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Multi-kernel Auto-Tuning on GPUs: Performance and Energy-Aware Optimization

Multi-kernel Auto-Tuning on GPUs: Performance and Energy-Awa...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： João Guerreiro Aleksandar Ilic Nuno Roma Pedro Tomás INESC-ID Instituto Superior Técnico Universidade de Lisboa Portugal

Prompted by their very high computational capabilities and memory bandwidth, Graphics processing Units (GPUs) are already widely used to accelerate the execution of many scientific applications. However, programmers are still required to have a very detailed knowledge of the GPU internal architecture when tuning the kernels, in order to improve either performance or energy-efficiency. Moreover, different GPU devices have different characteristics, moving a kernel to a different GPU typically requires re-tuning the kernel execution, in order to efficiently exploit the underlying hardware. The procedure proposed in this work is based on real-time kernel profiling and GPU monitoring and it automatically tunes parameters from several concurrent kernels to maximize the performance or minimize the energy consumption. Experimental results on NVIDIA GPU devices with up to 4 concurrent kernels show that the proposed solution achieves near optimal configurations. Furthermore, significant energy savings can be achieved by using the proposed energy-efficiency auto-tuning procedure.

关键词： Kernel Graphics processing units Optimization Instruction sets Performance evaluation Frequency measurement Energy consumption

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A-DRM: Architecture-aware distributed Resource Management of Virtualized Clusters 15

A-DRM: Architecture-aware Distributed Resource Management of...

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11th ACM SIGPLAN/SIGOPS international conference on Virtual Execution Environments

作者： Wang, Hui Isci, Canturk Subramanian, Lavanya Choi, Jongmoo Qian, Depei Mutlu, Onur Beihang Univ Beijing 100191 Peoples R China IBM Thomas J Watson Res Ctr Cambridge MA USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Dankook Univ Yongin Gyeonggi Do South Korea

ISBN: (纸本)9781450334501

Virtualization technologies has been widely adopted by large-scale cloud computing platforms. These virtualized systems employ distributed resource management (DRM) to achieve high resource utilization and energy savings by dynamically migrating and consolidating virtual machines. DRM schemes usually use operating-system-level metrics, such as CPU utilization, memory capacity demand and I/O utilization, to detect and balance resource contention. However, they are oblivious to microarchitecture-level resource interference (e.g., memory bandwidth contention between different VMs running on a host), which is currently not exposed to the operating system. We observe that the lack of visibility into microarchitecture-level resource interference significantly impacts the performance of virtualized systems. Motivated by this observation, we propose a novel architecture-aware DRM scheme (A-DRM), that takes into account microarchitecture-level resource interference when making migration decisions in a virtualized cluster. A-DRM makes use of three core techniques: 1) a profiler to monitor the microarchitecture-level resource usage behavior online for each physical host, 2) a memory bandwidth interference model to assess the interference degree among virtual machines on a host, and 3) a cost-benefit analysis to determine a candidate virtual machine and a host for migration. Real system experiments on thirty randomly selected combinations of applications from the CPU2006, PARSEC, STREAM, NAS parallel Benchmark suites in a four-host virtualized cluster show that A-DRM can improve performance by up to 26.55%, with an average of 9.67%, compared to traditional DRM schemes that lack visibility into microarchitecture-level resource utilization and contention.

关键词： virtualization microarchitecture live migration performance counters resource management

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Charm++ and MPI: Combining the Best of Both Worlds

Charm++ and MPI: Combining the Best of Both Worlds

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international Symposium on parallel and distributed processing (IPDPS)

作者： Nikhil Jain Abhinav Bhatele Jae-Seung Yeom Mark F. Adams Francesco Miniati Chao Mei Laxmikant V. Kale Department of Computer Science University of Illinois at Urbana-Champaign Urbana Illinois USA Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore California USA Lawrence Berkeley National Laboratory Berkeley California USA Institute for Astronomy ETH Zurich Zurich Switzerland Mountain View Google Inc. California USA

Charm++ and MPI embody two distinct perspectives for writing parallel programs. While MPI provides a process-centric, user-driven model for developing parallel codes, Charm++ supports work-centric, system-driven parallel programming. One of them might be a better or more natural fit for individual modules that constitute a parallel application. In this paper, we present a framework that enables hybrid parallel programming with Charm++ and MPI, and allows programmers to develop different modules of a parallel application in these two languages while facilitating smooth interoperation. We describe the challenges in enabling interoperation between Charm++ and MPI, and present techniques for managing the control flow and resource sharing between the two. Finally, we demonstrate the benefits of interoperation between Charm++ and MPI through several case studies that use production applications and libraries, including CHARM/Chombo, EpiSimdemics, NAMD, FFTW, MPI-IO and ParMETIS.

关键词： Libraries Writing Runtime Process control parallel programming Productivity

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LCIndex: A Local and Clustering Index on distributed Ordered Tables for Flexible Multi-dimensional Range Queries

LCIndex: A Local and Clustering Index on Distributed Ordered...

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international conference on parallel processing (ICPP)

作者： Chen Feng Xi Yang Fan Liang Xian-He Sun Zhiwei Xu ICT SKL Computer Architecture China University of Chinese Academy of Sciences Beijing China Department of Computer Science Illinois Institute of Technology Chicago USA

ISBN: (纸本)9781467375887

A lot of Not Only SQL (NoSQL) databases have been proposed in the era of big data. distributed Ordered Table (DOT) is one kind of No SQL database that has attracted lots of attention. It horizontally partitions table into regions and distributes regions to region servers according to the keys. Multi-Dimensional Range Query (MDRQ) is a common operation over DOTs. Many indexing techniques have been proposed to improve the performance of MDRQ, but they cannot guarantee high performance on both insert and flexible MDRQ at the same time. In this paper, we propose a novel indexing technique named LC Index, short for Local and Clustering Index, to solve this issue. Experimental results confirm that LC Index can achieve high performance on both insert operations and flexible MDRQ.

关键词： Indexing Servers US Department of Transportation Throughput Prototypes

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Machines Tuning Machines: Configuring distributed Stream Processors with Bayesian Optimization

Machines Tuning Machines: Configuring Distributed Stream Pro...

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IEEE international conference on Cluster Computing

作者： Lorenz Fischer Shen Gao Abraham Bernstein Department of Informatics University of Zurich Switzerland

Modern distributed computing frameworks such as Apache Hadoop, Spark, or Storm distribute the workload of applications across a large number of machines. Whilst they abstract the details of distribution they do require the programmer to set a number of configuration parameters before deployment. These parameter settings (usually) have a substantial impact on execution efficiency. Finding the right values for these parameters is considered a difficult task and requires domain, application, and framework expertise. In this paper, we propose a machine learning approach to the problem of configuring a distributed computing framework. Specifically, we propose using Bayesian Optimization to find good parameter settings. In an extensive empirical evaluation, we show that Bayesian Optimization can effectively find good parameter settings for four different stream processing topologies implemented in Apache Storm resulting in significant gains over a parallel linear approach.

关键词： Topology Bayes methods Optimization Storms parallel processing Fasteners Message systems

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Algorithms for Mapping parallel Processes onto Grid and Torus Architectures

Algorithms for Mapping Parallel Processes onto Grid and Toru...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Roland Glantz Hening Meyerhenke Alexander Noe Institute of Theoretical Informatics Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

Static mapping is the assignment of parallel processes to the processing elements (PEs) of a parallel system, where the assignment does not change during the application's lifetime. In our scenario we model an application's computations and their dependencies by an application graph. This graph is first partitioned into (nearly) equally sized blocks. These blocks need to communicate at block boundaries. To assign the processes to PEs, our goal is to compute a communication-efficient bijective mapping between the blocks and the PEs. This approach of partitioning followed by bijective mapping has many degrees of freedom. Thus, users and developers of parallel applications need to know more about which choices work for which application graphs and which parallel architectures. To this end, we not only develop new mapping algorithms (derived from known greedy methods). We also perform extensive experiments involving different classes of application graphs (meshes and complex networks), architectures of parallel computers (grids and tori), as well as different partitioners and mapping algorithms. Surprisingly, the quality of the partitions, unless very poor, has little influence on the quality of the mapping. More importantly, one of our new mapping algorithms always yields the best results in terms of the quality measure maximum congestion when the application graphs are complex networks. In case of meshes as application graphs, this mapping algorithm always leads in terms of maximum congestion AND maximum dilation, another common quality measure.

关键词： Partitioning algorithms Complex networks Topology Computers Computational modeling Computer architecture Informatics

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Intermediate representation for heterogeneous multi-core: A survey

Intermediate representation for heterogeneous multi-core: A ...

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international conference on VLSI Systems, Architecture, Technology and applications (VLSI-SATA)

作者： Meena Belwal Sudarshan TSB Department of Computer Science and Engineering School of Engineering India

One of the necessary conditions to gain performance improvement through heterogeneous multi-core is to exploit the parallelism in the program. Compiler applies various transformations to the code to achieve execution efficiency. Code optimization is one of the important tasks performed by the compiler before generating the target code. With the availability of various parallel programming models in literature, Intermediate representation (IR) is the key point of applying several optimizations. IR is a form of program which is independent of the source language and the target architecture. There are several IR techniques specifically designed for each compiler framework depending on the input programming language. This article studies the most popular IR techniques for heterogeneous multi-core, classifies them into three broad categories and performs a comparison among them based on the data structure used and their importance in academia and research.

关键词： Benchmark testing Program processors Multicore processing parallel processing Kernel Plasmas Digital video broadcasting

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26th international conference on Database and Expert Systems applications, DEXA 2015

26th International Conference on Database and Expert Systems...

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26th international conference on Database and Expert Systems applications, DEXA 2015

ISBN: (纸本)9783319228518

The proceedings contain 42 papers. The special focus in this conference is on Knowledge Management, Consistency, Mobility, Privacy and Security. The topics include: A logic based approach for restoring consistency in P2P deductive databases;expert system with web interface based on logic of plausible reasoning;extending knowledge-based profile matching in the human resources domain;sensitive business process modeling for knowledge management;partial order preserving encryption search trees;an auditory user interface for geo-service delivery;a diversity-seeking mobile news app based on difference analysis of news articles;candidate pruning technique for skyline computation over frequent update streams;mining frequent closed flows based on approximate support with a sliding window over packet streams;a dynamic final object pruning algorithm to efficiently produce skyline points over data streams;a graph evolution technique for web service composition;can data integration quality be enhanced on multi-cloud using SLA;an efficient gear-shifting power-proportional distributed file system;a divide-and-conquer approach;ontology-driven data partitioning and recovery for flexible query answering;detecting near-duplicate documents using sentence level features;a dwell time-based technique for personalised ranking model;an evaluation of diversification techniques;temporal object indexing for xml documents;expressing and processing path-centric xml queries;a logical framework for xml reference specification;towards to a flash efficient multi-dimensional index;supporting fluctuating transactional workload;indexing multi-dimensional data in modular data centers and a modified tripartite model for document representation in internet sociology.

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Efficient parallelization of the Google Trigram Method for Document Relatedness Computation

Efficient Parallelization of the Google Trigram Method for D...

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international conference on parallel processing Workshops (ICPPW)

作者： Xinxin Kou Jie Mei Zhimin Yao Andrew Rau-Chaplin Aminul Islam Abidalrahman Moh'd Evangelos Milios Faculty of Computer Science Dalhousie University Halifax Canada

Finding pair wise document relatedness plays an important role in a variety of Natural Language processing problems. Google Trigram Method (GTM) is one of the corpus-based unsupervised method that can be used to capture word relatedness and document relatedness. It has been shown that it is possible to apply GTM to construct high quality document relatedness applications. However, there are challenges in implementing GTM for pair-wise document relatedness computation on a large volume of document set given its high computational complexity. This paper presents time and space efficient methods for the computation of pair-wise document relatedness using GTM. In order to improve the performance algorithmic engineering, data structure enhancement, and parallel computing methods are applied. Two parallel methods are discussed in this paper: shared memory multicore implementation and distributed memory Hadoop implementation. Both parallel methods provide an order of magnitude improvement in accelerating the pair-wise document relatedness computation using GTM.

关键词： Dictionaries Arrays Google Multicore processing parallel processing Acceleration

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parallel QR algorithm for the C-method: Application to the diffraction by gratings and rough surfaces 23

Parallel QR algorithm for the C-method: Application to the d...

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23rd High Performance Computing Symposium, HPC 2015, Part of the 2015 Spring Simulation Multi-conference, SpringSim 2015

作者： Pan, Cihui Emad, Nahid Dusséaux, Richard Laboratoire PRiSM 45 avenue des Etats-Unis Versailles78035 France Laboratoire LATMOS 11 Boulevard d'Alembert Guyancourt78280 France Laboratoire Maison de la Simulation Bâtiment 565 Gif-sur-Yvette cedex91191 France Université de Versailles Saint-Quentin en Yvelines Laboratoire PRiSM 45 avenue des Etats-Unis Versailles78035 France Université de Versailles Saint-Quentin en Yvelines Laboratoire LATMOS 11 Boulevard d'Alembert Guyancourt78280 France

ISBN: (纸本)9781510810600

The curvilinear coordinate method (C-method) is an exact method for analysing of electromagnetic waves scattering from rough surfaces. It is based on Maxwell's equations under covariant form written in a non-orthogonal coordinate system. This method leads to an eigenvalue system. All the eigenvalues and eigenvectors of the scattering matrix are required. The QR algorithm seems to be a suitable solution for this high dimension, dense, non-symmetric and complex scattering matrix. In this paper, we present the parallel QR algorithm that is specifically designed for the C-method. We define the "early shift" for the scattering matrix according to the property that we have observed. We mixed the "early shift", Wilkinson's shift and exceptional shift together to accelerate the convergence. Especially, we use the "early shift" first in order to have quick deflation of the real eigenvalues of the scattering matrix. The multi-window bulge chain chasing and parallel aggressive early deflation are used. The multi-window bulge chain chasing approach ensures that most computations arc performed in 3 BLAS operations. The aggressive early deflation approach can detect deflation much quicker and thus accelerate convergence. Mixed MPI-OpenMP techniques are utilized for performing the codes to distributed memory platforms. Numerical experiments are performed and applications of this parallel QR algorithm are applied to a real physical problem of diffraction. © 2015 Society for Modeling & Simulation international (SCS).

关键词： Chains

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