{"title":"高变率低能量势垒磁体加速优化技术的计算保真度与贝叶斯问题","authors":"Md Golam Morshed;Samiran Ganguly;Avik W. Ghosh","doi":"10.1109/LMAG.2023.3274051","DOIUrl":null,"url":null,"abstract":"Low energy barrier magnet (LBM) technology has recently been proposed as a candidate for accelerating algorithms based on energy minimization and probabilistic graphs because their physical characteristics have a one-to-one mapping onto the primitives of these algorithms. Many of these algorithms have a much higher tolerance for error compared to high-accuracy numerical computation. LBM, however, is a nascent technology, and devices show high sample-to-sample variability. In this letter, we take a deep dive into the overall fidelity afforded by this technology in providing computational primitives for these algorithms. We show, that while the computed results show finite deviations from zero-variability devices, the margin of error is almost always certifiable to a certain percentage. This suggests that LBM technology could be a viable candidate as an accelerator for popular emerging paradigms of computing.","PeriodicalId":13040,"journal":{"name":"IEEE Magnetics Letters","volume":"14 ","pages":"1-5"},"PeriodicalIF":1.1000,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Deep Dive Into the Computational Fidelity of High-Variability Low Energy Barrier Magnet Technology for Accelerating Optimization and Bayesian Problems\",\"authors\":\"Md Golam Morshed;Samiran Ganguly;Avik W. Ghosh\",\"doi\":\"10.1109/LMAG.2023.3274051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Low energy barrier magnet (LBM) technology has recently been proposed as a candidate for accelerating algorithms based on energy minimization and probabilistic graphs because their physical characteristics have a one-to-one mapping onto the primitives of these algorithms. Many of these algorithms have a much higher tolerance for error compared to high-accuracy numerical computation. LBM, however, is a nascent technology, and devices show high sample-to-sample variability. In this letter, we take a deep dive into the overall fidelity afforded by this technology in providing computational primitives for these algorithms. We show, that while the computed results show finite deviations from zero-variability devices, the margin of error is almost always certifiable to a certain percentage. This suggests that LBM technology could be a viable candidate as an accelerator for popular emerging paradigms of computing.\",\"PeriodicalId\":13040,\"journal\":{\"name\":\"IEEE Magnetics Letters\",\"volume\":\"14 \",\"pages\":\"1-5\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Magnetics Letters\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10120755/\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Magnetics Letters","FirstCategoryId":"101","ListUrlMain":"https://ieeexplore.ieee.org/document/10120755/","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A Deep Dive Into the Computational Fidelity of High-Variability Low Energy Barrier Magnet Technology for Accelerating Optimization and Bayesian Problems
Low energy barrier magnet (LBM) technology has recently been proposed as a candidate for accelerating algorithms based on energy minimization and probabilistic graphs because their physical characteristics have a one-to-one mapping onto the primitives of these algorithms. Many of these algorithms have a much higher tolerance for error compared to high-accuracy numerical computation. LBM, however, is a nascent technology, and devices show high sample-to-sample variability. In this letter, we take a deep dive into the overall fidelity afforded by this technology in providing computational primitives for these algorithms. We show, that while the computed results show finite deviations from zero-variability devices, the margin of error is almost always certifiable to a certain percentage. This suggests that LBM technology could be a viable candidate as an accelerator for popular emerging paradigms of computing.
期刊介绍:
IEEE Magnetics Letters is a peer-reviewed, archival journal covering the physics and engineering of magnetism, magnetic materials, applied magnetics, design and application of magnetic devices, bio-magnetics, magneto-electronics, and spin electronics. IEEE Magnetics Letters publishes short, scholarly articles of substantial current interest.
IEEE Magnetics Letters is a hybrid Open Access (OA) journal. For a fee, authors have the option making their articles freely available to all, including non-subscribers. OA articles are identified as Open Access.