introduces an error in the simulation results, which might seriously distort or even invalidate results. therefore, the error must be closely analyzed, and a method of error control must be provided. In addition to the basic properties of approximate techniques in time-parallel simulation, this work presents two use cases that illustrate the introduced concepts.

关键词： simulation parallel computing time-parallel simulation approximate method

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UMR2: A better and more realistic scheduling algorithm for the Grid

UMR2: A better and more realistic scheduling algorithm for t...

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18th IASTED international conference on parallel and distributed computing and systems

作者： Loc, Nguyen the Elnaffar, Said Katayama, Takuya Bao, Ho Tu JAIST 1-1 Asahidai Nomi Ishikawa 9231292 Japan UAE Univ Coll IT Al Ain U Arab Emirates

ISBN: (纸本)9780889866386

Numerous studies have been targeting the problem of scheduling divisible workloads in distributed computing environments. the UMR (Uniform Multi-Round) algorithm stands out from all others by being the first close-form optimal scheduling algorithm. However, present algorithms, including the UMR, do not pay due attention to optimizing the set of workers that get selected to participate in processing workload chunks. In addition to the absence of a good resource selection policy, the UMR relies primarily in its computation on the CPU speed and overlooks the role of other key parameters such as network bandwidth. In this paper, we propose an extended version of UMR, called UMR2, that overcomes these limitations and adopts a worker selection policy that aims at minimizing the makespan. We, theoretically and experimentally, show that UMR2 is superior to UMR, specifically in a WAN computing platform such as the Grid.

关键词： divisible loads multi-round algorithms Grid computing

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Automatic VM Allocation for Scientific Application

Automatic VM Allocation for Scientific Application

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Pumma, Sarunya Achalakul, Tiranee Li Xiaorong King Mongkuts Univ Technol Thonburi Dept Comp Engn Bangkok Thailand Inst High Performance Comp Agcy Sci Res & Technol Singapore Singapore

ISBN: (纸本)9781467345651;9780769549033

Cloud has been the main technology utilized as a high performance computing (HPC) platform. the characteristics of cloud can satisfy a large scale processing required by scientific applications, which are mostly compute-intensive with big data. Cloud can also reduce the computing cost through sharing and virtualizing of resources. In the cloud, a large number of virtual machines (VM) can be generated on demands. In order to obtain the optimal cost and high efficiency in the task execution on the public cloud, the suitable amount of virtual machines should be properly determined prior to the start of the computation. Moreover, the application should be effectively partitioned and distributed onto the virtual machines. In this paper, we propose an automatic mechanism to allocate the optimal numbers of resources in the cloud. the novel resource estimation model and scheduling algorithm are presented. We select an analytic application with high level of computations in the field of epidemic forecast to demonstrate the use of the designed mechanism. Experimental studies have been conducted to examine the resource prediction accuracy and the scalability of running the application on the cloud.

关键词： cloud computing scheduling algorithm resource estimation resource allocation regression

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Design and Development of an Adaptive Workflow-Enabled Spatial-Temporal Analytics Framework

Design and Development of an Adaptive Workflow-Enabled Spati...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Li, Xiaorong Calheiros, Rodrigo N. Lu, Sifei Wang, Long Palit, Henry Zheng, Qin Buyya, Rajkumar A STAR Inst Inst High Performance Comp Singapore Singapore Univ Melbourne Dept Comp & Informat Syst Cloud Comp & Distributed Syst Lab Melbourne Vic Australia

ISBN: (纸本)9781467345651;9780769549033

Cloud computing is a suitable platform for execution of complex computational tasks and scientific simulations that are described in the form of workflows. Such applications are managed by Workflow Management System (WfMS). Because existing WfMSs are not able to autonomically provision resources to real-time applications and schedule them while supporting fault tolerance and data privacy, we present a highly-scalable workflow-enabled analytics system that manages inter-dependable analytics tasks adaptively with varying operational requirements on a common platform and enables visualization of multidimensional datasets of real world phenomena. In this paper, we present the architecture of such a WfMS and evaluate it in terms of performance for execution of workflows in Clouds. A real world application of climate-associated dengue fever prediction was evaluated on public, private, and hybrid Clouds and experienced effective speedup in all the environments.

关键词： cloud computing data privacy dynamic resource fault tolerance workflow

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Enhancing Cloud Object Storage Performance using Dynamic Replication Approach

Enhancing Cloud Object Storage Performance using Dynamic Rep...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Jindarak, Kanatorn Uthayopas, Putchong Kasetsart Univ Fac Engn Dept Comp Engn HPCNC Bangkok Thailand

ISBN: (纸本)9781467345651;9780769549033

the cloud storage is a new paradigm of data storage. Because of the internet connection speed increasing, everyone can store data on the cloud storage. Some data is shared for many user accesses, some data is private data. It has different characteristic of access pattern. In this work, the adaptive dynamic replication is presented. the model of dynamic replication is discussed. We propose the object-based storage as our cloud storage architecture. the storage object life time is used for handle our dynamic replication mechanism. the experimental results show the distribution of storage object workload that has some characteristic that relate with storage object life time and other factors.

关键词： cloud storage cloud computing object placement replication object-based storage

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Implementation of surface-to-surface contact algorithms using iterative solvers on parallel computers

Implementation of surface-to-surface contact algorithms usin...

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18th IASTED international conference on parallel and distributed computing and systems

作者： Kim, Eui Joong Laursen, Tod A. Samsung SDS IT R&D Ctr Seoul South Korea Duke Univ Dept Civil & Environm Engn Durham NC 27708 USA

ISBN: (纸本)9780889866386

In this work, we introduce a robust parallel surface-to-surface contact solution strategy for three dimensional frictional contact problems. A new algorithm is described which has improved overall capability with respect to numerical robustness and spatial convergence rates, showing also good parallel efficiency. In part because numerical methods for contact problems typically result in ill-conditioned and highly unsymmetric stiffness matrices, direct methods for equation solving have typically been preferred in such applications. However, for large-scale contact numerical modeling, the direct method appears to be limited by its requirements for memory and computation time, which scale with the number of unknowns n as )(n(1.5)) and O(n(2)), respectively. In this paper, we have implemented a parallel contact algorithm using iterative solution methods, and have applied it to several numerical examples using an Intel Xeon based Linux cluster and an HP-Compaq AlphaServer with up to 512 processors. Relatively good scalable performance has been observed in the applications tested.

关键词： mortar contact implicit dynamic/quasi-static problem parallel iterative solver

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