{"title":"数据存储和大脑启发计算的新兴记忆技术:印度研究见解的全球视角,重点是电阻性记忆","authors":"Sandip Lashkare, Wasi Uddin, Kumar Priyadarshi, Udayan Ganguly","doi":"10.1007/s40010-023-00828-w","DOIUrl":null,"url":null,"abstract":"<div><p>This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions.</p></div>","PeriodicalId":744,"journal":{"name":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","volume":"93 3","pages":"459 - 476"},"PeriodicalIF":0.8000,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories\",\"authors\":\"Sandip Lashkare, Wasi Uddin, Kumar Priyadarshi, Udayan Ganguly\",\"doi\":\"10.1007/s40010-023-00828-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions.</p></div>\",\"PeriodicalId\":744,\"journal\":{\"name\":\"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences\",\"volume\":\"93 3\",\"pages\":\"459 - 476\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s40010-023-00828-w\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","FirstCategoryId":"103","ListUrlMain":"https://link.springer.com/article/10.1007/s40010-023-00828-w","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories
This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions.