Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

Chen, B.; Kantowski, R.; Dai, X.; Baron, E.; Van der Mark, P.

doi:10.1016/j.ascom.2017.03.005

Title: Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

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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. Here, we conclude that the Xeon Phi is a very promising alternative to GPUs for modern high performance microlensing simulations. LESS

Authors:

Chen, B. ^[1]; Kantowski, R. ^[2]; Dai, X. ^[2];

^[2]; Van der Mark, P. ^[1]

Florida State Univ., Tallahassee, FL (United States)
The Univ. of Oklahoma, Norman, OK (United States)

Publication Date:: Fri Apr 07 00:00:00 EDT 2017

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Univ. of California, Oakland, CA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1543509

Alternate Identifier(s):: OSTI ID: 1396366

Grant/Contract Number:: AC02-05CH11231

Resource Type:: Accepted Manuscript

Journal Name:: Astronomy and Computing

Additional Journal Information:: Journal Volume: 19; Journal Issue: C; Journal ID: ISSN 2213-1337

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; 79 ASTRONOMY AND ASTROPHYSICS; Astronomy & Astrophysics; Computer Science; Gravitational lensing; Micro; Quasars; Supermassive black holes; Accretion; Accretion disks Methods; Numerical; Parallel processors

Citation Formats


                    Chen, B., Kantowski, R., Dai, X., Baron, E., and Van der Mark, P. Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor.  United States: N. p., 2017. 
Web.  doi:10.1016/j.ascom.2017.03.005.

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                    Chen, B., Kantowski, R., Dai, X., Baron, E., & Van der Mark, P. Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor.  United States.  https://doi.org/10.1016/j.ascom.2017.03.005

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                    Chen, B., Kantowski, R., Dai, X., Baron, E., and Van der Mark, P. Fri .  
"Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor".  United States.  https://doi.org/10.1016/j.ascom.2017.03.005.  https://www.osti.gov/servlets/purl/1543509.

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@article{osti_1543509,

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

  author       = {Chen, B. and Kantowski, R. and Dai, X. and Baron, E. and Van der Mark, P.},

  abstractNote = {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. Here, we conclude that the Xeon Phi is a very promising alternative to GPUs for modern high performance microlensing simulations. LESS},

  doi          = {10.1016/j.ascom.2017.03.005},

  journal      = {Astronomy and Computing},

  number       = C,

  volume       = 19,

  place        = {United States},

  year         = {Fri Apr 07 00:00:00 EDT 2017},

  month        = {Fri Apr 07 00:00:00 EDT 2017}

}

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