Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor
- Florida State Univ., Tallahassee, FL (United States)
- The Univ. of Oklahoma, Norman, OK (United States)
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
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Univ. of California, Oakland, CA (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1543509
- Alternate ID(s):
- OSTI ID: 1396366
- Journal Information:
- Astronomy and Computing, Journal Name: Astronomy and Computing Journal Issue: C Vol. 19; ISSN 2213-1337
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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