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检索条件"任意字段=Seventh International Symposium on Parallel Architectures, Algorithms and Programming"

共 513 条记录，以下是321-330 订阅

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Embedding smart buffers for window operations in a stream-oriented C-to-VHDL compiler

Embedding smart buffers for window operations in a stream-or...

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4th IEEE international symposium on Electronic Design, Test and Applications

作者： Diet, Fabian D'Hollander, Erik H. Beyls, Kristof Devos, Harald Univ Ghent ELIS Dept Parallel Informat Syst B-9000 Ghent Belgium

ISBN: (纸本)9780769531106

Important classes of algorithms which can benefit from the advantages of C-to-VHDL compiling are window operations. These execute a number of instructions on a large amount of array data. Since arrays are usually translated into FPGA block memory structures, it is important to minimize the required number of block memory accesses. Recently, a smart buffer has been introduced, in which a number of past and present array elements can be temporarily stored to be reused over a number of different loop nest iterations. In this paper, the smart buffer approach is analysed for use in the stream-oriented Impulse-C compiler. Experimental automatic generation of VHDL code for this buffer is described. The smart buffer is then linked with the VHDL code generated by the Impulse-C compiler to obtain data efficient designs.

关键词： C (programming language)

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Task parallelism for Object Oriented Programs

Task Parallelism for Object Oriented Programs

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international symposium on parallel architectures, algorithms and Networks (ISPAN)

作者： Nasser Giacaman Oliver Sinnen Department of Electrical and Computer Engineering University of Auckland New Zealand

parallel computing is notoriously challenging due to the difficulty in developing correct and efficient programs. With the arrival of multi-core processors for desktop systems, desktop applications must now be parallelised. However achieving task parallelism for such object-oriented programs has traditionally been, and still remains, difficult. This paper presents a powerful task concept for parallel object-oriented programming and presents the results from a source-to-source compiler and runtime system. With the addition of a single keyword, the sequential code does not require restructuring and asynchronous task management is performed on behalf of the programmer; the parallel code required to realise task parallelism looks very much like the sequential counterpart. An intuitive solution is provided to handle task dependencies as well as integrating different task concepts into one model.

关键词： parallel processing Yarn programming profession Libraries Multicore processing Object oriented programming Program processors Concurrent computing parallel architectures Application software

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parallelizing Optimal Multiple Sequence Alignment by Dynamic programming

Parallelizing Optimal Multiple Sequence Alignment by Dynamic...

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international symposium on parallel and Distributed Processing with Applications, ISPA

作者： Manal Helal Hossam El-Gindy Lenore Mullin Bruno Gaeta School of Computer Science and Engineering Faculty of Engineering University of New South Wales Sydney Australia National Science Foundation WA USA

Optimal multiple sequence alignment by dynamic programming, like many highly dimensional scientific computing problems, has failed to benefit from the improvements in computing performance brought about by multi-processor systems, due to the lack of suitable scheme to manage partitioning and dependencies. A scheme for parallel implementation of the dynamic programming multiple sequence alignment is presented, based on a peer to peer design and a multidimensional array indexing method. This design results in up to 5-fold improvement compared to a previously described master/slave design, and scales favourably with the number of processors used. This study demonstrates an approach for parallelising multi-dimensional dynamic programming and similar algorithms utilizing multi-processor architectures.

关键词： Dynamic programming Sequences Indexing Computer architecture Concurrent computing High performance computing Peer to peer computing Tensile stress Multidimensional systems Master-slave

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Hardware Implementation of P Systems Using Microcontrollers. An Operating Environment for Implementing a Partially parallel Distributed Architecture

Hardware Implementation of P Systems Using Microcontrollers....

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international symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Sandra Maria Gomez Canaval Abraham Gutierrez Rodriguez Santiago Alonso Villaverde Natural Computing Group Universidad Politecnica de Madrid Madrid Spain

Nowadays, important efforts in the research of the Transition P Systems have been focused on the simulation/implementation of the massively parallel character ofthe model. The distributed implementation of P Systems hasmet with the communications bottleneck problem. In thissense, there are several research works on analysis for distributed architectures that are technology independent and avoiding communication collisions. Recent works presentanalysis on the suitability for implementing theses architectures using an universal membrane hardware/software component based on microcontrollers. These implementations are directly programming on hardware components and the resulting data is analyzed by means of a specific program which translates the execution bit code into intelligible data for researchers. The aim of this work is to present an operating environment to automate manual tasks performed during the loading, execution and interpretation of P System into distributed architectures based on microcontrollers as well as the interpretation from inner binary data representation inside of microcontrollers.

关键词： Hardware Microcontrollers Biomembranes Computer architecture Independent component analysis Biological system modeling Power system modeling Evolution (biology) Network topology Scientific computing

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A parallel Dynamic programming Algorithm on a Multi-core Architecture 07

A Parallel Dynamic Programming Algorithm on a Multi-core Arc...

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19th Annual symposium on parallelism in algorithms and architectures

作者： Tan, Guangming Sun, Ninghui Gao, Guang R. Chinese Acad Sci Key Lab Comp Syst & Architecture Beijing Peoples R China

ISBN: (纸本)9781595936677

Dynamic programming is an efficient technique to solve combinatorial search and optimization problem. There have been many parallel dynamic programming algorithms. The purpose of this paper is to study a family of dynamic programming algorithm where data dependence appear between non-consecutive stages, in other words, the data dependence is non-uniform. This kind of dynamic programming is typically called nonserial polyadic dynamic programming. Owing to the: non-uniform data dependence;it is harder to optimize this problem for parallelism and locality on parallel architectures. In this paper, we address the chanllenge of exploiting fine grain parallelism and locality of nonserial polyadic dynamic programming on a multi-core architecture. We present a programming and execution model for multi-core architectures with memory hierarchy. In the framework of the new model, the parallelism and locality benifit from a data dependence transformation. We propose a parallel pipelined algorithm for filling the dynamic programming matrix by decomposing the computation operators. The new parallel algorithm tolerates the memory access latency using multi-thread and is easily improved with the technique. We formulate and analytically solve the optimization problem determing the the size that minimizes the total execution time. The experiments on a simulator give a validation of the proposed model and show that the fine grain parallel algorithm achieves sub-linear speedup and that a potential high scalability on multi-core arichitecture.

关键词： Dynamic programming Data Dependence Multicore Memory Hierarchy Scalabilitiy

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A parallel BSP algorithm for irregular dynamic programming

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7th international symposium on Advanced parallel Processing Technologies

作者： Low, Malcolm Yoke Hean Liu, Weiguo Schmidt, Bertil Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore Univ New South Wales Asia Singapore Singapore

ISBN: (纸本)9783540768364

Dynamic programming is a widely applied algorithm design technique in many areas such as computational biology and scientific computing. Typical applications using this technique are compute-intensive and suffer from long runtimes on sequential architectures. Therefore, several parallel algorithms for both fine-grained and coarse-grained architectures have been introduced. However, the commonly used data partitioning scheme can not be efficiently applied to irregular dynamic programming algorithms, i.e. dynamic programming algorithms with an uneven load density pattern. In this paper we present a tunable parallel Bulk Synchronous parallel (BSP) algorithm for such kind of applications. This new algorithm can balance the workload among processors using a tunable block-cyclic data partitioning method and thus is capable of getting almost linear performance gains. We present a theoretical analysis and experimentally show that it leads to significant runtime savings for pairwise sequence alignment with general gap penalties using BSPonMPI on a PC cluster.

关键词： BSP irregular dynamic programming partitioning load balancing scientific computing

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SWARM: A parallel programming framework for multicore processors

SWARM: A parallel programming framework for multicore proces...

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21st international parallel and Distributed Processing symposium, IPDPS 2007

作者： Bader, David A. Kanade, Varun Madduri, Kamesh College of Computing Georgia Institute of Technology Atlanta GA 30332

ISBN: (纸本)1424409101

Due to fundamental physical limitations and power constraints, we are witnessing a radical change in commodity microprocessor architectures to multicore designs. Continued performance on multicore processors now requires the exploitation of concurrency at the algorithmic level. In this paper, we identify key issues in algorithm design for multicore processors and propose a computational, model for these systems. We introduce SWARM (Software and algorithms for Running on Multi-core), a portable open-source parallel library of basic primitives that fully exploit multicore processors. Using this framework, we have implemented efficient parallel algorithms for important primitive operations such as prefixsums, pointer-jumping, symmetry breaking, and list ranking;for combinatorial problems such as sorting and selection;for parallel graph theoretic algorithms such as spanning tree, minimum spanning tree, graph decomposition, and tree contraction;and for computational genomics applications such as maximum parsimony. The main contributions of this paper are the design of the SWARM multicore framework, the presentation of a multicore algorithmic model, and validation results for this model. SWARM is freely available as open-source from http: //***/. © 2007 IEEE.

关键词： parallel programming

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SWARM: A parallel programming Framework for Multicore Processors

SWARM: A Parallel Programming Framework for Multicore Proces...

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international symposium on parallel and Distributed Processing (IPDPS)

作者： David A. Bader Varun Kanade Kamesh Madduri College of Computing Georgia Institute of Technology Atlanta GA USA

Due to fundamental physical limitations and power constraints, we are witnessing a radical change in commodity microprocessor architectures to multicore designs. Continued performance on multicore processors now requires the exploitation of concurrency at the algorithmic level. In this paper, we identify key issues in algorithm design for multicore processors and propose a computational model for these systems. We introduce SWARM (software and algorithms for running on multi-core), a portable open-source parallel library of basic primitives that fully exploit multicore processors. Using this framework, we have implemented efficient parallel algorithms for important primitive operations such as prefix-sums, pointer-jumping, symmetry breaking, and list ranking; for combinatorial problems such as sorting and selection; for parallel graph theoretic algorithms such as spanning tree, minimum spanning tree, graph decomposition, and tree contraction; and for computational genomics applications such as maximum parsimony. The main contributions of this paper are the design of the SWARM multicore framework, the presentation of a multicore algorithmic model, and validation results for this model. SWARM is freely available as open-source from http://***/.

关键词： parallel programming Multicore processing Open source software Tree graphs Concurrent computing Algorithm design and analysis Microprocessors Computer architecture Process design Computational modeling

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Development of Control for a Serpentine Robot

Development of Control for a Serpentine Robot

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IEEE international symposium on Computational Intelligence in Robotics and Automation (CIRA)

作者： William R. Hutchison Betsy J. Constantine Johann Borenstein Jerry Pratt Behavior Systems Boulder CO USA University of Michigan Ann Arbor MI USA Yobotics Inc. Cincinnati OH USA

This paper describes the development and testing of control of the OmniTread OT-4 robot by the seventh generation (7G) control system. Control of OT-4 was developed in the Yobotics 3D simulator by an iterative process combining genetic algorithm, learning and analytic programming techniques. The control system developed in simulation was tested by controlling the real OT-4 robot in the laboratory. The performance of the real OT-4 robot under 7G control on stairs, parallel bars, a slalom course, and stairs with obstacles corresponded well to the simulated performance on which development of the control system was based.

关键词： Control system synthesis System testing Control systems Analytical models Genetic algorithms Algorithm design and analysis Robot programming Laboratories parallel robots Robot control

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Coarse-grain parallel Execution for 2-dimensional PDE Problems

Coarse-grain Parallel Execution for 2-dimensional PDE Proble...

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international symposium on parallel and Distributed Processing (IPDPS)

作者： Georgios Goumas Nikolaos Drosinos Vasileios Karakasis Nectarios Koziris School of Electrical and Computer Engineering Computer Systems Laboratory National and Technical University of Athens Greece

This paper presents a new approach for the execution of coarse-grain (tiled) parallel SPMD code for applications derived from the explicit discretization of 1-dimensional PDE problems with finite-differencing schemes. Tiling transformation is an efficient loop transformation to achieve coarse-grain parallelism in such algorithms, while rectangular tile shapes are the only feasible shapes that can be manually applied by program developers. However, rectangular tiling transformations are not always valid due to data dependencies, and thus requiring the application of an appropriate skewing transformation prior to tiling in order to enable rectangular tile shapes. We employ cyclic mapping of tiles to processes and propose a method to determine an efficient rectangular tiling transformation for a fixed number of processes for 2-dimensional, skewed PDE problems. Our experimental results confirm the merit of coarse-grain execution in this family of applications and indicate that the proposed method leads to the selection of highly efficient tiling transformations.

关键词： Tiles Finite difference methods Shape Concurrent computing parallel processing parallel architectures programming profession Guidelines Systems engineering and theory Laboratories

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