Ziwei Li, Han Xu, Zheyu Liu, Li Luo, Qi Wei, Fei Qiao
{"title":"一种2.17μW@120fps超低功耗双模CMOS图像传感器","authors":"Ziwei Li, Han Xu, Zheyu Liu, Li Luo, Qi Wei, Fei Qiao","doi":"10.1109/ASP-DAC52403.2022.9712591","DOIUrl":null,"url":null,"abstract":"This paper proposes an ultra-low-power CMOS Image Sensor (CIS) chip based on sensing-with-computing (Senputing) architecture to reduce the power bottleneck of vision system. This Senputing chip achieves BNN 1st-layer convolution in analog domain with ultra-low power consumption. It has two working modes, Normal-Sensor (NS) mode and Direct- Photocurrent-Computation (DPC) mode. The prototype measurement results under 65nm CMOS process on MNIST classification task shows that the power of feature map computation is 2.17μW with 120fps frame rates and 98.1% accuracy. The computation efficiency reaches to 11.49TOPs/W, which is 14.8× higher than state-of-art works.","PeriodicalId":239260,"journal":{"name":"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","volume":"206 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A 2.17μW@120fps Ultra-Low-Power Dual-Mode CMOS Image Sensor with Senputing Architecture\",\"authors\":\"Ziwei Li, Han Xu, Zheyu Liu, Li Luo, Qi Wei, Fei Qiao\",\"doi\":\"10.1109/ASP-DAC52403.2022.9712591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an ultra-low-power CMOS Image Sensor (CIS) chip based on sensing-with-computing (Senputing) architecture to reduce the power bottleneck of vision system. This Senputing chip achieves BNN 1st-layer convolution in analog domain with ultra-low power consumption. It has two working modes, Normal-Sensor (NS) mode and Direct- Photocurrent-Computation (DPC) mode. The prototype measurement results under 65nm CMOS process on MNIST classification task shows that the power of feature map computation is 2.17μW with 120fps frame rates and 98.1% accuracy. The computation efficiency reaches to 11.49TOPs/W, which is 14.8× higher than state-of-art works.\",\"PeriodicalId\":239260,\"journal\":{\"name\":\"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)\",\"volume\":\"206 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASP-DAC52403.2022.9712591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASP-DAC52403.2022.9712591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A 2.17μW@120fps Ultra-Low-Power Dual-Mode CMOS Image Sensor with Senputing Architecture
This paper proposes an ultra-low-power CMOS Image Sensor (CIS) chip based on sensing-with-computing (Senputing) architecture to reduce the power bottleneck of vision system. This Senputing chip achieves BNN 1st-layer convolution in analog domain with ultra-low power consumption. It has two working modes, Normal-Sensor (NS) mode and Direct- Photocurrent-Computation (DPC) mode. The prototype measurement results under 65nm CMOS process on MNIST classification task shows that the power of feature map computation is 2.17μW with 120fps frame rates and 98.1% accuracy. The computation efficiency reaches to 11.49TOPs/W, which is 14.8× higher than state-of-art works.