{"title":"利用百万规模的非冯诺依曼计算加速机器学习和高性能计算","authors":"L. Daudet","doi":"10.1109/PN52152.2021.9597985","DOIUrl":null,"url":null,"abstract":"Current large-scale computations, for instance in High Performance Computing or in the training of massive Machine Learning models, often suffer from the “memory bottleneck”, especially when dealing with high-dimensional data. Here, we present a new non-von Neumann photonic hardware, leveraging multiple light scattering. Optical Processing Units can be seamlessly integrated into a variety of hybrid photonics / silicon pipelines implementing state-of-the-art Machine Learning or High Performance Computing algorithms. They offer a credible pathway towards a new generation of large-scale computing, both scalable and sustainable.","PeriodicalId":6789,"journal":{"name":"2021 Photonics North (PN)","volume":"9 1 1","pages":"1-1"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging million-scale Non von Neumann computations for accelerated Machine Learning and High Performance Computing\",\"authors\":\"L. Daudet\",\"doi\":\"10.1109/PN52152.2021.9597985\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Current large-scale computations, for instance in High Performance Computing or in the training of massive Machine Learning models, often suffer from the “memory bottleneck”, especially when dealing with high-dimensional data. Here, we present a new non-von Neumann photonic hardware, leveraging multiple light scattering. Optical Processing Units can be seamlessly integrated into a variety of hybrid photonics / silicon pipelines implementing state-of-the-art Machine Learning or High Performance Computing algorithms. They offer a credible pathway towards a new generation of large-scale computing, both scalable and sustainable.\",\"PeriodicalId\":6789,\"journal\":{\"name\":\"2021 Photonics North (PN)\",\"volume\":\"9 1 1\",\"pages\":\"1-1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Photonics North (PN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PN52152.2021.9597985\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Photonics North (PN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PN52152.2021.9597985","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Leveraging million-scale Non von Neumann computations for accelerated Machine Learning and High Performance Computing
Current large-scale computations, for instance in High Performance Computing or in the training of massive Machine Learning models, often suffer from the “memory bottleneck”, especially when dealing with high-dimensional data. Here, we present a new non-von Neumann photonic hardware, leveraging multiple light scattering. Optical Processing Units can be seamlessly integrated into a variety of hybrid photonics / silicon pipelines implementing state-of-the-art Machine Learning or High Performance Computing algorithms. They offer a credible pathway towards a new generation of large-scale computing, both scalable and sustainable.