Parallel science and engineering applications: the Charm++ approach (Boca Raton, 2014). - ОГЛАВЛЕНИЕ / CONTENTS

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ОбложкаParallel science and engineering applications: the Charm++ approach / ed. by L.V.Kale, A.Bhatele. - Boca Raton: CRC/Taylor & Francis, 2014. - xxxvi, 274 p.: ill. - (Series in computational physics). - Bibliogr.: p.247-269. - Ind.: p.271-274. - ISBN 978-1-4665-0412-7
 

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Оглавление / Contents
 
List of Figures .............................................. xiii
List of Tables ................................................ xxi
Series in Computational Physics ............................. xxiii
Foreword ...................................................... xxv
Preface ..................................................... xxvii
About the Editors .......................................... xxxiii
Contributors ................................................. xxxv
1  The Charm++ Programming Model ................................ 1
   Laxmikant V. Kale and Gengbin Zheng
   1.1  Design Philosophy ....................................... 2
   1.2  Object-Based Programming Model .......................... 3
   1.3  Capabilities of the Adaptive Runtime System ............. 8
   1.4  Extensions to the Basic Model .......................... 10
   1.5  Charm++ Ecosystem ...................................... 13
   1.6  Other Languages in the Charm++ Family .................. 14
   1.7  Historical Notes ....................................... 15
   1.8  Conclusion ............................................. 16
2  Designing Charm ++ Programs ................................. 17
   Laxmikant V. Kale
   2.1  Simple Stencil: Using Over-Decomposition and Selecting
        Grainsize .............................................. 17
        2.1.1  Grainsize Decisions ............................. 18
        2.1.2  Multicore Nodes ................................. 21
        2.1.3  Migrating Chares, Load Balancing and Fault
               Tolerance ....................................... 21
   2.2  Multi-Physics Modules Using Multiple Chare Arrays ...... 23
        2.2.1  LeanMD .......................................... 24
   2.3  SAMR: Chare Arrays with Dynamic Insertion and
        Flexible Indices ....................................... 27
   2.4  Combinatorial Search: Task Parallelism ................. 29
   2.5  Other Features and Design Considerations ............... 30
   2.6  Utility of Charm++ for Future Applications ............. 31
   2.7  Summary ................................................ 32
3  Tools for Debugging and Performance Analysis ................ 35
   Filippo Gioachin, Chee Wai Lee, Jonathan Lifflander,
   Yanhua Sun and Laxmikant V. Kale
   3.1  Introduction ........................................... 36
   3.2  Scalable Debugging with CharmDebug ..................... 36
        3.2.1  Accessing User Information ...................... 37
        3.2.2  Debugging Problems at Large Scale ............... 40
        3.2.3  Summary ......................................... 46
   3.3  Performance Visualization and Analysis via
        Projections ............................................ 47
        3.3.1  A Simple Projections Primer ..................... 49
        3.3.2  Features of Projections via Use Cases ........... 51
        3.3.3  Advanced Features for Scalable Performance
               Analysis ........................................ 58
        3.3.4  Summary ......................................... 59
   3.4  Conclusions ............................................ 60
4  Scalable Molecular Dynamics with NAMD ....................... 61
   James C. Phillips, Klaus Schulten, Abhinav Bhatele, Chao
   Mei, Yanhua Sun, Eric J. Bohm and Laxmikant V. Kale
   4.1  Introduction ........................................... 61
   4.2  Need for Biomolecular Simulations ...................... 62
   4.3  Parallel Molecular Dynamics ............................ 63
   4.4  NAMD's Parallel Design ................................. 64
        4.4.1  Force Calculations .............................. 65
        4.4.2  Load Balancing .................................. 66
   4.5  Enabling Large Simulations ............................. 67
        4.5.1  Hierarchical Load Balancing ..................... 67
        4.5.2  SMP Optimizations ............................... 68
        4.5.3  Optimizing Fine-Grained Communication in NAMD ... 70
        4.5.4  Parallel Input/Output ........................... 71
   4.6  Scaling Performance .................................... 72
   4.7  Simulations Enabled by NAMD ............................ 75
   4.8  Summary ................................................ 76
5  OpenAtom: Ab initio Molecular Dynamics for Petascale
   Platforms ................................................... 79
   Glenn J. Martyna, Eric J. Bohm, Ramprasad Venkataraman,
   Laxmikant V. Kale and Abhinav Bhatele
   5.1  Introduction ........................................... 80
   5.2  Car-Parrinello Molecular Dynamics ...................... 81
        5.2.1  Density Functional Theory, KS Density Functional
               Theory and the Local Density Approximation ...... 82
        5.2.2  DFT Computations within Basis Sets .............. 84
        5.2.3  Molecular Dynamics .............................. 84
        5.2.4  Ab initio Molecular Dynamics and CPAIMD ......... 84
        5.2.5  Path Integrals .................................. 85
        5.2.6  Parallel Tempering .............................. 86
   5.3  Parallel Application Design ............................ 87
        5.3.1  Modular Design and Benefits ..................... 87
        5.3.2  Parallel Driver ................................. 89
        5.3.3  Topology Aware Mapping .......................... 93
   5.4  Charm++ Feature Development ............................ 95
   5.5  Performance ............................................ 97
   5.6  Impact on Science and Technology ....................... 98
        5.6.1  Carbon Based Materials for Photovoltaic
               Applications .................................... 98
        5.6.2  Metal Insulator Transitions for Novel Devices .. 102
               Future Work .................................... 103
6  N-body Simulations with ChaNGa ............................. 105
   Thomas R. Quinn, Pritish Jetley, Laxmikant V. Kale and
   Filippo Gioachin
   6.1  Introduction .......................................... 106
   6.2  Code Design ........................................... 107
        6.2.1  Domain Decomposition and Load Balancing ........ 108
        6.2.2  Tree Building .................................. 110
        6.2.3  Tree Walking ................................... 112
        6.2.4  Force Softening ................................ 113
        6.2.5  Periodic Boundary Conditions ................... 114
        6.2.6  Neighbor Finding ............................... 114
        6.2.7  Multi-Stepping ................................. 115
   6.3  Accuracy Tests ........................................ 115
        6.3.1  Force Errors ................................... 115
        6.3.2  Cosmology Tests ................................ 116
   6.4  Performance ........................................... 121
        6.4.1  Domain Decomposition and Tree Build
               Performance .................................... 121
        6.4.2  Single-Stepping Performance .................... 123
        6.4.3  Multi-Stepping Performance ..................... 125
        6.4.4  ChaNGa on GPUs ................................. 125
   6.5  Conclusions and Future Work ........................... 133
7  Remote Visualization of Cosmological Data Using Salsa ...... 137
   Orion Sky Lawlor and Thomas R. Quinn
   7.1  Introduction .......................................... 137
   7.2  Salsa Client/Server Rendering Architecture ............ 138
        7.2.1  Client Server Communication Styles ............. 139
        7.2.2  Image Compression in Salsa ..................... 141
        7.2.3  GPU Particle Rendering on the Server ........... 142
   7.3  Remote Visualization User Interface ................... 144
   7.4  Example Use: Galaxy Clusters .......................... 145
8  Improving Scalability of BRAMS: a Regional Weather
   Forecast Model ............................................. 149
   Eduardo R. Rodrigues, Celso L. Mendes and Jairo Panetta
   8.1  Introduction .......................................... 150
   8.2  Load Balancing Strategies for Weather Models .......... 151
   8.3  The BRAMS Weather Model ............................... 153
   8.4  Load Balancing Approach ............................... 154
        8.4.1  Adaptations to AMPI ............................ 155
        8.4.2  Balancing Algorithms Employed .................. 157
   8.5  New Load Balancer ..................................... 158
   8.6  Fully Distributed Strategies .......................... 162
        8.6.1  Hilbert Curve-Based Load Balancer .............. 162
        8.6.2  Diffusion-Based Load Balancer .................. 164
   8.7  Experimental Results .................................. 166
        8.7.1  First Set of Experiments: Privatization
               Strategy ....................................... 166
        8.7.2  Second Set of Experiments: Virtualization
               Effects ........................................ 167
        8.7.3  Third Set of Experiments: Centralized Load
               Balancers ...................................... 171
        8.7.4  Fourth Set of Experiments: Distributed Load
               Balancers ...................................... 174
   8.8  Final Remarks ......................................... 182
9  Crack Propagation Analysis with Automatic Load Balancing ... 187
   Orion Sky Lawlor, M. Scot Breitenfeld, Philippe H.
   Geubelle and Gengbin Zheng
   9.1  Introduction .......................................... 187
        9.1.1  ParFUM Framework ............................... 188
        9.1.2  Implementation of the ParFUM Framework ......... 190
   9.2  Load Balancing Finite Element Codes in Charm++ ........ 193
        9.2.1  Runtime Support for Thread Migration ........... 193
        9.2.2  Comparison to Prior Work ....................... 194
        9.2.3  Automatic Load Balancing for FEM ............... 195
        9.2.4  Load Balancing Strategies ...................... 196
        9.2.5  Agile Load Balancing ........................... 197
   9.3  Cohesive and Elasto-plastic Finite Element Model of
        Fracture .............................................. 199
        9.3.1  Case Study 1: Elastc-Plastic Wave Propagation .. 202
        9.3.2  Case Study 2: Dynamic Fracture ................. 206
   9.4  Conclusions ........................................... 210
10 Contagion Diffusion with EpiSimdemics ...................... 211
   Keith R. Bisset, Ashwin M. Aji, Tariq Kamal, Jae-Seung
   Yeom, Madhav V. Marathe, Eric J. Bohm and Abhishek Gupta
   10.1 Introduction .......................................... 212
   10.2 Problem Description ................................... 215
        10.2.1 Formalization .................................. 215
        10.2.2 Application to Computational Epidemiology ...... 217
   10.3 EpiSimdemics Design ................................... 218
        10.3.1 The Disease Model .............................. 220
        10.3.2 Modeling Behavior of Individual Agents ......... 220
        10.3.3 Intervention and Behavior Modification ......... 221
        10.3.4 Social Network Representation .................. 223
   10.4 EpiSimdemics Algorithm ................................ 224
   10.5 Charm++ Implementation ................................ 227
        10.5.1 Designing the Chares ........................... 228
        10.5.2 The EpiSimdemics Algorithm ..................... 230
        10.5.3 Charm++ Features ............................... 232
   10.6 Performance of EpiSimdemics ........................... 232
        10.6.1  Experimental Setup ............................ 233
        10.6.2  Performance Characteristics ................... 233
        10.6.3  Effects of Synchronization .................... 234
        10.6.4  Effects of Strong Scaling ..................... 235
        10.6.5  Effects of Weak Scaling ....................... 236
        10.6.6  Effect of Load Balancing ...................... 237
   10.7 Representative Study .................................. 241
Bibliography .................................................. 247
Index ......................................................... 271


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