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Development and implementation of a parallel algorithm for the fast design of oligonucleotide probe sets for diagnostic DNA microarrays

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2004年第9期16卷 873-893页

作者： Meier, H Krause, A Kräutner, M Bode, A Tech Univ Munich Inst Informat LRR TUM D-85748 Garching Germany

We describe an accurate method for the automatic parallel generation of oligonucleotide probe sets for DNA microarrays. This approach includes a component for high-performance specificity evaluation of designed probes in large data sets. The three main algorithmic components of the method, namely probe preselection, hybridization prediction and probe selection are explained in detail. We introduce new combinatorial techniques for the efficient selection of probe sets of high differentiation capability even from sequence databases of conserved homologous genes. These techniques include the automatic generation of group specific probes as well as the design of excluding probes. A basic prototype has been implemented including a shared memory parallelization. Test runs have been performed on a multiprocessor personal computer with subsets of a small subunit ribosomal ribonucleic acid database, containing very conserved sequence data. The applicability of our program is pointed out by designing a set of oligonucleotide probes that shall allow a comprehensive parallel identification and differentiation of several groups of extremophilic prokaryotes by DNA microarray. The probe set is accessible via the Internet. On applying the parallel version on a dual processor system an efficiency of 80% was achieved. Copyright (C) 2004 John Wiley Sons, Ltd.

关键词： DNA microarray bioinformatic algorithm molecular sequence analysis parallel and distributed computing oligonucleotide probe combinatorial DNA chip

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Performance Comparison of GPU-Accelerated Particle Flow and Particle Filters

Performance Comparison of GPU-Accelerated Particle Flow and ...

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International Conference on Information Fusion

作者： Vesselin P. Jilkov Jiande Wu Huimin Chen Department of Electrical Engineering University of New Orleans

ISBN: (纸本)9781479902842

This paper presents design, implementation, and performance evaluation results of a parallel particle filter (PF) and a particle flow filter (PFF) using a Graphics Processing Unit (GPU) as a parallel computing environment to speedup the computation. Simulation results from a high dimensional nonlinear filtering problem show that, for the considered example, the parallel PFF implementation is significantly superior to the parallel PF implementation in both estimation accuracy and computational performance. It is demonstrated that using GPU can markedly accelerate both particle filters and particle flow filters through parallelization.

关键词： Nonlinear filtering Particle filter Particle flow filter parallel and distributed computing GPU

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Coupling the Parareal algorithm with the Waveform Relaxation method for the solution of Differential Algebraic Equations

Coupling the Parareal algorithm with the Waveform Relaxation...

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第十届电子商务、工程及科学领域的分布式计算和应用（DCABES）国际学术研讨会

作者： Thomas Cadeau Frédéric Magoulès Applied Mathematics and Systems Laboratory Ecole Centrale Paris Chtenay-Malabry France

In this paper,a coupling strategy of the Parareal algorithm with the Waveform Relaxation method is presented for the parallel solution of differential algebraic *** classical Waveform Relaxation(in space) method and the Parareal(in time) method are first recalled,followed by the introduction of a coupled Parareal-Waveform Relaxation method recently introduced for the solution of partial differential ***,this coupled method is extended to the solution of differential algebraic *** experiments,performed on parallel multicores architectures,illustrate the impressive performances of this new method.

关键词： Differential Algebraic Equations Domain decomposition method Waveform Relaxation method Parareal algorithm parallel and distributed computing

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CSinparallel: Using WebMapReduce to Teach parallel computing Concepts, Hands-on (Abstract Only) 16

CSinParallel: Using WebMapReduce to Teach Parallel Computing...

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Proceedings of the 47th ACM Technical Symposium on computing Science Education

作者： Richard A. Brown Elizabeth Shoop Joel C. Adams St. Olaf College Northfield MN USA Macalester College St. Paul MN USA Calvin College Grand Rapids MI USA

ISBN: (纸本)9781450336857

Map-reduce computation is the on-ramp to data-intensive cloud computing, and arguably the most widely deployed form of parallel/distributed computing. Participants will carry out exercises designed for students at CS1, intermediate, and advanced levels that introduce data-intensive scalable computing concepts using WebMapReduce (WMR), a simplified open-source interface to the dominant Hadoop map-reduce programming environment. WMR supports programming in a choice of languages including Python, Java, C++, and C#. Besides a hands-on experience with introductory teaching materials, the workshop includes an overview of teaching advanced map-reduce programming using WMR, and a comparison of WMR to direct Hadoop programming. All materials will reside on ***, and the demonstration WMR system is reservable for participants' courses. Intended audience: CS instructors. Web-enabled laptop required.

关键词： design patterns csinparallel parallel and distributed computing cs1 exemplars wmr webmapreduce map-reduce education advanced courses distributed computing curriculum parallel design patterns parallel computing parallelism

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A Method for Predicting a Penalty of Contentions by Considering Priorities of Routing among Packets on Direct Interconnection Network

A Method for Predicting a Penalty of Contentions by Consider...

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The Fourth International Joint Conference on Computational Science and Optimization(第四届计算科学与优化国际大会 CSO 2011)

作者： Takeshi Nanri Yoshiyuki Morie Ryutaro Susukita Research Institute for Information Technology Kyushu University Fkuoka Japan Institute of Systems Information Technologies and Nanotechnologies Fkuoka Japan

Contentions can degrade the performance of communication significantly on network topology like 3D-Mesh/Torus. On these topologies, it is important to establish a method for predicting penalty of contentions to enable precise and fast tuning on communications. For example, techniques of tuning such as choosing dynamically faster algorithm of collective communications or finding appropriate task-allocation depends on the preciseness of the performance prediction. This research proposes a method for predicting a penalty of contentions by using detailed analysis of packet priority on direct interconnection network. Usually, the penalty of contentions is predicted by counting the number of communications issued on the same link at the same time. However, the actual amount of delay caused by contentions depends on the way of arbitrating messages. The message is divided into the packets and transmitted. Then, the contentions between those packets are arbitrated by applying the priority to each packet Therefore, when the contentions occur, the message which has a lower priority is blocked. By considering these priorities, the method proposed in this research becomes to predict the penalty of contentions more accurately and faster. In the evaluation experiment, the penalty of contentions predicted without considering packet priority is the twice or more than it predicted by simulation. On the other hand, the proposed method of predicting the penalty of contentions is predictable in the accuracy within 20％ against simulation. Moreover, the prediction by proposed method is possible to execute it enough at short time.

关键词： parallel and distributed computing Prediction Contentions Direct Interconnection Network Routing of Packet

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parallel Algorithms for Dynamic Shortest Path Problems

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International Transactions in Operational Research 2002年第3期9卷 279-302页

作者： Chabini, Ismail Ganugapati, Sridevi Department of Civil and Environmental Engineering Massachusetts Institute of Technology United States

The development of intelligent transportation systems (ITS) and the resulting need for the solution of a variety of dynamic traffic network models and management problems require faster-than-real-time computation of shortest path problems in dynamic networks. Recently, a sequential algorithm was developed to compute shortest paths in discrete time dynamic networks from all nodes and all departure times to one destination node. The algorithm is known as algorithm DOT and has an optimal worst-case running-time complexity. This implies that no algorithm with a better worst-case computational complexity can be discovered. Consequently, in order to derive algorithms to solve all-to-one shortest path problems in dynamic networks, one would need to explore avenues other than the design of sequential solution algorithms only. The use of commercially-available high-performance computing platforms to develop parallel implementations of sequential algorithms is an example of such avenue. This paper reports on the design, implementation, and computational testing of parallel dynamic shortest path algorithms. We develop two shared-memory and two message-passing dynamic shortest path algorithm implementations, which are derived from algorithm DOT using the following parallelization strategies: decomposition by destination and decomposition by transportation network topology. The algorithms are coded using two types of parallel computing environments: a message-passing environment based on the parallel virtual machine (PVM) library and a multi-threading environment based on the SUN Microsystems Multi-Threads (MT) library. We also develop a time-based parallel version of algorithm DOT for the case of minimum time paths in FIFO networks, and a theoretical parallelization of algorithm DOT on an ‘ideal’ theoretical parallel machine. Performances of the implementations are analyzed and evaluated using large transportation networks, and two types of parallel computing platforms: a distr

关键词： Computer algorithms Dynamic networks Dynamic shortest paths Intelligent transportation systems parallel and distributed computing

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A parallel scheduling algorithm for parallel applications

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parallel Algorithms and Applications 1995年第4期6.0卷 303-316页

作者： Bozyigit, Muslim Abdulghani, Amin A. University of Cambridge Computer Laboratory Cambridge CB2 3QG New Museums Site United Kingdom Rutgers University Computer Science Department NJ United States

In this work, a parallel scheduling algorithm for scheduling a set of n partially ordered tasks on an m-processor parallel computing system is studied. The method is based on a conventional list scheduling, in particular, an earliest-task-first approach. Otherwise, the algorithm developed is an original algorithm. It is designed for a hypercube type system and is tested on a Transputer based environment. The time complexity of the algorithm is 0(n(log n + log m)). The parallel scheduling algorithm produces the same schdules as its sequential counterpart whose complexity is O(mn²(logn + logm)), but in a shorter time. © 1995, Taylor & Francis Group, LLC. All rights reserved.

关键词： Hypercube parallel algorithms parallel and distributed computing parallel scheduling Transputers

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Workshop on tools for program development and analysis in computational science

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Procedia Computer Science 2010年第1期1卷 2105-2105页

作者： Christof Klausecker Arndt Bode Andreas Knüpfer Dieter Kranzlmüller Jie Tao Jens Volkert Roland Wismüller Ludwig-Maximilians-Universität München 80538 Munich Germany Technische Universität München 85748 Garching near Munich Germany Leibniz Supercomputing Centre 85748 Garching near Munich Germany Technische Universität Dresden 01062 Dresden Germany Karlsruhe Institute of Technology 76131 Karlsruhe Germany Johannes Kepler University Linz 4040 Linz Austria University of Siegen 57068 Siegen Germany

The use of supercomputing technology, parallel and distributed processing, and sophisticated algorithms is of major importance for computational scientists. Yet, the scientists’ goals are to solve their challenging scientific problems, not the software engineering tasks associated with it. For that reason, computational science and engineering must be able to rely on dedicated support from program development and analysis tools. The primary intention of this workshop is to bring together developers of tools for scientific computing and their potential users. Tool developers present how their tools support scientists and engineers during program development and analysis. The users report their experiences employing such tools, especially highlighting the benefits and possible improvements.

关键词： parallel and distributed computing Program development Performance analysis Debugging tools Program optimization Resource management

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Performance and profiling data of plane-wave calculations in quantum ESPRESSO simulation on three supercomputing centres

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DATA IN BRIEF 2023年 50卷 109614页

作者： Marurngsith, Worawan Waiphinit, Supakiet Rosmode, Wiraporn Bavontaweepanya, Ruchipas Fan, Jiaxin Thammasat Univ Lampang Campus Fac Sci & Technol Dept Comp Sci 248 M 2 Hang Chat Lampang 52190 Thailand Thammasat Univ Rangsit Campus Thammasat Univ Res Unit Quantum Technol 99 Khlong Luang Pathum Thani 12120 Thailand Natl Computat Infrastruct Canberra Australia

This dataset reflects the parallel execution profiles of five Quantum ESPRESSO simulation (QE) versions in finding the total energy of the Cerium Oxide lattice using the self -consistent field (SCF) method. The data analysis used a strong scale setting to identify the optimal parameters and computing resources needed to complete a single SCF loop for one specific material efficiently. This analysis notably contributed to achieving the Best Performance Award at the 5th APAC HPC-AI Competition. The data comprises three sets. The first set features the parallel execution traces captured via the Extrae performance profiling tool, offering a broad view of the QE's model execution behaviour and how it used computational resources. The second set records how long QE's model ran on a single node at three HPC centres: ThaiSC TARA in Thailand, NSCC ASPIRE-1 in Singapore, and NCI Gadi in Australia. This set focuses on the impact of adjusting three parameters for K-point parallelisation. The final set presents benchmarking data generated by scaling out the QE's model across 32 nodes (1,536 CPU cores) on the NCI Gadi super-computer. Despite its focus on a single material, the dataset serves as a roadmap for researchers to estimate required computational resources and understand scalability bottle-necks, offering general guidelines adaptable across different HPC systems.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Performance evaluation High performance computing Quantum physics simulation Profiling parallel and distributed computing Catalytic reaction Student competition Message Passing Interface

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Flexible and extensible load balancing

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Software: Practice and Experience 1999年第11期27卷

作者： Chi-Chung Hui Samuel T Chanson Department of Computer Science The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

This paper presents the design philosophy and implementation of the BALANCE system. BALANCE is a flexible, network independent and computer architecture independent load balancing system which allows the building of reusable parallel and distributed applications. By implementing related services as bi generic servers with their connection endpoints registered in BALANCE, the clients can easily access the servers by server system call s. To demonstrate the flexibility of BALANCE, several widely different applications have been implemented and evaluated, including system servers, parallel and distributed applications and a scheduling testbed. The use of generic servers to improve system modularity and code reuse is also discussed. © 1997 John Wiley & Sons, Ltd.

关键词： load balancing load sharing workstation clusters processor scheduling algorithms parallel and distributed computing

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