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检索条件"任意字段=8th International Conference on Algorithms and Architectures for Parallel Processing"

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Modeling and Optimizing the Power Performance of Large Matrices Multiplication on Multi-core and GPU Platform with CUDA

Modeling and Optimizing the Power Performance of Large Matri...

引用

8th international conference on parallel processing and Applied Mathematics

作者： Ren, Da Qi Suda, Reiji Univ Tokyo Dept Comp Sci Bunkyo Ku 7-3-1 Hongo Tokyo 1130033 Japan

ISBN: (纸本)9783642143892

the power efficiency of large-scale computing on multiprocessing systems is an important issue that interrelated to both of the hardware architectures and the software methodologies. Aiming to design power-efficient high performance program, we have measured the power consumption of large matrices multiplication on multi-core and GPU platform. Based on the obtained power characteristic values of each computing component, we abstract the energy estimations by incorporating physical power constrains from the hardware devices and analysis of the program execution behaviors. We optimize the matrices multiplication algorithm in order to improve its power performance, and the efficiency promotion has been finally validated by measuring the program execution.

关键词： Graphics processing unit

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Secure Information processing with Privacy Assurance - Standard based Design and Development for Biometric Applications

Secure Information Processing with Privacy Assurance - Stand...

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8th international conference on Privacy, Security and Trust (PST)

作者： Sy, Bon K. Ramirez, Adam Krishnan, Arun P. Kumara Queens Coll Dept Comp Sci 65-30 Kissena Blvd Flushing NY 11367 USA CUNY Univ Grad Ctr 65-30 Kissena Blvd Flushing NY 11367 USA

ISBN: (纸本)9781424475742

this paper presents the design and development of a technique referred to as SIPPA - Secure Information processing with Privacy Assurance - for biometric data reconstruction. SIPPA enables a client/server model with the following two properties: (1) the client party can compare the similarity between his/her sample data with the source data on the server side --- without each party revealing his/her data to another, nor to a third party. If the sample data is "sufficiently similar" to the source data, the client can reconstruct the source data by using only the sample data and some helper data with negligible overhead provided by the server. the main contributions of this paper are: (1) algorithmic steps of SIPPA and its relationship to privacy homomorphism, (2) a parallel SIPPA architecture, and (3) the realization of parallel SIPPA as a service component for BioAPI 2.0 framework using Java RMI technology. To demonstrate its potential application, we apply SIPPA to the reconstruction of biometric data, and more specifically, biometric face images represented in terms of linearized vectors.

关键词： Java RMI technology biometric data reconstruction biometrics (access control) parallel SIPPA architecture parallel architectures privacy assurance secure information processing security of data standard based design

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Fast In-Place Sorting with CUDA Based on Bitonic Sort

Fast In-Place Sorting with CUDA Based on Bitonic Sort

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8th international conference on parallel processing and Applied Mathematics

作者： Peters, Hagen Schulz-Hildebrandt, Ole Luttenberger, Norbert Univ Kiel Dept Comp Sci Res Grp Commun Syst D-24098 Kiel Germany

ISBN: (纸本)9783642143892

State of the art graphics processors provide high processing power and furthermore, the high programmability of GPUs offered by frameworks like CUDA increases their usability as high-performance co-processors for general-purpose computing. Sorting is well-investigated in Computer Science in general, but (because of this new field of application for GPUs) there is a demand for high-performance parallel sorting algorithms that fit to the characteristics of modern GPU-architecture. We present, a high-performance in-place implementation of Batcher's bitonic sorting networks for CUDA-enabled GPUs. We adapted}Atonic sort for arbitrary input length and assigned compare/exchange-operations to threads in a way that decreases low-performance global-memory access and thereby greatly increases the performance of the implementation.

关键词： GPU GPGPU CUDA parallel Sorting Multicore

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Real-Time Linux Framework for Designing parallel Mobile Robotic Applications

Real-Time Linux Framework for Designing Parallel Mobile Robo...

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10th international conference on algorithms and architectures for parallel processing

作者： Aracil, Joan Dominguez, Carlos Hassan, Houcine Crespo, Alfons Univ Politecn Valencia Dept Comp Engn DISCA E-46071 Valencia Spain

ISBN: (纸本)9783642131356

A real-time emotional architecture (RTEA) for building parallel robotic applications is presented. RTEA allows the application developer to focus in the design and implementation of the agent processes, because the architecture itself solves, in an autonomous way the decision about the attention to be paid to each of these processes. From the functional point of view, an RTEA selects and adapts its objectives depending on its physical (actuators) and its mental (processing) capabilities. this characteristic makes the architecture a useful solution in such applications that have to deal with several simultaneous tasks, that has real-time constraints, and where the objectives are defined in a flexible way. From the viewpoint of the design and development of applications, RTEA defines its different entities as independent modules. this modularity facilitates the programmer the development of each part of the project. To control the processing capacity of the agent and to guarantee the fulfilment of the temporal constraints of the processes. RTEA has been implemented in a real-time kernel (rt-linux). Mobile robot Experiments have been carried out to show how emotional system influence the mental organisation of the robot when it performs navigational tasks under different environmental conditions.

关键词： Linux

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parallel and Distributed Programming 16th

Parallel and Distributed Programming

引用

16th international Euro-Par conference on parallel processing

作者： Kielmann, thilo Clematis, Andrea Gorlatch, Sergei Lastovetsky, Alexey Vrije Univ Amsterdam Netherlands

ISBN: (纸本)9783642152900

Developing parallel or distributed applications is a hard task and it requires advanced algorithms, realistic modeling, efficient design tools, high-level programming abstractions, high-performance implementations, and experimental evaluation. Ongoing research in this field emphasizes the design and development of correct, high-performance, portable, and scalable parallel programs. Related to these central needs, important work addresses methods for reusability, performance prediction, large-scale deployment, self-adaptivity, and fault-tolerance. Given the rich history in this field, practical applicability of proposed methods, models, algorithms, or techniques is a key requirement for timely research. this topic is focusing on parallel and distributed programming in general, except for work specifically targeting multicore architectures, which has matured to becoming a Euro-Par topic of its own. © 2010, Springer-Verlag Berlin Heidelberg.

关键词： Fault tolerance

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Scalable Co-clustering algorithms

Scalable Co-clustering Algorithms

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10th international conference on algorithms and architectures for parallel processing

作者： Kwon, Bongjune Cho, Hyuk Univ Texas Austin Biomed Engn Austin TX 78712 USA Sam Houston State Univ Comp Sci Huntsville TX 77340 USA

ISBN: (纸本)9783642131189

Co-clustering has been extensively used in varied applications because of its potential to discover latent local patterns that are otherwise unapparent by usual unsupervised algorithms such as k-means. Recently, a unified view of co-clustering algorithms, called Bregman co-clustering (BCC), provides a general framework that even contains several existing co-clustering algorithms, thus we expect to have more applications of this framework to varied data types. However, the amount of data collected from real-life application domains easily grows too big to fit in the main memory of a single processor machine. Accordingly, enhancing the scalability of BCC can be a critical challenge in practice. To address this and eventually enhance its potential for rapid deployment to wider applications with larger data, we parallelize all the twelve co-clustering algorithms in the BCC framework using message passing interface (MPI). In addition, we validate their scalability on eleven synthetic datasets as well as one real-life dataset, where we demonstrate their speedup performance in terms of varied parameter settings.

关键词： Co-clustering Message Passing Interface Distributed Co-clustering Scalable Co-clustering parallel Co-clustering

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A Blocking Strategy on Multicore architectures for Dynamically Adaptive PDE Solvers

A Blocking Strategy on Multicore Architectures for Dynamical...

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8th international conference on parallel processing and Applied Mathematics

作者： Eckhardt, Wolfgang Weinzierl, Tobias Tech Univ Munich D-85748 Garching Germany

ISBN: (纸本)9783642143892

this paper analyses a PDE solver working on adaptive Cartesian grids. While a rigorous element-wise formulation of this solver offers great flexibility concerning dynamic adaptivity, and while it comes along with very low memory requirements, the realisation's speed can not cope with codes working on patches of regular grids-in particular, if the latter deploy patches to several cores. Instead of composing a grid of regular patches, we suggest to identify regular patches throughout the recursive;element-wise grid traversal. Our code then unrolls the recursion for these regular grid blocks automatically, and it deploys their computations to several cores. It hence benefits from multicores on regular subdomains, but preserves its simple, element-wise character and its ability to handle arbitrary dynamic refinement and domain topology changes.

关键词： Software architecture

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Comparative Study of parallel algorithms for Asynchronous Cellular Automata Simulation on Different Computer architectures

Comparative Study of Parallel Algorithms for Asynchronous Ce...

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9th international conference on Cellular Automata for Research and Industry

作者： Kalgin, Konstantin RAS SB Inst Computat Math & Math Geophys Moscow Russia

ISBN: (纸本)9783642159787

Overview and experimental comparative study of parallel algorithms of asynchronous cellular at simulation is presented. the algorithms are tested for the model of physicochemical process of surface CO + O-2 reaction over the supported Pd nanoparticles on different parallel computers. For testing we use shared memory computers, distributed memory computers (i.e. clusters), and graphical processing unit. Characterization of these algorithms in respect of methods of parallelism maintenance is given.

关键词： parallel algorithms

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Automated Tuning in parallel Sorting on Multi-core architectures

Automated Tuning in Parallel Sorting on Multi-core Architect...

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16th international Euro-Par conference on parallel processing

作者： Lin, Haibo Li, Chao Wang, Qian Zhao, Yi Pan, Ninghe Zhuang, Xiaotong Shao, Ling IBM Res Beijing Beijing Peoples R China Univ Massachusetts Boston MA USA Beijing Inst Technol Beijing Peoples R China IBM Syst & Technol Grp Beijing Peoples R China IBM Watson Res Ctr Yorktown Hts NY USA

ISBN: (纸本)9783642152764

Empirical search is an emerging strategy used in systems like ATLAS, FFTW and SPIRAL to find the parameter values of the implementation that deliver near-optimal performance for a particular machine. However, this approach has only proven successful for scientific kernels or serial symbolic sorting. Even commercial libraries like Intel MKL or IBM ESSL do not include parallel version of sorting routines. In this paper we study empirical search in the generation of parallel sorting routines for multi-core systems. parallel sorting presents new challenges that the relative performance of the algorithms depends not only on the characteristics of the architectures and input data, but also on the data partitioning schemes and thread interactions. We have studied parallel sorting algorithms including quick sort, cache-conscious radix sort, multi-way merge sort, sample sort and quick-radix sort, and have built a sorting library using empirical search and artificial neural network. Our results show that this sorting library could generate the best parallel sorting algorithms for different input sets on both x86 and SPARC multi-core architectures, with a peak speedup of 2.2x and 3.9x, respectively.

关键词： Sorting

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A New parallel Method of Smith-Waterman Algorithm on a Heterogeneous Platform

A New Parallel Method of Smith-Waterman Algorithm on a Heter...

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10th international conference on algorithms and architectures for parallel processing

作者： Chen, Bo Xu, Yun Yang, Jiaoyun Jiang, Haitao Univ Sci & Technol China Dept Comp Sci Key Lab High Performance Comp Hefei Anhui Peoples R China

ISBN: (纸本)9783642131189

Smith-Waterman algorithm is a classic dynamic programming algorithm to solve the problem of biological sequence alignment. However, with the rapid increment of the number of DNA and protein sequences, the originally sequential algorithm is very time consuming due to there existing the same computing task computed repeatedly on large-scale data. Today's CPU (graphics processor unit) consists of hundreds of processors, so it has a more powerful computation capacity than the current multicore CPU. And as the programmability of GPU improved continuously, using it to do generous purpose computing is becoming very popular. In order to accelerate sequence alignment, previous researchers use the parallelism of the anti-diagonal of similarity matrix to parallelize the Smith-Waterman algorithm on CPU. In this paper, we design a new parallel algorithm which exploits the parallelism of the column of similarity matrix to parallelize the Smith-Waterman algorithm on a heterogeneous system based on CPU and CPU. the experiment result shows that our new parallel algorithm is more efficient than that of previous, which takes full advantage of the features of both the CPU and CPU and obtains approximately 37 times speedup compared with the sequential algorithm named OSEARCH implemented on Intel dual-core E2140 processor.

关键词： parallel algorithms

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