Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor
March 28, 2017 ยท Declared Dead ยท ๐ Astronomy and Computing
"No code URL or promise found in abstract"
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Authors
Bin Chen, Ronald Kantowski, Xinyu Dai, Eddie Baron, Paul Van der Mark
arXiv ID
1703.09707
Category
astro-ph.IM
Cross-listed
astro-ph.HE,
cs.DC
Citations
5
Venue
Astronomy and Computing
Last Checked
1 month ago
Abstract
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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