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parallel sparse matrix-vector multiplication as a test case for hybrid MPI OpenMP programming

Parallel sparse matrix-vector multiplication as a test case ...

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25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Schubert, Gerald Hager, Georg Fehske, Holger Wellein, Gerhard Erlangen Regional Computing Center University of Erlangen-Nuremberg 91058 Erlangen Germany Institute for Physics University of Greifswald 17487 Greifswald Germany

ISBN: (纸本)9780769543857

We evaluate optimized parallel sparse matrix-vector operations for two representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect to basic architectural properties of standard multicore chips. Going beyond the single node, parallel sparse matrix-vector operations often suffer from an unfavorable communication to computation ratio. Starting from the observation that nonblocking MPI is not able to hide communication cost using standard MPI implementations, we demonstrate that explicit overlap of communication and computation can be achieved by using a dedicated communication thread, which may run on a virtual core. We compare our approach to pure MPI and the widely used "vector-like" hybrid programming strategy. © 2011 IEEE.

关键词： Application programming interfaces (API)

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Detection and correction of silent data corruption for large-scale high-performance computing

Detection and correction of silent data corruption for large...

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25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Fiala, David North Carolina State University Department of Computer Science Raleigh NC United States

ISBN: (纸本)9780769543857

Faults have become the norm rather than the exception for high-end computing on clusters with 10s/100s of thousands of cores, and this situation will only become more dire as we reach exascale computing. Exacerbating this situation, some of these faults will not be detected, manifesting themselves as silent errors that will corrupt memory while applications continue to operate but report incorrect results. This paper introduces RedMPI, an MPI library residing in the profiling layer of any standards-compliant MPI implementation. RedMPI is capable of both online detection and correction of soft errors that occur in MPI applications without requiring code changes to application source code. By providing redundancy, RedMPI is capable of transparently detecting corrupt messages from MPI processes that become faulted during execution. Furthermore, with triple redundancy RedMPI "votes" out MPI messages of a faulted process by replacing corrupted results with corrected results from unfaulted processes. We present an evaluation of RedMPI on an assortment of applications to demonstrate the effectiveness and assess associated overheads. Fault injection experiments establish that RedMPI is not only capable of successfully detecting injected faults, but can also correct these faults while carrying a corrupted application to successful completion without propagating invalid data. © 2011 IEEE.

关键词： Redundancy

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Towards intelligent data placement for scientific workflows in collaborative cloud environment

Towards intelligent data placement for scientific workflows ...

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25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Liu, Xin Datta, Anwitaman School of Computer Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9780769543857

Recently emerged cloud computing offers a promising platform for executing scientific workflow applications due to its similar performance compared to the grid, lower cost, elasticity and so on. Collaborative cloud environments, which share resources of multiple geographically distributed data centers owned by different organizations enable researchers from all over the world to conduct their large scale data intensive research together through Internet. However, since scientific workflows consume and generate huge amount of data, it is thus essential to manage the data effectively for the purpose of high performance and cost effectiveness. In this paper, we propose intelligent data placement strategy to improve performance of workflows while minimizing data transfer among data centers. Specifically, at the startup stage, the whole dataset is divided into small data items which are then distributed among multiple data centers by considering these data centers' computation capability, storage budget, data item correlation, etc. During the runtime stage, when intermediate data is generated, it is placed on the suitable data centers using linear discriminant analysis by taking into account the same metrics as at the startup stage, as well as data centers' past behaviors (i.e., trustworthiness in terms of task delay). Simulation results demonstrate the promise of our data placement strategy by showing that compared to existing data placement strategies, our proposal effectively places the data to improve computation progress on the whole while minimizing the communication overheads incurred by data movement. © 2011 IEEE.

关键词： Cloud computing

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computing the tree of life: Leveraging the power of desktop and service grids

Computing the tree of life: Leveraging the power of desktop ...

引用

25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Bazinet, Adam L. Cummings, Michael P. Center for Bioinformatics and Computational Biology University of Maryland College Park MD 20742 United States

ISBN: (纸本)9780769543857

The trend in life sciences research, particularly in molecular evolutionary systematics, is toward larger data sets and ever-more detailed evolutionary models, which can generate substantial computational loads. Over the past several years we have developed a grid computing system aimed at providing researchers the computational power needed to complete such analyses in a timely manner. Our grid system, known as The Lattice Project, was the first to combine two models of grid computing - the service model, which mainly federates large institutional HPC resources, and the desktop model, which harnesses the power of PCs volunteered by the general public. Recently we have developed a "science portal" style web interface that makes it easier than ever for phylogenetic analyses to be completed using GARLI, a popular program that uses a maximum likelihood method to infer the evolutionary history of organisms on the basis of genetic sequence data. This paper describes our approach to scheduling thousands of GARLI jobs with diverse requirements to heterogeneous grid resources, which include volunteer computers running BOINC software. A key component of this system provides a priori GARLI runtime estimates using machine learning with random forests. © 2011 IEEE.

关键词： Phylogenetic

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On using pattern matching algorithms in MapReduce applications

On using pattern matching algorithms in MapReduce applicatio...

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9th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2011

作者： Rizvandi, Nikzad Babaii Taheri, Javid Zomaya, Albert Y. Center for Distributed and High Performance Computing School of Information Technologies University of Sydney Australia Australian Technology Park Sydney NSW 1430 Australia

ISBN: (纸本)9780769544281

In this paper, we study CPU utilization time patterns of several MapReduce applications. After extracting running patterns of several applications, they are saved in a reference database to be later used to tweak system parameters to efficiently execute unknown applications in future. To achieve this goal, CPU utilization patterns of new applications are compared with the already known ones in the reference database to find/predict their most probable execution patterns. Because of different patterns lengths, the Dynamic Time Warping (DTW) is utilized for such comparison;a correlation analysis is then applied to DTWs' outcomes to produce feasible similarity patterns. Three real applications (WordCount, Exim Mainlog parsing and Terasort) are used to evaluate our hypothesis in tweaking system parameters in executing similar applications. Results were very promising and showed effectiveness of our approach on pseudo-distributed MapReduce platforms. © 2011 IEEE.

关键词： MapReduce

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Efficient agreement protocols in asynchronous distributed systems

Efficient agreement protocols in asynchronous distributed sy...

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25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Moise, Izabela Université de Rennes 1 IRISA / INRIA Rennes France

ISBN: (纸本)9780769543857

The Consensus problem is a central paradigm of fault-tolerant distributed computing. In a purely asynchronous system, Consensus is impossible to solve in deterministic manner. However, by enriching the system with some synchrony assumptions, several solutions have been proposed in order to circumvent the impossibility result, among which the Paxos approach introduced by Lamport. The repeated use of consensus protocols as building-blocks for higher-level applications, motivated research to optimize their performances. Two main optimizations have been proposed that reduce the latency of learning a decision. However, the second optimization succeeds only in favorable circumstances, otherwise it can be counterproductive and increase the total latency of the protocol. We proposed an efficient framework, called the Paxos-MIC protocol that combines two optimizations dynamically. It solves several consensus instances and guarantees the persistence of all decision values. The protocol is adaptive as it tries to obtain the best performance gain depending on the current context. Between two consecutive consensus instances, the leader determines if the second optimization has to be triggered or not. We analyzed its behavior when both optimizations (or just the first) are used. We studied favorable and unfavorable scenarios where the second optimization may lead to an additional cost. © 2011 IEEE.

关键词： distributed computer systems

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The evaluation of an effective out-of-core run-time system in the context of parallel mesh generation

The evaluation of an effective out-of-core run-time system i...

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25th IEEE international parallel and distributed Processing symposium, IPDPS 2011

作者： Kot, Andriy Chernikov, Andrey N. Chrisochoides, Nikos P. Computer Science Department College of William and Mary Williamsburg VA United States Computer Science Department Old Dominion University Norfolk VA United States

ISBN: (纸本)9780769543857

We present an out-of-core run-time system that supports effective parallel computation of large irregular and adaptive problems, in particular unstructured mesh generation (PUMG). PUMG is a highly challenging application due to intensive memory accesses, unpredictable communication patterns, and variable and irregular data dependencies reflecting the unstructured spatial connectivity of mesh elements. Our runtime system allows to transform the footprint of parallel applications from wide and shallow into narrow and deep by extending the memory utilization to the out-of-core level. It simplifies and streamlines the development of otherwise highly time consuming out-of-core applications as well as the converting of existing applications. It utilizes disk, network and memory hierarchy to achieve high utilization of computing resources without sacrificing performance with PUMG. The runtime system combines different programming paradigms: multi-threading within the nodes using industrial strength software framework, one-sided active messages among the nodes, and an out-of-core subsystem for managing large datasets. We performed an evaluation on traditional parallel platforms to stress test all layers of the run-time system using three different PUMG methods with significantly varying communication and synchronization patterns. We demonstrated high overlap in computation, communication, and disk I/O which results in good performance when computing large out-of-core problems. The runtime system adds very small overhead (up to 18% on most configurations) when computing in-core which means performance is not compromised. © 2011 IEEE.

关键词： Mesh generation

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Performance driven distributed scheduling of parallel hybrid computations

Performance driven distributed scheduling of parallel hybrid...

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20th international symposium on Algorithms and Computations (ISAAC 2009)

作者： Narang, Ankur Shyamasundar, Rudrapatna K. IBM Res India Inst Area New Delhi 110070 India Tata Inst Fundamental Res Bombay 400005 Maharashtra India

Exascale computing is fast becoming a mainstream research area. In order to realize exascale performance, it is necessary to have efficient scheduling of large parallel computations with scalable performance on a large number of cores/processors. The scheduler needs to execute in a pure distributed and online fashion, should follow affinity inherent in the computation and must have low time and message complexity. Further, it should also avoid physical deadlocks due to bounded resources including space/memory per core. Simultaneous consideration of these factors makes affinity driven distributed scheduling particularly challenging. We attempt to address this challenge for hybrid parallel computations which contain tasks that have pre-specified affinity to a place and also tasks that can be mapped to any place in the system. Specifically, we address two scheduling problems of the type P(m)[M(j), prec]C(max). This paper presents online distributed scheduling algorithms for hybrid parallel computations assuming both unconstrained and bounded space per place. We also present the time and message complexity for distributed scheduling of hybrid computations. To the best of our knowledge, this is the first time that distributed scheduling algorithms for hybrid parallel computations have been presented and analyzed for time and message bounds under both unconstrained space and bounded space. (C) 2011 Elsevier B.V. All rights reserved.

关键词： distributed scheduling Multithreaded computation Asymptotic complexity Deadlock free scheduling Work stealing Online algorithm

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Proceedings - 2011 4th international symposium on parallel Architectures, Algorithms and Programming, PAAP 2011

Proceedings - 2011 4th International Symposium on Parallel A...

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2011 4th international symposium on parallel Architectures, Algorithms and Programming, PAAP 2011

ISBN: (纸本)9780769545752

The proceedings contain 66 papers. The topics discussed include: option pricing on the GPU with backward stochastic differential equation;DHFS: a high-throughput heterogeneous file system based on mainframe for cloud storage;security-driven fault tolerant scheduling algorithm for high dependable distributed real-time system;a polynomial algorithm for the vertex disjoint min-min problem in planar graphs;improving parallel FDTD method performance using SSE instructions;communication-aware design space exploration for efficient run-time MPSoC management;energy minimization for software real-time systems with uncertain execution time;an efficient algorithm for privacy preserving maximal frequent itemsets mining;distributed network resources monitoring based on multi-agent and matrix grammar;an implementation of GPU-based parallel optimization for an extended uncertain data query algorithm;and job scheduling optimization for multi-user MapReduce clusters.

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A scalable and elastic publish/subscribe service

A scalable and elastic publish/subscribe service

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25th IEEE international parallel and distributed Processing symposium, IPDPS 2011

作者： Li, Ming Ye, Fan Kim, Minkyong Chen, Han Lei, Hui IBM T.J. Watson Research Center Hawthorne NY 10532 United States

ISBN: (纸本)9780769543857

The rapid growth of sense-and-respond applications and the emerging cloud computing model present a new challenge: providing publish/subscribe as a scalable and elastic cloud service. This paper presents the Blue Dove attribute based publish/subscribe service that seeks to address such a challenge. Blue Dove uses a gossip-based one-hop overlay to organize servers into a scalable cluster. It proactively exploits skew ness in data distribution to achieve high performance. By assigning each subscription to multiple servers through a multidimensional subscription space partitioning technique, it provides multiple candidate servers for each publication message. A message can be matched on any of its candidate servers with one hop forwarding. The performance-aware forwarding in Blue Dove ensures that the message is sent to the least loaded candidate server for processing, leading to low latency and high throughput. The evaluation shows that Blue Dove has a linear capacity increase as the system scales up, adapts to sudden workload changes within tens of seconds, and achieves multifold higher throughput than the techniques used in the existing enterprise and peer-to-peer pub/sub systems. © 2011 IEEE.

关键词： Cloud computing

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