{"title":"采用数字内存计算设计的三维集成电路架构的能源/碳意识评估与优化","authors":"Hyung Joon Byun;Udit Gupta;Jae-Sun Seo","doi":"10.1109/JXCDC.2024.3479100","DOIUrl":null,"url":null,"abstract":"Several 2-D architectures have been presented, including systolic arrays or compute-in-memory (CIM) arrays for energy-efficient artificial intelligence (AI) inference. To increase the energy efficiency within constrained area, 3-D technologies have been actively investigated, which have the potential to decrease the data path length or increase the activation buffer size, enabling higher energy efficiency. Several works have reported the 3-D architectures using non-CIM designs, but investigations on 3-D architectures with CIM macros have not been well studied in prior works. In this article, we investigate digital CIM (DCIM) macros and various 3-D architectures to find the opportunity of increased energy efficiency compared with 2-D structures. Moreover, we also investigated the carbon footprint of 3-D architectures. We have built in-house simulators calculating energy and area given high-level hardware descriptions and DNN workloads and integrated with carbon estimation tool to analyze the embodied carbon of various hardware designs. We have investigated different types of 3-D DCIM architectures and dataflows, which have shown 42.5% energy savings compared with 2-D systolic arrays on average. Also, we have analyzed the tradeoff between performance and carbon footprint and their optimization opportunities.","PeriodicalId":54149,"journal":{"name":"IEEE Journal on Exploratory Solid-State Computational Devices and Circuits","volume":"10 ","pages":"98-106"},"PeriodicalIF":2.0000,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10714410","citationCount":"0","resultStr":"{\"title\":\"Energy-/Carbon-Aware Evaluation and Optimization of 3-D IC Architecture With Digital Compute-in-Memory Designs\",\"authors\":\"Hyung Joon Byun;Udit Gupta;Jae-Sun Seo\",\"doi\":\"10.1109/JXCDC.2024.3479100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Several 2-D architectures have been presented, including systolic arrays or compute-in-memory (CIM) arrays for energy-efficient artificial intelligence (AI) inference. To increase the energy efficiency within constrained area, 3-D technologies have been actively investigated, which have the potential to decrease the data path length or increase the activation buffer size, enabling higher energy efficiency. Several works have reported the 3-D architectures using non-CIM designs, but investigations on 3-D architectures with CIM macros have not been well studied in prior works. In this article, we investigate digital CIM (DCIM) macros and various 3-D architectures to find the opportunity of increased energy efficiency compared with 2-D structures. Moreover, we also investigated the carbon footprint of 3-D architectures. We have built in-house simulators calculating energy and area given high-level hardware descriptions and DNN workloads and integrated with carbon estimation tool to analyze the embodied carbon of various hardware designs. We have investigated different types of 3-D DCIM architectures and dataflows, which have shown 42.5% energy savings compared with 2-D systolic arrays on average. Also, we have analyzed the tradeoff between performance and carbon footprint and their optimization opportunities.\",\"PeriodicalId\":54149,\"journal\":{\"name\":\"IEEE Journal on Exploratory Solid-State Computational Devices and Circuits\",\"volume\":\"10 \",\"pages\":\"98-106\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-10-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10714410\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal on Exploratory Solid-State Computational Devices and Circuits\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10714410/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal on Exploratory Solid-State Computational Devices and Circuits","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10714410/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Energy-/Carbon-Aware Evaluation and Optimization of 3-D IC Architecture With Digital Compute-in-Memory Designs
Several 2-D architectures have been presented, including systolic arrays or compute-in-memory (CIM) arrays for energy-efficient artificial intelligence (AI) inference. To increase the energy efficiency within constrained area, 3-D technologies have been actively investigated, which have the potential to decrease the data path length or increase the activation buffer size, enabling higher energy efficiency. Several works have reported the 3-D architectures using non-CIM designs, but investigations on 3-D architectures with CIM macros have not been well studied in prior works. In this article, we investigate digital CIM (DCIM) macros and various 3-D architectures to find the opportunity of increased energy efficiency compared with 2-D structures. Moreover, we also investigated the carbon footprint of 3-D architectures. We have built in-house simulators calculating energy and area given high-level hardware descriptions and DNN workloads and integrated with carbon estimation tool to analyze the embodied carbon of various hardware designs. We have investigated different types of 3-D DCIM architectures and dataflows, which have shown 42.5% energy savings compared with 2-D systolic arrays on average. Also, we have analyzed the tradeoff between performance and carbon footprint and their optimization opportunities.