{"title":"目标驱动的PCB合成使用机器学习和云规模计算","authors":"Taylor Hogan","doi":"10.1145/3569052.3578907","DOIUrl":null,"url":null,"abstract":"X AI is a cloud-based system that leverages machine learning, and search to place and route printed circuit boards using physics-based analysis and high-level design. We propose a feedback-based Monte Carlo Tree Search (MCTS) algorithm to explore the space of possible designs. A metric, or metrics, is given to evaluate the quality of designs as MCTS learns about possible solutions. A policy and value network are trained during exploration to learn to accurately weight quality actions and identify useful design states. This is performed as a feedback loop in conjunction with other feedforward tools for placement and routing.","PeriodicalId":169581,"journal":{"name":"Proceedings of the 2023 International Symposium on Physical Design","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Goal Driven PCB Synthesis Using Machine Learning and CloudScale Compute\",\"authors\":\"Taylor Hogan\",\"doi\":\"10.1145/3569052.3578907\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"X AI is a cloud-based system that leverages machine learning, and search to place and route printed circuit boards using physics-based analysis and high-level design. We propose a feedback-based Monte Carlo Tree Search (MCTS) algorithm to explore the space of possible designs. A metric, or metrics, is given to evaluate the quality of designs as MCTS learns about possible solutions. A policy and value network are trained during exploration to learn to accurately weight quality actions and identify useful design states. This is performed as a feedback loop in conjunction with other feedforward tools for placement and routing.\",\"PeriodicalId\":169581,\"journal\":{\"name\":\"Proceedings of the 2023 International Symposium on Physical Design\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 International Symposium on Physical Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3569052.3578907\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 International Symposium on Physical Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3569052.3578907","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
X AI是一个基于云的系统,利用机器学习和搜索,使用基于物理的分析和高级设计来放置和布线印刷电路板。我们提出了一种基于反馈的蒙特卡罗树搜索(MCTS)算法来探索可能的设计空间。当MCTS了解到可能的解决方案时,给出了一个或多个度量来评估设计的质量。在探索过程中训练策略和价值网络,以学习准确地权重质量动作并识别有用的设计状态。这是作为与其他前馈工具的放置和路由的反馈循环一起执行的。
Goal Driven PCB Synthesis Using Machine Learning and CloudScale Compute
X AI is a cloud-based system that leverages machine learning, and search to place and route printed circuit boards using physics-based analysis and high-level design. We propose a feedback-based Monte Carlo Tree Search (MCTS) algorithm to explore the space of possible designs. A metric, or metrics, is given to evaluate the quality of designs as MCTS learns about possible solutions. A policy and value network are trained during exploration to learn to accurately weight quality actions and identify useful design states. This is performed as a feedback loop in conjunction with other feedforward tools for placement and routing.