2019 Student Research Conference:
32nd Annual Student Research Conference

Parallel Computation: Efficient Physics Simulations with Tensorflow

Katey J. Thompson
Prof. Timothy Wiser, Faculty Mentor

TensorFlow, Google’s machine-learning APO, has the potential to be a useful tool for physics simulation for systems with large numbers of initial conditions. Most relevant for our purposes, however, is that TensorFlow does parallel computation using GPUs. We have been working on simulations of basic physical systems in order to investigate the capabilities of the API. In the future, we would like to simulate a large number of dark matter particles in the solar system. Since the mass of dark matter in the solar system is small compared to the total mass, the internal interactions are effectively negligible. Ideally, TensorFlow will allow gravitational calculations to be performed simultaneously (i.e. more efficiently than other APIs are capable of).

Keywords: TensorFlow, physics, simulation, programming


Presentation Type: Oral Paper

Session: 210-5
Location: MC 211
Time: 11:15

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