Large-Scale Computing Techniques for Complex System Simulations

Large-Scale Computing......Page 5
Contents......Page 7
Foreword......Page 13
Preface......Page 17
Contributors......Page 21
1.1 INTRODUCTION......Page 25
1.2 GRID COMPUTING......Page 26
1.3 VIRTUALIZATION......Page 30
1.4 CLOUD COMPUTING......Page 32
1.4.1 Drawbacks of Cloud Computing......Page 33
1.4.2 Cloud Interfaces......Page 34
1.5 GRID AND CLOUD: TWO COMPLEMENTARY TECHNOLOGIES......Page 36
1.6 MODELING AND SIMULATION OF GRID AND CLOUD COMPUTING......Page 37
1.6.1 GridSim and CloudSim Toolkits......Page 38
1.7 SUMMARY AND OUTLOOK......Page 39
REFERENCES......Page 40
2.1 THE WORLDWIDE E-INFRASTRUCTURE LANDSCAPE......Page 43
2.2.1 The BalticGrid Infrastructure......Page 45
2.2.2 BalticGrid Applications: Providing Local Support to Global Science......Page 46
2.2.3 The Pilot Applications......Page 47
2.3 THE EGEE INFRASTRUCTURE......Page 49
2.3.1 The EGEE Production Service......Page 50
2.3.2 EGEE and BalticGrid: e-Infrastructures in Symbiosis......Page 52
2.4.1 Industry and Grids......Page 53
2.4.3 Clouds: A New Way to Attract SMEs and Start-Ups......Page 54
2.5 THE FUTURE OF EUROPEAN E-INFRASTRUCTURES: THE EUROPEAN GRID INITIATIVE (EGI) AND THE PARTNERSHIP FOR ADVANCED COMPUTING IN EUROPE (PRACE) INFRASTRUCTURES......Page 55
2.5.1 Layers of the Ecosystem......Page 56
2.6 SUMMARY......Page 57
REFERENCES......Page 58
 Chapter 3: Accelerated Many-Core GPU Computing for Physics and Astrophysics on Three Continents......Page 59
3.1 INTRODUCTION......Page 60
3.2 ASTROPHYSICAL APPLICATION FOR STAR CLUSTERS AND GALACTIC NUCLEI......Page 62
3.3 HARDWARE......Page 64
3.4 SOFTWARE......Page 65
3.5 RESULTS OF BENCHMARKS......Page 66
3.7 PHYSICAL MULTISCALE DISCRETE SIMULATION AT IPE......Page 73
3.8 DISCUSSION AND CONCLUSIONS......Page 77
REFERENCES......Page 78
4.1 INTRODUCTION......Page 83
4.2 SYSTEM ARCHITECTURE......Page 86
4.3 SYSTEM IMPLEMENTATION......Page 91
4.3.1 Key Components......Page 92
4.3.2 Novel Features in SWAGES......Page 93
4.4.1 Research Questions and Simulation Model......Page 95
4.4.3 Simulation Runs in SWAGES......Page 96
4.4.4 Data Management and Visualization......Page 97
4.5 DISCUSSION......Page 98
4.5.1 Automatic Parallelization of Agent-Based Models......Page 99
4.5.4 SWAGES Compared to Other Frameworks......Page 100
REFERENCES......Page 102
5.1 INTRODUCTION......Page 105
5.3 MOTIVATION AND RELATED WORK......Page 106
5.4 FROM REPAST S TO REPAST HPC......Page 114
5.4.3 Modeling......Page 115
5.5 PARALLELISM......Page 116
5.6 IMPLEMENTATION......Page 118
5.6.2 RepastProcess......Page 119
5.6.3 Scheduler......Page 120
5.6.4 Distributed Network......Page 121
5.6.5 Distributed Grid......Page 122
5.6.6 Data Collection and Logging......Page 123
5.6.7 Random Number Generation and Properties......Page 124
5.7 EXAMPLE APPLICATION: RUMOR SPREADING......Page 125
5.7.1 Performance Results......Page 127
REFERENCES......Page 131
6.1 INTRODUCTION......Page 135
6.2 REQUIREMENTS OF MULTISCALE SIMULATIONS......Page 136
6.2.1 Interactions between Single-Scale Models......Page 137
6.2.2 Interoperability, Composability, and Reuse of Simulation Models......Page 139
6.3.1 Tools for Multiscale Simulation Development......Page 140
6.3.2 Support for Composability......Page 141
6.3.3 Support for Simulation Sharing......Page 142
6.4.1 Architecture of the CompoHLA Environment......Page 143
6.4.2 Interactions within the CompoHLA Environment......Page 144
6.4.3 HLA Components......Page 146
6.5 CASE STUDY WITH THE MUSE APPLICATION......Page 148
6.6 SUMMARY AND FUTURE WORK......Page 151
ACKNOWLEDGMENTS......Page 152
REFERENCES......Page 153
7.1.1 The Challenge......Page 155
7.2 DATA-INTENSIVE COMPUTERS......Page 156
7.3.1 Data Mining and Data Integration......Page 158
7.3.2 Making Data Mining Easier......Page 159
7.3.3 The ADMIRE Workbench......Page 161
REFERENCES......Page 163
8.1 INTRODUCTION......Page 165
8.2.1 Modeling GRNs......Page 167
8.2.2 QCG-OMPI......Page 172
8.2.3 A Topology-Aware Evolutionary Algorithm......Page 176
8.3.1 Scaling and Speedup of the Topology-Aware Evolutionary Algorithm......Page 179
8.3.2 Reverse-Engineering Results......Page 182
8.4 CONCLUSIONS......Page 184
REFERENCES......Page 185
9.1 INTRODUCTION......Page 187
9.2 DISTRIBUTED AND PARALLEL SIMULATIONS......Page 189
9.3 PROGRAMMING AND EXECUTION ENVIRONMENTS......Page 192
9.3.1 QCG-OMPI......Page 193
9.3.2 QCG-ProActive......Page 195
9.4 QCG MIDDLEWARE......Page 198
9.4.1 QCG-Computing Service......Page 199
9.4.2 QCG-Notification and Data Movement Services......Page 200
9.4.3 QCG-Broker Service......Page 201
9.5.1 Eclipse Parallel Tools Platform (PTP) for QCG......Page 203
9.6 QOSCOSGRID SCIENCE GATEWAYS......Page 204
9.7 DISCUSSION AND RELATED WORK......Page 206
REFERENCES......Page 208
Glossary......Page 211
Index......Page 219