Study of Accelerating Infrared Imaging Simulation Based on CUDA

Song Wang; Shan Liang Yang; Ge Li

doi:10.4028/www.scientific.net/AMM.651-653.2045

Paper Titles

Design and Implementation of Facial Sketch System Based on Cloud Computing Platform and Big Data
p.2028

Design and Realization of IE Vulnerabilities Mining Based on Fuzz Testing
p.2032

Hybrid Laser/Microwave Wireless Communication System for Fractionated Cluster Spacecraft
p.2036

RFID Technology Applied in Medicine Distribution Center
p.2040

Study of Accelerating Infrared Imaging Simulation Based on CUDA
p.2045

The Application Research on Ergonomics Based on the CATIA Software Platform
p.2050

The Design and Development of Information Conformance Test System Based on IEC 61968
p.2055

The Design and Implementation of a Certain Information System Joint Debugging and Status Monitoring System
p.2059

Using Expert Systems and Cloud Computing to Build a Diabetes Diagnosis System
p.2063

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 651-653Study of Accelerating Infrared Imaging Simulation...

Study of Accelerating Infrared Imaging Simulation Based on CUDA

Abstract:

This paper builds an infrared scene of sphere target based on JAMSE, which provides EO/IR environment and is suite to build infrared imaging simulation system of engineering and engagement-level. In addition, to speed up this infrared imaging simulation, we analyzed the process of external rendering mode, which is applied in JMAES EO/IR environment, and found the external rendering image compounding is a highly independently process, which is suite to parallel computing. After testing on NVIDIA TESLA C2075 GPU with CUDA, and comparing the performance with the corresponding sequentialprocess on CPU, we got a satisfied result. This process obtains a speed up of over 10.

You might also be interested in these eBooks

Material Science, Civil Engineering and Architecture Science, Mechanical Engineering and Manufacturing Technology II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 651-653)

Pages:

2045-2049

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.651-653.2045

Citation:

Cite this paper

Online since:

September 2014

Authors:

Song Wang*, Shan Liang Yang, Ge Li

Keywords:

CUDA, Infrared Imaging Simulation, JMASE

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] LIANG Shuzhong, Guo Gang, Li Ge, Research on EO/IR Environment Simulation in JMASE, Computer Simulation, 1006 – 9348 (2006) 07 – 0183 – 04.

Google Scholar

[2] Lu Zhifeng, Wang Chuncai, Guo Gang, Li Ge, Research on External Rendering in Infrared Imaging Simulation, Computer Simulation, 1006 – 9348 (2007) 09 – 0206 – 04.

Google Scholar

[3] Huang Chaochao, Wu Xiaodi, Tong Wuqin, Infrared Image Simulation Based On Statistical Learning Theory, Int J Infrared Milli Waves (2007) 28, p.1143 – 1153.

DOI: 10.1007/s10762-007-9270-4

Google Scholar

[4] Ni Li a, *, Zeya Su a, Zheng Chen b, Dong Han b , A real – time aircraft infrared imaing simulation platform, Optik 124(2013), p.2885 – 2893.

DOI: 10.1016/j.ijleo.2012.08.083

Google Scholar

[5] DimtriKomatitsha, b, *, David Micheaa, Gordon Erlebacherc, Porting a high-order finite-element earthquake modeling application to NVIDIA graphics cards using CUDA, J. Parallel Distrib. Comput. 69(2009) , pp.451-460.

DOI: 10.1016/j.jpdc.2009.01.006

Google Scholar

[6] Svetlin A. Manavski, CUDA COMPATIBLE GPU AS AN EFFICIENT HARDWARE ACCELERATOR FOR AES CRYPTOGRAPHY, 2007 IEEE International Conference on Signal Processing and Communications(ICSPC 2007), pp.65-68.

DOI: 10.1109/icspc.2007.4728256

Google Scholar

[7] CUDA C PROGRAMMING GUIDE, NVIDIA, PG – 02829 – 001_v5. 5.

Google Scholar