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Adaptive task size control on high level programming for GPU/CPU work sharing

Adaptive task size control on high level programming for GPU...

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13th international conference on algorithms and architectures for parallel processing, ICA3PP 2013

作者： Odajima, Tetsuya Boku, Taisuke Sato, Mitsuhisa Hanawa, Toshihiro Kodama, Yuetsu Namyst, Raymond thibault, Samuel Aumage, Olivier Graduate School of Systems and Information Engineering University of Tsukuba Japan Center for Computational Sciences University of Tsukuba Japan University of Bordeaux LaBRI INRIA Bordeaux Sud-Ouest France

ISBN: (纸本)9783319038889

On the work sharing among GPUs and CPU cores on GPU equipped clusters, it is a critical issue to keep load balance among these heterogeneous computing resources. We have been developing a runtime system for this problem on PGAS language named XcalableMP-dev/ StarPU [1]. through the development, we found the necessity of adaptive load balancing for GPU/CPU work sharing to achieve the best performance for various application codes. In this paper, we enhance our language system XcalableMP-dev/ StarPU to add a new feature which can control the task size to be assigned to these heterogeneous resources dynamically during application execution. As a result of performance evaluation on several benchmarks, we confirmed the proposed feature correctly works and the performance with heterogeneous work sharing provides up to about 40% higher performance than GPU-only utilization even for relatively small size of problems. © Springer international Publishing Switzerland 2013.

关键词： Graphics processing unit

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POIGEM: A programming-oriented instruction level GPU energy model for CUDA program

POIGEM: A programming-oriented instruction level GPU energy ...

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13th international conference on algorithms and architectures for parallel processing, ICA3PP 2013

作者： Zhao, Qi Yang, Hailong Luan, Zhongzhi Qian, Depei Sino-German Joint Software Institute Department of Computer Science and Engineering Beihang University No.37 Xuanyuan Road Beijing 100191 China

ISBN: (纸本)9783319038582

GPU architectures tend to be increasingly important in multi-core era nowadays due to their formidable computational horsepower. With the assistant of effective programming paradigms as CUDA, GPUs are widely adopted to accelerate scientific applications. Meanwhile, the surging energy consumption by GPUs becomes a major challenge to both GPU architects and programmers. In addition to the efforts designing energy efficient GPU architecture, comprehensive understanding on how programming affects the energy consumption of GPU application is also indispensable from the programmer perspective. In this paper, we present a programming-oriented PTX instruction level energy model to provide programmers the ability of predicting the energy consumption of their program. Distinct from previous models which require hardware performance counters or architectural simulations, our model relies on the PTX instruction of a CUDA program which is not only portable but also accurate. With the selected PTX instructions based on empirical study, we apply linear regression to build the GPU energy model. One appealing advantage of our model is that it does not require any instrumentation or profiling of the GPU application during execution. Actually, our model is able to advise the programmers step by step to illustrate how their way of programming impacts the final energy consumption, especially at the stage of hacking the codes. Our model is evaluated on NVIDIA GeForce GTX 470 with Rodinia benchmark suites. the results show the accuracy of our model is promising with average prediction error below 3.7%. With the help of our GPU energy model, the programmers are gaining valuable insights to improve the energy efficiency of the application. © Springer international Publishing Switzerland 2013.

关键词： Graphics processing unit

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A linguistic-based method for automatically extracting spatial relations from large non-structured data

A linguistic-based method for automatically extracting spati...

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13th international conference on algorithms and architectures for parallel processing, ICA3PP 2013

作者： Elia, Annibale Guglielmo, Daniela Maisto, Alessandro Pelosi, Serena Department of Political Social and Communication Science SemanticItaLab University of Salerno via Giovanni Paolo II 132 84084 Fisciano Italy Department of Electric Engineering and Information Technologies University of Naples Federico II via Claudio 21 80125 Napoli Italy

ISBN: (纸本)9783319038889

this paper presents a Lexicon-Grammar based method for automatic extraction of spatial relations from Italian non-structured data. We used the software Nooj to build sophisticated local grammars and electronic dictionaries associated with the lexicon-grammar classes of the Italian intransitive spatial verbs (i.e. 234 verbal entries) and we applied them to the Italian text Il Codice da Vinci ('the Da Vinci Code', by Dan Brown) in order to parse the spatial predicate-arguments structures. In addition, Nooj allowed us to automatically annotate (in XML format) the words (or the sequence of words) that in each sentence (S) of the text play the 'spatial roles' of Figure (F), Motion (M) and Ground (G). Finally the results of the experiment and the evaluation of this method will be discussed. © Springer international Publishing Switzerland 2013.

关键词： Natural language processing systems

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GPU-Based parallel EDF-Schedulability Analysis of Multi-modal Real-Time Systems

GPU-Based Parallel EDF-Schedulability Analysis of Multi-moda...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Masud Ahmed Safraz Rampersaud Nathan Fisher Daniel Grosu Loren Schwiebert Department of Computer Science Wayne State University USA

Real-time multi-modal systems are useful in modeling embedded systems that dynamically change computational requirements over time (e.g., adaptive cruise control systems). For meeting timing constraints of such multi-modal systems, Earliest-Deadline-First (EDF) is an attractive real-time scheduling algorithm due to its optimality on uniprocessor platforms. However, checking EDF-schedulability of a real-time multi-modal system is a difficult problem that requires substantial computational effort. Today's cost efficient and massively parallel GPU platforms can be effectively leveraged to solve this difficult problem. Existing algorithms for EDF-schedulability of real-time multi-modal systems cannot exploit the entire computational power of a GPU, therefore, in this research, we develop a parallel algorithm leveraging the advantages of a GPU device. Experimental results establish the superior performance of our proposed algorithm upon a low end GPU over the implementation of existing algorithms on a cluster of computers using either MPI or OpenMP. In addition to performance, our proposed algorithm is a cost effective and power efficient alternative against comparable algorithms for multi-core and parallel computing platforms.

关键词： Real-time systems Graphics processing units Hardware Algorithm design and analysis Clustering algorithms parallel algorithms

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parallelizing Dynamic Time Warping Algorithm Using Prefix Computations on GPU

Parallelizing Dynamic Time Warping Algorithm Using Prefix Co...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Limin Xiao Yao Zheng Wenqi Tang Guangchao Yao Li Ruan School of Computer Science and Engineering Beihang University Beijing China

the dynamic time warping (DTW) algorithm has O(n2) time complexity, which indicates that it is hard to process large-scale time series within an acceptable time. Recently, many researchers have used graphics processing units (GPUs) to accelerate the algorithm. Owing to the data dependence of DTW, however, most of existing GPU-based DTW algorithms exploits task-level parallelism by simply replicating the serial algorithm on every multiprocessor of a GPU. the fundamental issue with such coarse-grained parallelism is that the solvable problem size is severely limited by the share memory and cache of a GPU multiprocessor. In this study, we introduce a specific transformation of data dependence by using prefix computations. Further, we propose an efficient GPU-parallel DTW algorithm to address the problem of instance sizes limitation. the efficiency of our algorithm is validated through experiments, which demonstrate improved performance over existing GPU-based task-level parallel DTW algorithms. Our experimental results indicate speedups up to 99 times faster on NVIDIA GTX480, compared to CPU implementations.

关键词： Time series analysis Graphics processing units Heuristic algorithms parallel algorithms Arrays Instruction sets

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DPAgg: A Dynamic Partition Aggregation on Multicore Processor in Main-Memory Database

DPAgg: A Dynamic Partition Aggregation on Multicore Processo...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Dateng Hao Li Sun Computer Science and Technology Department of Donghua University Shanghai China

ISBN: (纸本)9781479909735

Multicore processor provides an opportunity of query performance enhancement in database by parallel processing. However, the increasing of cores and computing performance of multicore processor can't be utilized efficiently because of the bottleneck of memory access. It is known to all that aggregation is one of the most important operators in database. In this paper, we present a new dynamic partition aggregation algorithm. It's a group by value based partition algorithm like most the state-of-art parallel aggregation algorithms. First, the algorithm introduces dynamic partition strategy into aggregation in order to make it more adaptive to different characteristic data. Second, it sets the optimized cache level to L2 not last level cache. third, the improvements that are proposed for Radix-Clustered hash join are also been modified and applied into aggregation in order to reduce overhead cost of partition operations. Our experiments show the superiority of our dynamic partition aggregation algorithm on multicore processor.

关键词： Partitioning algorithms Multicore processing Algorithm design and analysis Databases Heuristic algorithms Clustering algorithms Memory management

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parallel numerical optimization for fast adaptive nonlinear moving horizon estimation

Parallel numerical optimization for fast adaptive nonlinear ...

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IEEE international conference on Networking, Sensing and Control

作者： Tomáš Polóni Boris Rohal'-Ilkiv Tor Arne Johansen Institute of Automation Slovak University of Technology Bratislava Slovakia Slovenska Technicka Univerzita Bratislava SK Department of Engineering Cybernetics Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9781467351980

this paper proposes a novel strategy using parallel optimization computations for nonlinear moving horizon state estimation, and parameter identification problems of dynamic systems. the parallelization is based on the multi-point derivative-based Gauss-Newton search, as one of the most efficient algorithms for the nonlinear least-square problems. A numerical experiment is performed to demonstrate the parallel computations with the comparison to sequential computations.

关键词： Noise Equations Loss measurement Vectors Computational modeling Multicore processing Real-time systems

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Accelerating dynamics simulation of solidification processes of liquid metals using GPU with CUDA

Accelerating dynamics simulation of solidification processes...

引用

2013 IEEE 37th Annual Computer Software and Applications conference, COMPSAC 2013

作者： Liang, Jie Li, Kenli Shi, Lin Liao, Yingqiang School of Information Science and Engineering Hunan University Changshang China

ISBN: (纸本)9780769549798

Molecular dynamics simulation is a powerful tool to simulate and analyze complex physical processes and phenomena at atomic characteristic for predicting the natural time-evolution of a system of atoms. Precise simulation of processes such as liquid metal solidification processes simulation has strong requirements both in the simulation size and computing timescale. therefore, finding available computing resources is crucial to accelerate computation of solidification processes simulations. this paper presents a new approach to accelerate calculation of liquid metal solidification processes based on the previous study implemented on the CPU clusters, where the GPU-based MD (molecular dynamics) algorithm using a fine-grained spatial decomposition method enlarge the scale of the simulation system to a simulation system involving 10, 000, 000 atoms. the algorithms are implemented using FORTRAN and CUDA on a commodity NVIDIA Tesla M2050 card, where experimental results demonstrate that GPU-based calculations are typically 9-11 times faster than the corresponding sequential execution and approximately 1.5-2 times faster than 16-CPU clusters implementations. © 2013 IEEE.

关键词： Graphics processing unit

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Product Lifecycle Management in an Open Industry Framework 10

Product Lifecycle Management in an Open Industry Framework

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10th IFIP WG 5.1 international conference on Product Lifecycle Management (PLM)

作者： Fukuda, Shuichi Keio Univ SDM Kohoku Ku Yokohama Kanagawa 2238526 Japan

ISBN: (纸本)9783642415012

the basic concept of "an Open Industry Framework" is proposed. Current industry framework is closed and industries are making their efforts to produce best quality products in their own particular field. this is because current industries developed on the basis of their inventions. But quickly increasing diversification and frequent and extensive changes are calling for an open framework. In this new framework, industries operate on the basis of parallel Distributed processing model. they process multiple tasks in parallel among different types of industries. To achieve such a goal, modular production is called for but current ones are not fully integrated between design and manufacturing. We have to develop a module system which integrates design and manufacturing and which can be shared across industries. When such a system is developed, industries will be divided into two groups. One is subsystem suppliers and the other is system integrators. the subsystem here works in the same way as Lego pieces. Such a framework will enable to distribute production activities to local factories according to their capabilities so that it will increase local employment and their buying power. And we do not have to carry heavy final product over a long distance. thus, an Open Industry Framework will reduce time to market, cost and energy consumption considerably and industries can be more flexible and adaptive and can satisfy the basic needs of customers.

关键词： open Industry framework parallel distributed processing different types of industries modular production basic needs

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Novel Multi-Layer Network Decomposition Boosting Acceleration of Multi-core algorithms

Novel Multi-Layer Network Decomposition Boosting Acceleratio...

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IEEE international conference on Application-specific Systems, architectures and Processors

作者： Athanasios K. Grivas Terrence Mak Alex Yakovlev Jonny Wray School of Electrical and Electronic Engineering Newcastle University UK Department of Computer Science and Engineering The Chinese University of Hong Kong China

ISBN: (纸本)9781479904945

Complex networks are a technique for the modeling and analysis of large data sets in many scientific and engineering disciplines. Due to their excessive size conventional algorithms and single core processors struggle with the efficient processing of such networks. Employing multi-core graphic processing units (CPUs) could provide sufficient processing power for the analysis of such networks. However, commonly designed algorithms cannot exploit these massively parallel processing power for the analysis of such networks. In this paper, we present the Multi Layer Network Decomposition (MLND) approach which provides a general approach for parallel network analysis using multi-core processors via efficient partitioning and mapping of networks onto GPU architectures. Evaluation using a 336 core GPU graphic card demonstrated a 16x speed-up in complex network analysis relative to a CPU based approach.

关键词： MLND GPU Multi-core algorithms GRAPPER PICK UP Graphics processing Unit processing power complex networks central processing units Network multilayer network Multi-core processors Network analysis

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