Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/628561
Title: Compressed Coverage Masks for Path Rendering on Mobile GPUs
Authors: Pavel Krajcevski;Dinesh Manocha
subject: Texture compression|2D path rendering|coverage masks
Year: 2016
Publisher: IEEE
Abstract: We present an algorithm to accelerate resolution independent curve rendering on mobile GPUs. Recent trends in graphics hardware have created a plethora of compressed texture formats specific to GPU manufacturers. However, certain implementations of platform independent path rendering require generating grayscale textures on the CPU containing the extent that each pixel is covered by the curve. In this paper, we demonstrate that generating a compressed grayscale texture prior to uploading it to the GPU creates faster rendering times in addition to the memory savings. We implement a real-time compression technique for coverage masks and compare our results against the GPU-based implementation of the highly optimized Skia rendering library. We also analyze the worst case properties of our compression algorithms. We observe up to a 2× speed improvement over the existing GPU-based methods in addition to up to a 9:1 improvement in GPU memory gains. We demonstrate the performance on multiple mobile platforms.
Description: 
URI: http://localhost/handle/Hannan/163306
http://localhost/handle/Hannan/628561
ISSN: 1077-2626
volume: 22
issue: 10
Appears in Collections:2016

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Title: Compressed Coverage Masks for Path Rendering on Mobile GPUs
Authors: Pavel Krajcevski;Dinesh Manocha
subject: Texture compression|2D path rendering|coverage masks
Year: 2016
Publisher: IEEE
Abstract: We present an algorithm to accelerate resolution independent curve rendering on mobile GPUs. Recent trends in graphics hardware have created a plethora of compressed texture formats specific to GPU manufacturers. However, certain implementations of platform independent path rendering require generating grayscale textures on the CPU containing the extent that each pixel is covered by the curve. In this paper, we demonstrate that generating a compressed grayscale texture prior to uploading it to the GPU creates faster rendering times in addition to the memory savings. We implement a real-time compression technique for coverage masks and compare our results against the GPU-based implementation of the highly optimized Skia rendering library. We also analyze the worst case properties of our compression algorithms. We observe up to a 2× speed improvement over the existing GPU-based methods in addition to up to a 9:1 improvement in GPU memory gains. We demonstrate the performance on multiple mobile platforms.
Description: 
URI: http://localhost/handle/Hannan/163306
http://localhost/handle/Hannan/628561
ISSN: 1077-2626
volume: 22
issue: 10
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7378994.pdf1.1 MBAdobe PDFThumbnail
Preview File
Title: Compressed Coverage Masks for Path Rendering on Mobile GPUs
Authors: Pavel Krajcevski;Dinesh Manocha
subject: Texture compression|2D path rendering|coverage masks
Year: 2016
Publisher: IEEE
Abstract: We present an algorithm to accelerate resolution independent curve rendering on mobile GPUs. Recent trends in graphics hardware have created a plethora of compressed texture formats specific to GPU manufacturers. However, certain implementations of platform independent path rendering require generating grayscale textures on the CPU containing the extent that each pixel is covered by the curve. In this paper, we demonstrate that generating a compressed grayscale texture prior to uploading it to the GPU creates faster rendering times in addition to the memory savings. We implement a real-time compression technique for coverage masks and compare our results against the GPU-based implementation of the highly optimized Skia rendering library. We also analyze the worst case properties of our compression algorithms. We observe up to a 2× speed improvement over the existing GPU-based methods in addition to up to a 9:1 improvement in GPU memory gains. We demonstrate the performance on multiple mobile platforms.
Description: 
URI: http://localhost/handle/Hannan/163306
http://localhost/handle/Hannan/628561
ISSN: 1077-2626
volume: 22
issue: 10
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7378994.pdf1.1 MBAdobe PDFThumbnail
Preview File