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共 40 条记录，以下是11-20 订阅

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Energy-Aware Query processing on a parallel Database Cluster Node 16th

Energy-Aware Query Processing on a Parallel Database Cluster...

引用

16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Roukh, Amine Bellatreche, Ladjel Tziritas, Nikos Ordonez, Carlos Univ Mostaganem Mostaganem Algeria Univ Poitiers LIAS ISAE ENSMA Poitiers France Chinese Acad Sci Shenzhen Peoples R China Univ Houston Houston TX USA

ISBN: (纸本)9783319495835;9783319495828

In the last few years, we have been seeing a significant increase in research about the energy efficiency of hardware and software components in both centralized and parallel platforms. In data centers, DBMSs are one of the major energy consumers, in which, a large amount of data is queried by complex queries running daily. Having green nodes is a pre-condition to design an energy-aware parallel database cluster. Generally, the most existing DBMSs focus on high-performance during query optimization phase, while usually ignoring the energy consumption of the queries. In this paper, we propose a methodology, supported by a tool called EnerQuery, that makes nodes of parallel database clusters saving energy when optimizing queries. To show its effectiveness, we implement our proposal on the top of PostgreSQL DBMS query optimizer. A mathematical cost model based on a machine learning technique is defined and used to estimate the energy consumption of SQL queries.

关键词： Energy utilization

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Statistical Analysis of CCM.M-K1 international Comparison Based on Monte Carlo Method 16th

Statistical Analysis of CCM.M-K1 International Comparison Ba...

引用

16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Cai, Chang-qing Ren, Xiao-ping Hao, Guo-dong Wang, Jian Huang, Tao Natl Inst Metrol Beijing 100029 Peoples R China Cent S Univ Dept Intelligence Sci & Engn Changsha 410083 Hunan Peoples R China

ISBN: (纸本)9783319499567;9783319499550

the application of the Monte Carlo method is used in the processing of the measurement result of CCM.M-K1. this method can get over the limitations that apply in certain cases to the method described in GUM. Introduction and analysis of CCM.M-K1 measurement result was given out and commercial software named @RISK was used to purse numerical simulation and the result was compared with the final report of CCM.M-K1, which showed that differences between results of these two were negligible.

关键词： Key comparison Reference value Degree of equivalence Monte carlo method

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Efficient parallel Algorithm for Optimal DAG Structure Search on parallel Computer with Torus Network 16th

Efficient Parallel Algorithm for Optimal DAG Structure Searc...

引用

16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Honda, Hirokazu Tamada, Yoshinori Suda, Reiji Univ Tokyo Grad Sch Informat Sci & Technol Tokyo 1138656 Japan

ISBN: (纸本)9783319495835;9783319495828

the optimal directed acyclic graph search problem constitutes searching for a DAG with a minimum score, where the score of a DAG is defined on its structure. this problem is known to be NP-hard, and the state-of-the-art algorithm requires exponential time and space. It is thus not feasible to solve large instances using a single processor. Some parallel algorithms have therefore been developed to solve larger instances. A recently proposed parallel algorithm can solve an instance of 33 vertices, and this is the largest solved size reported thus far. In the study presented in this paper, we developed a novel parallel algorithm designed specifically to operate on a parallel computer with a torus network. Our algorithm crucially exploits the torus network structure, thereby obtaining good scalability. through computational experiments, we confirmed that a run of our proposed method using up to 20,736 cores showed a parallelization efficiency of 0.94 as compared to a 1296-core run. Finally, we successfully computed an optimal DAG structure for an instance of 36 vertices, which is the largest solved size reported in the literature.

关键词： Optimal DAG structure Optimal bayesian network structure parallel algorithm Distributed algorithm Torus network

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Cellular ANTomata as Engines for Highly parallel Pattern processing 16th

Cellular ANTomata as Engines for Highly Parallel Pattern Pro...

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Rosenberg, Arnold L. Northeastern Univ Comp & Informat Sci Boston MA 02115 USA

ISBN: (纸本)9783319499567;9783319499550

One important approach to high-performance computing has a (relatively) simple physical computer architecture emulate virtual algorithmic architectures (VAAs) that are highly optimized for important application domains. We expose the Cellular ANTomaton (CAnt) computing model-cellular automata enhanced with mobile FSMs (Ants)-as a highly efficient VAA for a variety of pattern-processing problems that are inspired by biocomputing applications. We illustrate the CAnt model via a scalable design for an n x n CAnt that solves the following bio-inspired problem in linear time. the Pattern-Assembly Problem. Inputs: a length-n master pattern II and r test patterns pi(0), . . . , pi(r-1), of respective lengths m(0) >= . . . >= m(r-1). the problem: Find every sequence of pi(k)'s, possibly with repetitions, that "assemble" (i.e., concatenate) to produce II;i.e., pi(j0) . . . pi(js-1) = II. Timing: m(1) + . . . + m(r) + O(n) steps, with a quite-small big-O constant.

关键词： HPC via emulation Cellular ANTomata Pattern assembly

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Light Loss-Less Data Compression, with GPU Implementation 16th

Light Loss-Less Data Compression, with GPU Implementation

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Funasaka, Shunji Nakano, Koji Ito, Yasuaki Hiroshima Univ Dept Informat Engn Kagamiyama 1-4-1 Higashihiroshima 7398527 Japan

ISBN: (纸本)9783319495835;9783319495828

there is no doubt that data compression is very important in computer engineering. However, most lossless data compression and decompression algorithms are very hard to parallelize, because they use dictionaries updated sequentially. the main contribution of this paper is to present a new lossless data compression method that we call Light Loss-Less (LLL) compression. It is designed so that decompression can be highly parallelized and run very efficiently on the GPU. this makes sense for many applications in which compressed data is read and decompressed many times and decompression performed more frequently than compression. We show optimal sequential and parallel algorithms for LLL decompression and implement them to run on Core i7-4790 CPU and GeForce GTX 1080 GPU, respectively. To show the potentiality of LLL compression method, we have evaluated the running time using five images and compared with well-known compression methods LZW and LZSS. Our GPU implementation of LLL decompression runs 91.1-176 times faster than the CPU implementation. Also, the running time on the GPU of our experiments show that LLL decompression is 2.49-9.13 times faster than LZW decompression and 4.30-14.1 times faster that LZSS decompression, although their compression ratios are comparable.

关键词： Data compression parallel algorithms GPGPU

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Comparative Analysis of OpenACC Compilers 16th

Comparative Analysis of OpenACC Compilers

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Barba, Daniel Gonzalez-Escribano, Arturo Llanos, Diego R. Univ Valladolid Dept Informat Valladolid Spain

ISBN: (纸本)9783319499567;9783319499550

OpenACC has been on development for a few years now. the OpenACC 2.5 specification was recently made public and there are some initiatives for developing full implementations of the standard to make use of accelerator capabilities. there is much to be done yet, but currently, OpenACC for GPUs is reaching a good maturity level in various implementations of the standard, using CUDA and OpenCL as backends. Nvidia is investing in this project and they have released an OpenACC Toolkit, including the PGI Compiler. there are, however, more developments out there. In this work, we analyze different available OpenACC compilers that have been developed by companies or universities during the last years. We check their performance and maturity, keeping in mind that OpenACC is designed to be used without extensive knowledge about parallel programming. Our results show that the compilers are on their way to a reasonable maturity, presenting different strengths and weaknesses.

关键词： parallel programming

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Shared Memory Tile-Based vs Hybrid Memory GOP-Based parallel algorithms for HEVC Encoder 16th

Shared Memory Tile-Based vs Hybrid Memory GOP-Based Parallel...

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Migallon, Hector Lopez-Granado, Otoniel Galiano, Vicente Pinol, Pablo Malumbres, Manuel P. Miguel Hernandez Univ Dept Phys & Comp Architecture Avda Univ S-N Alicante 03202 Spain

ISBN: (纸本)9783319495835;9783319495828

After the emergence of the new High Efficiency Video Coding standard, several strategies have been followed in order to take advantage of the parallel features available in it. Many of the parallelization approaches in the literature have been performed in the decoder side, aiming at achieving real-time decoding. However, the most complex part of the HEVC codec is the encoding side. In this paper, we perform a comparative analysis of two parallelization proposals. One of them is based on tiles, employing shared memory architectures and the other one is based on Groups Of Pictures, employing distributed shared memory architectures. the results show that good speed-ups are obtained for the tile-based proposal, especially for high resolution video sequences, but the scalability decreases for low resolution video sequences. the GOP-based proposal outperforms the tile-based proposal when the number of processes increases. this benefit grows up when low resolution video sequences are compressed.

关键词： HEVC Video coding parallel encoding Shared memory Distributed shared memory

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Automated parallel Simulation of Heart Electrical Activity Using Finite Element Method 16th

Automated Parallel Simulation of Heart Electrical Activity U...

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Sozykin, Andrey Epanchintsev, Timofei Zverev, Vladimir Khamzin, Svyatoslav Bersenev, Aleksandr Krasovskii Inst Math & Mech Ekaterinburg Russia Inst Immunol & Physiol UrB RAS Ekaterinburg Russia Ural Fed Univ Ekaterinburg Russia

ISBN: (纸本)9783319499567;9783319499550

In this paper we present an approach to the parallel simulation of the heart electrical activity using the finite element method with the help of the FEniCS automated scientific computing framework. FEniCS allows scientific software development using the near-mathematical notation and provides automatic parallelization on MPI clusters. We implemented the ten Tusscher-Panfilov (TP06) cell model of cardiac electrical activity. the scalability testing of the implementation was performed using up to 240 CPU cores and the 95 times speedup was achieved. We evaluated various combinations of the Krylov parallel linear solvers and the preconditioners available in FEniCS. the best performance was provided by the conjugate gradient method and the biconjugate gradient stabilized method solvers with the successive over-relaxation preconditioner. Since the FEniCS-based implementation of TP06 model uses notation close to the mathematical one, it can be utilized by computational mathematicians, biophysicists, and other researchers without extensive parallel computing skills.

关键词： Heart simulation Finite element method Scalability Krylov subspace methods FEniCS parallel computing

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On a parallel Algorithm for the Determination of Multiple Optimal Solutions for the LCSS Problem 16th

On a Parallel Algorithm for the Determination of Multiple Op...

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Ben Mabrouk, Bchira Hasni, Hamadi Mahjoub, Zaher Univ Tunis El Manar Fac Sci Tunis Univ CampusManar 2 Tunis 2092 Tunisia Higher Sch Technol & Comp Sci Charguia 2 Tunis 2035 Tunisia

ISBN: (纸本)9783319495835;9783319495828

For particular real world combinatorial optimization problems e.g. the longest common subsequence problem (LCSSP) from Bioinformatics, determining multiple optimal solutions (DMOS) is quite useful for experts. However, for large size problems, this may be too time consuming, thus the resort to parallel computing. We address here the parallelization of an algorithm for DMOS for the LCSSP. Considering the dynamic programming algorithm solving it, we derive a generic algorithm for DMOS (A-DMOS). Since the latter is a non perfect DO-loop nest, we adopt a three-step approach. the first consists in transforming the A-DMOS into a perfect nest. the second consists in choosing the granularity and the third carries out a dependency analysis in order to determine the type of each loop i.e. either parallel or serial. the practical performances of our approach are evaluated through experimentations achieved on input benchmarks and random DNA sequences and targeting a parallel multicore machine.

关键词： Bioinformatics Combinatorial optimization problem Dependency analysis Dynamic programming Longest common subsequence Loop nest Multiple optimal solutions Multicore machine parallelization Polyhedral algorithm

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GPU-Based Heterogeneous Coding Architecture for HEVC 16th

GPU-Based Heterogeneous Coding Architecture for HEVC

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Cebrian-Marquez, Gabriel Migallon, Hector Luis Martinez, Jose Lopez-Granado, Otoniel Pinol, Pablo Cuenca, Pedro Univ Castilla La Mancha Albacete Res Inst Informat I3A Plz Univ 2 Albacete 02071 Spain Miguel Hernandez Univ Dept Phys & Comp Architecture Elche 03202 Spain

ISBN: (纸本)9783319495835;9783319495828

the High Efficiency Video Coding (HEVC) standard has nearly doubled the compression efficiency of prior standards. Nonetheless, this increase in coding efficiency involves a notably higher computing complexity that should be overcome in order to achieve real-time encoding. For this reason, this paper focuses on applying parallel processing techniques to the HEVC encoder with the aim of reducing significantly its computational cost without affecting the compression performance. Firstly, we propose a coarse-grained slice-based parallelization technique that is executed in a multi-core CPU, and then, with finer level of parallelism, a GPU-based motion estimation algorithm. Both techniques define a heterogeneous parallel coding architecture for HEVC. Results show that speed-ups of up to 4.06x can be obtained on a quad-core platform with low impact in coding performance.

关键词： H.265 HEVC Heterogeneous parallel encoding GPU

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