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检索条件"任意字段=International Symposium on Parallel and Distributed Computing"

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Meteor Shower: A Reliable Stream Processing System for Commodity Data Centers

Meteor Shower: A Reliable Stream Processing System for Commo...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Huayong Wang Li-Shiuan Peh Emmanouil Koukoumidis Shao Tao Mun Choon Chan Computer Science and Artificial Intelligence Laboratory MIT USA School of Computing National University of Singapore Singapore

ISBN: (纸本)9781467309752

Large-scale failures are commonplace in commodity data centers, the major platforms for distributed Stream Processing Systems (DSPSs). Yet, most DSPSs can only handle single-node failures. Here, we propose Meteor Shower, a new fault-tolerant DSPS that overcomes large-scale burst failures while improving overall performance. Meteor Shower is based on checkpoints. Unlike previous schemes, Meteor Shower orchestrates operators' check pointing activities through tokens. The tokens originate from source operators, trickle down the stream graph, triggering each operator that receives these tokens to checkpoint its own state. Meteor Shower is a suite of three new techniques: 1) source preservation, 2) parallel, asynchronous check pointing, and 3) application-aware check pointing. Source preservation allows Meteor Shower to avoid the overhead of redundant tuple saving in prior schemes, parallel, asynchronous check pointing enables Meter Shower operators to continue processing streams during a checkpoint, while application-aware check pointing lets Meteor Shower learn the changing pattern of operators' state size and initiate checkpoints only when the state size is minimal. All three techniques together enable Meteor Shower to improve throughput by 226% and lower latency by 57% vs prior state-of-the-art. Our results were measured on a prototype implementation running three real world applications in the Amazon EC2 Cloud.

关键词： Checkpointing Cameras Digital signal processing Fault tolerance Fault tolerant systems Throughput

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The Necessity for Strong Reciprocators in Mobile Ad Hoc Networks

The Necessity for Strong Reciprocators in Mobile Ad Hoc Netw...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Marcin Seredynski Grégoire Danoy Pascal Bouvry Interdisciplinary Centre for Security Reliability and Trust University of Luxembourg Luxembourg Luxembourg Faculty of Sciences Technology and Communication University of Luxembourg Luxembourg Luxembourg

In civilian mobile ad hoc networks behaviour of network participants in accordance with the collective interest cannot be guaranteed. The cooperation in packet forwarding can emerge if the reciprocal tit-for-tat (TFT) principle is commonly used. This induces the nodes with self-regarding preferences to act cooperatively. However, as demonstrated in this paper, in certain conditions costs of using a reciprocal forwarding are greater than benefits. In such a case, the cooperation can emerge only if nodes with specific behaviour called strong reciprocity are present in the network. This paper analyses such conditions using a nature-inspired evolutionary approach. The computational experiments demonstrate that as soon as at least approximately 70% of nodes follow the TFT-principle in packet forwarding, benefits of its use exceed costs, regardless the forwarding behaviour of the remaining nodes. Consequently, strong reciprocators are not required for sustaining cooperative network. Below that threshold, the need for strong reciprocators depends on the composition of the remaining nodes. In particular, it is positively correlated with the number of unconditionally cooperative nodes as these nodes create incentives for free-riding behaviour.

关键词： Thin film transistors Mobile computing Relays Knowledge based systems Mobile ad hoc networks

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DMSS: A Dynamic Memory Scheduling System in Server Consolidation Environments

DMSS: A Dynamic Memory Scheduling System in Server Consolida...

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IEEE international symposium on Object/Component/Service-Oriented Real-Time distributed computing Workshops (ISORCW)

作者： Lanzheng Liu Rui Chu Yongchun Zhu Pengfei Zhang Liufeng Wang National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Systems and Technology Group IBM China Beijing China

As the foundation of cloud computing, Server consolidation allows multiple computer infrastructures running as virtual machines in a single physical node. It improves the utilization of most kinds of resource but memory under x86 architecture. Because of inaccurate memory usage estimate and the lack of memory resource management, there is much service performance degradation in data centers, even though they have occupied a large amount of memory. Furthermore, memory becomes insufficient for a physical server when a lot of virtual machines depend on it. In order to improve this, we present a dynamic memory scheduling system called DMSS, which can manage memory resources in server consolidation environments and allocate memory among virtual machines on demand. We have designed and implemented the corresponding memory scheduling policy based on Xen virtualization platform to enhance memory efficiency and achieve service level agreement. The benchmark shows that DMSS can make an accurate and rapid response to memory changes and save more than 30% physical memory with less than 5% performance degradation. DMSS actually brings in economic benefits to cloud service providers because more virtual machines can be accommodated at lower costs.

关键词： Memory management Virtual machine monitors Monitoring Resource management Servers Dynamic scheduling Degradation

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Predicting Potential Speedup of Serial Code via Lightweight Profiling and Emulations with Memory Performance Model

Predicting Potential Speedup of Serial Code via Lightweight ...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Minjang Kim Pranith Kumar Hyesoon Kim Bevin Brett School of Computer Science College of Computing Georgia Institute of Technology Atlanta GA USA Software and Services Group Intel Corporation Nashua NH USA

ISBN: (纸本)9781467309752

We achieve very small runtime overhead: approximately a 1.2-10 times slowdown and moderate memory consumption. We demonstrate the effectiveness of parallel Prophet in eight benchmarks in the Omp SCR and NAS parallel benchmarks by comparing our predictions with actual parallelized code. Our simple memory model also identifies performance limitations resulting from the memory system contention. We present parallel Prophet, which projects potential parallel speedup from an annotated serial program before actual parallelization. Programmers want to see how much speedup could be obtained prior to investing time and effort to write parallel code. With parallel Prophet, programmers simply insert annotations that describe the parallel behavior of the serial program. parallel Prophet then uses lightweight interval profiling and dynamic emulations to predict potential performance benefit. parallel Prophet models many realistic features of parallel programs: unbalanced workload, multiple critical sections, nested and recursive parallelism, and specific thread schedulings and paradigms, which are hard to model in previous approaches. Furthermore, parallel Prophet predicts speedup saturation resulting from memory and caches by onitoring cache hit ratio and bandwidth consumption in a serial program. We achieve very small runtime overhead: approximately a 1.2-10 times slowdown and moderate memory consumption. We demonstrate the effectiveness of parallel Prophet in eight benchmarks in the OmpSCR and NAS parallel benchmarks by comparing our predictions with actual parallelized code. Our simple memory model also identifies performance limitations resulting from memory system contention.

关键词： Emulation parallel processing Analytical models Predictive models Instruction sets Radiation detectors Prediction algorithms

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A Utility Based Power-Aware Autonomic Approach for Running Scientific Applications

A Utility Based Power-Aware Autonomic Approach for Running S...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Rajat Mehrotra Ioana Banicescu Srishti Srivastava Department of Electrical and Computer Engineering Mississippi State University USA Department of Computer Science and Engineering NSF Center for Autonomic Computing Mississippi State University USA

ISBN: (纸本)9781467309745

Traditionally, computational power and performance of the high performance computing (HPC) systems are assumed to depend upon the number of processors and speed of supercomputers. Supercomputers run at their peak performance to efficiently execute scientific applications. Therefore, these supercomputers consume enormous amount of power that results in increased operational cost. The high power consumption translates into high temperature of the physical HPC systems, which in turn results in high failure rate and decreased reliability. Employing an aggressive cooling system does not improve the situation, because it involves an additional operational and infrastructure cost. Slowing down these HPC systems results in loss of performance that is also not recommended. Moreover, the execution of scientific applications is affected adversely through the variation in available computational resources. This variation is due to the computational resource utilization by other applications running at the computing nodes. Therefore, the execution of a scientific application should be monitored with respect to its performance objectives (deadline etc.). Failure in meeting the deadlines may result in high cost in terms of revenue loss to the service providers. These issues raise the motivation towards the designing of an autonomic approach for managing power consumption in HPC systems without adversely affecting to the performance of the system. In this paper, we present a utility based power-aware approach that uses a model-based control theoretic framework for executing scientific applications. The approach and related simulations indicate that the performance and the power requirements of the system can dynamically be adjusted, while maintaining the predefined quality of service (QoS) goals in terms of deadline of execution and power consumption of the HPC system, even in the presence of computational resource related perturbations. This approach is autonomic, performance dire

关键词： Program processors Power demand Processor scheduling Dynamic scheduling Quality of service Availability Job shop scheduling

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Provisioning Policies for Elastic computing Environments

Provisioning Policies for Elastic Computing Environments

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Paul Marshall Henry Tufo Kate Keahey Department of Computer Science University of Colorado Boulder CO USA National Center for Atmospheric Research Boulder CO USA Argonne National Laboratory Argonne IL USA

ISBN: (纸本)9781467309745

Resources experience dynamic load as demand fluctuates. Therefore, resource providers must estimate the appropriate amount of resources to purchase in order to meet variable user demand. With the relatively recent introduction of infrastructure-as-a-service (IaaS) clouds (e.g. Amazon EC2) resource providers may choose to outsource demand as needed. As a result, a resource provider may decide to decrease his initial capital outlay and purchase a smaller resource that meets the needs of his users the majority of the time while budgeting for future outsourcing costs. When bursts in demand exceed the capacity of the resource, a resource provider can use elastic computing to outsource excess demand to IaaS clouds based on a defined budget. To create efficient elastic environments, existing services must be extended with elastic computing functionality and resource provisioning policies that match resource deployments with demand must be developed. In this paper we consider an elastic environment that extends a local cluster resource with IaaS resources. We present resource provisioning policies to dynamically match resource supply with demand. Our policies balance the requirements of users and administrators, such as minimizing the monetary cost of the IaaS deployment and reducing job queued time. We develop a discrete event simulator, the elastic cloud simulator (ECS), to evaluate our policies using scientific workloads. Our results demonstrate that by outsourcing on a flexible basis instead of simply provisioning the maximum number of instances preemptively, we reduce the average queued time by up to 58% and cost by 38%. Our results also demonstrate that our multi-variable policies provide more flexibility in balancing budget and time requirements than typical single-variable reference policies, giving resource providers controls to manage their elastic environments.

关键词： Genetic algorithms Resource management Outsourcing Standards Computational modeling Torque Optimization

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Proceedings - 2011 10th international symposium on distributed computing and Applications to Business, Engineering and Science, DCABES 2011

Proceedings - 2011 10th International Symposium on Distribut...

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2011 10th international symposium on distributed computing and Applications to Business, Engineering and Science, DCABES 2011

ISBN: (纸本)9780769544151

The proceedings contain 92 papers. The topics discussed include: parallel domain decomposition methods for ray-tracing on multi-cores and multi-processors;the research of Q learning-based estimation of distribution algorithm;chaotic relaxation asynchronous iterative parallel algorithm and its implementation;coupling the parareal algorithm with the waveform relaxation method for the solution of differential algebraic equations;the research of feature selection of text classification based on integrated learning algorithm;formal support for cyber physical system specification using aspect-oriented approach;moment problem of G-frames in Hilbert spaces;a highly practicable distributed architecture of network stream media;parallel implementation of fractal image compression in web service environment;a new carry-free adder model for ternary optical computer;and a web page classification algorithm based on link information.

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LDPLFS: Improving I/O Performance without Application Modification

LDPLFS: Improving I/O Performance without Application Modifi...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： S.A. Wright S.D. Hammond S.J. Pennycook I. Miller J.A. Herdman S.A. Jarvis Performance Computing and Visualisation Department of Computer Science University of Warwick UK Scalable Computer Architectures/CSRI Sandia National Laboratories Albuquerque NM USA Supercomputing Solution Centre UK Atomic Weapons Establishment Aldermaston UK

ISBN: (纸本)9781467309745

Input/Output (I/O) operations can represent a significant proportion of run-time when large scientific applications are run in parallel and at scale. In order to address the growing divergence between processing speeds and I/O performance, the parallel Log-structured File System (PLFS) has been developed by EMC Corporation and the Los Alamos National Laboratory (LANL) to improve the performance of parallel file activities. Currently, PLFS requires the use of either (i) the FUSE Linux Kernel module, (ii) a modified MPI library with a customised ROMIO MPI-IO library, or (iii) an application rewrite to utilise the PLFS API directly. In this paper we present an alternative method of utilising PLFS in applications. This method employs a dynamic library to intercept the low-level POSIX operations and retarget them to use the equivalents offered by PLFS. We demonstrate our implementation of this approach, named LDPLFS, on a set of standard UNIX tools, as well on as a set of standard parallel I/O intensive mini-applications. The results demonstrate almost equivalent performance to a modified build of ROMIO and improvements over the FUSE-based approach. Furthermore, through our experiments we demonstrate decreased performance in PLFS when ran at scale on the Lustre file system.

关键词： Fuses Libraries Bandwidth Standards Containers Program processors File systems

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Big Data Processing in Cloud computing Environments

Big Data Processing in Cloud Computing Environments

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international symposium on parallel Architectures, Algorithms and Networks (ISPAN)

作者： Changqing Ji Yu Li Wenming Qiu Uchechukwu Awada Keqiu Li College of Information Science and Technology Dalian Maritime University Dalian China College of Physical Science and Technology Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (纸本)9781467350648

With the rapid growth of emerging applications like social network analysis, semantic Web analysis and bioinformatics network analysis, a variety of data to be processed continues to witness a quick increase. Effective management and analysis of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing technics from system and application aspects. First, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including cloud computing platform, cloud architecture, cloud database and data storage scheme. Following the Map Reduce parallel processing framework, we then introduce Map Reduce optimization strategies and applications reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments.

关键词： Information management Data handling Data storage systems Cloud computing Computer architecture Data models distributed databases

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Dynamic Linear Solver Selection for Transient Simulations Using Machine Learning on distributed Systems

Dynamic Linear Solver Selection for Transient Simulations Us...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Paul R. Eller Jing-Ru C. Cheng Robert S. Maier Information Technology Laboratory Engineer Research and Development Center Vicksburg MS USA

ISBN: (纸本)9781467309745

Many transient simulations spend a significant portion of the overall runtime solving a linear system. A wide variety of preconditioned linear solvers have been developed to quickly and accurately solve different types of linear systems, each having options to customize the preconditioned solver for a given linear system. Transient simulations may produce significantly different linear systems as the simulation progresses due to special events occurring that make the linear systems more difficult to solve or the model moving closer to a state of equilibrium where the linear systems are easier to solve. Machine learning algorithms provide the ability to dynamically select the preconditioned linear solver for each linear system produced by a simulation. We can generate databases by computing attributes for each linear system, physical attributes for the transient simulation, computational attributes, and running times for a set of preconditioned solvers on each linear system. Machine learning algorithms can then use these databases to generate classifiers capable of dynamically selecting a preconditioned solver for each linear system given a set of attributes. This allows us to quickly and accurately compute each transient simulation using different preconditioned solvers throughout the simulation. This also provides the potential to produce speedups in comparison with using a single preconditioned solver for an entire transient simulation.

关键词： Linear systems Computational modeling Databases Machine learning Numerical models Transient analysis Machine learning algorithms

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