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检索条件"任意字段=Proceedings of the 2013 ACM symposium on Principles of distributed computing"

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Pattern programming approach for teaching parallel and distributed computing 13

Pattern programming approach for teaching parallel and distr...

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44th acm Technical symposium on Computer Science Education, SIGCSE 2013

作者： Wilkinson, Barry Villalobos, Jeremy Ferner, Clayton University of North Carolina Charlotte 9201 University City Blvd. Charlotte NC 28223 USA United States University of North Carolina 601 S. College Rd. Wilmington NC 28409 USA United States

ISBN: (纸本)9781450320306

In this paper, we describe an approach for teaching parallel and distributed computing at the undergraduate level using computational patterns. The goal is to promote higher-level structured design for parallel programming and make parallel programming easier and more scalable. A pattern programming framework has been developed to create a distributed application that avoids the need to write code in low level message-passing APIs such as MPI. Several patterns have been implemented including workpool, pipeline, synchronous and iterative all-to-all, and stencil. We have redesigned a regular senior undergraduate parallel programming course to begin with a pattern strategy using our framework and provide a detailed syllabus around patterns. Copyright © 2013 acm.

关键词： Parallel programming

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Exploring Dynamic Enactment of Scientific Workflows using Pilot-Abstractions 13

Exploring Dynamic Enactment of Scientific Workflows using Pi...

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13th IEEE/acm International symposium on Cluster, Cloud, and Grid computing (CCGrid)

作者： Santcroos, Mark van Schaik, Barbera D. C. Shahand, Shayan Olabarriaga, Silvia Delgado Luckow, Andre Jha, Shantenu Univ Amsterdam Acad Med Ctr KEBB Dept Bioinformat Lab NL-1012 WX Amsterdam Netherlands Rutgers State Univ ECE & RADICAL Piscataway NJ 08855 USA

ISBN: (纸本)9780769549965;9781467364652

Current workflow abstractions in general lack: (a) an adequate approach to handle distributed data and (b) proper separation between logical tasks and data-flow from their mapping onto physical locations. As the complexity and dynamism of data and processing distribution have increased, optimized mapping of logical tasks to physical resources have become a necessity to avoid bottlenecks. We argue that the management of dynamic data and compute should become part of the runtime system of workflow engines to enable workflows to scale as necessary to address big data challenges and fully exploit distributed computing infrastructures (DCI). In this paper we explore how the P* model for pilot-abstractions, which proposes a clear separation between the logical compute and data units and their realization as a job or a file in some physical resource, could provide these capabilities for such a runtime environment. The Pilot-API provides a general-purpose interface to pilot-abstractions and the ability to assign compute and data resources to them. We share our experience of using the case study of a DNA sequencing pipeline, to re-implement the workflow using the Pilot-API. This first exercise, which resulted in a running application that is discussed here, illustrates the potential of this API to address (a) and (b). Our initial results indicate that the pilot abstractions (as captured by the P* model) offer an interesting approach to explore the design of a new generation of workflow management systems and runtime environments that are capable of intelligently deciding on application-aware late binding to physical resources.

关键词： big data distributed computing pilot jobs scientific workflows

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Automated SLA Negotiation Framework for Cloud computing 13

Automated SLA Negotiation Framework for Cloud Computing

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13th IEEE/acm International symposium on Cluster, Cloud, and Grid computing (CCGrid)

作者： Wu, Linlin Garg, Saurabh Kumar Buyya, Rajkumar Chen, Chao Versteeg, Steve Univ Melbourne Dept Comp & Informat Syst Cloud Comp & Distributed Syst Lab Melbourne Vic 3010 Australia CA Technol Melbourne Vic Australia

ISBN: (纸本)9780769549965;9781467364652

A Service Level Agreement (SLA) is a legal contract between parties to ensure the Quality of Service (QoS) are provided the providers to the customers. A SLA negotiation between participants assists in defining the QoS requirements of critical service-based processes. However, the negotiation process for customers is a significant task particularly when there are multiple SaaS providers in the Cloud market, as service cost and quality are constantly changing and consumers have varying needs. Therefore, we propose a novel automated negotiation framework where a SaaS broker is utilized as the one-stop-shop for customers to achieve the required service efficiently when negotiating with multiple providers. The automated negotiation framework facilitates intelligent bilateral bargaining of SLAs between a SaaS broker and multiple providers to achieve different objectives for different participants. To maximize profit and improve customer satisfaction levels for the broker, we propose the design of counter offer generation strategies and decision making heuristics that take into account time, market constraints and trade-off between QoS parameters. Our negotiation heuristics are evaluated by extensive experimental studies of our framework using data from a real Cloud provider.

关键词： SLA negotiation Software-as-a-Service market-oriented Cloud computing resource allocation

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PPoPP 2013 - proceedings of the 2013 acm SIGPLAN symposium on principles and Practice of Parallel Programming

PPoPP 2013 - Proceedings of the 2013 ACM SIGPLAN Symposium o...

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18th acm SIGPLAN symposium on principles and Practice of Parallel Programming, PPoPP 2013

ISBN: (纸本)9781450319225

The proceedings contain 45 papers. The topics discussed include: a peta-scalable CPU-GPU algorithm for global atmospheric simulations;adoption protocols for fanout-optimal fault-tolerant termination detection;betweenness centrality: algorithms and implementations;complexity analysis and algorithm design for reorganizing data to minimize non-coalesced memory accesses on GPU;fast concurrent queues for x86 processors;FASTLANE: improving performance of software transactional memory for low thread counts;Ligra: a lightweight graph processing framework for shared memory;ownership passing: efficient distributed memory programming on multi-core systems;parallel suffix array and least common prefix for the GPU;Streamscan: fast scan algorithms for GPUs without global barrier synchronization;using hardware transactional memory to correct and simplify a readers-writer lock algorithm;and exploring different automata representations for efficient regular expression matching on GPUs.

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Sesame: A User-Transparent Optimizing Framework for Many-Core Processors 13

Sesame: A User-Transparent Optimizing Framework for Many-Cor...

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13th IEEE/acm International symposium on Cluster, Cloud, and Grid computing (CCGrid)

作者： Fang, Jianbin Varbanescu, Ana Lucia Sips, Henk Delft Univ Technol Parallel & Distributed Syst Grp Delft Netherlands

ISBN: (纸本)9780769549965;9781467364652

With the integration of more computational cores and deeper memory hierarchies on modern processors, the performance gap between naively parallelized code and optimized code becomes much larger than ever before. Very often, bridging the gap involves architecture-specific optimizations. These optimizations are difficult to implement by application programmers, who typically focus on the basic functionality of their code. Therefore, in this thesis, I focus on answering the following research question: "How can we address architecture-specific optimizations in a programmer-friendly way?" As an answer, I propose an optimizing framework for parallel applications running on many-core processors (Sesame). Taking a simple parallelized code provided by the application programmers as input, Sesame chooses and applies the most suitable architecture-specific optimizations, aiming to improve the overall application performance in a user-transparent way. In this short paper, I present the motivation for designing and implementing Sesame, its structure and its modules. Furthermore, I describe the current status of Sesame, discussing our promising results in source-to-source vectorization, automated usage of local memory, and autotuning for implementation-specific parameters. Finally, I discuss my work-in-progress and sketch my ideas for finalizing Sesame's development and testing.

关键词： Optimization Many-Core Processors OpenCL

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Simfrastructure: A Flexible and Adaptable Middleware Platform for Modeling and Analysis of Socially Coupled Systems 13

Simfrastructure: A Flexible and Adaptable Middleware Platfor...

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13th IEEE/acm International symposium on Cluster, Cloud, and Grid computing (CCGrid)

作者： Bisset, Keith R. Deodhar, Suruchi Makkapati, Hemanth Marathe, Madhav V. Stretz, Paula Barrett, Christopher L. Virginia Tech VBI Network Dynam & Simulat Sci Lab Blacksburg VA 24061 USA

ISBN: (纸本)9780769549965;9781467364652

Socially coupled systems are comprised of interdependent social, organizational, economic, infrastructure and physical networks. Today's urban regions serve as an excellent example of such systems. People and institutions confront the implications of the increasing scale of information becoming available due to a combination of advances in pervasive computing, data acquisition systems as well as high performance computing. Integrated modeling and decision making environments are necessary to support planning, analysis and counter factual experiments to study these complex systems. Here, we describe SIMFRASTRUCTURE - a flexible coordination middleware that supports high performance computing oriented decision and analytics environments to study socially coupled systems. Simfrastructure provides a multiplexing mechanism by which simple and intuitive user-interfaces can be plugged in as front-end systems, and high-end computing resources can be plugged in as back-end systems for execution. This makes the computational complexity of the simulations completely transparent to the users. The decoupling of user interfaces and data repository from simulation execution allows users to access simulation results asynchronously and enables them to add new datasets and simulation models dynamically. Simfrastructure enables implementation of a simple yet powerful modeling environment with built-in analytics-as-a-service platform, which provides seamless access to high end computational resources, through an intuitive interface for studying socially coupled systems. We illustrate the applicability of Simfrastructure in the context of an integrated modeling environment to study public health epidemiology.

关键词： Socially coupled systems middleware public health epidemiology distributed systems software architecture

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Automated, Elastic Resource Provisioning for NoSQL Clusters Using TIRAMOLA 13

Automated, Elastic Resource Provisioning for NoSQL Clusters ...

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13th IEEE/acm International symposium on Cluster, Cloud, and Grid computing (CCGrid)

作者： Tsoumakos, Dimitrios Konstantinou, Ioannis Boumpouka, Christina Sioutas, Spyros Koziris, Nectarios Ionian Univ Dept Informat Corfu Greece Natl Tech Univ Athens Sch Elect & Comp Engn Athens Greece

ISBN: (纸本)9780769549965;9781467364652

This work presents TIRAMOLA, a cloud-enabled, open-source framework to perform automatic resizing of NoSQL clusters according to user-defined policies. Decisions on adding or removing worker VMs from a cluster are modeled as a Markov Decision Process and taken in real-time. The system automatically decides on the most advantageous cluster size according to user-defined policies;it then proceeds on requesting/releasing VM resources from the provider and orchestrating them inside a NoSQL cluster. TIRAMOLA's modular architecture and standard API support allows interaction with most current IaaS platforms and increased customization. An extensive experimental evaluation on an HBase cluster confirms our assertions: The system resizes clusters in real-time and adapts its performance through different optimization strategies, different permissible actions, different input and training loads. Besides the automation of the process, it exhibits a learning feature which allows it to make very close to optimal decisions even with input loads 130% larger or alternating 10 times faster compared to the accumulated information.

关键词： Cloud Resource Provisioning Elasticity NoSQL Markov Decision Process Policy-based Optimization distributed Datastores Open-source

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Stretch Out and Compact: Workflow Scheduling with Resource Abundance 13

Stretch Out and Compact: Workflow Scheduling with Resource A...

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13th IEEE/acm International symposium on Cluster, Cloud, and Grid computing (CCGrid)

作者： Lee, Young Choon Zomaya, Albert Y. Univ Sydney Sch Informat Technol Ctr Distributed & High Performance Comp Sydney NSW 2006 Australia

ISBN: (纸本)9780769549965;9781467364652

Resource abundance is apparent in today's multicore era. Workflow applications common in science and engineering can take great advantage of such ample resource capacity. Yet, existing workflow scheduling algorithms have been mostly designed on the traditional and contrasting premise of scarce resource capacity relative to what applications require. In this paper, we address the problem of workflow scheduling exploiting resource abundance not only for performance, but also for resource efficiency. We first present the critical-pathfirst scheduling algorithm, which efficiently stretches out the schedule to proactively preserve critical path length, the shortest possible time of completion. We then develop an algorithm to compact the schedule for resource efficiency. The schedule is compacted by rearranging tasks making use of idle/inefficiency slots present in the schedule due to precedence constraints (synchronization). We have compared the performance of our scheduling algorithm with three previous algorithms and evaluated the efficacy of our schedule compaction algorithm by applying it to those four scheduling algorithms including our own. Experiments were conducted in a simulated environment with various real-world scientific workflows. Results show that our scheduling algorithm achieves a great performance to resource usage ratio. Further, our schedule compaction algorithm reduces resource usage by 33% on average ranging from 11.3% to 90.7% with no makespan increases.

关键词： workflow scheduling resource efficiency multicore machine cloud computing

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Transaction chains: achieving serializability with low latency in geo-distributed storage systems 13

Transaction chains: achieving serializability with low laten...

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24th acm symposium on Operating Systems principles (SOSP)

作者： Zhang, Yang Power, Russell Zhou, Siyuan Sovran, Yair Aguilera, Marcos Li, Jinyang NYU New York NY 10003 USA Microsoft Res Silicon Valley Redmond WA USA

ISBN: (纸本)9781450323888

Currently, users of geo-distributed storage systems face a hard choice between having serializable transactions with high latency, or limited or no transactions with low latency. We show that it is possible to obtain both serializable transactions and low latency, under two conditions. First, transactions are known ahead of time, permitting an a priori static analysis of conflicts. Second, transactions are structured as transaction chains consisting of a sequence of hops, each hop modifying data at one server. To demonstrate this idea, we built Lynx, a geo-distributed storage system that offers transaction chains, secondary indexes, materialized join views, and geo-replication. Lynx uses static analysis to determine if each hop can execute separately while preserving serializability-if so, a client needs wait only for the first hop to complete, which occurs quickly. To evaluate Lynx, we built three applications: an auction service, a Twitter-like microblogging site and a social networking site. These applications successfully use chains to achieve low latency operation and good throughput.

关键词： Static analysis

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SOSP 2013 - proceedings of the 24th acm symposium on Operating Systems principles

SOSP 2013 - Proceedings of the 24th ACM Symposium on Operati...

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24th acm symposium on Operating Systems principles, SOSP 2013

ISBN: (纸本)9781450323888

The proceedings contain 30 papers. The topics discussed include: the scalable commutativity rule: designing scalable software for multicore processors;everything you always wanted to know about synchronization but were afraid to ask;dandelion: a compiler and runtime for heterogeneous systems;timecard: controlling user-perceived delays in server-based mobile applications;fast dynamic binary translation for the kernel;VirtuOS: an operating system with kernel virtualization;from L3 to SEL4: what have we learnt in 20 years of L4 microkernels?;replication, history, and grafting in the on file system;IOFlow: a software-defined storage architecture;from ARIES to MARS: transaction support for next-generation, solid-state drives;asynchronous intrusion recovery for interconnected web services;towards optimization-safe systems: analyzing the impact of undefined behavior;and transaction chains: achieving serializability with low latency in geo-distributed storage systems.

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