Verfügbarkeit: Parallel computing

Parallel computing: numerics, applications, and trends

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Weitere Verfasser:	Trobec, Roman (HerausgeberIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	London Springer 2009
Schlagworte:	Parallelverarbeitung Programmierung
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	XXIV, 519 S. Ill., graph. Darst.
ISBN:	9781848824089 9781848824096

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Datensatz im Suchindex

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adam_text	Contents Overview - Parallel Computing: Numerics, Applications, and Trends..................................................... 1 Marian Vajteršic, Peter Zinterhof and Roman Trobec 1.1 Introduction .............................................. 1 1.1.1 Parallel Numerics ................................. 2 1.1.2 Parallel Architectures .............................. 4 1.1.3 Scalability ....................................... 6 1.1.4 Supercomputers................................... 7 1.1.5 Grid Computing................................... 8 1.1.6 Parallel Programming Languages .................... 9 1.1.7 Parallel Compilers................................. 11 1.2 Book Chapters ............................................ 13 1.2.1 Introduction to Parallel Computation ................. 13 1.2.2 Tools for Parallel and Distributed Computing .......... 14 1.2.3 Grid Computing ................................... 15 1.2.4 Parallel Structured Adaptive Mesh Refinement ......... 16 1.2.5 Applications and Parallel Implementation of QMC Integration ....................................... 17 1.2.6 Parallel Evolutionary Computation Framework for Single- and Multiobjective Optimization ........... 18 1.2.7 WaLBerla: Exploiting Massively Parallel Systems for Lattice Boltzmann Simulations ...................... 20 1.2.8 Parallel Pseudo-Spectral Methods for the Solution of the Time Dependent Schrödinger Equation .......... 21 1.2.9 Parallel Approaches in Molecular Dynamics Simulations 23 1.2.10 Parallel Computer Simulation of Heat Transfer in Bio-Tissue ..................................... 24 1.2.11 SVD Computing in LSI Applications for Data Retrieval . 25 1.2.12 Short-Vector SIMD Parallelization in Signal Processing . 27 1.2.13 Financial Applications: Parallel Portfolio Optimization .. 29 1.2.14 Future of Parallel Computing ........................ 30 Xlii xiv Contents 1.3 Conclusions .............................................. 32 References ..................................................... 36 2 Introduction to Parallel Computation .......................... 43 Selim G. Aki and Marius Nagy 2.1 Introduction .............................................. 44 2.2 Parallel Versus Sequential Computation ....................... 45 2.3 Parallel Computational Models .............................. 46 2.3.1 Shared-Memory Models ............................ 46 2.3.2 Interconnection Network Models .................... 48 2.3.3 Circuit Models .................................... 49 2.3.4 Clusters .......................................... 49 2.3.5 Grids ............................................ 51 2.4 Parallel Algorithm Design Methods .......................... 52 2.5 Theoretical Underpinnings ................................. 55 2.5.1 Speedup ......................................... 55 2.5.2 Slowdown ........................................ 57 2.5.3 Quality-Up ....................................... 57 2.5.4 Computations that Seem Inherently Sequential ......... 58 2.6 Parallel Algorithms for Conventional Computations ............ 60 2.6.1 Parallel Prefix and Suffix Computations on a Linked List 60 2.6.2 Sorting on a Model with Buses ...................... 63 2.7 Parallel Algorithms for Unconventional Computations .......... 66 2.7.1 Computations that Can be Simulated Sequentially ...... 67 2.7.2 Computations that Cannot be Simulated Sequentially ... 73 2.8 Non-Universality in Computation ............................ 77 2.9 Conclusion ............................................... 79 References ..................................................... 80 3 Tools for Parallel and Distributed Computing .................... 81 Thomas Fahringer 3.1 Introduction .............................................. 82 3.2 Related Work ............................................. 83 3.3 ASKALON Architecture ................................... 85 3.3.1 Data Repository ................................... 87 3.3.2 ASKALON Visualization Diagrams .................. 88 3.4 SCALEA ................................................ 88 3.4.1 Instrumentation ................................... 88 3.4.2 Overhead Analyzer ................................ 89 3.4.3 Performance Analyzer ............................. 90 3.5 ZENTURIO .............................................. 91 3.5.1 ZEN Experiment Specification Language .............. 91 3.5.2 Experiment Generator .............................. 92 3.5.3 Experiment Executor .............................. 93 3.6 AKSUM ................................................. 93 3.6.1 Search Engine .................................... 94 Contents xv 3.6.2 Reinforcement Learning for Performance Analysis ..... 97 3.7 Grid-Prophet ............................................. 98 3.7.1 Prediction Techniques .............................. 99 3.8 Experiments .............................................. 103 3.8.1 Performance Analysis with SCALEA .................103 3.8.2 Performance and Parameter Studies of a Three- Dimensional Particle-In-Cell Application with ZENTURIO ......................................105 3.8.3 Performance Analysis for a Backward Pricing Application with AKSUM ..........................106 3.8.4 Workflow Performance Prediction with the Grid-Prophet 108 3.9 Conclusions .............................................. Ill References ..................................................... Ill 4 Grid Computing ............................................ 117 Uroš Cibej, Anthony Sulistio and Rajkumar Buyya 4.1 Introduction ..............................................117 4.1.1 Grid Categorization ................................119 4.1.2 Comparison Between Clusters and Grids ..............122 4.1.3 Putting It All Together .............................122 4.2 Challenges in Grid Computing ..............................123 4.2.1 Resource Sharing ..................................124 4.2.2 Guaranteed Quality of Service .......................124 4.2.3 Resource Regulation ...............................126 4.2.4 Data Management .................................127 4.3 Tools and Applications .....................................129 4.3.1 Middleware ......................................130 4.3.2 Tools for Computationally Intensive Applications .......133 4.3.3 Tools for Workflow Composition and Execution ........134 4.3.4 Tools That Support Advance Reservation ..............135 4.3.5 G-Lambda Grid Scheduling System ..................137 4.3.6 Application Fields .................................137 4.4 Conclusions and Future Trends ..............................139 References .....................................................140 5 Parallel Structured Adaptive Mesh Refinement .................. 147 Jarmo Rantakokko and Michael Thuné 5.1 Introduction ..............................................148 5.2 An Introduction to SAMR ..................................150 5.2.1 Approaches to Structured Adaptive Mesh Refinement ... 150 5.2.2 SAMR in a Computer Science Perspective .............153 5.2.3 Software Frameworks for SAMR ....................154 5.3 Details of SAMR .........................................155 5.3.1 Advancing the Solution on a Structured Adaptive Grid Hierarchy ........................................155 5.3.2 The Algorithmic Key Components of SAMR ..........157 xvi Contents 5.4 Computer Science Aspects of SAMR .........................158 5.4.1 Data Dependencies ................................158 5.4.2 Dynamic Load Balancing........................... 159 5.4.3 Parallelization Models .............................163 5.5 Some Results............................................. 164 5.5.1 An Integrated Decomposition and Partitioning Approach for Irregular Block-Structured Applications ... 164 5.5.2 A Hybrid Dynamic MPI-OpenMP Model .............165 5.5.3 Geographical Locality ..............................166 5.5.4 A Hybrid Patch/Domain-Based Partitioner Framework ..168 5.5.5 A Meta-Partitioner for Structured Grid Hierarchies .....168 5.6 Conclusions and Future Work ...............................169 References .....................................................170 6 Applications and Parallel Implementation of QMC Integration .....175 Peter Jez, Andreas Uhi and Peter Zinterhof 6.1 Introduction .............................................176 6.2 Monte Carlo and Quasi Monte Carlo Methods in Numerical Integration Over [0,1 )s ....................................177 6.2.1 Application of Reproducing Kernel Hubert Spaces .....181 6.3 QMC Methods for Integrals over R5 with a Weight Function .....182 6.3.1 Feynman s Path Integrals ...........................185 6.3.2 Application in Financial Engineering .................186 6.4 QMC Integration on Parallel Systems ........................188 6.5 Numerical Experiments ....................................191 6.5.1 Sequential Computations ...........................191 6.5.2 Parallel Case .....................................194 6.5.3 Experimental Results ..............................195 6.5.4 Overall Comparison ...............................206 6.6 Application of the Diaphony in Parallel Computation ...........208 6.7 Conclusion ...............................................211 References .....................................................213 7 Parallel Evolutionary Computation Framework for Single- and Multiobjective Optimization ..................................217 Bogdan Filipie and Matjaž Depolli 7.1 Introduction ..............................................218 7.2 Optimization Problems .....................................219 7.3 Evolutionary Algorithms ...................................222 7.3.1 Multiobjective Evolutionary Algorithms ..............224 7.4 Parallel Single- and Multiobjective Evolutionary Algorithms .....224 7.4.1 Parallelization Types ...............................224 7.4.2 Calculation of Speedups ............................226 7.5 Casting Process Optimization Task ...........................229 7.6 Parallel Evolutionary Computation Framework ................230 7.6.1 Speedup Estimation ...............................231 Contents xvii 7.7 Empirical Evaluation......................................233 7.7.1 Experimental Setup................................233 7.7.2 Experiments and Results ...........................234 7.8 Conclusion............................................... 239 References .....................................................240 8 WaLBerla: Exploiting Massively Parallel Systems for Lattice Boltzmann Simulations .......................................241 Christian Feichtinger, Jan Götz, Stefan Donath, Klaus Iglberger and Ulrich Rüde 8.1 Motivation ...............................................242 8.2 Introduction to the Lattice Boltzmann Method .................243 8.3 Domain Partitioning Using Patches ..........................245 8.3.1 Memory Reduction ................................247 8.4 Communication Concept ...................................247 8.4.1 Process Local Communication .......................248 8.4.2 MPI Communication ...............................248 8.5 Performance Studies .......................................249 8.5.1 Serial Experiments ................................250 8.5.2 Parallel Experiments ...............................252 8.5.3 IBM Cell Processor ................................258 8.6 Conclusion ...............................................258 References .....................................................259 9 Parallel Pseudo-Spectral Methods for the Time-Dependent Schrödinger Equation ........................................261 Tore Birkeland and Tor S0revik 9.1 Introduction ..............................................261 9.2 Time Stepping and Split Operator Technique ..................264 9.3 Variable Transformations and Spectral Bases ..................265 9.3.1 Cartesian Coordinates and Fourier Basis ..............265 9.3.2 Spherical Coordinates ..............................266 9.4 Parallelizing Many Dimensional FFTs ........................267 9.5 Creating a Framework for Combining Discretization Methods .... 271 9.5.1 Wavefunction .....................................272 9.5.2 Operators and Transforms ..........................273 9.5.3 Split-Step Propagator ..............................274 9.5.4 Explicit Propagators ...............................275 9.6 A Numerical Example .....................................275 9.6.1 Physical Model ...................................275 9.6.2 Numerical Considerations ..........................276 9.6.3 Scalability .......................................277 9.7 Conclusion ...............................................278 References .....................................................278 xviii Contents 10 Parallel Approaches in Molecular Dynamics Simulations ..........281 Dušanka Janežič, Urban Borštnik and Matej Praprotnik 10.1 Split Integration Symplectic Method .........................282 10.1.1 Calculation of Infrared Spectra ......................288 10.1.2 Enlarging the Integrational Time Step .................290 10.2 Parallel Computers ........................................290 10.2.1 Parallel Computing ................................291 10.2.2 Parallel Computer Types ............................292 10.2.3 Reducing Computational Complexity in Molecular Dynamics Simulations .............................293 10.3 Parallel Molecular Dynamics Computer Simulations ............294 10.3.1 Methods for Parallel Molecular Dynamics Simulations .. 295 10.3.2 Specialized Processors .............................296 10.3.3 Global Communication in Parallel Molecular Dynamics Simulations .............................298 10.4 Parallelization of SISM ....................................299 10.4.1 The Distributed Diagonal Force Decomposition Method . 299 10.5 Conclusions ..............................................301 References .....................................................302 11 Parallel Computer Simulations of Heat Transfer in Biological Tissues ....................................................307 Roman Trobec 11.1 Introduction ..............................................308 11.2 Principal Steps in Computer Simulation ......................311 11.3 Numerical Solution of Partial Differential Equations ............314 11.3.1 Finite Difference Method ...........................315 11.3.2 Finite Element Method .............................316 11.3.3 Solution Methods of Time-Dependent PDEs ...........316 11.3.4 Computational and Memory Complexity ..............320 11.4 Diffusion Equation ........................................321 11.4.1 Analytical Solution ................................324 11.4.2 Finite Differences with Gradient Term ................324 11.4.3 Explicit Finite Difference Scheme ....................325 11.4.4 Comparison of Results .............................328 11.5 Bio-Heat Equation ........................................330 11.6 Geometric Modeling of a Knee ..............................333 11.7 Simulation Methods and Parameters .........................336 11.8 Variation of Simulation Parameters ..........................338 11.9 Simulation Results ........................................340 11.9.1 Washing Out During Arthroscopy ....................341 11.9.2 Resting After Arthroscopy ..........................342 11.9.3 Postoperative Topical Cooling .......................342 11.10 Validation of Results ......................................345 11.11 Parallel Implementation ....................................347 Contents xix 11.11.1 Opportunities for Parallelization .....................348 11.11.2 Computation and Communication Complexity .........349 11.11.3 Measured Speedup ................................352 11.12 Conclusions ..............................................354 References .....................................................356 12 Parallel SVD Computing in the Latent Semantic Indexing Applications for Data Retrieval ................................359 Gabriel Okša and Marian Vajteršic 12.1 Introduction ..............................................359 12.2 Two Updating Problems in LSI ..............................361 12.2.1 Updating Documents ..............................361 12.2.2 Updating Terms ...................................362 12.3 Two Downdating Problems in LSI ...........................363 12.3.1 Downdating Documents ............................364 12.3.2 Downdating Terms ................................366 12.4 Kogbetliantz Method for Triangular Matrices ..................366 12.4.1 Butterfly Form of Triangular Matrices ................367 12.4.2 Modulus Pivot Strategy .............................368 12.4.3 Block Version and Parallelism .......................370 12.5 Parallel Two-sided Block-Jacobi SVD Algorithm with Dynamic Ordering .................................................377 12.6 LSI Implemented on a Grid .................................383 12.6.1 Storage ..........................................383 12.6.2 Updating Documents ..............................384 12.6.3 Updating Terms ...................................385 12.6.4 Downdating Documents ............................385 12.6.5 Downdating Terms ................................386 12.6.6 Retrieval of Documents ............................387 12.7 LSI Implemented on a Distributed System ....................388 12.7.1 Building a Global Approximation ....................389 12.7.2 Updating and Downdating ..........................391 12.7.3 Retrieval of Documents ............................392 12.8 Conclusions ..............................................394 References .....................................................395 13 Short-Vector SIMD Parallelization in Signal Processing ...........397 Rade Kutil 13.1 Introduction ..............................................397 13.1.1 Signal Processing Algorithms .......................398 13.1.2 Short-Vector SIMD ................................399 13.2 General Vectorization Approaches ...........................401 13.2.1 Loop Unrolling ...................................401 13.2.2 Straight Line Code Vectorization .....................401 13.2.3 Loop Fusion ......................................402 13.2.4 Loop Transposition ................................402 xx Contents 13.2.5 Algebraic Transforms ..............................403 13.3 Convolution Type Algorithms ...............................404 13.3.1 Simple FIR Filter ..................................404 13.3.2 The Haar Filter ...................................407 13.3.3 Biorthogonal 7/9 Without Lifting ....................408 13.3.4 Biorthogonal 7/9 With Lifting .......................414 13.3.5 Conclusion .......................................418 13.4 Recursive Algorithms ......................................419 13.4.1 Sequential IIR Algorithm ...........................420 13.4.2 Scheduling Approach ..............................420 13.4.3 Algebraic Transforms ..............................421 13.4.4 Experimental Results ..............................422 13.5 Block Algorithms .........................................423 13.5.1 Data Layout ......................................424 13.5.2 Basic FFT-Blocks .................................425 13.5.3 Automatic Tuning and Signal Processing Languages (SPL) ...........................................426 13.6 Mixed Algorithms .........................................428 13.6.1 Recursive Convolution - Wavelet Transforms ..........428 13.6.2 Multi-dimensional Algorithms .......................429 13.7 Conclusion ...............................................431 References .....................................................432 14 Financial Applications: Parallel Portfolio Optimization ............435 Andreas Grothey 14.1 Introduction ..............................................436 14.2 Asset and Liability Management by Stochastic Programming .... 437 14.2.1 Stochastic Programming ............................438 14.2.2 Asset and Liability Management Models ..............440 14.2.3 Model Extensions .................................444 14.3 Parallel Solution Approaches: Decomposition .................446 14.4 Parallel Solution Approaches: Interior Point Based Algorithms ... 448 14.4.1 IPM Applied to Stochastic Programming Problems .....451 14.4.2 Results ..........................................457 14.5 Parallel Solution Approaches: Heuristics and Evolutionary Algorithms ...............................458 14.6 Other Approaches .........................................458 14.7 Detailed Comparison of Parallel Interior Point Approaches ......459 14.7.1 OOPS (Gondzio and Grothey) .......................459 14.7.2 Riccati-Based IPM Solver (Blomvall and Lindberg) .....461 14.7.3 Tree Sparse IPM Solver (Steinbach)..................464 14.8 Conclusions ..............................................465 References .....................................................466 Contents xxi 15 The Future of Parallel Computation ............................471 Selim G. Aki and Marius Nagy 15.1 Introduction ..............................................472 15.2 Quantum Computing ......................................475 15.2.1 Quantum Mechanics ...............................475 15.2.2 Mathematical Framework ...........................478 15.2.3 Entanglement .....................................484 15.3 Parallelism in Quantum Computing ..........................485 15.3.1 Quantum Parallelism ...............................485 15.4 Examples ................................................488 15.4.1 Parallelizing the Quantum Fourier Transform ..........488 15.4.2 Quantum Decoherence .............................496 15.4.3 Quantum Error-Correction ..........................499 15.4.4 Quantum Distinguishability .........................502 15.4.5 Transformations Obeying a Global Condition ..........506 15.5 Looking Ahead ...........................................507 References .....................................................508 Index .............................................................511
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spelling	Parallel computing numerics, applications, and trends Roman Trobec ... ed. London Springer 2009 XXIV, 519 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Parallelverarbeitung (DE-588)4075860-6 gnd rswk-swf Programmierung (DE-588)4076370-5 gnd rswk-swf Parallelverarbeitung (DE-588)4075860-6 s Programmierung (DE-588)4076370-5 s 1\p DE-604 Trobec, Roman edt Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017606971&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk
spellingShingle	Parallel computing numerics, applications, and trends Parallelverarbeitung (DE-588)4075860-6 gnd Programmierung (DE-588)4076370-5 gnd
subject_GND	(DE-588)4075860-6 (DE-588)4076370-5
title	Parallel computing numerics, applications, and trends
title_auth	Parallel computing numerics, applications, and trends
title_exact_search	Parallel computing numerics, applications, and trends
title_full	Parallel computing numerics, applications, and trends Roman Trobec ... ed.
title_fullStr	Parallel computing numerics, applications, and trends Roman Trobec ... ed.
title_full_unstemmed	Parallel computing numerics, applications, and trends Roman Trobec ... ed.
title_short	Parallel computing
title_sort	parallel computing numerics applications and trends
title_sub	numerics, applications, and trends
topic	Parallelverarbeitung (DE-588)4075860-6 gnd Programmierung (DE-588)4076370-5 gnd
topic_facet	Parallelverarbeitung Programmierung
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017606971&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT trobecroman parallelcomputingnumericsapplicationsandtrends

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