KATO: Knowledge Alignment and Transfer for Transistor Sizing of Different Design and Technology

arXiv:2404.14433v1 Announce Type: new
Abstract: Automatic transistor sizing in circuit design continues to be a formidable challenge. Despite that Bayesian optimization (BO) has achieved significant success, it is circuit-specific, limiting the accumulation and transfer of design knowledge for broader applications. This paper proposes (1) efficient automatic kernel construction, (2) the first transfer learning across different circuits and technology nodes for BO, and (3) a selective transfer learning scheme to ensure only useful knowledge is utilized. These three novel components are …

abstract alignment applications arxiv bayesian challenge cs.ce cs.lg design kernel knowledge optimization paper success technology transfer type