An Embedded GPU Triangle Rasterization Algorithm for Hardware Implementation

LIU Qing-nan; ZENG Ze-cang; DU Hui-min; DING Jia-long

Chinese

您当前的位置：

首页 >

文章列表页 >

An Embedded GPU Triangle Rasterization Algorithm for Hardware Implementation

更新时间：2026-09-04

- An Embedded GPU Triangle Rasterization Algorithm for Hardware Implementation
- Vol. 35, Issue 9, Pages: 26-31(2018)
- 作者机构：
  
  西安邮电大学机构电子工程学院,陕西,西安,710121
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
移动端阅览
刘青楠, 曾泽仓, 杜慧敏, 丁家隆. 一种易于硬件实现的嵌入式GPU三角形光栅化算法[J]. 微电子学与计算机, 2018, 35(9): 26-31.

LIU Qing-nan, ZENG Ze-cang, DU Hui-min, et al. An Embedded GPU Triangle Rasterization Algorithm for Hardware Implementation[J]. 2018, 35(9): 26-31.
刘青楠, 曾泽仓, 杜慧敏, 丁家隆. 一种易于硬件实现的嵌入式GPU三角形光栅化算法[J]. 微电子学与计算机, 2018, 35(9): 26-31. DOI：

LIU Qing-nan, ZENG Ze-cang, DU Hui-min, et al. An Embedded GPU Triangle Rasterization Algorithm for Hardware Implementation[J]. 2018, 35(9): 26-31. DOI：

摘要

在嵌入式GPU中

三角形光栅化的性能是决定图形处理器性能的一个重要因素.传统的三角形光栅化算法需要处理大量的无关像素

会降低GPU的处理速度.本文针对采用瓦片渲染的嵌入式GPU

提出一种基于瓦片的递归的三角形光栅化算法

三角形光栅化会引起图形的几何走样

本文利用超级采样中的反走样算法

只用加法和移位实现了RGSS反走样算法.用C++语言实现了所提出的三角形光栅化及反走样算法.并在Xilinx zc706开发板上对算法进行了验证.结果表明

光栅化算法可完成对任意三角形的渲染

RGSS反走样算法处理后的三角形抗锯齿效果明显

该算法易于硬件实现

适用于采用瓦片渲染的嵌入式GPU中.

Abstract

In Embedded GPU

Triangle rasterization is an important factor in determining the performance of graphics processors. Traditional algorithms generate several redundant pixels and cut down the efficiency of GPU. A recursive triangular rasterization algorithm is proposed for tile-based embedded GPU. In addition

the triangular rasterization will cause the aliasing of the graph. The super-sampling anti-aliasing algorithm

RGSS

is used and implemented only by addition and shift operations. The C + + language is used to implement the triangular rasterization and anti-aliasing algorithm. The results show that the rasterization algorithm can complete the rendering of any triangle

and the triangular anti-aliasing effect of RGSS anti-aliasing algorithm is obvious. Anti-aliasing algorithm can significantly improve the rasterization of the anti-aliasing effect and suitable for using in tiled base rendering embedded GPU.

关键词

Keywords

references

Popescu V, Rosen P. Forward rasterization[J]. ACM Transactions on Graphics (TOG), 2006, 25(2): 375-411. DOI: 375

Fuchs H, Goldfeather J, Hultquist J P, et al. Fast spheres, shadows, textures, transparencies, and imgage enhancements in pixel-planes[C]// Conference on Computer Graphics and Interactive Techniques. ACM, 1985: 111-120.

Akeninemoller T, Haines E, Hoffman N. Real-time rendering[J]. A.k.peters Limited, 2008, 32(2):163-173. DOI: 163

Popescu V, Rosen P. Forward rasterization[J]. ACM Transactions on Graphics (TOG), 2006, 25(2): 375-411. DOI: 375

Sun C H, Tsao Y M, Lok K H, et al. Universal Rasterizer with edge equations and tile-scan triangle traversal algorithm for graphics processing units[C]// IEEE International Conference on Multimedia and Expo. IEEE Press, 2009: 1358-1361.

Hraa.high-resolution antialiasing through multisampling[C]//USENIX Technical Conference. 2001.

Cook R L. Stochastic sampling in computer graphics[J]. Acm Transactions on Graphics, 1986, 5(1):51-72. DOI: 51

Shen Y L, Seo S W, Zhang Y, et al. A Low Hardware Cost 2D Vector Graphic Rendering Algorithm for Supersampling Antialiasing[J]. Computer Engineering % Applications, 2010, 1(31):141-144. DOI: 141

符鹤, 谢永芳. TBR架构GPU中三角形高效光栅化[J].中国图象图形学报, 2015, 20(4):527-532. DOI: 527

Lindholm E, Nickolls J, Oberman S, et al. NVIDIA Tesla: A Unified Graphics and Computing Architecture[J]. IEEE Micro, 2008, 28(2):39-55. DOI: 39

杜慧敏, 郝哲, 王鹏超, 等.三角形的光栅化与反走样算法[J].西安邮电大学学报, 2015, 20(3):33-38. DOI: 33

Garber L. GPUs Go Mobile [J]. Computer.2013, 46(2): 16-19. DOI: 16

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Microservices anomaly detection based on the correlation of monitoring metrics

Lightweight countermeasures against Spectre attacks on the branch prediction unit

Aerial vehicle detection algorithm based on multi-scale fusion and small-object enhancement

Aerial small object detection algorithm based on improved RT-DETR

Steganography model guided by attention mechanism and improved dense convolution

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰