{"title":"通过多位 QD-NVRAM 使用点积进行内存计算","authors":"R. Gudlavalleti, J. Chandy, E. Heller, F. Jain","doi":"10.1142/s012915642440055x","DOIUrl":null,"url":null,"abstract":"This paper presents in-memory computing using fast write/erase quantum dot (QD) nonvolatile random access memory (NVRAM). In comparison to NVMs, multi-state NVRAMs offer enhanced Compute-In-Memory capability for applications in deep neural network architecture. Dot product is the methodology that enables an array structure for multiply and accumulate (MAC) operation. We show an approach to dot product computation using multi-state quantum dot channel (QDC) FETs and QD-NVRAM.","PeriodicalId":35778,"journal":{"name":"International Journal of High Speed Electronics and Systems","volume":"44 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"In-Memory Computing Using Dot-Product via Multi-Bit QD-NVRAMs\",\"authors\":\"R. Gudlavalleti, J. Chandy, E. Heller, F. Jain\",\"doi\":\"10.1142/s012915642440055x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents in-memory computing using fast write/erase quantum dot (QD) nonvolatile random access memory (NVRAM). In comparison to NVMs, multi-state NVRAMs offer enhanced Compute-In-Memory capability for applications in deep neural network architecture. Dot product is the methodology that enables an array structure for multiply and accumulate (MAC) operation. We show an approach to dot product computation using multi-state quantum dot channel (QDC) FETs and QD-NVRAM.\",\"PeriodicalId\":35778,\"journal\":{\"name\":\"International Journal of High Speed Electronics and Systems\",\"volume\":\"44 13\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of High Speed Electronics and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s012915642440055x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of High Speed Electronics and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s012915642440055x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
In-Memory Computing Using Dot-Product via Multi-Bit QD-NVRAMs
This paper presents in-memory computing using fast write/erase quantum dot (QD) nonvolatile random access memory (NVRAM). In comparison to NVMs, multi-state NVRAMs offer enhanced Compute-In-Memory capability for applications in deep neural network architecture. Dot product is the methodology that enables an array structure for multiply and accumulate (MAC) operation. We show an approach to dot product computation using multi-state quantum dot channel (QDC) FETs and QD-NVRAM.
期刊介绍:
Launched in 1990, the International Journal of High Speed Electronics and Systems (IJHSES) has served graduate students and those in R&D, managerial and marketing positions by giving state-of-the-art data, and the latest research trends. Its main charter is to promote engineering education by advancing interdisciplinary science between electronics and systems and to explore high speed technology in photonics and electronics. IJHSES, a quarterly journal, continues to feature a broad coverage of topics relating to high speed or high performance devices, circuits and systems.