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distributed loop scheduling schemes for cloud systems

Distributed loop scheduling schemes for cloud systems

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Han, Yiming Chronopoulos, Anthony T. Department of Computer Science University of Texas at San Antonio San Antonio TX United States

ISBN: (纸本)9780769549798

Cloud computing infrastructure offers the computing resources as a homogeneous collection of virtual machine instances by different hardware on figurations, which is transparent to end users. In fact, the computational powers of these virtual machine instances are different and behaves as a heterogeneous environment. Thus, scheduling and load balancing for high performance computations become challenging on such systems. In this paper, we propose a hierarchical distributed scheduling scheme suitable for parallel loops with independent iterations on a cloud computing system. We also evaluate various performance aspects associated with our distributed scheduling scheme. © 2013 IEEE.

关键词： Virtual machine

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A novel distributed multidimensional management approach for modelling proactive decision making

A novel distributed multidimensional management approach for...

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12th international symposium on distributed Computing and Applications to Business, Engineering and Science, DCABES 2013

作者： Behbahani, Masoud Pesaran Khaddaj, Souheil Choudhury, Islam in Oxford Oxford United Kingdom School of Computing and Information Systems Kingston University London United Kingdom Azad University Khorasgan Branch Esfahan Iran

ISBN: (纸本)9780769550602

The aim of this paper is to propose a new model for supporting proactive decision making in large enterprises. These organizations usually encounter enormous electronic transactions upon distributed infrastructures. The stockpiled data collections in these systems are the best source for providing necessary material for decision-making process to support managers and executives. The existing models for supporting decision-making, encounter practical problems while facing distributed databases. This paper introduces a new model that is designed to tackle the problem. The paper shows how the proposed model can be the best blueprint to increase the competitive advantage of an organization by intelligent use of the collections of data and synthesize useful knowledge. The proposed model is multidimensional because it is based on multidimensional data model concepts. It is also multilayer because it widely depends on multilayer mining theory concepts. The paper also presents the results of an empirical study to evaluate the model and the results of applying the model to real data collections. © 2013 IEEE.

关键词： Decision making

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Enabling distributed Generation Powered Sustainable High-Performance Data Center

Enabling Distributed Generation Powered Sustainable High-Per...

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19th IEEE international symposium on High Performance Computer Architecture (HPCA)

作者： Li, Chao Zhou, Ruijin Li, Tao Univ Florida Dept Elect & Comp Engn Intelligent Design Efficient Architectures Lab Gainesville FL 32611 USA

ISBN: (纸本)9781467355872

The necessity for capping carbon emission has significantly restricted the potential of modern data centers. For this matter, both industry and academia are proactively seeking opportunities on cross-layer power management schemes that could open a door for sustainable high-performance computing platform. In this paper we investigate an emerging trend in the IT industry: using promising onsite distributed generation (DG) techniques to provide premium clean energy to the computing load. We develop data center power demand shaping (PDS), a novel technique that allows data centers to utilize onsite green energy efficiently. In contrast to prior design, PDS takes advantage of a so-far unexplored power supply feature, i.e., the load following capabilities of DG systems to avoid the high performance penalty issue incurred during supply tracking. In addition, PDS features two adaptive power management schemes: DGR Boost and UPS Boost. These two workload-aware optimization methods leverage mature computer tuning knobs to achieve attractive data center performance improvement. Using real-world data center traces and industry data of distributed generation systems, we show that our technique can come within 1.2% performance of an ideal oracle, which is roughly a 37% improvement over existing supply tracking based design. Our design could save over 100 metric tons of carbon emissions annually for a 10MW data center.

关键词： computer centres distributed power generation parallel processing pollution power aware computing sustainable development

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Not seeing the parse trees from the parse forest of a context-free parallel communicating grammar system

Not seeing the parse trees from the parse forest of a contex...

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2013 IEEE 12th international symposium on parallel and distributed Computing, ISPDC 2013

作者： Bruda, Stefan D. Wilkin, Mary Sarah Ruth Department of Computer Science Bishop's University Sherbrooke QC Canada

ISBN: (纸本)9780769550183

parallel communicating grammar systems (PCGS) were introduced awhile ago purportedly to analyze concurrent systems on a language-theoretic level. To our knowledge however no actual relationship between PCGS and practical computing systems was ever investigated. We believe that PGCS with context-free components (CF-PCGS) have high practical potential, especially in the area of formal methods, so we started to bring CF-PCGS to a more practical level by studying a construct that has proven useful elsewhere: the parse tree (and forest). We show first that the original definition we introduced earlier falls short of all the desired properties: While each derivation has a corresponding parse forest, there are parse forests that do not correspond to any derivation, this applies to all the CF-PCGS variants. Because of this limitation we introduce a tighter version of parse trees (and forests) for CF-PCGS. Unfortunately we find that the new version does not bring any advantage over the original definition except for one, very restrictive variant of CF-PCGS. Overall beside providing a convenient tool to be used in conjunction with CF-PCGS, this work strongly suggests the aforementioned PCGS variant as the most promising model for practical applications in general and for grammatical approaches to formal verification of concurrent, recursive systems in particular. © 2013 IEEE.

关键词： Forestry

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Accelerating Batch Analytics with Residual Resources from Interactive Clouds

Accelerating Batch Analytics with Residual Resources from In...

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IEEE 21st Annual international symposium on Modeling, Analysis and Simulation of Computer and Telecommunication (MASCOTS)

作者： Clay, R. Benjamin Shen, Zhiming Ma, Xiaosong N Carolina State Univ Dept Comp Sci Raleigh NC 27695 USA

ISBN: (纸本)9780769551029

The popularity of cloud-based interactive computing services (e. g., virtual desktops) brings new management challenges. Each interactive user leaves abundant but fluctuating residual resources while being intolerant to latency, precluding the use of aggressive VM consolidation. In this paper, we present the Resource Harvester for Interactive Clouds (RHIC), an autonomous management framework that harnesses dynamic residual resources aggressively without slowing the harvested interactive services. RHIC builds ad-hoc clusters for running throughput-oriented "background" workloads using a hybrid of residual and dedicated resources. These hybrid clusters offer significant gains over normal dedicated clusters: 20-40% cost and 20-29% energy savings in our testbed. For a given background job, RHIC intelligently discovers and maintains the ideal cluster size and composition, to meet user-specified goals such as cost/energy minimization or deadlines. RHIC employs black-box workload performance modeling, requiring only systemlevel metrics and incorporating techniques to improve modeling accuracy with bursty and heterogeneous residual resources. We demonstrate the effectiveness and adaptivity of our RHIC prototype with two parallel data analytics frameworks, Hadoop and HBase. Our results show that RHIC finds near-ideal cluster sizes and compositions across a wide range of workload/goal combinations.

关键词： distributed computing Performance analysis Adaptive systems

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Optimal splitters for temporal and multi-version databases 13

Optimal splitters for temporal and multi-version databases

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2013 ACM SIGMOD Conference on Management of Data, SIGMOD 2013

作者： Le, Wangchao Li, Feifei Tao, Yufei Christensen, Robert University of Utah United States Chinese University of Hong Kong Hong Kong Korea Advanced Institute of Science and Technology Korea Republic of

ISBN: (纸本)9781450320375

Temporal and multi-version databases are ideal candidates for a distributed store, which offers large storage space, and parallel and distributed processing power from a cluster of (commodity) machines. A key challenge is to achieve a good load balancing algorithm for storage and processing of these data, which is done by partitioning the database. We introduce the concept of optimal splitters for temporal and multi-version databases, which induce a partition of the input data set, and guarantee that the size of the maximum bucket be minimized among all possible configurations, given a budget for the desired number of buckets. We design efficient methods for memory- and disk-resident data respectively, and show that they significantly outperform competing baseline methods both theoretically and empirically on large real data sets. Copyright © 2013 ACM.

关键词： Database systems

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Modeling communication in cache-coherent SMP systems - A case study with Xeon Phi

Modeling communication in cache-coherent SMP systems - A cas...

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22nd ACM international symposium on High-Performance parallel and distributed Computing, HPDC 2013

作者： Ramos, Sabela Hoefler, Torsten Computer Architecture Group University of A Coruña A Coruña Spain Scalable Parallel Computing Lab. ETH Zurich Zurich Switzerland

ISBN: (纸本)9781450319102

Most multi-core and some many-core processors implement cache coherency protocols that heavily complicate the design of optimal parallel algorithms. Communication is performed implicitly by cache line transfers between cores, complicating the understanding of performance properties. We developed an intuitive performance model for cache-coherent architectures and demonstrate its use with the currently most scalable cache-coherent many-core architecture, Intel Xeon Phi. Using our model, we develop several optimal and optimized algorithms for complex parallel data exchanges. All algorithms that were developed with the model beat the performance of the highly-tuned vendor-specific Intel OpenMP and MPI libraries by up to a factor of 4.3. The model can be simplified to satisfy the tradeoff between complexity of algorithm design and accuracy. We expect that our model can serve as a vehicle for advanced algorithm design. © 2013 ACM.

关键词： Electronic data interchange

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Taxonomy-based fragmentation for anti-instantiation in distributed databases

Taxonomy-based fragmentation for anti-instantiation in distr...

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2013 IEEE/ACM 6th international Conference on Utility and Cloud Computing, UCC 2013

作者： Wiese, Lena Institute of Computer Science University of Göttingen Goldschmidtstrasse 7 37077 Göttingen Germany

ISBN: (纸本)9780769551524

One feature of cloud storage systems is data fragmentation (or sharding) so that data can be distributed over multiple servers and sub queries can be run in parallel on the fragments. On the other hand, flexible query answering can enable a database system to find related information for a user whose original query cannot be answered exactly. Query generalization is a way to implement flexible query answering on the syntax level. In this paper we study a taxonomy-based fragmentation for the generalization operator Anti-Instantiation with which related information can be found in distributed data. © 2013 IEEE.

关键词： Taxonomies

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proceedings of the 2013 Sigmod/PODS Ph.D. symposium on PhD symposium

Proceedings of the 2013 Sigmod/PODS Ph.D. Symposium on PhD S...

引用

2013 Sigmod/PODS Ph.D. symposium on PhD symposium

ISBN: (纸本)9781450321556

The proceedings contain 12 papers. The topics discussed include: exploiting in-network processing for big data management;deepsea: self-adaptive data partitioning and replication in scalable distributed data systems;designing a database system for modern processing architectures;learning queries for relational, semi-structured, and graph databases;turning scientists into data explorers;information diffusion in online social networks;exploratory mining of collaborative social content;discovering and disambiguating named entities in text;the tantalizing new prospect of index-based diversified retrieval;effective hashing for large-scale multimedia search;efficient and scalable monitoring and summarization of large probabilistic data;and RDF-4G: algorithmic building blocks for large-scale graph analytics.

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Efficient parallel and distributed algorithms for GIS polygonal overlay processing

Efficient parallel and distributed algorithms for GIS polygo...

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Puri, Satish Prasad, Sushil K. Department of Computer Science Georgia State University Atlanta 30303 GA United States

ISBN: (纸本)9780769549798

Polygon overlay is one of the complex operations in Geographic Information systems (GIS). In GIS, a typical polygon tends to be large in size often consisting of thousands of vertices. Sequential algorithms for this problem are in abundance in literature and most of the parallel algorithms concentrate on parallelizing edge intersection phase only. Our research aims to develop parallel algorithms to find overlay for two input polygons which can be extended to handle multiple polygons and implement it on General Purpose Graphics Processing Units (GPGPU) which offers massive parallelism at relatively low cost. Moreover, spatial data files tend to be large in size (in GBs) and the underlying overlay computation is highly irregular and compute intensive. MapReduce paradigm is now standard in industry and academia for processing large-scale data. Motivated by MapReduce programming model, we propose to develop and implement scalable distributed algorithms to solve large-scale overlay processing in this dissertation. © 2013 IEEE.

关键词： MapReduce

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