O. Alvarado-Nava, Hilda María Chablé Martínez, Eduardo Rodríguez-Martínez
{"title":"GPGPU实现的分形图像编码","authors":"O. Alvarado-Nava, Hilda María Chablé Martínez, Eduardo Rodríguez-Martínez","doi":"10.1109/IWOBI.2014.6913947","DOIUrl":null,"url":null,"abstract":"The programming model of general propose computing on graphic processing units (GPGPU) offers great efficiency for applications acceleration. This feature is granted by the ability of partitioning a sequential application into smaller subproblems with high computing requirements; those subproblems can be executed in parallel by a graphics processing unit (GPU) and partial results can be transferred to main memory where the central processing unit (CPU) collects and presents them. On the other hand, Fractal Image Coding (FIC) is a lossy compression technique with promising features, however it has been relegated due to its large coding time. The present article propose a parallel implementation of FIC on a GPGPU system which achieves an acceleration on coding time of about 129 times.","PeriodicalId":433659,"journal":{"name":"3rd IEEE International Work-Conference on Bioinspired Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"GPGPU implementation of fractal image coding\",\"authors\":\"O. Alvarado-Nava, Hilda María Chablé Martínez, Eduardo Rodríguez-Martínez\",\"doi\":\"10.1109/IWOBI.2014.6913947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The programming model of general propose computing on graphic processing units (GPGPU) offers great efficiency for applications acceleration. This feature is granted by the ability of partitioning a sequential application into smaller subproblems with high computing requirements; those subproblems can be executed in parallel by a graphics processing unit (GPU) and partial results can be transferred to main memory where the central processing unit (CPU) collects and presents them. On the other hand, Fractal Image Coding (FIC) is a lossy compression technique with promising features, however it has been relegated due to its large coding time. The present article propose a parallel implementation of FIC on a GPGPU system which achieves an acceleration on coding time of about 129 times.\",\"PeriodicalId\":433659,\"journal\":{\"name\":\"3rd IEEE International Work-Conference on Bioinspired Intelligence\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3rd IEEE International Work-Conference on Bioinspired Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWOBI.2014.6913947\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd IEEE International Work-Conference on Bioinspired Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWOBI.2014.6913947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The programming model of general propose computing on graphic processing units (GPGPU) offers great efficiency for applications acceleration. This feature is granted by the ability of partitioning a sequential application into smaller subproblems with high computing requirements; those subproblems can be executed in parallel by a graphics processing unit (GPU) and partial results can be transferred to main memory where the central processing unit (CPU) collects and presents them. On the other hand, Fractal Image Coding (FIC) is a lossy compression technique with promising features, however it has been relegated due to its large coding time. The present article propose a parallel implementation of FIC on a GPGPU system which achieves an acceleration on coding time of about 129 times.
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