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On Graphs, GPUs, and Blind Dating A Workload to Processor Matchmaking Quest

On Graphs, GPUs, and Blind Dating A Workload to Processor Ma...

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IEEE 27th international parallel and distributed processing symposium (IPDPS)

作者： Gharaibeh, Abdullah Costa, Lauro Beltrao Santos-Neto, Elizeu Ripeanu, Matei Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9780769549712

Graph processing has gained renewed attention. The increasing large scale and wealth of connected data, such as those accrued by social network applications, demand the design of new techniques and platforms to efficiently derive actionable information from large scale graphs. Hybrid systems that host processing units optimized for both fast sequential processing and bulk processing (e. g., GPU-accelerated systems) have the potential to cope with the heterogeneous structure of real graphs and enable high performance graph processing. Reaching this point, however, poses multiple challenges. The heterogeneity of the processing elements (e. g., GPUs implement a different parallel processing model than CPUs and have much less memory) and the inherent irregularity of graph workloads require careful graph partitioning and load assignment. In particular, the workload generated by a partitioning scheme should match the strength of the processing element the partition is allocated to. This work explores the feasibility and quantifies the performance gains of such low-cost partitioning schemes. We propose to partition the workload between the two types of processing elements based on vertex connectivity. We show that such partitioning schemes offer a simple, yet efficient way to boost the overall performance of the hybrid system. Our evaluation illustrates that processing a 4-billion edges graph on a system with one CPU socket and one GPU, while offloading as little as 25% of the edges to the GPU, achieves 2x performance improvement over state-of-the-art implementations running on a dual-socket symmetric system. Moreover, for the same graph, a hybrid system with dual-socket and dual-GPU is capable of 1.13 Billion breadth-first search traversed edge per second, a performance rate that is competitive with the latest entries in the Graph500 list, yet at a much lower price point.

关键词： graph theory graphics processing units parallel processing

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Massively parallel Model of Extended Memory Use In Evolutionary Game Dynamics

Massively Parallel Model of Extended Memory Use In Evolution...

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IEEE 27th international parallel and distributed processing symposium (IPDPS)

作者： Randles, Amanda Peters Rand, David G. Lee, Christopher Morrisett, Greg Sircar, Jayanta Nowak, Martin A. Pfister, Hanspeter Harvard Univ Sch Engn & Appl Sci Cambridge MA 02138 USA Harvard Univ Program Evolutionary Dynam Cambridge MA 02138 USA

ISBN: (纸本)9780769549712

To study the emergence of cooperative behavior, we have developed a scalable parallel framework for evolutionary game dynamics. This is a critical computational tool enabling large-scale agent simulation research. An important aspect is the amount of history, or memory steps, that each agent can keep. When six memory steps are taken into account, the strategy space spans 2(4096) potential strategies, requiring large populations of agents. We introduce a multi-level decomposition method that allows us to exploit both multi-node and thread-level parallel scaling while minimizing communication overhead. We present the results of a production run modeling up to six memory steps for populations consisting of up to 1018 agents, making this study one of the largest yet undertaken. The high rate of mutation within the population results in a non-trivial parallel implementation. The strong and weak scaling studies provide insight into parallel scalability and programmability trade-offs for large-scale simulations, while exhibiting near perfect weak and strong scaling on 16,384 tasks on Blue Gene/Q. We further show 99% weak scaling up to 294,912 processors 82% strong scaling efficiency up to 262,144 processors of Blue Gene/P. Our framework marks an important step in the study of game dynamics with potential applications in fields ranging from biology to economics and sociology.

关键词： game theory evolutionary dynamics multicore optimization

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Closed Cube Algorithm Research for distributed Storage

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2nd international Conference on Mechatronics and Control Engineering (ICMCE 2013)

作者： Ding, Junshuai You, Jinguo Zhou, Shuili Kumming Univ Sci & Technol Kunming Peoples R China

ISBN: (纸本)9783037858943

Data cube is to improve the efficiency of an important means in data query, while the enclosed data cube used by eliminating non-enclosed data cube tuples to reduce the disk space and improve the query response time. Based on the MapReduce parallel processing technology research, the MapReduce-based closed data cube generation algorithm is proposed,which can effectively improve the closed data cube massive data generation rate. The simulation results show that the proposed MCDC algorithm in practical applications can offer conditional definition by users to build closed data cube that is needed. parallel processing capability of distribution system has been fully developed.

关键词： Data Cube MapReduce Non-closed Tuples Closed Cube distributed Systems

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On the Merits of distributed Work-stealing on Selective Locality-aware Tasks

On the Merits of Distributed Work-stealing on Selective Loca...

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42nd Annual international Conference on parallel processing (ICPP)

作者： Paudel, Jeeva Tardieu, Olivier Amaral, Jose Nelson Univ Alberta Edmonton AB T6G 2M7 Canada IBM Corp Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA

ISBN: (纸本)9780769551173

Improving the performance of work-stealing load-balancing algorithms in distributed shared-memory systems is challenging. These algorithms need to overcome high costs of contention among workers, communication and remote data-references between nodes, and their impact on the locality preferences of tasks. Prior research focus on stealing from a victim that best exploits data locality, and on using special deques that minimize the contention between local and remote workers. This work explores the selection of tasks that are favourable for migration across nodes in a distributed memory cluster, a lesser-explored dimension to distributed work-stealing. The selection of tasks is guided by the application-level task locality rather than hardware memory topology as is the norm in the literature. The prototype for the performance evaluation of these ideas is implemented in X10, a realization of the asynchronous partitioned global address space programming model. This evaluation reveals the applicability of this new approach on several real-world applications chosen from the Cowichan and the Lonestar suites. On a cluster of 128 processors, the new work-stealing strategy demonstrates a speedup between 12% and 31% over X10's existing scheduler. Moreover, the new strategy does not degrade the performance of any of the applications studied.

关键词： APGAS distributed Work Stealing Performance X10

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Composing Relaxed Transactions

Composing Relaxed Transactions

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IEEE 27th international parallel and distributed processing symposium (IPDPS)

作者： Gramoli, Vincent Guerraoui, Rachid Letia, Mihai Univ Sydney Sydney NSW 2006 Australia Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9780769549712

As the classic transactional abstraction is sometimes considered too restrictive in leveraging parallelism, a lot of work has been devoted to devising relaxed transactional models with the goal of improving concurrency. Nevertheless, the quest for improving concurrency has somehow led to neglect one of the most appealing aspects of transactions: software composition, namely, the ability to develop pieces of software independently and compose them into applications that behave correctly in the face of concurrency. Indeed, a closer look at relaxed transactional models reveals that they do jeopardize composition, raising the fundamental question whether it is at all possible to devise such models while preserving composition. This paper shows that the answer is positive. We present outheritance, a necessary and sufficient condition for a (potentially relaxed) transactional memory to support composition. Basically, outheritance requires child transactions to pass their conflict information to their parent transaction, which in turn maintains this information until commit time. Concrete instantiations of this idea have been used before, classic transactions being the most prevalent example, but we believe to be the first to capture this as a general principle as well as to prove that it is, strictly speaking, equivalent to ensuring composition. We illustrate the benefits of outheritance using elastic transactions and show how they can satisfy outheritance and provide composition without hampering concurrency. We leverage this to present a new (transactional) Java package, a composable alternative to the concurrency package of the JDK, and evaluate efficiency through an implementation that speeds up state of the art software transactional memory implementations (TL2, LSA, SwissTM) by almost a factor of 3.

关键词： transactional memory multicore processing scalability

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Acceleration of an Asynchronous Message Driven Programming Paradigm on IBM Blue Gene/Q

Acceleration of an Asynchronous Message Driven Programming P...

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IEEE 27th international parallel and distributed processing symposium (IPDPS)

作者： Kumar, Sameer Sun, Yanhua Kale, Laxmikant V. IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA Univ Illinois Urbana Urbana Urbana IL USA

ISBN: (纸本)9780769549712

IBM Blue Gene/Q is the next generation Blue Gene machine that can scale to tens of Peta Flops with 16 cores and 64 hardware threads per node. However, significant efforts are required to fully exploit its capacity on various applications, spanning multiple programming models. In this paper, we focus on the asynchronous message driven parallel programming model - Charm++. Since its behavior (asynchronous) is substantially different from MPI, that presents a challenge in porting it efficiently to BG/Q. On the other hand, the significant synergy between BG/Q software and Charm++ creates opportunities for effective utilization of BG/Q resources. We describe various novel fine-grained threading techniques in Charm++ to exploit the hardware features of the BG/Q compute chip. These include the use of L2 atomics to implement lockless producer-consumer queues to accelerate communication between threads, fast memory allocators, hardware communication threads that are awakened via low overhead interrupts from the BG/Q wakeup unit. Burst of short messages is processed by using the ManytoMany interface to reduce runtime overhead. We also present techniques to optimize NAMD computation via Quad processing Unit (QPX) vector instructions and the acceleration of message rate via communication threads to optimize the Particle Mesh Ewald (PME) computation. We demonstrate the benefits of our techniques via two benchmarks, 3D Fast Fourier Transform, and the molecular dynamics application NAMD. For the 92,000-atom ApoA1 molecule, we achieved 683 mu s/step with PME every 4 steps and 782 mu s/step with PME every step.

关键词： IBM computers fast Fourier transforms molecular dynamics method multiprocessing systems parallel machines parallel programming

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A preemption-based runtime to efficiently schedule multi-process applications on heterogeneous clusters with GPUs

A preemption-based runtime to efficiently schedule multi-pro...

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

作者： Sajjapongse, Kittisak Wang, Xiang Becchi, Michela Dept. of Electrical and Computer Engineering University of Missouri Columbia MO United States

ISBN: (纸本)9781450319102

In the last few years, thanks to their computational power, their progressively increasing programmability and their wide adoption in both the research community and in industry, GPUs have become part of HPC clusters (for example, the US Titan and Stampede and the Chinese Tianhe-1A supercomputers). As a result, widely used open-source cluster resource managers (e.g. SLURM and TORQUE) have recently been extended with GPU support capabilities. These systems, however, provide simple scheduling mechanisms that often result in resource underutilization and, thereby, in suboptimal performance. In this paper, we propose a runtime system that can be integrated with existing cluster resource managers to enable a more efficient use of heterogeneous clusters with GPUs. Differently from previous work, we focus on multi-process GPU applications including synchronization (for example, hybrid MPI-CUDA applications). We discuss the limitations and inefficiencies of existing scheduling and resource sharing schemes in the presence of synchronization. We show that preemption is an effective mechanism to allow efficient scheduling of hybrid MPI-CUDA applications. We validate our runtime on a variety of benchmark programs with different computation and communication patterns. © 2013 ACM.

关键词： Graphics processing unit

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distributed computing method based on mathematical morphology

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2nd international Conference on Green Communications and Networks, GCN 2012

作者： Wang, Yanbo Modern Education Technique Center Changchun University of Chinese Medicine Changchun 130117 China

ISBN: (纸本)9783642354694

The mathematical basis of mathematical morphology is set theory, which is widely used in the field of image processing, and distributed computing methods will require significant computing resources case that is broken down into small pieces, it has a plurality of computer parallel collaborative, and finally gives the results. Based on the heterogeneous network workstation as research platform, the mapping hyperspectral image processing technology is studied as a case that discusses the mathematical morphology and distributed computing method in the platform applications surveying and mapping hyperspectral image processing heterogeneous. Hyperspectral imaging is a new remote sensing technology. Its effective response time is the key of space earth science and planetary exploration. In response to this problem, the distributed calculation method is realized based on mathematical morphology to establish performance evaluation indicators. Through comparative analysis, the method is verified that using the morphological algorithm of distributed algorithm has a time advantage, which will contribute to the high spectrum image to select the appropriate distributed computing technology and to adopt a particular application strategy. © 2013 Springer-Verlag.

关键词： distributed computer systems

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Efficient lidar point cloud data managing and processing in a Hadoop-based distributed framework 2

Efficient lidar point cloud data managing and processing in ...

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2nd international symposium on Spatiotemporal Computing, ISSC 2017

作者： Wang, C. Hu, F. Sha, D. Han, X. Hainan Geomatics Center National Administration of Surveying Mapping and Geoinformation of China Haikou Hainan570203 China Department of Geography and GeoInformation Science Center for Intelligent Spatial Computing George Mason University FairfaxVA22030-4444 United States

Light Detection and Ranging (LiDAR) is one of the most promising technologies in surveying and mappingï1/4city management, forestry, object recognition, computer vision engineer and others. However, it is challenging to efficiently storage, query and analyze the high-resolution 3D LiDAR data due to its volume and complexity. In order to improve the productivity of Lidar data processing, this study proposes a Hadoop-based framework to efficiently manage and process LiDAR data in a distributed and parallel manner, which takes advantage of Hadoop's storage and computing ability. At the same time, the Point Cloud Library (PCL), an open-source project for 2D/3D image and point cloud processing, is integrated with HDFS and MapReduce to conduct the Lidar data analysis algorithms provided by PCL in a parallel fashion. The experiment results show that the proposed framework can efficiently manage and process big LiDAR data. © Authors 2017.

关键词： distributed computing GIS Hadoop HDFS Lidar data MapReduce PCL Point cloud

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Handling Uncertainty: Pareto-Efficient BoT Scheduling on Hybrid Clouds

Handling Uncertainty: Pareto-Efficient BoT Scheduling on Hyb...

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42nd Annual international Conference on parallel processing (ICPP)

作者： HoseinyFarahabady, M. Reza Samani, Hamid R. D. Leslie, Luke M. Lee, Young Choon Zomaya, Albert Y. Univ Sydney Ctr Distributed & High Performance Comp Sch Informat Technol Sydney NSW 2006 Australia

ISBN: (纸本)9780769551173

Coping with uncertainty is a challenging and complex problem particularly in hybrid cloud environments-private cloud plus public cloud. Conflicting goals of minimizing the cost and performance, unknown prior knowledge about task running times, and a lack of estimation tools are just a few of the challenges that resource management systems in those environments encounter. The aim in this paper is to find Pareto-optimal schedules for large-scale Bag-of-Tasks (BoT) applications that meet user-defined constraints, such as deadline or budget or some tradeoff between them. BoT applications are common in science and engineering and consist of many independent tasks. To achieve the user's chosen Pareto-optimal schedule, we develop a dynamic resource allocation process for hybrid clouds. We also present a hybrid approach to estimating task running times that incorporates several estimators with a feedback control system to cope with the inherent uncertainty in such estimation. Through extensive experiments on a testbed hybrid cloud, using Amazon EC2 as a public cloud, we show that the proposed approach can achieve near-optimality with little overhead, and consistently achieves a solution within 2% of the user's chosen Pareto-optimal schedule. Further, we demonstrate that our approach performs better than an extended List scheduling approach by reducing both the total cost and time needed to run the application by almost 20% and 5% on average, respectively.

关键词： Uncertainty Resource allocation Cloud bursting Cost efficiency Pareto-frontier Bag-of-Tasks applications

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