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A New Structured Peer-to-Peer Architecture Based on Physical Distance

A New Structured Peer-to-Peer Architecture Based on Physical...

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international conference on parallel and distributed systems (ICPADS)

作者： Song Wang Yong Ma Gang Wang Xiaoguang Liu The Equipment support Department Military Transportation University Tianjin China College of Information Technical Science Nankai-Baidu Joint Laboratory Nankai University Tianjin China

Recently, structured P2P (Peer-to-Peer) system has become more and more popular. However, P2P systems' large scale and high dynamics have brought a great challenge to data availability and accessing performance. Redundancy techniques are used to solve these problems. However, in structured P2P systems, due to the consistent hash, the overlay network could not match underlying physical network well. The nodes close to each other in the overlay network may have long distances of physical network. In this paper, we put forward a new P2P architecture that constructs node identifiers and places redundant data according to physical location information. It can provide better load balance and access performance. The node's identifier is divided into four parts, representing the node's state, ISP, city and IP respectively, so the nodes having similar identifiers are close to each other in the physical network. Moreover, a query tree is used to help a node routing queries quickly in the physical network. In addition, we maintain an access list for each file. When a node becomes overloaded, replicas are placed on another node selected in the routing path according to the access list, so subsequent access requests could be met in advance.

关键词： Peer to peer computing Delay Cities and towns Routing Computer architecture IP networks Redundancy

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Advances in e-Infrastructures for computational sciences and engineering

Advances in e-Infrastructures for computational sciences and...

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ACS/IEEE international conference on Computer systems and Applications

作者： Wolfgang Gentzsch Open Grid Forum DEISA-Distributed European Initiative of Supercomputing Applications Germany

Summary form only: Over the last 50 years, computational sciences and engineering have advanced the development of new and ever faster and better computers, algorithms, and software tools, and vice versa, computers have advanced sciences. But the better the technologies the more demanding our computational science applications. This progress is everywhere, at the level of technologies and computer architectures, at the middleware level, at the algorithm and application level, and even at the level of computing paradigms, where we evolved from mainframes, to vector and parallel computers, to grids and clouds, recently. We successfully optimized our algorithms and mapped them to the underlying architecture, e.g. with overlapping communication with computation, better load balancing through domain decomposition into parallel processes, or using library routines optimized for the specific architecture and processors. In our presentation, we will concentrate on the use of grid and cloud technologies for HPC, focusing on the European EU-funded DEISA distributed European Infrastructure for Supercomputing Applications project, analyzing different HPC loads and their suitability for grids and for clouds, and taking a closer look at lessons learned and recommendations on how to build sustainable e-Infrastructures for computational sciences and engineering in the future.

关键词： Europe

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Flexible Clusters for High-Performance computing

Flexible Clusters for High-Performance Computing

引用

IEEE international conference on High Performance computing and Communications (HPCC)

作者： Paolo Anedda Massimo Gaggero Giovanni Busonera Omar Schiaratura Gianluigi Zanetti Distributed Computing Group CRS4 Pula Italy

High Performance Computational Clusters are, in general, rather rigid objects that present to their user a limited number of degrees of freedom related, usually, only to the specification of the resources requested and to the selection of specific applications and libraries. While in standard production environments this is reasonable and actually desirable, it can become an hindrance when one needs a dynamic and flexible computational environment, for instance for experiments and evaluation, where very different computational approaches, e.g., map-reduce, standard parallel jobs and virtual HPC clusters need to coexist on the same physical facility. In this paper we will present our efforts to address some of these challenges while maintaining a unified cluster management environment.

关键词： Hardware Virtual machining Computer architecture Performance evaluation Operating systems Graphics processing unit

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Optimizing Service Level Agreements for Autonomic Cloud Bursting Schedulers

Optimizing Service Level Agreements for Autonomic Cloud Burs...

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international conference on parallel Processing Workshops (ICPPW)

作者： Sriram Kailasam Nathan Gnanasambandam Janakiram Dharanipragada Naveen Sharma Distributed and Object Systems Laboratory Department of Comp. Science and Engineering Indian Institute of Technology Madras Chennai India Xerox Research Center Webster Xerox Corporation Webster NY USA

The practice of computing across two or more data centers separated by the Internet is growing in popularity due to an explosion in scalable computing demands and pay-as-you-go schemes offered on the cloud. While cloud-bursting is addressing this process of scaling up and down across data centers (i.e. between private and public clouds), offering service level guarantees, is a challenge for inter-cloud computation, particularly for best-effort traffic and large files. The parallel workload we address is real-time and involves inter-cloud processing and analysis of images and documents. In our production printing domain, dedicated processing/network resources are cost-prohibitive. Further, the problem is exacerbated by data intensive computing - we encounter huge file sizes atypical of intercloud parallel processing. To address these problems we propose three flavors of autonomic cloud-bursting schedulers that offer probabilistic guarantees on service levels required by customers (such as speed-up and queue sequence preservation) by adapting to changing workload characteristics, variation in bandwidth and available resources. In particular, these opportunistic schedulers use a quadratic response surface model for processing time in concert with a time-of-day dependent bandwidth predictor to increase the throughput and utilization while simultaneously reducing out-of-sequence completions for a document processing workload.

关键词： Clouds Bandwidth Integrated circuits Measurement Out of order Response surface methodology Real time systems

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Hybrid programming implementation and analysis of CG method in high-performance cluster

Hybrid programming implementation and analysis of CG method ...

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international conference on Computer Design and Applications (ICCDA)

作者： Lijuan Shi Weifeng Shi School of Information Science and Technology Northwest University Xi'an China

ISBN: (纸本)9781424471645;9781424471638

CG Method is the most prominent iterative method for solving sparse systems of linear equations. Implementing the CG method in high-performance cluster has practical significance in many fields such as science and engineering. The advantages of using hybrid MPI+OpenMP programming in high-performance cluster are full use of cluster's features between the nodes with a distributed storage and within nodes shared storage. Coarse-grained message passing communication is implemented by MPI between the nodes. Fine-grained shared-memory communication is implemented by OpenMP within the nodes, which reduces the running time of parallel algorithm.

关键词： Character generation Equations parallel programming Message passing Libraries Blades Linear programming Information science Concurrent computing

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A Stack-on-Demand Execution Model for Elastic computing

A Stack-on-Demand Execution Model for Elastic Computing

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international conference on parallel Processing (ICPP)

作者： Ricky K. K. Ma King Tin Lam Cho-Li Wang Chenggang Zhang Department of Computer Science University of Hong Kong Hong Kong China

Cloud computing is all the rage these days; its confluence with mobile computing would bring an even more pervasive influence. Clouds per se are elastic computing infrastructure where mobile applications can offload or draw tasks in an on-demand push-pull manner. Lightweight and portable task migration support enabling better resource utilization and data access locality is the key for success of mobile cloud computing. Existing task migration mechanisms are however too coarse-grained and costly, offsetting the benefits from migration and hampering flexible task partitioning among the mobile and cloud resources. We propose a new computation migration technique called stack-on-demand (SOD) that exports partial execution states of a stack machine to achieve agile mobility, easing into small-capacity devices and flexible distributed execution in a multi-domain workflow style. Our design also couples SOD with a novel object faulting technique for efficient access to remote objects. We implement the SOD concept into a middleware system for transparent execution migration of Java programs. It is shown that SOD migration cost is pretty low, comparing to several existing migration mechanisms. We also conduct experiments with an iPhone handset to demonstrate the elasticity of SOD by which server-side heavyweight processes can run adaptively on the cell phone.

关键词： Java Mobile communication Clouds Message systems Cloud computing Computational modeling Runtime

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Making Human Connectome Faster: GPU Acceleration of Brain Network Analysis

Making Human Connectome Faster: GPU Acceleration of Brain Ne...

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international conference on parallel and distributed systems (ICPADS)

作者： Di Wu Tianji Wu Yi Shan Yu Wang Yong He Ningyi Xu Huazhong Yang Department of Electronic Engineering Tsinghua National Laboratory of Information Science and Technology Tsinghua University China State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University China Hardware Computing Group Microsoft Research Asia China

The research on complex Brain Networks plays a vital role in understanding the connectivity patterns of the human brain and disease-related alterations. Recent studies have suggested a noninvasive way to model and analyze human brain networks by using multi-modal imaging and graph theoretical approaches. Both the construction and analysis of the Brain Networks require tremendous computation. As a result, most current studies of the Brain Networks are focused on a coarse scale based on Brain Regions. Networks on this scale usually consist around 100 nodes. The more accurate and meticulous voxel-base Brain Networks, on the other hand, may consist 20K to 100K nodes. In response to the difficulties of analyzing large-scale networks, we propose an acceleration framework for voxel-base Brain Network Analysis based on Graphics Processing Unit (GPU). Our GPU implementations of Brain Network construction and modularity achieve 24x and 80x speedup respectively, compared with single-core CPU. Our work makes the processing time affordable to analyze multiple large-scale Brain Networks.

关键词： Graphics processing unit Correlation Algorithm design and analysis Instruction sets Sparse matrices Eigenvalues and eigenfunctions Hardware

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Non-fragile control for a class of networked switched fuzzy time-delay systems

Non-fragile control for a class of networked switched fuzzy ...

引用

international conference on Machine Learning and Cybernetics (ICMLC)

作者： Yi Liu Li-Ying Sun Computing Center Liaoning University of Technology Jinzhou China Electric Engineering College Liaoning University of Technology Jinzhou China

The stabilization problem of a class of networked switched fuzzy time-delay systems is investigated under the assumption that the controller gain to be designed has variations, single-packet transmission, and network-induced delay less than one sampling period. The design method of the non-fragile state-feedback controllers and the switched laws is proposed based on parallel distributed compensation method and the multiple Lyapunov functions technique, such that the networked uncertain switched fuzzy time-delay system is globally asymptotically stable. A sufficient condition for the existence of non-fragile state-feedback controllers is given in terms of matrix inequalities. Simulation results show the effectiveness of the design method.

关键词： Switches Networked control systems Linear matrix inequalities Cybernetics Lyapunov method Fuzzy systems

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Towards a Network-Independent Policy Specification

Towards a Network-Independent Policy Specification

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Euromicro conference on parallel, distributed and Network-Based Processing

作者： Cataldo Basile Antonio Lioy Marco Vallini Dipartimento di Automatica e Informatica Politecnico di Torino Italy

A very ambitious objective in the field of policy-based systems is the provision of an intuitive and transparent way for policy specification, refinement and enforcement. This is one of the key enabling technologies for a simplified security management of complex networked environments. Currently, security policies are enforced by configuring the end devices by means of low-level device-specific parameters manually derived from high level specifications. This process, defined as policy translation, is still performed without a holistic view of the overall security requirements. This paper presents the Network Contextualization Tool (NCTool), a software supporting administrators in performing network dependent activities when configuring security enabled devices. The tool provides a great advantage in the management of complex networks. In fact, it simplifies the network administration tasks and reduces effort and responsibilities for the administrators, thus decreasing the risk of mistaken configurations.

关键词： Computer science Collaborative work Social network services Databases Information analysis Computer networks Telecommunication computing Software libraries international collaboration Laboratories

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parallel Simultaneous Co-clustering and Learning with Map-Reduce

Parallel Simultaneous Co-clustering and Learning with Map-Re...

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IEEE international conference on Granular computing (GRC)

作者： Meghana Deodhar Clinton Jones Joydeep Ghosh Electrical and Computer Engineering University of Texas Austin Austin TX USA

Many data mining applications involve predictive modeling of very large, complex datasets. Such applications present a need for innovative algorithms and associated implementations that are not only effective in terms of prediction accuracy, but can also be efficiently run on distributed computational systems to yield results in reasonable time. This paper focuses on predictive modeling of multirelational data such as dyadic data with associated covariates or “side-information”. We first give illustrative examples of applications that involve such data and then describe a general framework based on Simultaneous CO-clustering And Learning (SCOAL), which applies a divide-and-conquer approach to data analysis. We show that the main elements of the SCOAL algorithm can be effectively parallelized using the Map-Reduce framework. Experiments on Amazon's EC2 demonstrate that the proposed parallelizations result in considerable improvements in run time when using a cluster of machines.

关键词： Data models Computational modeling Predictive models Clustering algorithms Motion pictures Data mining Prediction algorithms

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