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31st IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Xie, Wei Chen, Yong Texas Tech Univ Dept Comp Sci Lubbock TX 79413 USA

ISBN: (纸本)9781538639146

Elastic distributed storage systems have been increasingly studied in recent years because power consumption has become a major problem in data centers. Much progress has been made in improving the agility of resizing small- and large-scale distributed storage systems. However, most of these studies focus on metadata based distributed storage systems. On the other hand, emerging consistent hashing based distributed storage systems are considered to allow better scalability and are highly attractive. We identify challenges in achieving elasticity in consistent hashing based distributed storage. These challenges cannot be easily solved by techniques used in current studies. In this paper, we propose an elastic consistent hashing based distributed storage to solve two problems. First, in order to allow a distributed storage to resize quickly, we modify the data placement algorithm using a primary server design and achieve an equal-work data layout. Second, we propose a selective data re-integration technique to reduce the performance impact when resizing a cluster. Our experimental and trace analysis results confirm that our proposed elastic consistent hashing works effectively and allows significantly better elasticity.

关键词： Elasticity

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dOpenCL: Towards a Uniform Programming Approach for distributed Heterogeneous Multi-/Many-Core systems

dOpenCL: Towards a Uniform Programming Approach for Distribu...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Kegel, Philipp Steuwer, Michel Gorlatch, Sergei Univ Munster Dept Math & Comp Sci Munster Germany

ISBN: (纸本)9780769546766

Modern computer systems are becoming increasingly heterogeneous by comprising multi-core CPUs, GPUs, and other accelerators. Current programming approaches for such systems usually require the application developer to use a combination of several programming models (e. g., MPI with OpenCL or CUDA) in order to exploit the full compute capability of a system. In this paper, we present dOpenCL (distributed OpenCL) - a uniform approach to programming distributed heterogeneous systems with accelerators. dOpenCL extends the OpenCL standard, such that arbitrary computing devices installed on any node of a distributed system can be used together within a single application. dOpenCL allows moving data and program code to these devices in a transparent, portable manner. Since dOpenCL is designed as a fully-fledged implementation of the OpenCL API, it allows running existing OpenCL applications in a heterogeneous distributed environment without any modifications. We describe in detail the mechanisms that are required to implement OpenCL for distributed systems, including a device management mechanism for running multiple applications concurrently. Using three application studies, we compare the performance of dOpenCL with MPI+OpenCL and a standard OpenCL implementation.

关键词： OpenCL Heterogeneous systems distributed systems GPU Computing dOpenCL

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parallel association rule mining based on FI-growth algorithm

Parallel association rule mining based on FI-growth algorith...

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international Conference on parallel and distributed systems

作者： Manaskasemsak, Bundit Benjamas, Nunnapus Rungsawang, Arnon Surarerks, Athasit Uthayopas, Putchong Kasetsart Univ Dept Comp Engn MIKE Lab Bangkok 10900 Thailand Kasetsart Univ Dept Comp Engn HPCNC Lab Bangkok 10900 Thailand Chulalongkorn Univ Dept Comp Engn ELITE Lab Bangkok 10330 Thailand Minist Informat & Commun Technol Software Ind Promot Agcy Thai Natl Grid Ctr Bangkok Thailand

ISBN: (纸本)9781424418893

Association rule mining is one of the most important techniques in data mining. It extracts significant patterns from transaction databases and generates rules used in many decision support applications. Many organizations such as industrial, commercial, or even scientific sites may produce large amount of transactions and attributes. Mining effective rules from such large volumes of data requires much time and computing resources. In this paper, we propose a parallel FI-growth association rule mining algorithm for rapid extraction of frequent itemsets from large dense databases. We also show that this algorithm can efficiently be parallelized in a cluster computing environment. The preliminary experiments provide quite promising results, with nearly ideal scaling on small clusters and about half of ideal (15 fold speedup) on a thirty-two processor cluster.

关键词： Association rules

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Massive parallel Fluid Flow Simulations using Hierarchical Data Format Version 5 (HDF5) 15

Massive Parallel Fluid Flow Simulations using Hierarchical D...

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15th international symposium on parallel and distributed Computing (ISPDC)

作者： Ertl, Christoph Frisch, Jerome Mundani, Ralf-Peter Tech Univ Munich Computat Engn Munich Germany Rhein Westfal TH Aachen Inst Energy Efficiency & Sustainable Bldg E3D Aachen Germany

ISBN: (纸本)9781509041527

More and more massive parallel codes running on several hundreds of thousands of cores enter the computational science and engineering domain, allowing high-fidelity computations up to trillions of unknowns for very detailed analyses of the underlying problems. During such runs, typically gigabytes of data are being produced, hindering both efficient storage and (interactive) data exploration. Here, advanced approaches based on inherently distributed data formats such as HDF5 become necessary in order to avoid long latencies when storing the data and to support fast (random) access when retrieving the data for visual processing. Avoiding file locking and using collective buffering, we achieved write bandwiths to a single file close to the theoretical peak on a modern supercomputing cluster. The structure of our output file supports a very fast interactive visualisation and introduces additional steering functionality.

关键词： Mathematical model Data structures Visualization Servers distributed databases Computational modeling

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Decentralized Runtime Verification of LTL Specifications in distributed systems 29

Decentralized Runtime Verification of LTL Specifications in ...

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29th IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Mostafa, Menna Bonakdarpour, Borzoo Univ Waterloo Sch Comp Sci Waterloo ON N2L 3G1 Canada McMaster Univ Dept Comp & Software Hamilton ON L8S 4L8 Canada

ISBN: (纸本)9781479986484

Runtime verification is a lightweight automated formal method for specification-based runtime monitoring as well as testing of large real-world systems. While numerous techniques exist for runtime verification of sequential programs, there has been very little work on specification-based monitoring of distributed systems. In this paper, we propose the first sound and complete method for runtime verification of asynchronous distributed programs for the 3-valued semantics of LTL specifications defined over the global state of the program. Our technique for evaluating LTL properties is inspired by distributed computation slicing, an approach for abstracting distributed computations with respect to a given predicate. Our monitoring technique is fully decentralized in that each process in the distributed program under inspection maintains a replica of the monitor automaton. Each monitor may maintain a set of possible verification verdicts based upon existence of concurrent events. Our experiments on runtime monitoring of a simulated swarm of flying drones show that due to the design of our Algorithm, monitoring overhead grows only in the linear order of the number of processes and events that need to be monitored.

关键词： Runtime monitoring Asynchronous distributed systems Formal methods

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A Fast Repair Code Based on Regular Graphs for distributed Storage systems

A Fast Repair Code Based on Regular Graphs for Distributed S...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Wang, Yan Wang, Xin Fudan Univ Sch Comp Sci Shanghai Key Lab Intelligent Informat Proc Shanghai 200433 Peoples R China

ISBN: (纸本)9780769546766

distributed storage systems (DSS) play an important role in data storage applications, since they provide high reliability for huge data storage requirement. As node failures are frequent in a large distributed storage system, the performance of repairing node failure causes many researchers' interests. In this paper, we propose a distributed storage code to minimize the coding complexity during the repairing process, at a cost of inducing larger redundancy. Our code construction is based on regular graphs and exploits simple look-up repair. We analyze the performance of the proposed code, and compare them with existing distributed storage codes. Analytical results show that the proposed code outperforms the others in terms of low repair complexity and disk I/O overhead.

关键词： distributed storage systems Erasure codes Regenerating codes

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Improved Time Bounds for Linearizable Implementations of Abstract Data Types

Improved Time Bounds for Linearizable Implementations of Abs...

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IEEE 28th international parallel & distributed Processing symposium (IPDPS)

作者： Wang, Jiaqi Talmage, Edward Lee, Hyunyoung Welch, Jennifer L. Texas A&M Univ Dept Comp Sci & Engn College Stn TX 77843 USA

ISBN: (纸本)9780769552071

Linearizability is a well-known consistency condition for shared objects in concurrent systems. We focus on the problem of implementing linearizable objects of arbitrary data types in message-passing systems with bounded, but uncertain, message delay and bounded, but non-zero, clock skew. We present an algorithm that exploits axiomatic properties of different operations to reduce the running time of each operation below that obtainable with previously known algorithms. We also prove lower bounds on the time complexity of various kinds of operations, specified by the axioms they satisfy, resulting in reduced gaps in some cases and tight bounds in others.

关键词： linearizability abstract data types time bounds distributed computing

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Fast Convergence to Fairness for Reduced Long Flow Tail Latency in Datacenter Networks 36

Fast Convergence to Fairness for Reduced Long Flow Tail Late...

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36th IEEE international parallel and distributed Processing symposium (IEEE IPDPS)

作者： Snyder, John Lebeck, Alvin R. Duke Univ Dept Comp Sci Durham NC 27706 USA

ISBN: (纸本)9781665481069

Many data-intensive applications, such as distributed deep learning and data analytics, require moving vast amounts of data between compute servers in a distributed system. To meet the demands of these applications, datacenters are adopting Remote Direct Memory Access (RDMA), which has higher bandwidth and lower latency than traditional kernel-based networking. To ensure high performance of RDMA networks, congestion control manages queue depth on switches, and historically focused on moderating queue depth to ensure small flows complete quickly. Unfortunately, one side-effect of many common decisions is that large flows are starved of bandwidth. This negatively impacts the flow completion time (FCT) of large, bandwidth-bound flows, which are integral to the performance of data-intensive applications. The FCT is particularly impacted at the tail, which is increasingly critical for predictable application performance. We identify the root causes of the poor performance for long flows and measure the impact. We then design mechanisms that improve long flow FCT without compromising small flow performance. Our evaluations show that these improvements reduce 99.9% tail FCT of long flows by over 2x.

关键词： distributed processing Protocols Additives distributed databases Tail Bandwidth Throughput

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COMBINED COMMUNICATION NETWORK DESIGN AND FILE ALLOCATION FOR distributed databases.

Proceedings of International Wire and Cable Symposium

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Proceedings of international Wire and Cable symposium 1981年 197-210页

作者： Irani, Keki B. Khabbaz, Nicholas G.

The problem of the combined communication network design and file allocation for distributed databases is addressed. It consists of finding the allocation of database files over a set of computer sites and of the design of the communication network, i. e. , the design of the network topology, and the allocation of the communication channel capacities. The objective is to minimize the total cost of storing the database files and of leasing the communication channels subject to the constraints of network reliability, file availability, and communication delay. The network topologies are restricted to be of maximal connectivity and minimal diameter. A heuristic algorithm to solve the problem is described and some results are presented.

关键词： DATA BASE systems

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An Efficient Scheduling Algorithm for Energy Consumption Constrained parallel Applications on Heterogeneous distributed systems 15

An Efficient Scheduling Algorithm for Energy Consumption Con...

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15th IEEE international symposium on parallel and distributed Processing with Applications (ISPA) / 16th IEEE international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Song, Jinlin Xie, Guoqi Li, Renfa Chen, Xiaoming Hunan Univ Coll Comp Sci & Elect Engn Changsha Hunan Peoples R China Key Lab Embedded & Network Comp Hunan Prov Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

As the explosive growth of energy consumption in current heterogeneous distributed systems, energy consumption constraint has been one of the primary design issues Minimizing the schedule length while satisfying the energy consumption constraint of parallel applications is one of the most important problem which has been studied recently. Previous studies have proposed a preassignment approach which tried to presuppose the minimum energy consumption assignment for unassigned tasks to solve the problem based on the dynamic voltage and frequency scaling (DVFS) technique. However, the preassignment of unassigned tasks with the minimum energy consumption does not necessarily lead to the minimization of the schedule length. In this study, we propose an efficient scheduling algorithm using a relative average assignments for tasks. The results of experiments on two real parallel applications validate that the proposed algorithm can obtain shorter schedule length while satisfying the energy consumption constraint compared with the state-ofthe-art methods in various situations.

关键词： dynamic voltage and frequency scaling (DVFS) energy consumption constraint heterogeneous distributed systems parallel application schedule length

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