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CPU-OpenGL GPU-Based Real Time Beam Tracking by Mems Phase SLM.

Record Type:	Electronic resources : Monograph/item
Title/Author:	CPU-OpenGL GPU-Based Real Time Beam Tracking by Mems Phase SLM./
Author:	Tang, Chin-I.
Description:	1 online resource (93 pages)
Notes:	Source: Masters Abstracts International, Volume: 84-03.
Contained By:	Masters Abstracts International84-03.
Subject:	Optics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29322867click for full text (PQDT)
ISBN:	9798841726678

CPU-OpenGL GPU-Based Real Time Beam Tracking by Mems Phase SLM.
Tang, Chin-I.

CPU-OpenGL GPU-Based Real Time Beam Tracking by Mems Phase SLM. - 1 online resource (93 pages)

Source: Masters Abstracts International, Volume: 84-03.

Thesis (M.S.)--The University of Arizona, 2022.

Includes bibliographical references

A GPU-accelerated real-time CGH computation and display framework for beam steering is reported in this dissertation. This approach utilizes CUDA for CGH computation and OpenGL API for 2D CGH rendering. The deterministic method for CGH beam steering is suitable for GPU computation because such method possesses low complexity, massive calculation, and independency of each pixel, which enables pixel-wise parallel processing with GPU. The performance of the presented approach for GPU-based CGH calculation and display on GTX 1650-Ti, results in ~10 times faster than CPU-based processing on i7-10750H 2.6GHz, which also achieves the maximum refresh rate (180 FPS) of the current generation of Texas Instrument Phase Light Modulator (PLM). In addition, we combine deep learning model (YOLOv4-tiny) for object detection and recognition, enable the system doing AI-based dynamic beam steering and trace the object of interest. Instead of single beam steering, multi-beam with variable beam ratio beam steering is also conducted on the same GPU framework, resulting in the beam steering speed more than 1k beams/second. Furthermore, the beam ratio simulation is introduced, which matches the measured beam ratio results. This simulation model allows us to predict and control the energy distribution. Thus, the AI-based dynamic multi-beam tracking with varying beam ratio is demonstrated in this dissertation.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798841726678Subjects--Topical Terms:

517925
Optics.
Subjects--Index Terms:

Beam steeringIndex Terms--Genre/Form:

542853
Electronic books.

CPU-OpenGL GPU-Based Real Time Beam Tracking by Mems Phase SLM.
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100 1 $a Tang, Chin-I. $3 3698442
245 1 0 $a CPU-OpenGL GPU-Based Real Time Beam Tracking by Mems Phase SLM.
264 0 $c 2022
300 $a 1 online resource (93 pages)
336 $a text $b txt $2 rdacontent
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500 $a Source: Masters Abstracts International, Volume: 84-03.
500 $a Advisor: Takashima, Yuzuru.
502 $a Thesis (M.S.)--The University of Arizona, 2022.
504 $a Includes bibliographical references
520 $a A GPU-accelerated real-time CGH computation and display framework for beam steering is reported in this dissertation. This approach utilizes CUDA for CGH computation and OpenGL API for 2D CGH rendering. The deterministic method for CGH beam steering is suitable for GPU computation because such method possesses low complexity, massive calculation, and independency of each pixel, which enables pixel-wise parallel processing with GPU. The performance of the presented approach for GPU-based CGH calculation and display on GTX 1650-Ti, results in ~10 times faster than CPU-based processing on i7-10750H 2.6GHz, which also achieves the maximum refresh rate (180 FPS) of the current generation of Texas Instrument Phase Light Modulator (PLM). In addition, we combine deep learning model (YOLOv4-tiny) for object detection and recognition, enable the system doing AI-based dynamic beam steering and trace the object of interest. Instead of single beam steering, multi-beam with variable beam ratio beam steering is also conducted on the same GPU framework, resulting in the beam steering speed more than 1k beams/second. Furthermore, the beam ratio simulation is introduced, which matches the measured beam ratio results. This simulation model allows us to predict and control the energy distribution. Thus, the AI-based dynamic multi-beam tracking with varying beam ratio is demonstrated in this dissertation.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Optics. $3 517925
650 4 $a Computer science. $3 523869
650 4 $a Computational physics. $3 3343998
653 $a Beam steering
653 $a CGH
653 $a GPU computing
653 $a LiDAR
653 $a Phase light modulator
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0752
690 $a 0984
690 $a 0216
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a The University of Arizona. $b Optical Sciences. $3 1019548
773 0 $t Masters Abstracts International $g 84-03.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29322867 $z click for full text (PQDT)