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Hellmich, Stephan: GPU accelerated n-body integrators for long-term simulations of planetary systems. 2017
Inhalt
1 Introduction
1.1 Minor planets in the solar system
1.1.1 Asteroids
1.1.2 Comets
1.2 Dynamical evolution of minor planets
1.3 Motivation for this work
2 Solving the n-body problem
2.1 The n-body problem
2.2 Numerical integration
2.2.1 Explicit methods
2.2.2 Symplectic methods
2.2.3 A higher order integration scheme
2.3 Tuning the method for solar system like n-body problems
2.3.1 Mixed Variable Symplectic method
2.3.2 Integrating minor bodies of infinitesimal mass
2.3.3 Encounters between minor bodies and planets
2.3.4 Limitations due to machine precision
2.4 The Yarkovsky Effect
Diurnal Component
Seasonal Component
3 General-Purpose Computation on Graphics Processing Units
3.1 The History of Graphics Processing Units (GPUs)
3.2 General-Purpose Computation on Graphics Processing Units
3.3 CUDA Computing architecture on Nvidia GPUs
3.3.1 Fundamental differences between GPU and CPU
3.3.2 Programming model
3.3.3 Performance guidelines
Launch as many threads as possible
Economize memory transfers between host and device
Maximize device memory bandwidth
Avoid divergence within a single warp
Find the right ratio between block size and register count
4 cuSwift - a library of GPU based n-Body Integrators
4.1 Included Integration Methods
4.1.1 Wisdom-Holman-Mapping (WHM)
CPU implementation
GPU Implementation
Data layout
Memory management
Thread divergence
Dynamic memory reallocation
4.1.2 RMVS
CPU Implementation
GPU Implementation
Memory management for close encounter processing
Close encounter handling
4.2 Yarkovsky effect
5 Validation and Benchmarking
5.1 Test setup for WHM
5.1.1 The dynamics of Pluto
Why Pluto?
5.1.2 A fictitious population of Plutos
5.1.3 Validating cuWHM
Fused multiply-add
Drift methods
Conclusions
5.2 Test setup for RMVS
5.2.1 Monitoring the Jacobi constant in the restricted three body problem
5.2.2 Creating a set of particles frequently involved in close encounters
5.2.3 Validating cuRMVS
Conclusions
5.3 Test setup for the Yarkovsky effect
5.3.1 Validating the Yarkovsky effect
Conclusions
5.4 Performance
5.4.1 Test setup
5.4.2 Speedup
WHM
RMVS
Conclusions
6 Impact of the Yarkovsky effect on the Jupiter Trojan Asteroids
6.1 Jupiter's Trojan asteroids
6.2 Does the Yarkovsky force affect Jupiter Trojans?
6.2.1 A Fictitious, long-lived population of Jupiter Trojans
Without considering the Yarkovsky effect
When considering the Yarkovsky effect
6.2.2 A more realistic population
Estimating the libration amplitude
Finding an appropriate integration interval
Run time of the integrations
6.3 Results and discussion
Influence of the physical properties
Ratio of escaped L4 and L5 Trojans
Implications on the libration amplitude
Conclusions
Caveats
7 Future work
7.1 Improve and Implement more non-gravitational effects
7.1.1 Improve the Yarkovsky effect and include YORP Effect
7.1.2 Include YORP Effect
7.1.3 Acceleration due to cometary activity
7.1.4 Collisions and Fragmentation
7.2 Implement additional Integration Methods
8 Bibliography