Open source acceleration of wave optics simulations on energy efficient high-performance computing platforms

Jeffrey Beck; Jeremy P. Bos

doi:10.1117/12.2264874

1 May 2017 Open source acceleration of wave optics simulations on energy efficient high-performance computing platforms

Jeffrey Beck, Jeremy P. Bos

Proceedings Volume 10204, Long-Range Imaging II; 102040F (2017) https://doi.org/10.1117/12.2264874
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

We compare several modifications to the open-source wave optics package, WavePy, intended to improve execution time. Specifically, we compare the relative performance of the Intel MKL, a CPU based OpenCV distribution, and GPU-based version. Performance is compared between distributions both on the same compute platform and between a fully-featured computing workstation and the NVIDIA Jetson TX1 platform. Comparisons are drawn in terms of both execution time and power consumption. We have found that substituting the Fast Fourier Transform operation from OpenCV provides a marked improvement on all platforms. In addition, we show that embedded platforms offer some possibility for extensive improvement in terms of efficiency compared to a fully featured workstation.

Conference Presentation

Citation Download Citation

Jeffrey Beck and Jeremy P. Bos "Open source acceleration of wave optics simulations on energy efficient high-performance computing platforms", Proc. SPIE 10204, Long-Range Imaging II, 102040F (1 May 2017); https://doi.org/10.1117/12.2264874

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available