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In this bachelor thesis a code for astrophysical self-gravitating fluid
simulation is developed. The code runs mainly on the GPU. Minimal
simplifications of the physical model and some parameters for accuracy
and tuning allow simulations to be performed at interactive framerates
on most modern consumer grade computers that feature a dedicated
graphics card. It is used to simulate the birth of stars from a turbulent
molecular cloud. Multiple features of star formation, like accretion
discs and fragmentation, can be observed in the simulation, even when
low particle counts are used.
In this thesis, the performance of the IceCube projects photon propagation
code (clsim) is optimized. The process of GPU code analysis and perfor-
mance optimization is described in detail. When run on the same hard-
ware, the new version achieves a speedup of about 3x over the original
implementation. Comparing the unmodified code on hardware currently
used by IceCube (NVIDIA GTX 1080) against the optimized version run on
a recent GPU (NVIDIA A100) a speedup of about 9.23x is observed. All
changes made to the code are shown and their performance impact as well
as the implications for simulation accuracy are discussed individually.
The approach taken for optimization is then generalized into a recipe.
Programmers can use it as a guide, when approaching large and complex
GPU programs. In addition, the per warp job-queue, a design pattern used
for load balancing among threads in a CUDA thread block, is discussed in
detail.
