{"title":"OpenCL在GPU和FPGA上实现非锐化滤波","authors":"Ozge Unel, Toygar Akgun","doi":"10.1109/SIU.2014.6830203","DOIUrl":null,"url":null,"abstract":"The purpose of this study is to evaluate the performance of two dimensional multi-threaded linear filtering process on the GPU and FPGA platforms. To obtain the implementation on varying platforms, OpenCL API is used. OpenCL provides platform independent programming advantage. The results on three different platforms are compared to each other within this scope. These platforms are CPU, GPU, and FPGA. With changing filter and video frame sizes, varying processing times on these platforms are observed, and platform dependent advantages/disadvantages are studied.","PeriodicalId":384835,"journal":{"name":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"OpenCL implementation of unsharp filtering on GPU and FPGA\",\"authors\":\"Ozge Unel, Toygar Akgun\",\"doi\":\"10.1109/SIU.2014.6830203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of this study is to evaluate the performance of two dimensional multi-threaded linear filtering process on the GPU and FPGA platforms. To obtain the implementation on varying platforms, OpenCL API is used. OpenCL provides platform independent programming advantage. The results on three different platforms are compared to each other within this scope. These platforms are CPU, GPU, and FPGA. With changing filter and video frame sizes, varying processing times on these platforms are observed, and platform dependent advantages/disadvantages are studied.\",\"PeriodicalId\":384835,\"journal\":{\"name\":\"2014 22nd Signal Processing and Communications Applications Conference (SIU)\",\"volume\":\"169 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 22nd Signal Processing and Communications Applications Conference (SIU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2014.6830203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2014.6830203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OpenCL implementation of unsharp filtering on GPU and FPGA
The purpose of this study is to evaluate the performance of two dimensional multi-threaded linear filtering process on the GPU and FPGA platforms. To obtain the implementation on varying platforms, OpenCL API is used. OpenCL provides platform independent programming advantage. The results on three different platforms are compared to each other within this scope. These platforms are CPU, GPU, and FPGA. With changing filter and video frame sizes, varying processing times on these platforms are observed, and platform dependent advantages/disadvantages are studied.