TILOS AI研究所的AI/ML,优化和EDA

A. Kahng
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引用次数: 1

摘要

优化意味着找到给定问题的最佳解决方案,但规模和复杂性的挑战使许多现实世界的优化需求无法实现。大规模学习优化研究所(TILOS)是由加州大学圣地亚哥分校与麻省理工学院、国立大学、宾夕法尼亚大学、德克萨斯大学奥斯汀分校和耶鲁大学合作成立的一个新的国家人工智能研究所。TILOS由美国国家科学基金会赞助,英特尔公司提供部分支持。TILOS的使命是:在规模和实践中使不可能的优化成为可能。本讲座介绍了TILOS,其研究议程,以及它如何旨在建立人工智能和机器学习,优化和使用领域的“国家联系”,包括集成电路设计和设计自动化。该演讲将指出学习和优化的相互作用可以提高EDA结果的规模和质量的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI/ML, Optimization and EDA in the TILOS AI Research Institute
Optimization means finding the best possible solution to a given problem -- but challenges of scale and complexity keep many real-world optimization needs beyond reach. The Institute for Learning-enabled Optimization at Scale (TILOS) is a new National AI Research Institute led by UC San Diego in partnership with MIT, National University, Penn, UT Austin and Yale. TILOS is sponsored by the U.S. National Science Foundation, with partial support from Intel Corporation. The TILOS mission: make impossible optimizations possible, at scale and in practice. This talk introduces TILOS, its research agenda, and how it aims to establish a "national nexus" of AI and machine learning, optimization, and use domains that include integrated-circuit design and design automation. The talk will point out directions along which the interplay of learning and optimization can boost the scaling and quality of EDA outcomes.
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