Study of Accelerating Infrared Imaging Simulation Based on CUDA

2014 ◽  
Vol 651-653 ◽  
pp. 2045-2049
Author(s):  
Song Wang ◽  
Shan Liang Yang ◽  
Ge Li
Keyword(s):  
Parallel Computing ◽  
Infrared Imaging ◽  
Simulation System ◽  
Simulation Based ◽  
Imaging Simulation ◽  
Speed Up

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.

Simulation-Based Scheduling of Waterway Projects Using a Parallel Genetic Algorithm

2015 ◽  
pp. 334-347 ◽  
Author(s):  
Ning Yang ◽  
Shiaaulir Wang ◽  
Paul Schonfeld
Keyword(s):  
Genetic Algorithm ◽  
Parallel Computing ◽  
Message Passing ◽  
Message Passing Interface ◽  
Computation Time ◽  
Parallel Genetic Algorithm ◽  
Simulation Based ◽  
Multiple Processors ◽  
Simulation Based Optimization ◽  
Speed Up

A Parallel Genetic Algorithm (PGA) is used for a simulation-based optimization of waterway project schedules. This PGA is designed to distribute a Genetic Algorithm application over multiple processors in order to speed up the solution search procedure for a very large combinational problem. The proposed PGA is based on a global parallel model, which is also called a master-slave model. A Message-Passing Interface (MPI) is used in developing the parallel computing program. A case study is presented, whose results show how the adaption of a simulation-based optimization algorithm to parallel computing can greatly reduce computation time. Additional techniques which are found to further improve the PGA performance include: (1) choosing an appropriate task distribution method, (2) distributing simulation replications instead of different solutions, (3) avoiding the simulation of duplicate solutions, (4) avoiding running multiple simulations simultaneously in shared-memory processors, and (5) avoiding using multiple processors which belong to different clusters (physical sub-networks).

scholarly journals Simulation-Based Scheduling of Waterway Projects Using a Parallel Genetic Algorithm

2016 ◽  
pp. 1071-1084
Author(s):  
Ning Yang ◽  
Shiaaulir Wang ◽  
Paul Schonfeld
Keyword(s):  
Genetic Algorithm ◽  
Parallel Computing ◽  
Message Passing ◽  
Message Passing Interface ◽  
Computation Time ◽  
Parallel Genetic Algorithm ◽  
Simulation Based ◽  
Multiple Processors ◽  
Simulation Based Optimization ◽  
Speed Up

A Parallel Genetic Algorithm (PGA) is used for a simulation-based optimization of waterway project schedules. This PGA is designed to distribute a Genetic Algorithm application over multiple processors in order to speed up the solution search procedure for a very large combinational problem. The proposed PGA is based on a global parallel model, which is also called a master-slave model. A Message-Passing Interface (MPI) is used in developing the parallel computing program. A case study is presented, whose results show how the adaption of a simulation-based optimization algorithm to parallel computing can greatly reduce computation time. Additional techniques which are found to further improve the PGA performance include: (1) choosing an appropriate task distribution method, (2) distributing simulation replications instead of different solutions, (3) avoiding the simulation of duplicate solutions, (4) avoiding running multiple simulations simultaneously in shared-memory processors, and (5) avoiding using multiple processors which belong to different clusters (physical sub-networks).

PDE Computing Model of Internet Virtual Simulation Based on ANSYS

2014 ◽  
Vol 556-562 ◽  
pp. 6106-6110
Author(s):  
Jin Gen Tang ◽  
Ji Yuan Deng
Keyword(s):  
Parallel Computing ◽  
Computing System ◽  
Simulation System ◽  
Virtual Simulation ◽  
Machining Process ◽  
System Response ◽  
Computing Model ◽  
Simulation Based ◽  
Response Performance ◽  
Parallel Link

This paper establishes a parallel Internet virtual simulation PDE computing model based on quasi-linear, linear and nonlinear mathematical principles of computer, and obtains a partial differential equation for parallel computing system. The parallel computing can greatly improve the speed and accuracy of computer virtual simulation system. In order to validate the calculation, the paper uses ACC-8S interface board to realize the parallel link of computer, and two pieces of different material deformation in machining process was simulated by ANSYS software, and it concludes the contour of deformation . Finally, the system has been applied to the volleyball match virtual simulation system, and it gets the system response performance through simulation and calculation, which provides a technical reference for the training of volleyball players.

Research on Infrared Imaging Modeling and Simulation of Armored Vehicles

2014 ◽  
Vol 651-653 ◽  
pp. 2372-2376 ◽  
Author(s):  
Ni Li ◽  
Qing Hua Liu
Keyword(s):  
Infrared Imaging ◽  
Infrared Image ◽  
Simulation System ◽  
Image Generation ◽  
Spatial Effects ◽  
Atmospheric Transmission ◽  
Radiation Characteristics ◽  
Imaging Simulation ◽  
Armored Vehicle ◽  
Simulation Systems

Real-time infrared imaging technology with high fidelity is greatly desired in current simulation systems. An integrated infrared imaging simulation system including infrared radiation characteristics whose model was established by modeling different components of an armored vehicle respectively, atmospheric transmission effects and infrared sensor effects that mainly comprises frequency domain effects and spatial effects was established in this paper. The final infrared image can be generated by taking advantage of the simulation system. The simulation carried out in this paper has proved the validity and effectiveness of the established models, which could be of great significance in satisfying the requirements of dynamic infrared image generation in a photoelectric warfare simulation system.

A New Grid Multi-Scroll Chaotic System and the Simulation Based on Labview

2012 ◽  
Vol 538-541 ◽  
pp. 2666-2669
Author(s):  
Yong Huang
Keyword(s):  
Chaotic System ◽  
Chaotic Attractor ◽  
Step Function ◽  
Simulation System ◽  
Unstable System ◽  
Simulation Based ◽  
Two Parameters ◽  
The Way

In order to get the grid Multi-Scroll in the two directions, based on a simple unstable system, the way of the combination of the translational transform and step function was put forward to make the scrolls extending in the x and y directions in this paper. The quantity of scrolls can be controlled by two parameters N and M. A simulation system was designed with Labview to simulate grid Multi-Scroll chaotic system, it demonstrates the existence of grid Multi-Scroll chaotic attractor.

scholarly journals Comparison of Serial and Parallel Computation on Predicting Missing Data with EM Algorithm

2021 ◽  
Vol 18 (1) ◽  
pp. 22-30
Author(s):  
Erna Nurmawati ◽  
Robby Hasan Pangaribuan ◽  
Ibnu Santoso
Keyword(s):  
Parallel Computing ◽  
Missing Data ◽  
Data Processing ◽  
Em Algorithm ◽  
Parallel Computation ◽  
Incomplete Data ◽  
Parallel Programs ◽  
Missing Value ◽  
Speed Up ◽  
Compute Time

One way to deal with the presence of missing value or incomplete data is to impute the data using EM Algorithm. The need for large and fast data processing is necessary to implement parallel computing on EM algorithm serial program. In the parallel program architecture of EM Algorithm in this study, the controller is only related to the EM module whereas the EM module itself uses matrix and vector modules intensively. Parallelization is done by using OpenMP in EM modules which results in faster compute time on parallel programs than serial programs. Parallel computing with a thread of 4 (four) increases speed up, reduces compute time, and reduces efficiency when compared to parallel computing by the number of threads 2 (two).

Design of Imaging Simulation System for Infrared Image Sensor

2013 ◽  
Vol 28 (5) ◽  
pp. 788-792
Author(s):  
程瑶 CHENG Yao ◽  
鲁进 LU Jin ◽  
孟丽娅 MENG Li-ya
Keyword(s):  
Infrared Image ◽  
Image Sensor ◽  
Simulation System ◽  
Imaging Simulation
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