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Lightweight Transactional Arrays for Read-Dominated Workloads 1

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11th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Anjo, Ivo Cachopo, Joao Univ Tecn Lisboa INESC ID Lisboa Inst Super Tecn ESW P-1000029 Lisbon Portugal

ISBN: (数字)9783642246692

ISBN: (纸本)9783642246685

Many common workloads rely on arrays as a basic data structure on top of which they build more complex behavior. Others use them because they are a natural representation for their problem domains. Software Transactional Memory (STM) has been proposed as a new concurrency control mechanism that simplifies concurrent programming. Yet, most STM implementations have no special representation for arrays. this results, on many STMs, in inefficient internal representations, where much overhead is added while tracking each array element individually, and on other STMs in false-sharing conflicts, because writes to different elements on the same array result in a conflict. In this work we propose new designs for array implementations that are integrated with the STM, allowing for improved performance and reduced memory usage for read-dominated workloads, and present the results of our implementation of the new designs on top of the JVSTM, a Java library STM.

关键词： parallel Programming Software Transactional Memory

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Efficient parallel Message Computation for MAP Inference

Efficient Parallel Message Computation for MAP Inference

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IEEE international conference on Computer Vision (ICCV)

作者： Alchatzidis, Stavros Sotiras, Aristeidis Paragios, Nikos Ecole Cent Paris Ctr Visual Comp Chatenay Malabry France INRIA Saclay Equipe GALEN Orsay France

ISBN: (纸本)9781457711022

First order Markov Random Fields (MRFs) have become a predominant tool in Computer Vision over the past decade. Such a success was mostly due to the development of efficient optimization algorithms both in terms of speed as well as in terms of optimality properties. Message passing algorithms are among the most popular methods due to their good performance for a wide range of pairwise potential functions (PPFs). their main bottleneck is computational complexity. In this paper, we revisit message computation as a distance transformation using a more formal setting than [8] to generalize it to arbitrary PPFs. the method is based on [20] yielding accurate results for a specific class of PPFs and in most other cases a close approximation. the proposed algorithm is parallel and thus enables us to fully take advantage of the computational power of parallel processing architectures. the proposed scheme coupled with an efficient belief propagation algorithm [8] and implemented on a massively parallel coprocessor provides results as accurate as state of the art inference methods, though is in general one order of magnitude faster in terms of speed.

关键词： Approximation algorithms Approximation methods Belief propagation Graphics processing unit Labeling Optimization Vectors

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Application of FPGA for High-Speed Dynamic Response Simulator for Large-Scale MDOF Systems 8

Application of FPGA for High-Speed Dynamic Response Simulato...

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8th international conference on Structural Dynamics (EURODYN)

作者： Igarashi, Akira Matshima, Jun-ichi Kyoto Univ Dept Civil & Earth Resources Engn Nishikyo Ku Kyoto 6158540 Japan Nomura Res Inst Ltd Chiyoda Ku Tokyo 1000005 Japan

ISBN: (纸本)9789076019314

Application of FPGA (Field Programmable Gate Array) to a numerical simulator for the purpose of achieving fast computation of MDOF structural model in the real-time experimental hybrid simulation system is investigated. Design and performance analysis of logic circuits required for high-speed dynamic simulation of MDOF structural system model are performed, and verification of the implementation of the designed logic circuit to actual FPGA device is verified. Furthermore, limitation of computational performance of a single FPGA unit in terms of the speed of the processing and the number of DOF of the structural model applied is investigated.

关键词： Real-time hybrid simulation Logic circuit parallel computing

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Proceedings of the 8th ACM international conference on Computing Frontiers, CF'11

Proceedings of the 8th ACM International Conference on Compu...

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8th ACM international conference on Computing Frontiers, CF'11

ISBN: (纸本)9781450306980

the proceedings contain 40 papers. the topics discussed include: efficient stack distance computation for priority replacement policies;elastic pipeline: addressing GPU on-chip shared memory bank conflicts;pruning hardware evaluation space via correlation-driven application similarity analysis;scaling scientific applications on clusters of hybrid multicore/GPU nodes;performance optimization by dynamic code transformation;increasing power/performance resource efficiency on virtualized enterprise servers;a reconfigurable cache architecture for energy efficiency;hybrid high-performance low-power and ultra-low energy reliable caches;dynamic co-management of persistent ram main memory and storage resources;cluster-based topologies for 3D stacked architectures;universal optical multi-drop bus for heterogeneous memory architecture;CNC-hadoop: a graphical coordination language for distributed multiscale parallelism;and a parallel programming framework orchestrating multiple languages and architectures.

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Performance Evaluation of Open Source Seismic Data processing Packages

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11th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Aziz, Izzatdin A. Goscinski, Andrzej M. Hobbs, Michael M. Deakin Univ Fac Sci & Technol Sch Informat Technol Geelong Vic 3217 Australia

ISBN: (纸本)9783642246494

In many businesses, including hydrocarbon industries, reducing cost is of high priority. Although hydrocarbon industries appear able to afford the expensive computing infrastructure and software packages used to process seismic data in the search for hydrocarbon traps, it is always imperative to find ways to minimize cost. Seismic processing costs can be significantly reduced by using inexpensive, open source seismic data processing packages. However, hydrocarbon industries question the processing performance capability of open source packages, claiming that their seismic functions are less integrated and provide almost no technical guarantees for one to use. the objective of this paper is to demonstrate, through a comparative analysis, that open source seismic data processing packages are capable of executing the required seismic functions on an actual industrial workload. To achieve this objective we investigate whether or not open source seismic data processing packages can be executed using the same set of seismic data through data format conversions, and whether or not they can achieve reasonable performance and speedup when executing parallel seismic functions on a HPC cluster. Among the few open source packages available on the Internet, the subjects of our study are two popular packages: Seismic UNIX (SU) and Madagascar.

关键词： High performance computing open source seismic data processing packages Seismic data processing Seismic UNIX Madagascar

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Fast two dimensional convex hull on the GPU

Fast two dimensional convex hull on the GPU

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25th IEEE international conference on Advanced Information Networking and Applications Workshops, WAINA 2011

作者： Srungarapu, Srikanth Reddy, Durga Prasad Kothapalli, Kishore Narayanan, P.J. International Institute of Information Technology Hyderabad Gachibowli Hyderabad 500 032 India

ISBN: (纸本)9780769543383

General purpose programming on the graphics processing units(GPGPU) has received a lot of attention in the parallel computing community as it promises to offer a large computational power at a very low price. GPGPU is best suited for regular data parallel algorithms. they are not directly amenable for algorithms which have irregular data access patterns such as convex hull, list ranking etc. In this paper, we present a GPU-optimized implementation for finding the convex hull of a two dimensional point set. Our implementation tries to minimize the impact of irregular data access patterns. Our implementation can find the convex hull of 10 million random points in less than 0.2 seconds and achieves a speedup of up to 14 over the standard sequential CPU implementation. We also discuss some of the practical issues relating to the implementation of convex hull algorithms on massively multi-threaded architectures like that of the GPU. © 2011 IEEE.

关键词： Graphics processing unit

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Dynamic Data Race Detection for Correlated Variables

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11th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Jannesari, Ali Westphal-Furuya, Markus Tichy, Walter F. Karlsruhe Inst Technol Inst Program Struct & Data Org D-76131 Karlsruhe Germany

ISBN: (纸本)9783642246494

In parallel programs concurrency bugs are often caused by unsynchronized accesses to shared memory locations, which are called data races. In order to support programmers in writing correct parallel programs, it is therefore highly desired to have tools on hand that automatically detect such data races. Today, most of these tools only consider unsynchronized read and write operations on a single memory location. Concurrency bugs that involve multiple accesses on a set of correlated variables may be completely missed. Tools may overwhelm programmers with data races on various memory locations, without noticing that the locations are correlated. In this paper, we propose a novel approach to data race detection that automatically infers sets of correlated variables and logical operations by analyzing data and control dependencies. For data race detection itself, we combine a modified version of the lockset algorithm with happens-before analysis providing the first hybrid, dynamic race detector for correlated variables. We implemented our approach on top of the Valgrind, a framework for dynamic binary instrumentation. Our evaluation confirmed that we can catch data races missed by existing detectors and provide additional information for correct bug fixing.

关键词： data race detection parallel programs dynamic analysis correlated variables

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Resource planning for parallel processing in the cloud

Resource planning for parallel processing in the cloud

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13th IEEE international Workshop on FTDCS 2011, the 8th international conference on ATC 2011, the 8th international conference on UIC 2011 and the 13th IEEE international conference on HPCC 2011

作者： Shi, Justin Y. Taifi, Moussa Khreishah, Abdallah Department of Computer and Information Sciences Temple University Philadelphia PA 19122 United States

ISBN: (纸本)9780769545387

Before the emergence of commercial cloud computing, interests in parallel algorithm analysis have been mostly academic. When computing and communication resources are charged by hours, cost effective parallel processing would become a required skill. this paper reports a resource planning study using a method derived from classical program time complexity analysis, we call Timing Models. Unlike existing qualitative performance analysis methods, a Timing Model uses application instrumented capacity measures to capture the quantitative dependencies between a computer program (sequential or parallel) and its processing environments. For applications planning to use commercial clouds, this tool is ideally suited for choosing the most cost-effective configuration. the contribution of the proposed tool is its ability to explore multiple dimensions of a program quantitatively to gain non-trivial insights. this paper uses a simple matrix multiplication application to illustrate the modeling, program instrumentation and performance prediction processes. Since cloud vender do offer HPC hardware resources, we use Amazon EC2 as the target processing environments. the computing and communication models are not only useful in choosing the processing platform but also for understanding the resource usage bills. Comparisons between predicted and actual resource usages show that poor processing granularity wastes resources. Prediction errors are minimized near the optimal number of processors. © 2011 IEEE.

关键词： Cloud computing

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Adaptive parallel interval global optimization algorithms based on their performance for non-dedicated multicore architectures

Adaptive parallel interval global optimization algorithms ba...

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19th international Euromicro conference on parallel, Distributed and Network-Based processing (PDP)

作者： Sanjuan-Estrada, J. F. Casado, L. G. Garcia, I. Univ Almeria Dept Comp Architecture & Elect Almeria Spain Univ Malaga Dept Comp Architecture Malaga Spain

ISBN: (纸本)9780769543284

Branch and Bound (B&B) algorithms are highly parallelizable but they are irregular and dynamic load balancing techniques have been used to avoid idle processors. In previous work, authors use a dynamic number of threads at run time, which depends on the measured performance of the application for just one interval B&B algorithm running on the system. In this way, load balancing is achieved by thread generation decisions. In this work, we extend the study of these models to non-dedicated systems. In order to have a controlled testbed and comparable results, several instances of the interval global optimization algorithm are executed in the system, with the same model and problem to solve. therefore, a non-dedicated system is simulated because the execution of one application affects the execution of the other instances. this paper discusses different methods and models to decide when a thread should be created. Experiments show which of the proposed methods performs best in terms of maximum running time per application, using the fewest running threads. Following this parallel programming methodology, which is well suited for other B&B codes, applications can adapt their parallelism level to their performance and load of the system (at run time). this work represents a step forward towards increasing the performance of parallel algorithm running in non-dedicated and heterogeneous systems. the adaptive model discussed in this work is able to reduce the overall execution time for a set of instances of the same application running simultaneously. It also exempts the user from specifying the number of threads each application should use.

关键词： multi-threaded branch-and-bound global optimization non-dedicated multicore thread generation decisions sleeping threads kernel idle thread

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A graph-theory-based method for parallelizing the multiple-flow-direction algorithm on CUDA compatible graphics processing units

A graph-theory-based method for parallelizing the multiple-f...

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2011 IEEE international conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM 2011 - In Conjunction with 8th Beijing international Workshop on Geographical Information Science, BJ-IWGIS 2011

作者： Zhan, Lijun Qin, Chengzhi State Key Laboratory of Resources and Environment Information System Chinese Academy of Sciences Beijing 100101 China Graduate School of the Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781424483495

Flow direction algorithm based on gridded DEM is one kind of the most widely used algorithms in digital terrain analysis. Being a typical recursive algorithm, flow direction algorithm coded traditionally for sequential computation is very time consuming, especially for application on the gridded DEM of large-area with high spatial resolution. Recently, the graphics processing units (GPUs) were applied to speeding up the execution of single flow direction algorithm (SFD) by parallel computing based on compute unified device architecture (CUDA). Although multiple flow direction (MFD) algorithms perform generally better than SFD, parallel MFD algorithm on GPU hasn't been reported. In this paper, first we designed a CUDA-based parallel implementation on the NVIDIA GPU of a widely-used MFD algorithm (FD8) by using the parallelization strategy of the existing CUDA-based parallel SFD algorithm. Further analysis shows that this parallelization strategy has a problem of computing redundancy. then, we proposed a graph-theory-based parallel implementation of FD8 algorithm in which the problem of computing redundancy could be released. the application result shows that the proposed graph-theory-based parallel FD8 algorithm gets faster acceleration than the parallel FD8 algorithm using the parallelization strategy of the existing CUDA-based parallel SFD algorithm, and performs much faster than the traditional serial FD8 algorithm. © 2011 IEEE.

关键词： Graphics processing unit

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