Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

Bin Chen, Ronald Kantowski, Xinyu Dai, Eddie Baron, Paul Van der Mark
Research Computing Center, Florida State University, Tallahassee, FL 32306, USA
arXiv:1703.09707 [astro-ph.IM], (28 Mar 2017)


   title={Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor},

   author={Chen, Bin and Kantowski, Ronald and Dai, Xinyu and Baron, Eddie and Mark, Paul Van der},






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Recently Graphics Processing Units (GPUs) have been used to speed up very CPU-intensive gravitational microlensing simulations. In this work, we use the Xeon Phi coprocessor to accelerate such simulations and compare its performance on a microlensing code with that of NVIDIA’s GPUs. For the selected set of parameters evaluated in our experiment, we find that the speedup by Intel’s Knights Corner coprocessor is comparable to that by NVIDIA’s Fermi family of GPUs with compute capability 2.0, but less significant than GPUs with higher compute capabilities such as the Kepler. However, the very recently released second generation Xeon Phi, Knights Landing, is about 5.8 times faster than the Knights Corner, and about 2.9 times faster than the Kepler GPU used in our simulations. We conclude that the Xeon Phi is a very promising alternative to GPUs for modern high performance microlensing simulations.
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