Prof. John R. Humphrey
at EM Photonics Inc
SPIE Involvement:
Author | Instructor
Publications (13)

Proceedings Article | 13 June 2014
Proc. SPIE. 9095, Modeling and Simulation for Defense Systems and Applications IX
KEYWORDS: Control systems, Computer programming, Switching, Parallel computing, Manufacturing, Standards development, Wavefronts, Detection and tracking algorithms, Algorithm development, Photonics

Proceedings Article | 13 June 2014
Proc. SPIE. 9095, Modeling and Simulation for Defense Systems and Applications IX
KEYWORDS: Linear algebra, Field programmable gate arrays, Matrix multiplication, Matrices, Standards development, Algorithm development, Optimization (mathematics), Graphics processing units, Computer programming, Image processing

Proceedings Article | 9 June 2014
Proc. SPIE. 9076, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XI
KEYWORDS: Image processing, Cameras, Turbulence, Algorithm development, Video, Video surveillance, Video processing, Surveillance, Image enhancement, Speckle imaging

Proceedings Article | 29 May 2013
Proc. SPIE. 8752, Modeling and Simulation for Defense Systems and Applications VIII
KEYWORDS: Chemical elements, Computational fluid dynamics, Data communications, Computer architecture, Data processing, Photonics, Profiling, Defense and security, Computer simulations, Parallel computing

Proceedings Article | 21 May 2011
Proc. SPIE. 8060, Modeling and Simulation for Defense Systems and Applications VI
KEYWORDS: Linear algebra, MATLAB, Matrices, Graphics processing units, Computing systems, Parallel computing, Performance modeling, Mathematics, Chemical elements, Excel

Showing 5 of 13 publications
Course Instructor
SC1069: GPU for Defense Applications
This course teaches the basics of utilizing modern programmable graphics processing units (GPUs) for military applications. The modern GPU is a fully programmable parallel programming environment that performs computations an order of magnitude faster than the modern CPU. In this course, we will learn broadly about the architecture of the GPU, the appropriate situations where speedups may be obtained and gain an understanding of the tools and languages that are available for development. Programming is not a part of the curriculum. We will also discuss the available GPU platforms, with an emphasis on rugged, deployable, and low-power offerings. Lastly, the bulk of the course will center on applications and case studies, with emphasis on applications we have produced, including: real-time image processing for the reduction of atmospheric turbulence, applied accelerated linear algebra, image enhancement via super resolution, computational fluid dynamics, and computational electromagnetics.
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