Y. S. Mehrabani, Samaneh Goldani Gigasari, Mohammad Mirzaei, Hamidreza Uoosefian
{"title":"一种用于CNFET技术中图像处理运动和边缘检测系统的新型高效非精确全加法器单元","authors":"Y. S. Mehrabani, Samaneh Goldani Gigasari, Mohammad Mirzaei, Hamidreza Uoosefian","doi":"10.1145/3524061","DOIUrl":null,"url":null,"abstract":"In this paper, a novel and highly efficient inexact Full Adder cell by exploiting two logic styles including conventional CMOS (C-COMS) and pass transistor logic (PTL) are presented. The so-called carbon nanotube field-effect transistor (CNFET) technology is used to implement circuits at the transistor level. To justify the efficiency of our design, extensive simulations are performed at the transistor level as well as application level. Transistor-level simulations which are carried out by the HSPICE 2008 tool, demonstrate at least 12% higher performance in terms of power-delay-area product (PDAP) of the proposed circuit compared to the latest designs. At the application level, by using the MATLAB tool, inexact Full Adders are employed in the structure of the ripple carry adder (RCA) that is applied in motion and edge detection algorithms. Computer simulation results confirm the appropriate quality of the output images in terms of the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) criteria. At last, to make a compromise between hardware and application level parameters, the power-delay-area-1/PSNR product (PDAPP) and power-delay-area-1/SSIM product (PDASP) are considered as figures of merit. The proposed circuit shows remarkable improvement from the PDAPP and PDASP points of view compared to its counterparts.","PeriodicalId":240416,"journal":{"name":"ACM Journal of Emerging Technologies in Computing System","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Novel Highly-Efficient Inexact Full Adder Cell for Motion and Edge Detection Systems of Image Processing in CNFET Technology\",\"authors\":\"Y. S. Mehrabani, Samaneh Goldani Gigasari, Mohammad Mirzaei, Hamidreza Uoosefian\",\"doi\":\"10.1145/3524061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a novel and highly efficient inexact Full Adder cell by exploiting two logic styles including conventional CMOS (C-COMS) and pass transistor logic (PTL) are presented. The so-called carbon nanotube field-effect transistor (CNFET) technology is used to implement circuits at the transistor level. To justify the efficiency of our design, extensive simulations are performed at the transistor level as well as application level. Transistor-level simulations which are carried out by the HSPICE 2008 tool, demonstrate at least 12% higher performance in terms of power-delay-area product (PDAP) of the proposed circuit compared to the latest designs. At the application level, by using the MATLAB tool, inexact Full Adders are employed in the structure of the ripple carry adder (RCA) that is applied in motion and edge detection algorithms. Computer simulation results confirm the appropriate quality of the output images in terms of the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) criteria. At last, to make a compromise between hardware and application level parameters, the power-delay-area-1/PSNR product (PDAPP) and power-delay-area-1/SSIM product (PDASP) are considered as figures of merit. The proposed circuit shows remarkable improvement from the PDAPP and PDASP points of view compared to its counterparts.\",\"PeriodicalId\":240416,\"journal\":{\"name\":\"ACM Journal of Emerging Technologies in Computing System\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Journal of Emerging Technologies in Computing System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3524061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Journal of Emerging Technologies in Computing System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3524061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Highly-Efficient Inexact Full Adder Cell for Motion and Edge Detection Systems of Image Processing in CNFET Technology
In this paper, a novel and highly efficient inexact Full Adder cell by exploiting two logic styles including conventional CMOS (C-COMS) and pass transistor logic (PTL) are presented. The so-called carbon nanotube field-effect transistor (CNFET) technology is used to implement circuits at the transistor level. To justify the efficiency of our design, extensive simulations are performed at the transistor level as well as application level. Transistor-level simulations which are carried out by the HSPICE 2008 tool, demonstrate at least 12% higher performance in terms of power-delay-area product (PDAP) of the proposed circuit compared to the latest designs. At the application level, by using the MATLAB tool, inexact Full Adders are employed in the structure of the ripple carry adder (RCA) that is applied in motion and edge detection algorithms. Computer simulation results confirm the appropriate quality of the output images in terms of the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) criteria. At last, to make a compromise between hardware and application level parameters, the power-delay-area-1/PSNR product (PDAPP) and power-delay-area-1/SSIM product (PDASP) are considered as figures of merit. The proposed circuit shows remarkable improvement from the PDAPP and PDASP points of view compared to its counterparts.