一种基于gpu的JPEG2000并行1层编码器

Roto Le, R. I. Bahar, J. Mundy
{"title":"一种基于gpu的JPEG2000并行1层编码器","authors":"Roto Le, R. I. Bahar, J. Mundy","doi":"10.1109/SASP.2011.5941091","DOIUrl":null,"url":null,"abstract":"The JPEG2000 image compression standard provides superior features to the popular JPEG standard; however, the slow performance of software implementation of JPEG2000 has kept it from being widely adopted. More than 80% of the execution time for JPEG2000 is spent on the Tier-1 coding engine. While much effort over the past decade has been devoted to optimizing this component, its performance still remains slow. The major reason for this is that the Tier-1 coder consists of highly serial operations, each operating on individual bits in every single bit plane of the image samples. In addition, in the past there lacked an efficient hardware platform to provide massively parallel acceleration for Tier-1. However, the recent growth of general purpose graphic processing unit (GPGPU) provides a great opportunity to solve the problem with thousands of parallel processing threads. In this paper, the computation steps in JPEG2000 are examined, particularly in the Tier-1, and novel, GPGPU compatible, parallel processing methods for the sample-level coding of the images are developed. The GPGPU-based parallel engine allows for significant speedup in execution time compared to the JasPer JPEG2000 compression software. Running on a single Nvidia GTX 480 GPU, the parallel wavelet engine achieves 100× speedup, the parallel bit plane coder achieves more than 30× speedup, and the overall Tier-1 coder achieves up to 17× speedup.","PeriodicalId":375788,"journal":{"name":"2011 IEEE 9th Symposium on Application Specific Processors (SASP)","volume":"81 26","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"A novel parallel Tier-1 coder for JPEG2000 using GPUs\",\"authors\":\"Roto Le, R. I. Bahar, J. Mundy\",\"doi\":\"10.1109/SASP.2011.5941091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The JPEG2000 image compression standard provides superior features to the popular JPEG standard; however, the slow performance of software implementation of JPEG2000 has kept it from being widely adopted. More than 80% of the execution time for JPEG2000 is spent on the Tier-1 coding engine. While much effort over the past decade has been devoted to optimizing this component, its performance still remains slow. The major reason for this is that the Tier-1 coder consists of highly serial operations, each operating on individual bits in every single bit plane of the image samples. In addition, in the past there lacked an efficient hardware platform to provide massively parallel acceleration for Tier-1. However, the recent growth of general purpose graphic processing unit (GPGPU) provides a great opportunity to solve the problem with thousands of parallel processing threads. In this paper, the computation steps in JPEG2000 are examined, particularly in the Tier-1, and novel, GPGPU compatible, parallel processing methods for the sample-level coding of the images are developed. The GPGPU-based parallel engine allows for significant speedup in execution time compared to the JasPer JPEG2000 compression software. Running on a single Nvidia GTX 480 GPU, the parallel wavelet engine achieves 100× speedup, the parallel bit plane coder achieves more than 30× speedup, and the overall Tier-1 coder achieves up to 17× speedup.\",\"PeriodicalId\":375788,\"journal\":{\"name\":\"2011 IEEE 9th Symposium on Application Specific Processors (SASP)\",\"volume\":\"81 26\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 9th Symposium on Application Specific Processors (SASP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SASP.2011.5941091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 9th Symposium on Application Specific Processors (SASP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SASP.2011.5941091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

摘要

JPEG2000图像压缩标准提供了比流行的JPEG标准更好的特性;然而,JPEG2000软件实现的缓慢性能阻碍了它的广泛采用。JPEG2000超过80%的执行时间花在了Tier-1编码引擎上。虽然在过去的十年里,人们一直致力于优化这个组件,但它的性能仍然很慢。主要原因是第1层编码器由高度串行的操作组成,每个操作在图像样本的每个位平面中的单个位上操作。此外,过去缺乏有效的硬件平台来为Tier-1提供大规模并行加速。然而,近年来通用图形处理单元(GPGPU)的发展为解决数千个并行处理线程的问题提供了一个很好的机会。本文研究了JPEG2000的计算步骤,特别是第1层的计算步骤,并开发了新的、与GPGPU兼容的、用于图像样本级编码的并行处理方法。与JasPer JPEG2000压缩软件相比,基于gpgpu的并行引擎可以显著加快执行时间。并行小波引擎在单个Nvidia GTX 480 GPU上实现了100倍的加速,并行位平面编码器实现了30倍以上的加速,整体Tier-1编码器实现了17倍的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel parallel Tier-1 coder for JPEG2000 using GPUs
The JPEG2000 image compression standard provides superior features to the popular JPEG standard; however, the slow performance of software implementation of JPEG2000 has kept it from being widely adopted. More than 80% of the execution time for JPEG2000 is spent on the Tier-1 coding engine. While much effort over the past decade has been devoted to optimizing this component, its performance still remains slow. The major reason for this is that the Tier-1 coder consists of highly serial operations, each operating on individual bits in every single bit plane of the image samples. In addition, in the past there lacked an efficient hardware platform to provide massively parallel acceleration for Tier-1. However, the recent growth of general purpose graphic processing unit (GPGPU) provides a great opportunity to solve the problem with thousands of parallel processing threads. In this paper, the computation steps in JPEG2000 are examined, particularly in the Tier-1, and novel, GPGPU compatible, parallel processing methods for the sample-level coding of the images are developed. The GPGPU-based parallel engine allows for significant speedup in execution time compared to the JasPer JPEG2000 compression software. Running on a single Nvidia GTX 480 GPU, the parallel wavelet engine achieves 100× speedup, the parallel bit plane coder achieves more than 30× speedup, and the overall Tier-1 coder achieves up to 17× speedup.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信